Copyright by Julia Marie O’Rourke 2017

The Dissertation Committee for Julia Marie O’Rourke Certifies that this is the approved version of the following dissertation:

A New Paradigm for Evaluating Environmental Sustainability in a Complex Systems Context and Recommendations for Incorporating that Paradigm into Sustainable Design and LCA

Committee:

Carolyn Seepersad, Supervisor

Dongmei Chen

Richard Crawford

Varun Rai

Michael Webber A New Paradigm for Evaluating Environmental Sustainability in a Complex Systems Context and Recommendations for Incorporating that Paradigm into Sustainable Design and LCA

by

Julia Marie O’Rourke

Dissertation Presented to the Faculty of the Graduate School of The University of Texas at Austin

in Partial Fulfillment of the Requirements for the Degree of

Doctor of Philosophy

The University of Texas at Austin December 2017 Dedication

To Hayley

Acknowledgements

I would like to thank:  my husband, Pete, for his unwavering support, his belief in me, and the many sacrifices he made so that I could finish;  my parents, Kathy and Kevin, for their love and encouragement, for

maintaining an environment where I could be successful, and for their many hours of grandparenting;  my grandparents – Mary, Edward, Francis, and RoseAnn – who taught me to value education, enjoy the journey, and work hard;  my many teachers throughout the years, who showed me that science could be fun, who encouraged me to consider engineering and research, and who taught me how to teach myself;

 my friends, mentors, colleagues, and labmates, who inspired me, challenged me, and served as a sounding board for my ideas;  my advisor, Dr. Seepersad, who believed in me and encouraged me to take advantage of every enrichment opportunity available, and whose support made this dissertation possible; and

 my committee members – Dr. Chen, Dr. Crawford, Dr. Rai, and Dr. Webber – for their thoughtful feedback.

Finally, I would like to acknowledge support from a William Powers, Jr. Graduate Fellowship, a National Science Foundation Graduate Research Fellowship, a Cockrell School of Engineering Recruitment Fellowship, a Leigh Family Endowed Graduate

v Fellowship, the Pexa Education Trust, and the Department of Mechanical Engineering at University of Texas at Austin.

vi A New Paradigm for Evaluating Environmental Sustainability in a Complex Systems Context and Recommendations for Incorporating that Paradigm into Sustainable Design and LCA

Julia Marie O’Rourke, Ph.D. The University of Texas at Austin, 2017

Supervisor: Carolyn Seepersad

As consumers become increasingly eco-conscious, environmentally sustainable design has arisen to meet their demand for lower-impact products. Unfortunately, the sustainable design process as it is currently implemented often results in designs that do not ultimately result in reduced environmental damage. This occurs for a variety of reasons, including a failure to account for contextual factors and how they influence environmental impact, as will be discussed in Chapter 5, and the adoption of an overly-reductionist approach to addressing environmental problems, as will be argued in Chapter 9. The purpose of this research is to: (1) identify and discuss the problems in the current paradigm for sustainability that undermine efforts to address environmental issues via sustainable design; (2) propose a new paradigm for environmental sustainability and environmental impact that addresses the problems with the current paradigm and conceives of sustainability as an emergent property of a complex system composed of global energy and material flows; and (3) show how this new paradigm can be applied in practice to life cycle assessment (LCA) methods, the sustainable design process, efforts in eco- consumption, and research in related fields to more reliably address environmental problems. vii Chapters 1 through 4 introduce this work and provide background information related to LCA, scale and system boundaries, and network-related approaches to environmental impact assessment. Chapters 5 through 7 discuss context in LCA and sustainable design, namely, how contextual factors can affect the environmental impact associated with a given design and the environmental damage associated with a given impact, the implications of variability in impact due to contextual factors, and how other environmental impact measurement frameworks account for context. Chapters 8 and 9 present the current paradigm for environmental sustainability and problems with the reductionist approach. Chapter 10 presents a new paradigm for environmental sustainability as an emergent property of complex global systems; Chapter 11 presents a summary of findings, with examples; and Chapter 12 concludes.

viii Table of Contents

List of Tables ...... xxiii

List of Figures ...... xxv

Chapter 1: Introduction ...... 1 1.1 Background ...... 1 1.2 Purpose ...... 2 1.3 Hypothesis...... 3 1.4 Dissertation Overview ...... 3 1.4.1 Introduction and Background ...... 4 1.4.2 Context in LCA and Sustainable Design ...... 4 1.4.3 The Current Paradigm for Sustainability ...... 5 1.4.4 The New Paradigm for Sustainability and Recommendations .....5

Chapter 2: Life Cycle Assessment ...... 6 2.1 LCA Overview ...... 6 2.1.1 LCA Basics ...... 6 2.1.2 LCA Phases ...... 7 2.2 LCA Approaches ...... 8 2.2.1 Process, Input-Output, and Hybrid LCA ...... 8 2.2.1.1 Process LCA ...... 8 2.2.1.2 Input-Output LCA ...... 9 2.2.1.3 Hybrid LCA ...... 11 2.2.2 Attributional vs. Consequential LCA ...... 13 2.2.2.1 Attributional LCA ...... 13 2.2.2.2 Consequential LCA ...... 14 2.2.2.3 Why does this distinction matter? ...... 15 2.3 Challenges Associated with Implementing LCA ...... 17 2.3.1 Subjectivity in LCA ...... 17 2.3.1.1 Goal and Scope ...... 17 2.3.1.2 Functional Unit ...... 18 ix 2.3.1.3 System Boundary ...... 19 2.3.1.4 Timeframe ...... 20 2.3.1.5 Allocation ...... 20 2.3.1.6 Weighting ...... 22 2.3.2 Limited Applicability of LCA Results ...... 22 2.3.2.1 Uncertainty ...... 23 2.3.2.2 Difficult to Compare Studies and Apply Results to Other Problems ...... 24 2.3.2.3 LCA Cannot Show That One Product is Environmentally Superior to Another...... 25 2.3.2.4 LCAs Do Not Predict Actual Environmental Impacts ....27 2.4 Conclusion ...... 29

Chapter 3: Scale and System Boundaries ...... 31 3.1 Scale ...... 31 3.1.1 What is Scale? ...... 31 3.1.2 The Effect of Scale on LCAs ...... 32 3.1.3 Preference in LCA for Small-Scale Analyses ...... 33 3.2 System Boundary ...... 34 3.3 Conclusion ...... 36

Chapter 4: Network-Related Approaches to Environmental Assessment ...... 38 4.1 Industrial Ecology ...... 38 4.2 Industrial Symbiosis and Eco-Industrial Parks ...... 39 4.3 Material Flow Analysis ...... 41 4.4 Exergy Flow Analysis ...... 42 4.5 Industrial Metabolism ...... 43 4.6 Conclusion ...... 44

Chapter 5: The Effect of Contextual Factors on Environmental Impact and Environmental Damage ...... 46 5.1 The Amount of Impact Depends on Context ...... 46 5.1.1 User Characteristics and Behavior ...... 47

x 5.1.2 Usage Context ...... 49 5.1.3 Available Technology and Infrastructure ...... 51 5.1.4 Contextual Factors Can Affect the Amount of Impact in Every Life Cycle Phase – Solar PV Example ...... 53 5.1.4.1 Materials Production ...... 53 5.1.4.2 Manufacturing ...... 53 5.1.4.3 Transportation ...... 54 5.1.4.4 Use ...... 54 5.1.4.5 End-of-Life ...... 56 5.1.4.6 Further Reading ...... 57 5.2 The Amount of Damage Caused by a Given Impact Depends on Context58 5.2.1 Some Environments are More Sensitive to Impacts than Others58 5.2.2 Chemical Thresholds and Dose-Response Effects Change the Amount of Damage Caused by Chemical Emissions in Different Environments ...... 60 5.3 Examples of Contextual Factors to Consider When Assessing the Environmental Impact of Products ...... 62 5.4 The Difficulty in Accounting for Context in Prospective LCA ...... 65 5.5 Discussion ...... 67 5.5.1 LCAs Typically Do Not Account for Context ...... 67 5.5.2 Why Context is Often Neglected in LCA ...... 68 5.5.3 How This Limits LCA ...... 70 5.6 Conclusion ...... 71

Chapter 6: Implications of Variability in Environmental Impact Due to Context and Approaches for Sustainable Designers Moving Forward ...... 74 6.1 Implications of Environmental Impact Variation Due to Context ...... 74 6.1.1 The Background System Changes over Time, Meaning the Low- Impact Option Changes as Well ...... 75 6.1.1.1 Context Changes over Time...... 75 6.1.1.2 Changes in Context Can Cause Changes in the Relative Environmental Impact of Alternatives ...... 76 6.1.1.3 Considerations for Designers and Consumers ...... 78 xi 6.1.2 Usage and Consumption Patterns Vary Significantly, Reducing the Usefulness of General LCA Results for Individuals...... 79 6.1.3 The Lowest-Impact Option Is a Function of Both the Context and the Customer Need...... 81 6.2 Method for Visualizing Environmental Impact Scenarios...... 81 6.2.1 Individual Approach ...... 82 6.2.2 Global Approach ...... 86 6.3 Future Work ...... 90 6.3.1 Minimizing the Context-Sensitivity of Designs’ Environmental Impacts ...... 90 6.3.2 A Method to Group and Screen Contexts ...... 91 6.4 Conclusion ...... 93

Chapter 7: Learning from Other Environmental Impact Measurement Frameworks and How They Account for Context ...... 95 7.1 Environmental Risk Assessment...... 95 7.2 Environmental Impact Assessment ...... 96 7.3 Constructs of Environmental Impact from Ecology ...... 97 7.3.1 How Environmental Impact is Accounted for in Ecology ...... 98 7.3.1.1 Biological Organisms Can Have Both Positive and Negative Environmental Impacts ...... 98 7.3.1.2 Biologists Assess the Environmental Impact of Organisms within a Context ...... 99 7.3.1.3 Sustainability in Biology is about Preserving Biodiversity on a Global and Local Scale ...... 100 7.3.2 Applying Biological Constructs of Environmental Impact to Products / A New Ecology-Inspired LCA Framework ...... 102 7.3.2.1 The New Framework ...... 102 7.3.2.2 Discussion of Environmental Issues Raised by Using the New Framework...... 106 7.4 Conclusion ...... 107

Chapter 8: Current Paradigm of Environmental Sustainability ...... 110 8.1 Sustainability...... 111

xii 8.1.1 Three Pillar Model of Sustainability ...... 111 8.1.2 Resources for Future Generations ...... 112 8.1.3 The Earth Can Continue to Support Human Life ...... 113 8.2 Environmental Impact ...... 114 8.2.1 Environmental Impacts, Problems, and Issues are Typically Defined in Terms of Human Impacts ...... 114 8.2.2 Why Focus on Anthropogenic Impacts? ...... 115 8.3 The Reductionist Approach to Achieving Sustainability is to Minimize Human Environmental Impact on Small Scales ...... 116 8.3.1 Sustainable Products ...... 118 8.3.1.1 Having No Impact, Minimal Impact, or Having a Reduced Impact ...... 119 8.3.1.2 Possessing Sustainable Design Characteristics or Features121 8.3.2 Sustainable People ...... 122 8.3.2.1 Buying Low-Impact Products ...... 123 8.3.2.2 Making Sustainable Lifestyle Changes ...... 124 8.3.2.3 Using Only One’s Share of Earth’s Resources ...... 124 8.4 Conclusion ...... 125

Chapter 9: Problems with the Reductionist Approach ...... 128 9.1 It Is Difficult, if Not Impossible, to Achieve Small-Scale Sustainability128 9.1.1 For Products, Minimizing Low-Level Impacts Is Not Enough 129 9.1.2 For Consumers, Minimizing Low-Level Impacts Is Not Enough130 9.1.3 Conclusion ...... 132 9.2 Minimizing Low-Level Impacts May Not Lead to Decreased Impact Overall Because of System-Level Effects ...... 132 9.2.1 Low-Level Environmental Effects May Not ‘Ripple Up’ the Supply Chain ...... 132 9.2.2 Network Effects ...... 134 9.2.2.1 Basics of Network Effects ...... 134 9.2.2.2 Previous Work in LCA Related to Environmental Impact Networks ...... 135 9.2.2.3 Examples of Environmental Impact Networks ...... 136 xiii 9.2.2.4 Examples Demonstrating the Importance of Environmental Network Effects ...... 139 9.2.2.5 Where Network Effects Might Arise ...... 142 9.2.3 Scale Effects...... 144 9.2.3.1 Basics of Scale Effects ...... 144 9.2.3.2 Example of Scale Effects ...... 145 9.2.3.3 Consider Many Scales Together ...... 145 9.2.4 Quantity-Related Effects ...... 147 9.2.4.1 The Total Impact Matters ...... 147 9.2.4.2 Environmental Economies (or Diseconomies) of Scale151 9.2.4.3 Problems That Arise When Quantity-Related Effects Are Not Considered in LCA ...... 151 9.2.4.4 Does Achieving Sustainability Require a Reduction in Personal Consumption? ...... 152 9.2.5 Rebound Effects ...... 155 9.2.6 Synergistic Effects ...... 157 9.2.7 Collective Effects ...... 158 9.2.9 Discussion ...... 159 9.2.10 Conclusion ...... 159 9.3 The Reductionist Approach Neglects Context and Its Significant Influence on Overall Environmental Impact ...... 161 9.4 The Reductionist Approach Misses An Important Avenue to Achieving Sustainability: Implementing Systems-Level, Structural Changes ....163 9.5 Focusing on Small-Scale Impacts May Distract from Opportunities for Large-Scale Change ...... 166 9.6 Conclusion ...... 167

Chapter 10: The New Paradigm of Environmental Sustainability as an Emergent Property of Complex Global Systems...... 169 10.1 The Need for a New Paradigm ...... 170 10.1.1 Sustainability Is Not a Collective Property ...... 170 10.1.2 Sustainability Is Not a Design Attribute ...... 170 10.1.3 Impacts Are Not Inherently Good or Bad for the Environment172 xiv 10.1.4 Large Impacts Are Not Inherently Unsustainable ...... 174 10.2 What Is Environmental Impact in This Paradigm? ...... 174 10.2.1 Environmental Impact is a Network ...... 175 10.2.2 Biological Ideas of Environmental Impact Adopted ...... 177 10.2.2.1 Non-Anthropogenic Impacts Are Considered ...... 177 10.2.2.2 Both ‘Negative’ and ‘Positive’ Impacts Are Considered178 10.3 What is Environmental Sustainability in This Paradigm? ...... 180 10.3.1 Sustainability Is an Emergent Property of a Complex System180 10.3.2 Sustainability Means Preserving Biodiversity and Maintaining a Habitat for Humans ...... 181 10.3.3 Focus on Sustainability on a Global Scale ...... 182 10.4 Implications of the New Paradigm for Sustainable Design ...... 183 10.4.1 Sustainable Designers Should Work to Redesign Energy and Material Networks ...... 184 10.4.2 Sustainable Designers Should Strive to ‘Balance’ Environmental Impacts, Not ‘Minimize’ Human Impacts ...... 184 10.4.3 Designers Should Continue to Strive for Efficiency ...... 185 10.4.4 The Focus of Sustainable Design Shifts to Protecting Humans and Preserving Biodiversity Globally ...... 185 10.4.5 Designs Cannot be ‘Sustainable’ Because Sustainability Is an Emergent Property of a System ...... 187 10.4.6 For Sustainability, Size of the Impact of a Design Does Not Matter ...... 187 10.5 Conclusion ...... 188

Chapter 11: Summary of Findings, with Examples ...... 189 11.1 Advice to LCA Practitioners ...... 189 11.1.1 Consider consequential LCA...... 189 11.1.1.1 Example: ...... 190 11.1.1.2 Related Sections: ...... 192 11.1.2 Consider hybrid LCA or process LCA with network modeling.192 11.1.2.1 Example: ...... 192 11.1.2.2 Related Sections: ...... 194 xv 11.1.3 Select the scale of analysis and the functional unit to intentionally influence the focus of the study and the aspects of the product/fleet/industry/economy that are modeled in detail...... 194 11.1.3.1 Example: ...... 194 11.1.3.2 Related Sections: ...... 196 11.1.4 When in doubt, select the highest relevant scale of analysis and largest relevant functional unit...... 196 11.1.4.1 Example: ...... 197 11.1.4.2 Related Sections: ...... 197 11.1.5 Focus on larger environmental problems and perform LCAs on larger scales to make better use of the time and resources necessary to do LCA right...... 197 11.1.5.1 Example: ...... 198 11.1.5.2 Related Sections: ...... 198 11.1.6 Conduct uncertainty analysis and/or sensitivity analysis...... 198 11.1.6.1 Example: ...... 199 11.1.6.2 Related Sections: ...... 200 11.1.7 Conduct contextual analysis...... 201 11.1.7.1 Example: ...... 201 11.1.7.2 Related Sections: ...... 204 11.1.8 Include assessment of damage to biodiversity...... 205 11.1.8.1 Example: ...... 205 11.1.8.2 Related Sections: ...... 205 11.1.9 Explicitly account for the positive aspects of some human-caused environmental impacts...... 206 11.1.9.1 Example: ...... 206 11.1.9.2 Related Sections: ...... 206 11.1.10 Conduct contextual analysis, and avoid labelling impacts as ‘good’ or ‘bad’ for the environment...... 207 11.1.10.1 Example: ...... 207 11.1.10.2 Related Sections: ...... 207 11.1.11 Show your work, and emphasize the environmental impact model and assumptions in LCA publications...... 208 xvi 11.1.11.1 Example: ...... 208 11.1.11.2 Related Sections: ...... 210 11.2 Advice to Sustainable Designers ...... 211 11.2.1 Work to balance the global environmental impact network, minimizing waste and optimizing flows between entities...... 211 11.2.1.1 Example: ...... 211 11.2.1.2 Related Sections: ...... 215 11.2.2 Select the scale of the entity to design intentionally, with the awareness that the choice will influence the types of design solutions developed...... 215 11.2.2.1 Example: ...... 216 11.2.2.2 Related Sections: ...... 219 11.2.3 Focus on designing big, high-level systems to make better use of the time and resources necessary to do sustainable design right.219 11.2.3.1 Example: ...... 219 11.2.3.2 Related Sections: ...... 220 11.2.4 Ask big-picture, fundamental questions that challenge the proposed focus of the sustainable design project, and adjust the scope accordingly...... 221 11.2.4.1 Example: ...... 221 11.2.4.2 Related Sections: ...... 222 11.2.5 Generate novel concepts for products with significantly-reduced impacts using alternate ideation techniques during conceptual design...... 222 11.2.5.1 Example: ...... 223 11.2.5.2 Related Sections: ...... 223 11.2.6 Avoid labelling designs ‘sustainable,’ ‘unsustainable,’ ‘high- impact,’ or ‘low-impact’...... 223 11.2.6.1 Example: ...... 224 11.2.6.2 Related Sections: ...... 225 11.2.7 Design products that benefit the environment...... 225 11.2.7.1 Example: ...... 225 11.2.7.2 Related Sections: ...... 226 xvii 11.2.8 Consider methods and approaches other than LCA to assess and reduce environmental impact...... 226 11.2.8.1 Example: ...... 226 11.2.8.2 Related Sections: ...... 227 11.2.9 When identifying and assessing potential redesign avenues, consider the wider context surrounding a design, and model relevant interactions within the supply chain, economy, or physical environment, for instance...... 227 11.2.9.1 Example: ...... 228 11.2.9.2 Related Sections: ...... 229 11.2.10 Connect small-scale LCAs to larger-scale network models to account for systems-level effects...... 229 11.2.10.1 Example: ...... 230 11.2.10.2 Related Sections: ...... 230 11.2.11 Consider the likelihood that certain product scenarios will occur, and favor options for reducing impact that are within the designer’s control...... 230 11.2.11.1 Example: ...... 231 11.2.11.2 Related Sections: ...... 233 11.2.12 Identify environmentally favorable and unfavorable contexts for designs, and promote or discourage product adoption in these contexts accordingly...... 233 11.2.12.1 Example: ...... 233 11.2.12.2 Related Sections: ...... 234 11.2.13 Identify contexts to focus on during redesign to minimize the impact of the entire product fleet...... 234 11.2.13.1 Example: ...... 235 11.2.13.2 Related Sections: ...... 235 11.2.14 Consider segmenting the market and designing different products optimized to have low environmental impacts in different contexts...... 236 11.2.14.1 Example: ...... 236 11.2.14.2 Related Sections: ...... 236

xviii 11.2.15 Redesign products to minimize the context sensitivity of environmental impact...... 236 11.2.15.1 Example: ...... 237 11.2.15.2 Related Sections: ...... 238 11.2.16 Consider how context might change over the life of the product, potentially amplifying or negating any anticipated environmental benefits...... 239 11.2.16.1 Example: ...... 239 11.2.16.2 Related Sections: ...... 240 11.3 Advice to Eco-conscious Consumers...... 240 11.3.1 Avoid unnecessary consumption, even if it has a low per-unit impact...... 240 11.3.1.1 Example: ...... 241 11.3.1.2 Related Sections: ...... 241 11.3.2 Focus on protesting, lobbying, changing company policies, and other, large-scale environmental efforts...... 242 11.3.2.1 Example: ...... 242 11.3.2.2 Related Sections: ...... 243 11.3.3 Focus eco-consumption and conservation efforts on occasions when the marginal environmental impact is larger than the average impact...... 244 11.3.3.1 Example: ...... 244 11.3.3.2 Related Sections: ...... 244 11.3.4 Assess the extent to which the environmental impact of the product you are purchasing is context-dependent...... 245 11.3.4.1 Example: ...... 245 11.3.4.2 Related Sections: ...... 245 11.3.5 Consider how your context may affect the product’s impact. Ask: ‘Is product A or product B better for the environment, given my needs and situation?’ ...... 245 11.3.5.1 Example: ...... 246 11.3.5.2 Related Sections: ...... 246 11.3.6 Consider how your pro-environmental behavior may affect your own consumption (and impact) via rebound effects...... 247 xix 11.3.6.1 Example: ...... 247 11.3.6.2 Related Sections: ...... 247 11.3.7 Consider how your pro-environmental behavior may work with – or against – the pro-environmental behavior of others via collective effects...... 247 11.3.7.1 Example: ...... 248 11.3.7.2 Related Sections: ...... 248 11.3.8 Be wary of environmental product claims. However, when the environmental tradeoffs of a product have been thoroughly studied by many different researchers, trust the results...... 248 11.3.8.1 Example: ...... 249 11.3.8.1 Related Sections: ...... 250 11.3.9 When available, use results from context-specific consequential LCAs to guide environmentally-motivated decisions...... 250 11.3.9.1 Example: ...... 250 11.3.9.2 Related Sections: ...... 251 11.4 Advice to Sustainable Design and LCA Researchers ...... 251 11.4.1 Develop tools and methods to generate models of environmental impact networks, analyze these models, and redesign these networks to achieve environmental goals...... 251 11.4.1.1 Example: ...... 252 11.4.1.2 Related Sections: ...... 253 11.4.2 Develop tools and methods to minimize the context-sensitivity of the environmental impact of designs...... 254 11.4.2.1 Example: ...... 254 11.4.2.2 Related Sections: ...... 254 11.4.3 Develop a method for screening contexts and matching designs with contexts to achieve environmental goals...... 255 11.4.3.1 Example: ...... 255 11.4.3.2 Related Sections: ...... 256 11.5 The New Approach in Practice, Compared to the Old Approach...... 257 11.5.1 Life Cycle Assessment ...... 257 11.5.2 Sustainable Design ...... 258 xx 11.5.3 Eco-conscious Consumers ...... 260 11.5.4 Sustainable Design and LCA Researchers ...... 261 11.6 Sustainability Strategies for Designers in Old and New Paradigms ...262 11.7 Flowchart Summarizing the New Sustainable Design Process ...... 263 11.8 Conclusion ...... 267

Chapter 12: Conclusion...... 268 12.1 Summary of Dissertation ...... 268 12.1.1 Introduction and Literature Review ...... 268 12.1.2 Context in LCA and Sustainable Design ...... 268 12.1.3 The Current, Reductionist Paradigm for Sustainability ...... 268 12.1.4 The New Paradigm for Sustainability and Practical Recommendations ...... 269 12.2 Major Contributions ...... 269 12.3 The Value of the New Paradigm and What Success Looks Like ...... 270 12.4 Future Work ...... 271 12.5 Concluding Remarks ...... 274

Appendix: The Importance of Contextual Factors in Determining the Greenhouse Gas Emission Impacts of Solar Photovoltaic Systems ...... 276 A.1 Abstract ...... 276 A.2 Introduction ...... 276 A.3 Background and Motivation...... 278 A.3.1 Basics of Life Cycle GHG Emissions for Solar PV...... 278 A.3.2 Variation in GHG Intensity Estimates ...... 279 A.3.2.1 Technological Factors ...... 279 A.3.2.2 Methodological Factors ...... 280 A.3.2.3 Contextual Factors ...... 281 A.4 Identifying Contextual Factors that Affect the GHG Emission Impact of Solar PV ...... 282 A.4.1 Materials Extraction ...... 282 A.4.2 Manufacturing ...... 282 A.4.3 Transportation ...... 283 xxi A.4.4 Use ...... 284 A.4.5 End-of-Life...... 285 A.5 Sensitivity Studies of Contextual Factors ...... 286 A.5.1 Model Framework ...... 287 A.5.2 Input Data ...... 288 A.5.3 Test Case ...... 289 A.5.3.1 The Effect of Differences in Solar Insolation during Use291 A.5.3.2 GHG Intensity vs. Net GHG Emissions...... 293 A.5.3.3 Complexities of Type and Timing of Backup Generation294 A.5.3.4 Accounting for Timing of Demand and PV Production297 A.5.4 Future Work ...... 302 A.6 Conclusion ...... 302 A.7 Acknowledgments ...... 303 A.8 Appendix ...... 304

References ...... 307

xxii List of Tables

Table 1: Examples of how network effects might mitigate the expected environmental

benefits of a seemingly-sustainable action...... 141 Table 2: Annual electricity production, GHG intensity of electricity, and lifetime avoided GHG emissions estimates for a 4kW PV panel in three cities, assuming a 30 year panel lifetime, embedded emissions for the panel of

6200 kgCO2-eq, and the GHG intensity of avoided electricity is 533

gCO2/kWh...... 204

Table 3: Life Cycle Assessment – New Approach vs. Old Approach ...... 257

Table 4: Sustainable Design – New Approach vs. Old Approach ...... 258

Table 5: Eco-conscious Consumers – New Approach vs. Old Approach ...... 260 Table 6: Sustainable Design and LCA Researchers – New Approach vs. Old

Approach ...... 261 Table 7: Comparison of strategies in the old and new paradigm for sustainability that designers can use to restore balance in global material and energy flow

networks that are consistently out of balance...... 262 Table 8: Median GHG Intensities of Backup Electricity, Adapted from the IPCC

[196]...... 289 Table 9: Annual electricity production, GHG intensity of electricity, and lifetime avoided GHG emissions estimates for a 4kW PV panel in three cities,

assuming a 30 year panel lifetime, embedded emissions for the panel of

6200 kgCO2-eq, and the GHG intensity of avoided electricity is 533

gCO2/kWh...... 294

xxiii Table 10: Mass of avoided GHG emissions (kgCO2eq) associated with the use of a 4kW solar PV panel in Austin over 30 years, assuming 100% of the electricity from the panel offsets electricity that would have been

generated from the ‘backup electricity source’ listed...... 297 Table 11: Summary of calculations estimating the effect timing and magnitude of household demand and solar electricity production from a 4kW PV

panel have on the annual useful electricity produced by the panel, assuming no energy storage system and no option to sell excess

electricity to the grid...... 300

xxiv List of Figures

Figure 1: Overview of chapters in dissertation...... 4

Figure 2: Examples of contextual factors...... 63 Figure 3: Hypothetical LCA of a car plotted from the beginning to the end of the

product life cycle in terms of GHG emissions each year...... 84 Figure 4: Hypothetical LCA of a car with 4 different use phase scenarios plotted from

the beginning to the end of the product life cycle in terms of GHG

emissions each year...... 85 Figure 5: Plot of a Hypothetical Global Solar PV Fleet LCA, displaying the environmental impact corresponding to each additional unit of installed

PV capacity...... 88 Figure 6: “Illustration of a theoretical multifunction process consisting of two separate sub-processes and of the activities that may be indirectly

affected by a change in the production of product B” [7]...... 138 Figure 7: Attributional vs. consequential LCA for an electric grid with 5 consumers.

...... 191 Figure 8: “Pareto profile with the total project cost and life cycle GHG emissions for 10 instances” [13]. This demonstrates the importance of the input-output

portion of the LCA (in yellow), as it represents a significant proportion

of the overall GHG impact for each of the 10 designs...... 193

xxv Figure 9: Left: “Energy inputs and outputs to a single energy production system. Energy inputs (blue) are” below “the horizontal line, and energy production (yellow) is shown above the line”; Right: “Energy inputs and outputs for an energy production industry growing asymptotically to some upper limit. Gross output is shown as a bold line; net output is

shown with the dashed line” [167]...... 195 Figure 10: “Sensitivity analysis for the health and environmental benefits from solar

energy. Results present the average annual benefits from displaced SO2,

NOx, and PM2.5 for solar panels within an eGRID subregion. Five cases are presented for 5 of the 22 eGRID subregions. The selected regions are: AZNM (Arizona and New Mexico), ERCT (Texas), MROE (Wisconsin), RFCW (Indiana, Ohio, and West Virginia), and SRMW

(Missouri and Illinois)” [87]...... 200 Figure 11: A list of potential contextual factors in each life cycle phase that may alter

the environmental impact of a solar PV panel...... 201 Figure 12: Model relating sunlight availability at the location of use to the GHG

emissions avoided for a PV panel...... 202 Figure 13: Annual average solar resource data for the US, shown for a solar collector

tilted at an angle equal to the latitude. Adapted from Roberts [181].203

Figure 14: “Process flow diagram with an internal commodity flow loop” [20].209 Figure 15: Just because an impact is large does not mean it is ‘unsustainable’ or that

the network is imbalanced...... 212 Figure 16: Just because an impact is small does not mean it is ‘sustainable’ or part of

a balanced network...... 214

xxvi Figure 17: Mindmap of concepts to reduce the environmental impact of a cell phone on a product scale (an energy efficient mode), fleet scale (supply chain optimization), company scale (product takeback program), and inter- company scale (industrial ecopark). Image sources:

[186][187][188][189]...... 217 Figure 18: Company-scale LCA of a bakery showing that transportation impacts

would be reduced if the bakery moved south to be closer to customers.

...... 228 Figure 19: Company-scale LCA with national-scale network analysis reveals a transportation imbalance in Sweden that would cause the proposed move

of the bakery to have little overall environmental effect...... 229 Figure 20: Connect a detailed process LCA model to a generic network representing global energy and material flows. Image credits: Global model [194],

process model [20]...... 230 Figure 21: Performance of solar panels relative to annual health and environmental

benefits from displaced SO2, NOx and PM2.5 emissions. “Sharp boundaries are due to the assumption that wind and solar only affect generators within the same eGRID subregion (i.e., imports and exports

of electricity between regions are ignored). Monetary values are in 2010

dollars” [87]...... 234 Figure 22: “Server power usage and energy efficiency at varying utilization levels, from idle to peak performance. Even an energy-efficient server still consumes about half its full power when doing virtually no work” [195].

...... 237

xxvii Figure 23: “Power usage and energy efficiency in a more energy-proportional server. This server has a power efficiency of more than 80 percent of its peak value for utilizations of 30 percent and above, with efficiency remaining

above 50 percent for utilization levels as low as 10 percent” [195].238 Figure 24: Interface carpet flow analysis model. “Flows and processes with asterisks involve only… materials that are not primary inputs to the final product

(in this case, carpet). For example, nylon and PVC are product materials,

whereas water and natural gas are process materials” [180]...... 253 Figure 25: Flowchart summarizing the sustainable design approach presented in this

work...... 264 Figure 26: Annual average solar resource data for the US, shown for a solar collector

tilted at an angle equal to the latitude. Adapted from Roberts [181].291 Figure 27: Hypothetical dispatch curve for summer 2011 from the EIA [211]

demonstrating how the electricity generation mix depends on electricity

demand and the cost of different types of generators...... 295 Figure 28: The timing and magnitude of the AC electricity production from a 4kW panel in Phoenix, compared to electricity demand of a typical home in

Phoenix, for February 1st and 2nd and August 1st and 2nd...... 298

xxviii Chapter 1: Introduction

1.1 BACKGROUND

Environmental problems abound: climate change; species extinctions and biodiversity loss; presence of carcinogens or otherwise harmful chemicals in air, food, and water; depletion of fossil fuel resources; loss of habitat and wilderness; and the list goes on. Many of these problems are caused by – or aggravated by – human beings, through our collective consumption of resources and production of waste.

In this context, many individuals feel the need to do what they can to avoid contributing to environmental problems. These individuals, known as eco-consumers, strive to minimize the harm their personal consumption causes to the environment by reducing their total consumption and by purchasing low-impact products. (The term ‘product’ in this work is a broad term referring to any instantiation of a design, such as a consumer product, a building, a service, a process, or a system.)

Environmentally sustainable design (hereafter referred to as ‘sustainable design’, except where expressly noted) has arisen in this context to provide eco-consumers with the lower-impact products they demand. Designs are typically regarded as being ‘sustainable’ if, through life cycle assessment (LCA), they are determined to have a smaller environmental impact than a functionally-equivalent comparison design.

Unfortunately, the sustainable design process as it is currently implemented often results in designs that further exacerbate environmental problems. For instance, triple pane windows are more efficient than single pane windows. Using conventional analysis and a reductionist approach, this might lead one to conclude that a design with triple pane

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windows is more ‘sustainable’ than one with single pane windows. For two buildings, identical in every way except one has triple pane windows and the other has single pane windows, this assessment is likely correct (assuming the increase in materials consumption for triple pane windows is countered by the energy savings over the life of the windows). However, decisions such as the type of window to use in a design are not made in isolation, and it is possible that the increased efficiency of triple pane windows may allow a designer to use more windows than he or she would otherwise. Through what is known as the rebound effect, this ‘sustainable’ design change may, in fact, lead to an increase in overall energy consumption of the building. After all, a triple pane window is more efficient than a single pane window, but still less efficient than a well-insulated wall. Examples such as the one given above occur for a variety of reasons that will be explored in detail in this work, including a failure to account for the influence of contextual factors on environmental impact, as will be discussed in Chapter 5, and the adoption of an overly-reductionist approach to addressing environmental problems, as will be argued in Chapter 9.

1.2 PURPOSE

The purpose of this research is to: (1) identify and discuss the problems in the current paradigm for sustainability that undermine efforts to address environmental issues via sustainable design; (2) propose a new paradigm for environmental sustainability and environmental impact that addresses the problems with the current paradigm and conceives of sustainability as an emergent property of a complex system composed of global energy and material flows; and (3) show how this new paradigm can be applied in practice to LCA

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methods, the sustainable design process, efforts in eco-consumption, and research in related fields to more reliably address environmental problems.

1.3 HYPOTHESIS

The hypothesis underlying this work is that a new paradigm for environmental sustainability will help resolve a number of pressing problems in sustainable design, such as the context-dependency of environmental impact and environmental damage, discussed in Chapter 5, and the scale-dependency of LCA results, addressed in Chapters 3 and 9. The new paradigm presented in this work conceives of environmental sustainability as an emergent property that arises out of a complex system, where components in the system are entities that have environmental impacts on each other via flows of energy and materials. Thinking about environmental sustainability in this way may help designers better account for critical contextual factors and better scope their design problems to achieve more significant and tangible benefits to the environment through their designs. It may also better align sustainable design theory with theories of environmental impact from other disciplines, such as biology.

1.4 DISSERTATION OVERVIEW

This section provides an overview of the dissertation. The content of this section is summarized in Figure 1, below.

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Figure 1: Overview of chapters in dissertation.

1.4.1 Introduction and Background

Chapter 1 introduces and outlines this work. Chapter 2 provides an overview of LCA, various approaches to LCA, and challenges associated with implementing LCA. Chapter 3 discusses how the scale of analysis and choice of system boundaries affect the focus and results of LCAs. Chapter 4 provides an overview of five network-related approaches to reducing the environmental impact of designs.

1.4.2 Context in LCA and Sustainable Design

Chapter 5 addresses context and its effect on the environmental impact of products and the environmental damage caused by certain types of impacts. Chapter 6 discusses the

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implications of context-generated differences in environmental impact and what this means for LCA practitioners and individuals using LCA results to make more environmentally- friendly decisions. Chapter 7 provides an overview of some environmental impact measurement frameworks besides LCA and presents a new LCA framework inspired by biological constructs of ‘environmental impact’ that better accounts for contextual effects.

1.4.3 The Current Paradigm for Sustainability

Chapter 8 presents the current, reductionist paradigm for environmental sustainability. Chapter 9 explains the mechanisms by which the reductionist approach to sustainability fails and by which emergent sustainability-related properties arise.

1.4.4 The New Paradigm for Sustainability and Recommendations

Chapter 10 presents a new paradigm for sustainability. Chapter 11 summarizes the findings of the dissertation in a list of recommendations based on the new paradigm to LCA practitioners, sustainable product designers, eco-conscious consumers, and researchers, with examples of how these recommendations can be applied in practice. Chapter 12 concludes.

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Chapter 2: Life Cycle Assessment

Life cycle assessment (LCA) is the tool of choice for assessing the environmental impact of products and is widely used in sustainable design. This chapter provides background information pertaining to LCA; it presents an overview of LCA, various approaches to LCA, and challenges associated with implementing LCA.

2.1 LCA OVERVIEW

This section explains what LCA is and walks through the typical steps in an LCA.

2.1.1 LCA Basics

LCA is a tool that helps practitioners assess the environmental impact of a product. It involves the “compilation and evaluation of the inputs, outputs and the potential environmental impacts of a product system throughout its life cycle” [1]. LCA has been addressed in ISO standards 14040:2006 and 14044:2006 that deal with the principles and framework of LCA and the requirements and guidelines for LCA [2].

LCA is one of many environmental management techniques, such as environmental risk assessment, environmental performance evaluation, environmental auditing, environmental impact assessment, strategic environmental assessment, cost-benefit analysis, material flow analysis, substance flow analysis, energy flow analysis, and the ecological footprint approach [1][3][4]. It is unique because it adopts a life cycle perspective [3] and considers the impact of a product in each phase of its life cycle, from raw materials extraction to end of life. This perspective helps to avoid shifting environmental problems to different life cycle stages, industrial processes [1], geographic regions, or environmental problems [3]. Consequently, LCA is the method of choice for

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assessing the environmental impact of products, processes, and systems and has been described as “the pre-eminent tool” [5] and “the most objective tool” [6] for this task. LCA is used in a variety of ways by different practitioners: (1) to better understand the environmental impact of a product [1] and how this impact could change in response to actions or design modifications [7]; (2) to identify a product’s worst environmental problems [8] and develop measures that reduce the product’s environmental impact

[9][10]; (3) to quantify the environmental impact of a product [11] and compare it to the impact of other products, design alternatives, and actions [7][8][12][13]; (4) to justify product claims and inform consumers via environmental product declarations [1][10][14] and labelling [11]; (5) to inform “decision-makers in industry, government or non- government organizations… for the purpose of strategic planning, priority setting, product or process design or redesign” [1], and (6) to assist the World Trade Organization in distinguishing “between justified environmental policies and those that constitute nontariff trade barriers” and might consequently violate international trade agreements [15].

2.1.2 LCA Phases

There are four phases in an LCA. The first is goal and scope definition, which involves defining the subject of the LCA, the reasons for conducting the LCA, and the manner in which the results will be used [1][3][5]. The subjective decisions made during goal definition then set the stage for selecting system boundaries, LCA approach, functional unit, impact categories, and the level of detail of the analysis [1][3][5][11].

The second phase of an LCA is life cycle inventory analysis (LCI). In this phase, data is compiled that relates the resources needed to produce a product to the emissions or

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wastes that are generated as a result of the product over the course of its life cycle [1][3][16]. The third phase is life cycle impact assessment (LCIA). LCIA involves relating LCI results (in the form of volumes of emissions, for instance) to actual environmental damage, either in terms of ‘midpoint categories’ (e.g. human toxicity, noise, and climate change) or to ‘damages’ inflicted on general categories such as ‘human health’ and ‘the biotic and abiotic natural environment’ [17][18]. The fourth phase is interpretation, where the results of the study are summarized and discussed, and conclusions and recommendations are made [1].

2.2 LCA APPROACHES

This section provides an overview of the different approaches that can be used in LCA, along with a discussion of their advantages and disadvantages. First, the differences between process, input-output, and hybrid LCAs are discussed. Second, the difference between attributional and consequential LCA is addressed.

2.2.1 Process, Input-Output, and Hybrid LCA

This section explains the differences between process, input-output, and hybrid LCA, which fundamentally relate to “the level of aggregation of the life cycle inventory and… the scope of the system boundary” [19].

2.2.1.1 Process LCA

Process LCA is the most commonly-used type of LCA. It has been referred to as “classical” LCA [10], “the most widely applied” LCA method [4], and the “life cycle

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method of choice for most applications, including virtually all sustainable engineering applications” [19]. Process LCA involves acquiring detailed data on each life cycle phase, including the specifics of manufacturing processes, transportation methods, and disposal options. Throughout the analysis, process LCA assumes linear relationships between inputs, outputs, and associated environmental impacts [20].

At some point in the analysis, a cutoff must made where less-significant impacts are excluded [19]. To do this, potential additional processes to include are assessed to see how large a contribution they would make to the overall environmental impact of the product, and processes with sufficiently-small impacts are excluded. There are a number of drawbacks to process LCA. First, the detailed data required for process LCA can be time consuming and costly to obtain [16][21]. Second, process LCA results underestimate the true impact of products [3][13][16][20][21] because (1) process LCAs typically do not include impacts associated with capital goods and overhead – such as offices, marketing, company cars, and lunchrooms – which can be significant, particularly for service industries [21], and (2) some environmental impacts are excluded from the LCA because they are small and meet the LCA’s cutoff criteria.

2.2.1.2 Input-Output LCA

Compared to process LCA, input-output LCA has much broader system boundaries but uses much more aggregated data. Input-output LCA is based on economic input-output analysis, which shows the relationships between all industry sectors in a national economy in monetary terms and presents results in national input-output tables [20]. Many countries

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publish economic input-output tables that list the amount of money spent on goods from other sectors to make the goods in a given industry sector [3]. LCA practitioners can take the data from these tables and convert it to show the relationship between environmental impacts from different industries. They can then model the supply chains of product systems using the relationships between economic data [11] and can estimate the environmental impact of an average product in a given industry sector during the upstream life cycle phases [3] (i.e. materials extraction and manufacturing).

There are two main advantages of input-output LCA over process LCA. First, input-output LCA is faster than process LCA because it does not involve locating and analyzing detailed process data. Second, input-output LCA considers much broader environmental impacts and does not encounter boundary cutoff problems because it includes relationships between all sectors of the economy. Because of these advantages, it has been described as “a more comprehensive and faster way of selecting boundaries” [5], as providing “greater comprehensiveness of the modelled supply chain” [11], as having “an expanded life cycle boundary” [13], and as being able to account for capital goods and overhead [21]. However, input-output LCA also has a number of disadvantages compared to process LCA. The main disadvantage is that input-output LCA is far less detailed than process LCA because it is based on highly-aggregated economic sector data [5][13][19].

This sector-level resolution “is much too coarse for major LCA applications such as raw materials selection and process redesign” [3] and prevents input-output LCA from being able to distinguish between the environmental impacts of similar products [11]. Hence, it 10

can only provide a first pass at understanding significant, sector-based differences [20] and is best used to address questions focused on “the overall environmental impact of a system (e.g., impacts of new telecommunication technologies) or comparisons between very different options on a regional, national, or international level (e.g., impacts of introducing fuel cell vehicles compared to the current state)” [11]. For instance, it has been used “to identify key products and services produced and consumed within the European Union countries that impose significant environmental loads” [3]. In contrast, process LCA is “very technology-specific and can resolve differences, for example, among different alloys of steel or different colors of paint” [10]. Other disadvantages include the following: (1) input-output LCA only accounts for the environmental impact in the early phases of the product life cycle and does not include impacts from the use phase or end of life [11], meaning many environmental impacts are omitted and the method does not meet ISO standards [20]; (2) input-output data is frequently older than data for process LCAs; (3) input-output tables do not account for imports [5][20]; and (4) input-output LCA may be prone to overestimate the impact of expensive, high tech components because the method is based on cost [16].

2.2.1.3 Hybrid LCA

Hybrid LCA combines the detailed analysis from process LCA with the breadth of information from input-output LCA to take advantage of the benefits of both approaches [11][13]. Hybrid LCA involves both detailed models of important processes and general, aggregated models of background processes [19]. There are three main hybrid LCA approaches which differ mainly in where they draw the boundary between the process portion and the input-output portion of the LCA. 11

Tiered hybrid analysis models important parts of upstream life cycle phases, as well as use and end-of-life, using process LCA, and the environmental impact of inputs to these phases is modeled using input-output LCA. In contrast, input-output based hybrid analysis only models the use and end-of-life phases using process LCA. A significant number of system inputs are then modeled using disaggregated input-output LCA, where a sector of an input- output table is manually broken down by the practitioner into individual products to make that part of the LCA more detailed and accurate [3], and the rest of the inputs are modeled using traditional input-output LCA [20]. Finally, integrated hybrid analysis involves a traditional process LCA, where all significant life cycle phases and processes within those phases are modeled in detail; then, input-output LCA is used at the cutoff points [20]. Consequently, integrated hybrid analysis is expected to be both the most accurate and complete LCA approach, but also the most time consuming. Suh and Huppes [20] state: “With time and money available, the choice clearly is for… integrated hybrid analysis.”

Hybrid LCA eliminates the need to cutoff processes with small contributions to the overall environmental impact, as occurs in process LCA; instead, processes with small impacts are accounted for, in aggregate, through the use of input-output LCA [3]. However, many of the drawbacks related to input-output LCA apply to the input-output portion of the hybrid LCA, such as concerns related to imports and the increased age and aggregated nature of the data [5]. Similarly, the drawbacks of the process portion – namely, increased time and cost of the analysis – remain as well. In addition, hybrid LCA has yet to be adopted by practitioners working on sustainable product design problems. According to a 2015 paper from Hanes and Bakshi [19]:“[t]o date… there have been no applications of hybrid methods to sustainable design problems.” 12

2.2.2 Attributional vs. Consequential LCA

This section explains the differences between attributional and consequential LCA. Fundamentally, these differences relate to the purpose of the LCA and whether the results are intended to describe the current state of environmental impact for a product, or whether they are intended to describe how environmental impact may respond to change.

2.2.2.1 Attributional LCA

Attributional LCA, sometimes referred to as ‘descriptive LCA’, is much more commonly used than consequential LCA [10]. It is focused on describing the current state of environmental impact for a product, and it models “the environmentally relevant physical flows to and from a life cycle and its subsystems” [22]. Attributional LCA uses linear equations, averaged data, and averaged impacts divided evenly between all functional units produced over a period of time [10]. This means the sum of small environmental impacts always equals the total impact, and “the order in which economic activities are analyzed” as well as “the amount of economic activity… analyzed” does not affect results [23]. In addition, attributional LCA assumes that both upstream supply and downstream demand are fully elastic, so that “demand for one unit of product leads to the production and supply of one unit of product, with associated emissions and resource consumptions” but other customers or applications of the product remain unaffected [11]. Consequently, attributional LCA helps to address the question of who is responsible for which environmental impacts [23], with each consumer responsible for the share of environmental impact proportional to the amount of the total product he or she consumes. However, attributional LCA is unable to provide information on the environmental 13

consequences of change, i.e. what effect consuming more or less of a product would have on the environment.

2.2.2.2 Consequential LCA

In contrast to attributional LCA, consequential LCA is focused on the consequences of change [7], allowing practitioners to ask how the environment is affected when one additional product or functional unit is produced [10]. A broader system is modeled in consequential LCA than in attributional LCA, with the model accounting for changes to the environment caused by the product that might occur outside the typical product life cycle [22]. Consequential LCA uses nonlinear models [11] with marginal data corresponding to either short-term or long-term potential changes [3], allowing each functional unit to have different environmental impacts. Hence, it is able to account for instances where, for instance, the pollution emission rate changes with production rate at a facility in a nonlinear manner [23]. Consequential LCA accounts for a number of causal economic relationships that are not considered in attributional LCA, including the reality that production and demand are sometimes inelastic and have effects on other product systems [11] and that the “decision to buy the product does not necessarily imply an increase in the amount of natural resources extracted… [and] the consequences of an action do not necessarily propagate through the life cycle” [22].

Unfortunately, identifying the marginal technology and acquiring marginal data can sometimes require a significant amount of effort. This is especially difficult for analyses examining scenarios in the future. In addition, consequential LCAs can become very 14

complex and highly uncertain if long time horizons are considered. Finnveden et al. [3] note, for instance, that:

If a decision affects the timing of an investment in a power plant, it is also likely to affect the point in time where the power plant is taken out of use, the timing of the investment made to replace the first plant, and so on… A decision can affect the production systems, at the margin, very far into the future… If an LCA includes marginal effects that occur far into the future, the uncertainty added can be larger than marginal effect itself.

2.2.2.3 Why does this distinction matter?

The environmental impact models in attributional and consequential LCI are very different approaches that answer different types of environmental questions; they model different features of a product’s environmental impact, use different types of data, and make different assumptions about the underlying structure of the economy. Attributional LCA can tell researchers what an individual’s environmental responsibility is. For instance, if there are 5 consumers on an electric grid, all consuming the same amount of electricity, they each are responsible for 1/5th of the environmental impact of the grid, even if some consume electricity that originated from a diesel generator and others consume electricity that originated from a solar panel. In contrast, consequential LCA can tell researchers what difference an individual can make and how that person can change the overall environmental impact. For instance, if one person reduces his or her electricity consumption on the grid shared with four other consumers, consequential LCA can estimate the overall reduction in environmental impact of the grid. This change in impact may be larger (or smaller) than the amount of environmental impact that individual is responsible for, because the marginal electricity on the grid (ex. diesel electricity) may have a very different impact than the average grid 15

electricity and because the impacts associated with the capital electricity-generating equipment are not reduced when consumption decreases. Because of these differences in the focus of attributional and consequential LCA, the models of environmental impact constructed by LCA practitioners for each approach are different as well. Attributional LCA models typically focus on the product itself and are more akin to process LCA, capturing the inflows and outflows of materials and energy from materials acquisition to end of life for an average functional unit. In contrast, consequential LCA models focus more on the decision at hand, capturing the broader context surrounding the use of a particular product. These models may not include representations of the product life cycle at all. For instance, a decision to not use electricity at a particular time may relate only to emissions saved from burning fuel, and not the emissions that occur over the life cycle associated with the construction, transport, or disposal of the generator. In this sense, attributional LCA is more product-focused and consequential LCA is more decision- or context-focused. Heijungs [23] proposes combining both approaches, using attributional LCA to identify key environmental problems and then using consequential LCA “to investigate the change that is introduced by switching to an alternative.” In going this route, information is gained from both approaches, but the environmental impact models are kept separate. In certain situations, however, it may be advantageous to combine attributional and consequential LCA models. For instance, when many designs are being considered for use in a system, and there is an additional environmentally-related decision to make regarding the system, these two choices may have compounding effects. It may then be advantageous to make one consequential LCA model of how the environment will be affected by the 16

decision and plug into it different attributional LCA models for the different designs under consideration for use in the system. The details and layout of such a modeling exercise is a task saved for future work.

2.3 CHALLENGES ASSOCIATED WITH IMPLEMENTING LCA

Unfortunately, there are many problems in LCA beyond the frequently-cited complaint that LCA requires a significant amount of detailed data, which can be expensive and time consuming to obtain [1][6][11][15][24]. This section provides a review of more fundamental problems in LCA that have been discussed by other authors, pertaining to the subjectivity that is pervasive throughout the LCA process as well as the implications and limitations the subjectivity in LCA has for the applicability of LCA results.

2.3.1 Subjectivity in LCA

Subjective values are fundamental to LCA. Even an individual’s perception that something constitutes an environmental impact “amounts to a value judgment” [23].

Below, a number of aspects of LCA that involve subjective decisions will be discussed.

2.3.1.1 Goal and Scope

The outcome of an LCA is influenced by personal values during goal and scope definition [5][25]. During this phase, practitioners subjectively define their problem and set the goal of the LCA. This “starting point has decisive implications for the procedure to be followed” [23] and can dictate the study’s focus. For instance, a particular study goal could lead practitioners to choose a consequential LCA rather than an attributional LCA, or a narrow study scope could cause practitioners to be so focused on minute details of product design that they miss the real opportunity to avoid environmental harm. In addition, 17

the choice of system boundary and level of detail to be used in the analysis is linked to the subjective choices made during this phase. For instance, the breadth, “depth of detail and time frame of an LCA may vary to a large extent, depending on the goal and scope definition” [1].

2.3.1.2 Functional Unit

A functional unit is “a measure of the function provided by a product or service”

[19]. Functional units serve as a reference relating the inputs and outputs of products during both the LCI and the LCIA [1] and as the basis for comparing the environmental impact of different products [25]. For example, an LCA examining different packaging options may have a functional unit of “1 m3 of packed and delivered product” and the study may compare different packaging materials, allowing the amount of packaging to vary with the requirements of each material [11]. The choice of functional unit is subjective. There are a variety of functional units that could be used for any LCA, and the goal and scope of the study affects the choice [1]. For instance, “in the case of buildings there are many functional units which could be considered (m2, m3… number of occupants, etc.)” [26]. Unfortunately, different functional units may lead to different LCA results [5][27][28]. For instance, Kim and Dale [27] conducted a study comparing E10 and E85 fuel using two different functional units: (1) one kg of pure ethanol in each vehicle, and (2) one km driven in each vehicle. Analysis using the first option found that E10 was better for the environment, due to the higher gasoline-equivalent fuel economy of the E10 vehicle; however, analysis using the second functional unit arrived at the opposite conclusion - that the E85 was superior because it replaced more crude oil per km [27]. 18

In addition, choosing a functional unit can be difficult because many products are multifunctional, meaning “various potential functional units may not address all functions” [5] and many properties of multifunctional products “may not be quantifiable or are difficult to evaluate” [29]. This can be an issue in the electricity sector, for example, where baseload electricity generators do not provide the same service as intermittent renewable generators due to the differences in the reliability of supply of the two generator types; for these two electricity sources to be comparable using the same functional unit, the intermittent source must be modeled with a storage system [16].

2.3.1.3 System Boundary

“The system boundary defines the unit processes to be included” in the LCA [1]. In both process and hybrid LCA, practitioners select which variables to include in their models of environmental impact and what size of impacts are small enough for them to exclude via the choice of cutoff criteria. Cutoff criteria are typically given as a percentage of the total mass, energy, or some other quantity with environmental significance for the product system being modeled below which the flow is considered negligible [25]. However, the choice of system boundary and cutoff criteria are subjective. The goal, intended use [1], and accuracy required of the results of the LCA [19] affect the choice of system boundary and the level of detail of the study. Cutoff criteria are determined subjectively because the processes excluded from the analysis “have often never been assessed by the practitioner, and therefore, their negligibility cannot be guaranteed” [21].

Determining cutoff criteria objectively would require practitioners to “have a perfect, holistic knowledge of all the possible effects a decision might have on the product system and consequently on the impacts of interest” [5], which is not possible. 19

Unfortunately, the subjective choices made “with respect to the system boundaries and what processes to include within these boundaries… are often decisive for the result of an LCA” [11]. “[T]here is no theoretical or empirical basis that guarantees that a small mass or energy contribution will always result in negligible environmental impacts,” and “although each single cutoff may have an insignificant contribution to the overall result, the sum of all cutoffs may change the results considerably” [21].

2.3.1.4 Timeframe

LCA practitioners also subjectively select a timeframe over which to integrate the environmental impacts of the product studied. The timeframe selected is a value choice related to “ethical views about impacts on future generations” [30]. Infinite time limits discount short-term impacts and are difficult to calculate accurately, whereas finite limits truncate, and thereby discount, long-term impacts [31]. The selected timeframe is relevant because pollution associated with a product can be emitted over thousands of years and have effects on the atmosphere for different periods of time. For instance, over one century, between 10-5 and 10-3 kg of heavy metals in municipal solid waste will be emitted per kg in a landfill, but the full kg of heavy metals will be emitted in an infinite timeframe [30]. Consequently, the selected timeframe can significantly affect the results of the LCA.

2.3.1.5 Allocation

The act of “partitioning the input or output flows of a process or a product system between the product system under study and one or more other product systems” is known as allocation [1]. Allocation is “one of the most discussed” [3] and “one of the most controversial” [11] methodological issues in LCA. Allocation is necessary when the

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product under study includes a multifunctional process in some life cycle phase. It is then important to know how much of the process’s impact should be attributed to the product being studied, and how much of the impact should be allocated to the other products or functions [7]. This occurs, for instance, when a production process has more than one product, when a waste management process has more than one waste flow, and when a recycling process provides both waste management and material production [7].

Unfortunately, it is not clear how best to allocate impacts because there are many plausible methods. Take, for example, “an incinerator for municipal solid waste which receives a large number of products and emits a number of pollutants” [30]. Chlorinated dioxins, a pollutant from the incinerator, could be allocated to the incoming waste components based on their chlorine content, heat value, carbon content, or flue gas volume, and the allocation method selected can have a significant effect on the results [30]. The ISO standard [25] provides guidelines for dealing with the problem of allocation, such as:

(1) avoiding allocation when possible by “dividing the unit process… into two or more sub-processes,” or “expanding the product system to include the additional functions related to the co-products”; (2) when allocation cannot be avoided, allocate the inputs and outputs based on “underlying physical relationships” between the different products or functions; and (3) when underlying physical relationships cannot be used, allocate based on other relationships that exist between the products, such as the relative economic value of the different products. However, the choice of allocation method is ultimately a subjective one made by the practitioner.

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2.3.1.6 Weighting

Weighting is an optional step in LCA [1] wherein different types of environmental impacts – such as noise and climate change – are subjectively assigned weights pertaining to the relative importance of each type of impact. Weighting enables, for instance, 1 km2 of land use impact to be compared to 1 ton of CO2 emissions. If both of these impacts occur in the same product, weighting then allows the numerical combination of these impacts, “even when their units and scales differ” so that the result of the LCA can be a single number representing the entire environmental impact of the product [31]. However, the results of LCAs that use weighting are inherently subjective because the relative weights of different types of environmental impacts must be selected based on the practitioner’s perspective on the relative importance of different types of impacts. As a result, “different parties will reach different weighting results based on the same indicator results” [25]. In addition, the choice to use weighting in one’s LCA is subjective, as is the choice of weighting method [3]. Despite the subjectivity it introduces, “weighting is widely used in practice” [3], although the ISO forbids it from being used in LCA studies that generate “comparative assertions intended to be disclosed to the public” [25].

2.3.2 Limited Applicability of LCA Results

As discussed in the previous section, LCA results are dependent on subjective decisions made throughout the LCA process. Consequently, there are a number of important implications regarding the reliability of LCA results, the types of insights LCA can reveal, and how LCAs can be used. These issues are discussed below.

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2.3.2.1 Uncertainty

First, LCAs contain a significant amount of uncertainty that is difficult, and sometimes impossible, to quantify. This uncertainty has the potential to undermine LCA results and recommendations, preventing deterministic statements from being made about environmental impacts and leading to inconclusive results. Environmental processes are highly complex; humans “have only a limited understanding of the processes that lead to deleterious consequences,” and comprehensive mapping of “even that limited understanding is infeasible for individual” LCAs [15]. “[M]odel imprecision, input uncertainty and data variability” all introduce uncertainty [1] that could potentially undermine the conclusions and recommendations of an LCA. Unfortunately, “uncertainties are often not considered in LCA studies although they can be high” [3]. Even when uncertainties are considered, information regarding uncertainty may be in a variety of forms, making it difficult or even impossible to mathematically combine into a single result [31]. For instance, there is no way to formulate a statistical distribution to describe the uncertainty associated with “the choice of methods for the impact assessment,” the “uncertainties in the described system (e.g. what will the waste management system look like in 15 years),” or gaps in data, such as the significant gaps in society’s understanding of how a wide range of new chemicals behave in the environment [30]. “Given this uncertainty, deterministic statements about environmental impacts are not possible” [15]. In addition, accounting for uncertainty in LCA “can lead to inconclusiveness. A complete representation of uncertainty may entail wide probability

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distributions or broad intervals of imprecision, propagating to results to make the alternatives under consideration indistinguishable” [31]. Even if you had unlimited access to massive amounts of detailed data, it is unlikely that LCA “would yield decisive information” about anything but the simplest of products [24]; even exploring the environmental tradeoffs between paper and polystyrene cups is surprisingly complex [32].

2.3.2.2 Difficult to Compare Studies and Apply Results to Other Problems

Second, LCA results are dependent on a number of subjective methodological decisions, regarding the selected LCA approach, data, and system boundary. This dependency of LCA results on subjective methodological decisions makes it difficult to compare studies and apply results to similar problems. There are many different LCA approaches, including attributional, consequential, process, input-output, and hybrid LCA, which an LCA practitioner can select for any given analysis. Each of these approaches provide different insights into the environmental impact of products, and unfortunately, these differing approaches can generate conflicting results [3][20][33]. For instance, Yue et al. [13] found that as much as 58.4% of the greenhouse gas (GHG) emissions for an ethanol supply chain in the UK came from the input-output portion of a hybrid LCA and would be excluded entirely from a process LCA alone; consequently, the choice of a process, input-output, or hybrid LCA can significantly affect the results. Similarly, choosing an attributional or consequential LCA approach will change the results significantly because these approaches are able to answer different types of questions, and they use different types of data. LCAs are highly dependent on the data used in the analysis and the system boundary selected, limiting the broader applicability of the findings. An LCA result “is a 24

single observation statement” related to running an environmental impact model one time “with a certain set of data and certain system boundaries” [30]. “[A] statement that one product is environmentally preferable to another one is a universal statement” [30]. Universal statements can only be presented as hypotheses or theories that can be falsified but are logically impossible to prove. Anyone can challenge the results of an LCA by asking “for a new situation with slightly different properties that were not included in the original calculations,” forcing the LCA practitioner to admit that the specific situation was not included in the analysis and no universal conclusions can be drawn [30].

The dependency of LCA on subjective decisions makes it difficult to compare studies and apply results to similar problems. “Comparing the results of different LCA or LCI studies is only possible if the assumptions and context of each study are equivalent” [1]. This is often not the case; for instance Khasreen et al. [26] observe that within the literature they analyzed: “there are no two studies which could be directly compared, due to differences in goal and scope of the study, methodologies used to achieve these different goals, and data used.” In addition, it is difficult to take conclusions from specific LCA studies and more broadly apply them to support general high-level policy decisions [11]. This poses a very real problem for researchers hoping to glean information from others’ LCA results, and for those trying to gain a more general understanding of the environmental differences between products or technologies via LCA meta-analyses.

2.3.2.3 LCA Cannot Show That One Product is Environmentally Superior to Another

Third, the subjectivity inherent in LCA makes it impossible to definitively show that one product is better for the environment than another. Many sources acknowledge this problem, stating: LCIA results are not sufficient support on which to base public claims 25

that one product is environmentally superior to another [25]; it is not “possible to show that a product is environmentally preferable to another one” in such a way “that others can reproduce the results and conclusions and that other stakeholders will have to accept the conclusions” using “LCA or any other related tool” [30]; LCA’s “reliance on preferences and the conditions of environmental decision making preclude the existence of uniquely correct methods and results. Competing claims of the environmental superiority of alternative products are therefore permissible” [15]; and “LCA will not provide definite, overall answers that many users may desire or clear unequivocal answers for some impact categories. This significantly limits LCA’s ability… to compare alternatives” [34]. This inability to definitively compare the environmental impact of products arises due to the many subjective decisions that pervade the LCA process. It is not possible to see beyond the subjectivity and, for instance, empirically measure environmental impact and scientifically attribute a certain amount of impact to a product [23], to verify the results of attributional LCAs, nor is it possible to “perform experiments at world level,” including all processes and time integration, to verify the results of consequential LCAs [30]. Instead, practitioners construct models of environmental impact. Many “[e]qually valid models, giving equally valid results, can… be developed from different starting points. It can therefore not be shown which method, or which result,” is correct [30]. Consequently, there is “a proliferation of equally correct methods and answers” to environmental questions, and situations can arise where some practitioners conduct an LCA and find Product A environmentally superior to Product B, and other practitioners legitimately come to the opposite conclusion [23].

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Unfortunately, this means that companies that manufacture products that are harmful to the environment can use LCA in a defensive way to confuse the facts and block policies that might ban its products. “If a product, or material, or policy is under attack… The company or authority under attack can claim that no action should be taken unless the alternatives are shown to be better,” which is “normally not possible” [30]. However, while it is not possible to show that one product is environmentally preferable to another via LCA, it is possible to use LCA to explore what the possible unintended side effects of switching products might be. For instance, if designers know that PVC flooring has additives they would like to avoid, they can use LCA “to consider the whole life-cycle of PVC and its alternatives” to try to ensure new, worse problems do not crop up when they switch materials [30]. While the results of such an analysis would contain “uncertainties and data gaps,” it may be possible to see, for instance, that polyolefin flooring avoids PVC’s environmental problem and does not result in any known major issues, whereas linoleum floorings avoid PVC’s problem but are associated with serious waste management concerns [30]. A material decision could therefore be made based on this analysis in favor of polyolefin flooring, even though the LCA does not show that polyolefin flooring is definitively environmentally preferable to the other options.

2.3.2.4 LCAs Do Not Predict Actual Environmental Impacts

Finally, a major limitation of LCA is that it does not, in fact, predict the actual environmental impact of a product. According to the ISO, “LCA addresses potential environmental impacts,” but “does not predict absolute or precise environmental impacts” [1]. Other sources agree: “LCA cannot quantify actual environmental effects or easily incorporate the multiplicity of other relevant factors necessary to determine actual impacts” 27

[34], and “LCIA results do not predict impacts on category endpoints, exceeding thresholds, safety margins or risks” [25]. LCA is unable to predict actual environmental impacts because: (1) potential environmental impacts in LCA are calculated relative to a functional unit [1], a measure that is “inadequate to deal with a multitude of factors involved in actual impacts” such as the overall quantity of units produced [34]; (2) environmental data is aggregated over space and time in an LCA [1], removing important details pertaining to threshold and dose- response information [25], and causing all emissions to be assumed to have environmental effects, an assumption which “goes beyond worst-case” scenarios and normally would “be considered either grossly conservative or unacceptably inaccurate” [34]; (3) there is inherent uncertainty in environmental impact models [1] and the precision in impact categories varies significantly [25]; (4) it is difficult to predict future environmental impacts [1]; and (5) personal values underlie many decisions in LCA [25].

The fact that LCA does not predict the actual environmental impact of products poses a major problem for LCA because the main purpose of the method is to learn about environmental impacts so that design or purchasing decisions can be made to better protect the environment. If LCA cannot predict the actual environmental impact of products, what assurance do decision makers have that their decisions based on LCA results will be any better for the environment than the alternative? A number of authors respond to this question by presenting LCA as an environmental systems analysis tool [30] or a decision support tool [15] that provides information about different parts of a product’s environmental impact to help make better decisions. LCAs help practitioners think through the many aspects of a product’s 28

environmental impact in each life cycle stage, identifying significant impact areas and weighing environmental tradeoffs. Consequently, authors claim that LCAs “provide a better basis for the decision making process” than intuition alone [30], and they state that “[a]n imperfect assessment is more likely than no assessment at all to lead to better- informed decisions” [15].

2.4 CONCLUSION

LCA is the method of choice for product designers trying to understand the environmental impact of their products and reduce that impact. While the most common type of LCA performed is an attributional, process LCA, there are many other approaches with different implications for the analysis. Process, input-output, and hybrid LCA differ in their detail and how they draw system boundaries. Process and hybrid LCA can both be quite detailed. Input-output LCA and hybrid LCA both have system boundaries that are very broad and encompass economic activity in a country’s economy. Given unlimited time, money, and data access, the best approach available is hybrid LCA, which can include a very detailed process model and then use input-output data to fill in the gaps that would otherwise be cutoff. Attributional and consequential LCA are very different approaches that answer different types of environmental questions. Attributional LCA can help identify who or what is responsible for a product’s environmental impact as well as ‘environmental hotspots’ that could be the focus of product redesign. Consequential LCA can determine the effects of change on the overall environmental impact – what happens if consumption decreases or increases either a little or a lot and what the impact of a new policy might have. 29

Regardless of the method chosen, LCA results are fundamentally subjective because of the subjective decision making pervasive throughout the LCA process. LCA results are not repeatable, scientific, or empirically verifiable. Consequently, basing environmental decisions on them may or may not contribute to actual environmental benefit, and it is unwise to apply results generated by researchers for a specific purpose to a different problem or context without careful analysis.

Rather than being a scientific environmental impact measurement technique, LCA is a decision support tool that helps practitioners identify the major environmental impact areas of concern for a product, understand tradeoffs, and get a sense for the overall environmental impact. LCA informs decision makers about the environmental implications of a product, and while it is by no means perfect, it is likely to result in better outcomes than if the decision maker had remained entirely uninformed. However, there is clearly significant space for researchers to develop improved, and more objective techniques for assessing the environmental implications of products. The next chapter provides further background information for this work. It delves into the specifics of how the choice of scale and system boundaries affect the outcomes of LCA.

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Chapter 3: Scale and System Boundaries

This chapter provides background information related to the scale of the analysis and the implications of choosing very broad – or very narrow – system boundaries when modeling environmental impact.

3.1 SCALE

3.1.1 What is Scale?

The scale of the analysis is reflected in the selection of functional unit. The larger the functional unit, the larger the scale of analysis. For instance, an LCA could analyze the environmental impact of electricity on a small scale (1 kWh consumed, a household’s daily consumption) or a large scale (national or global annual electricity consumption). Similarly, an LCA analyzing the impact of food consumption could use a small-scale functional unit, such as “having one meal,” or it could have larger-scale functional units, such as “living of one person for one year” or “subsistence of the world’s population for one year” [23]. As discussed in Chapter 2, the choice of functional unit is subjective and can alter the results of the study. Typically, the scale of analysis is selected based on the level at which a decision will be made. For instance, if a company is commissioning an LCA to inform an environmentally-motivated decision (e.g. whether to establish a product take- back program) the analysis is performed at a level of the company’s decision (the level of all products expected to be taken-back). Alternatively, if the purpose of the LCA is to help consumers make environmentally-friendly decisions, the analysis is conducted at the consumer level (focusing, for instance, on the impact of one product).

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3.1.2 The Effect of Scale on LCAs

The scale of the functional unit influences the focus of the LCA practitioner and the aspects of the product/fleet/industry/economy that are modeled in detail verses those that are assumed-away or modeled using averages or approximations. Small-scale analyses are more likely to have accurate data for low-level impacts and make assumptions about high-level phenomena, whereas large-scale analyses are more likely to have accurate high- level data and use averages and assumptions to account for small-scale phenomena. For instance, an LCA analyzing the impact of one solar PV panel is likely to have more detailed modeling of the technical aspects of the panel itself, the manufacturing process for the panel, assumptions about specific weather patterns, and detailed data related to the panel’s assumed performance, with general assumptions about equipment impacts that contain implicit assumptions about the total number of panels produced on the equipment. In contrast, an LCA analyzing the impact of a solar PV fleet is likely to have much more detailed and well-supported assumptions about the total fleet size, the timing of the fleet production and its effect on manufacturing equipment impact, but perhaps less information and more assumptions regarding the technical details of the panels. Choosing the right scale of analysis is important because it determines the types of environmental issues raised through the LCA and the types of solutions that will be proposed. Thus, the scale of analysis can significantly affect the conclusions of an LCA. For instance, Field et al. “demonstrate that a conventional crossover analysis based on a product life cycle can yield results that are very different from those developed when the entire fleet of products… is taken into consideration” [35]. The scale affects the conclusions because it alters the assumptions made in the analysis and also because higher-level

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analyses inherently account for the total quantity of impacts and therefore recognize more clearly any environmental economies of scale that may exist.

3.1.3 Preference in LCA for Small-Scale Analyses

In practice, the vast majority of LCAs adopt a small-scale, “product-centered” [35], “micro” perspective [10]. Hanes and Bakshi [19] agree, stating:

Most sustainable engineering methods… model the system of interest in detail at the smallest relevant scale, using fundamental engineering models or plant- or product-specific data. The larger scale life cycle is modeled in less detail using empirical data that represents regionally average production technology.

However, it can be risky to choose too small a scale of analysis; a small functional unit could cause practitioners to be so focused on minute details of product design that they miss the real opportunity to avoid environmental harm. For instance, “A team of design engineers may struggle for months over whether it is ‘preferable’ to use an aluminum or a plastic radiator-cap, while more fundamental questions about the sustainability of the gasoline-powered automobile are never raised” [24]. Similarly, airlines may tout the benefits of the aluminum saved through their ‘sustainability effort,’ but the bigger questions regarding whether the airline’s “overall operations—or commercial aviation itself—can long be sustained on today’s scale” are never posed [36]. This problem is common; many ‘sustainable’ designs are simply product or process tweaks, with the term ‘sustainable’ “at best indicating a practice or product slightly less damaging than the conventional alternative” [37]. In addition, LCA practitioners often are not motivated to do large-scale LCAs because there are few actors at this scale who benefit: “It is by no means certain that efforts to optimize environmental performance beyond the

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realm of an individual firm – and hence the realm of an individual firm’s financial liability – would increase profits” [24]. However, the environmental problems of concern to sustainable product designers and eco-conscious consumers – climate change, biodiversity loss, toxic impacts on humans – occur on large scales, and it may be advantageous to focus efforts at achieving accuracy in analyses at these higher levels where the impacts of concern occur. Field et al. [35] echo this argument when they state that “the product-centered focus of life-cycle assessment… embeds assumptions that may conflict with the realities of environmental problems” and that “a “fleet-centered” approach” is preferable because it “eliminates certain simplifying assumptions imposed upon the analysis by a product-centered approach.”

3.2 SYSTEM BOUNDARY

As mentioned in Chapter 2, system boundaries dictate the scope of an LCA and the processes and activities that are to be included in the study. The system boundary represents the barrier between processes modeled in detail and processes that are either assumed to have negligible effects (as in process LCA) or are represented using average data (as in hybrid approaches and input-output LCA). For instance, an LCA practitioner might assume that the GHG emissions associated with electricity consumed at a paper mill are the same as those for average emissions on the US electric grid if the electricity consumption of the paper mill is on the boundary of the system analyzed, but he or she may get detailed electricity emissions information if the electricity consumption of the mill is included within the system boundary. For any scale of analysis, there can be broad or narrow system boundaries (corresponding to the detailed analysis of either many or few entities on the

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selected scale of the functional unit), with broader system boundaries corresponding to a more detailed analysis. The choice of system boundaries can significantly alter the results of an LCA. Chapman [38] notes, for instance, that a study of the energy consumption of an electric furnace (with a thermal efficiency of 61%) and a standard fuel-heated furnace (with an efficiency of 27%) will arrive at opposite conclusions if the system boundary is set narrowly around the company (which will see less energy consumption if the electric furnace is chosen due to the higher efficiency) as opposed to if the boundary is set at the national level (and includes the efficiency of electricity production in the UK, which is given as 25%). Chapman concludes: “Thus the 2 to 1 ratio in favour of electric furnaces becomes almost a 2 to 1 ratio against… It is a disturbing conclusion that in good faith an industry could improve its own thermal efficiency whilst increasing the national energy consumption” [38].

Narrowly-focused studies with a smaller system boundary make general assumptions about the things outside the system boundary. These assumptions may have a significant effect on the result compared to an analysis of the broader system using detailed, context-specific data. Worryingly, a small system boundary can generate misleading results. O’Rourke et al. [24] state for instance, that “anything it seems can be an optimized industrial ecosystem” if the system boundary is “small enough”; for instance, coal mining can be considered an industrial ecosystem if one considers only the goal of eliminating waste from the processing and fails to account for the impact associated with losing fossil fuel resources and generating CO2 emissions.

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Ideally, the system would be scoped in such a way that the inputs could “be traced back to raw materials as found in nature” and “the outputs should ideally be emissions to nature” [3]. However, “Expanding the life cycle boundary is… impractical and computationally intractable for moderately large life cycle networks” [19] because product life cycles can be expanded almost indefinitely without capturing all inputs from nature and outputs to nature because of the interconnections within the economy. Chapman [38] states, for instance:

The production of a consumer product in the UK requires inputs from all the production processes in the country and, through international trade, from all the production processes in the world. For example, a loaf of bread requires wheat which has to be milled, cooked and transported. Transport requires fuel and vehicles, for which steel, rubber, copper and energy for fabrication are necessary. Shops and bakeries need bricks, steel, cement, wood and glass; wheat production must have tractors, fertilisers, insecticides etc. It is clearly impossible to determine the proportion of all the production processes in the world needed to produce a loaf of bread, or any other single product.

Likewise, Udo de Haes and Heijungs [39] provide a similar example:

In the… case of the transportation of collected glass, the fuel of the trucks is generally included, not the production of the trucks and even less the building of the factory in which the trucks were constructed. There is always a process behind a process. In general, LCA stops before the capital goods, in this case the production of the truck, but this is arbitrary and it is unknown what the relevance is of the not-included processes.

3.3 CONCLUSION

This chapter provided background on how the scale of analysis and choice of system boundaries affects the focus and results of LCAs. The scale of analysis has to do with the size of the functional unit, with, for instance, larger-scale analyses focused on an industry and smaller-scale analyses focused on a single 36

product. The scale of analysis influences the focus of the LCA practitioner and can significantly affect the results of the study. Although it is most common to conduct LCAs with a low-level functional unit, larger scales of analysis may be more advisable because the benefits that are found at larger scales of analysis are more likely to correspond to environmental benefits on the scales of interest when addressing environmental problems. Along a similar vein, the choice of system boundaries dictates the scope of an LCA and the processes to be included in the analysis in detail. The system boundaries selected can significantly influence LCA results. More narrowly-focused LCAs are less accurate because they model fewer processes in detail. However, there is a limit to how broadly- focused an LCA can be because the interconnected economy means there is an almost infinite number of processes that could be included in an LCA at any level of scale, and there is a finite amount of time LCA practitioners can spend modeling the processes for any given study.

The next chapter provides further background information related to network- related approaches to environmental assessment.

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Chapter 4: Network-Related Approaches to Environmental Assessment

In addition to LCA, there are numerous other approaches to assessing environmental impact of products, processes, and decisions. This chapter provides an overview of five existing approaches to reducing the environmental impact of designs that use network-related concepts.

4.1 INDUSTRIAL ECOLOGY

Industrial ecology (IE) models industrial systems in a manner patterned after natural ecosystems [40][41]. It combines elements of ecology and economics, studying the flows of energy and materials in both the ecosphere and the anthroposphere [42]. Aspects of natural ecosystems frequently discussed in IE literature “include closed materials cycles, evolutionary principles, resiliency of systems, and dynamic feedback” [24]. For instance, Frosh states that “In nature an ecological system operates through a web of connections in which organisms live and consume each other and each other's waste… nothing that contains available energy or useful material will be lost” [43]. In the IE analogy, the organism is “the industrial process or the set of industrial processes that leads to a particular product or product family” and ecology is “the network of all industrial processes” that “interact with each other” both economically and through “direct use of each other's material and energy wastes and products” [43].

IE is focused on dematerialization, which it seeks to achieve through closed-loop material networks patterned after those found in ecosystems [44] “so that the by- products… of one company are used as raw material by another company” [45]. IE achieves resource efficiency by “Reusing, remanufacturing, and recycling end-of-life

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products, using the wastes of one production process as inputs to another, and redesigning products, processes, and supply chains for improved efficiency” [46]. It is typically “applied at a local or regional level” and consequently emphasizes the importance of “interorganizational cooperation for sustainable development… whether in eco-industrial parks and regional networks or along the supply chain of certain product systems” [45] so that “companies, organizations and communities” can “work together to minimize environmental impact and use” each other’s waste [47]. Hence, IE deals with material flow networks. As a result, Schiller et al. [48] have commented that network analysis is a

“promising method to mediate between industrial ecology’s overall systems approach and the complex structures found in society.” IE is an umbrella topic that includes sustainable design, LCA, industrial symbiosis, and industrial metabolism, among others [24]. IE includes design for environment at a facility or firm level, industrial symbiosis and the study of eco-industrial parks at the inter- firm level, and materials and energy flow studies as part of the study of industrial metabolism at the regional or global level [49]. Some of these other topics will be discussed below.

4.2 INDUSTRIAL SYMBIOSIS AND ECO-INDUSTRIAL PARKS

Industrial symbiosis (IS) is a subset of IE, with a focus on the development of eco- industrial parks and organizing inter-firm relationships [49][50]. IS is a research discipline that examines how companies or facilities in “traditionally separate industries” can work collectively to physically “exchange… materials, energy, water, and/or by-products” [49] in a way that “yields mutually profitable transactions” [51] and reduces the collective environmental impact of the group by using the waste of one facility as raw material for 39

another [45]. Originally, IS focused on the exchange of materials and energy, but it was extended to include the sharing of information, logistics, and assets of companies [51]. IS exchanges occur at the level of firms [45][49] amongst colocated companies [44][50][52]. These exchanges are viewed as a network. IS networks allow for “novel sourcing of required inputs, value-added destinations for non-product outputs, and improved business and technical processes” [51]. To be considered IS, “at least three different entities,” “none of which is primarily engaged in a recycling-oriented business,” “must be involved in exchanging at least two different resources” [53].

The primary objective of IS from a sustainable design perspective is that it helps companies collectively achieve a lower environmental impact by making use of others’ waste within the system, reducing overall waste and increasing efficiency [47][54][55]. For instance, IS can improve the environment by “increasing energy efficiency through cogeneration and by-product reuse, recycling graywater to achieve overall reduction in drawdowns, recovering solvents, and reusing many, diverse residue streams that need not be rejected as wastes” [49]. In addition, the synergies created in IS networks can achieve greater resource efficiency than “can be achieved by fragmented pursuit of improvements in individual units” [56]. However, the environmental benefits conferred do not appear to be the main motivation for companies to engage in IS. Instead, “conventional business reasons” related to cost savings, enhanced “long-term resource security,” and “regulatory or permitting pressure” are the main motivation [53].

“Eco-industrial parks are… concrete realizations of the industrial symbiosis concept” [49]. They are communities of businesses that strive to achieve greater collective “environmental and economic performance through collaboration in managing 40

environmental and resource issues” than would be possible if each company “optimized its individual performance” separately [57]. The most famous eco-industrial park is in Kalundborg, Denmark, where “some significant…. environmental benefits have been achieved as a result of direct substitution, utility-sharing, and water/energy cascading” [50]. Unfortunately, the environmental benefits of IS are generally assumed, but not always well-studied. Authors state, for instance, that “the ecological impact that results from increased linkages among firms is one of the neglected outcome variables in” IS literature [52] and “symbiotic relationships… are presumed to provide environmental benefits, although these benefits have seldom been carefully measured” [53].

4.3 MATERIAL FLOW ANALYSIS

Material flow analysis (MFA) studies the stocks and flows of materials and goods through industrial sectors, ecosystems, and within individual industrial installations using modeling of various system elements based on mass balances [58][59][60]. It provides “information regarding the patterns of resource use and the losses of materials entering the environment” [58], identifying “potentially harmful or beneficial accumulations and depletions of stocks” [61]. Consequently, it is “a suitable tool for assessing long-term trends in material use” and “for studies involving resource scarcity and recycling from old scrap” [60]. MFA can be performed on a variety of scales according to the focus of the study.

For instance, when it is performed “on a national or regional scale… the material exchanges between an economy and the natural environment are analyzed,” whereas when MFA is performed on the scale of an industrial supply chain, the goal is to “optimize the production 41

processes so that materials and energy are used more efficiently… e.g., by recycling and waste reduction” [60]. LCA and MFA have many differences. LCA accounts for all relevant materials used to perform a function in a single product, whereas MFA is focused on tracking one (or a few) types of material flows in many products [58][60]. Unlike LCAs, MFAs do not typically include “impact assessment” [60], and “MFA is limited to a certain geographical entity (e.g., company, country, world) for a certain time period (days, years, etc.),” whereas an LCA “includes all relevant flows associated with a specific product or service, no matter where or when they occur” [58].

4.4 EXERGY FLOW ANALYSIS

Exergy is defined as “the measure of potential work embodied in a material” [62] and “the maximum theoretical useful work… obtainable as the system is brought into… equilibrium with the… environment” [63]. Unlike energy, exergy is not conserved. Instead, exergy measures “the degradation of energy (i.e., the decrease of its capacity to generate useful work) in conversion processes” [64]. Exergy loss in the form of “low temperature heat” and “chemically or physically reactive materials” can serve as a proxy for environmental damage [62]. “[B]y accounting for all the exergy streams of the system it is possible to determine the extent to which the system destroys exergy… The destroyed exergy… is responsible for the less-than-theoretical thermodynamic efficiency of the system” [65].

Exergy analysis involves performing an exergy balance on a control volume and “tracking and quantifying exergy destructions and efficiencies” [64]. Exergy can also be

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tracked through the production of a product, with each process viewed as adding “some exergy to its inputs” and destroying “some exergy in its internal irreversibilities” [66]. Exergy analysis can be used to improve “the efficiency of processes and systems” [67] by determining “the location, type, and true magnitude of the waste of energy resources” in products, industrial sectors, or an entire nation [68]. It can be used “in LCA… as a rough indicator for total environmental impact, or when performing an improvement assessment for identifying losses of useful energy. Exergy may also be used as a measure of the depletion and use of energy and material resources” [69].

4.5 INDUSTRIAL METABOLISM

The field of industrial metabolism is closely related to both IS and MFA and is sometimes considered a part of both fields [70]. Within the field of industrial metabolism, “industrial organizations are likened to biological organisms that consume food and discard waste products” and are “described by a conceptual material flow model” that encompasses

“the complete, end-to-end flow analyses from the time of "production", i.e. removal from a geochemical reservoir, to its fate in the receiving reservoir” [71]. Consequently, “Industrial metabolism focuses on analysis of materials stocks and flows, and potentials for reducing materials and energy dissipation in the environment” [24]. Its goal “is to analyze the entire flow of materials and identify and assess all possible emission sources and other effects in connection to these flows” [72]. Within industrial metabolism, flows of materials are tracked “along product life cycles, through whole economies, or along the paths of a single substance. These tools have been used in the design of product systems… with lower environmental impact” [44].

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4.6 CONCLUSION

This chapter provided an overview of five existing approaches to assessing and reducing the environmental impact of designs that use network-related concepts – industrial ecology (IE), industrial symbiosis (IS), material flow analysis (MFA), exergy flow analysis, and industrial metabolism. IE studies the flow of energy and materials between the ecosphere and anthroposphere, focusing on dematerialization and the development of closed-loop material cycles for human-made processes analogous to those found in biology. Similarly, IS focuses on the study and development of groups of companies cooperating to achieve greater resource efficiency than would be possible if each worked to reduce its environmental impact alone. MFA is a related field focused on analyzing the stocks and flows of one material or product through an economy, to glean an understanding of patterns of resource consumption and identify areas where resources accumulate or are depleted. Exergy flow analysis tracks the flow of exergy through a system to identify areas where efficiency improvements could be made. Finally, the field of industrial metabolism deals with modeling industrial organizations like biological organisms that consume resources and release wastes into the environment, with the flows of materials traced along product life cycles for the purposes of reducing environmental impact. The discussion presented in this chapter of the network-related techniques for assessing and improving the environmental impact of products will be brought to bear in Chapter 10, where the new paradigm for environmental impact and environmental sustainability is presented.

The focus of this work now shifts from presenting background information to exploring the effect of context in LCA and sustainable design. The next chapter delves into

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the specifics of how contextual factors affect the amount of environmental impact associated with a product and the amount of environmental damage associated with a particular type of impact.

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Chapter 5: The Effect of Contextual Factors on Environmental Impact and Environmental Damage

One problem in LCA and sustainable design that merits in-depth attention is the important role context plays in determining environmental impact and environmental damage. A product’s context encompasses the specific situations, settings, and the state of the environment surrounding the product throughout its life cycle. Each context is comprised of many different contextual factors, location- and time-specific elements of context, such as the source of electricity at the location of manufacture, the temperature at the location of use, and the proximity of a recycling facility to the location of disposal. The purpose of this chapter is to think more carefully about context and its effect on the environmental impact of products and the environmental damage caused by certain types of impacts. Section 1 shows how contextual factors can significantly alter the size of a design’s environmental impact. Section 2 discusses how and why different amounts of environmental damage may result from a given amount and type of environmental impact in different contexts. Section 3 provides examples of contextual factors to consider when assessing the environmental impact of products. Section 4 addresses the difficulty of accounting for context in prospective LCA. Section 5 presents the reasons contextual factors are often neglected in LCAs and how this limits LCA. Finally, Section 6 provides a summary of findings from the chapter.

5.1 THE AMOUNT OF IMPACT DEPENDS ON CONTEXT

The amount of environmental impact associated with a particular design is determined in part by contextual factors. For instance, the location of use is a contextual factor that may affect the environmental impact of the product in a number of ways, such 46

as how and how far the product must be transported (and, accordingly, the energy and emissions associated with transportation); the conditions during use, such as temperature or presence of corrosive materials (which affects product efficiency and lifetime); and proximity to a recycling facility (altering the likelihood of recycling at the end-of-life). Consequently, for every design, there is a distribution of environmental impacts identical products will have due to differences in contextual factors over each product’s life cycle.

This section addresses the variation in environmental impact as a result of contextual factors. It is broken into four parts. The first three review work concerning the variation in impact due to differences in: (1) user characteristics and behavior, (2) the usage context, and (3) the available technology and infrastructure. The final part uses the example of a solar PV panel to show how contextual factors can affect the environmental impact of a product in every life cycle phase.

5.1.1 User Characteristics and Behavior

This section reviews previous work in LCA and sustainable design literature concerning the variation in the environmental impact of products due to differences in user characteristics and behavior. Here, ‘user characteristics and behavior’ encompasses a number of contextual factors, such as who uses the product (user demographics, their skills, knowledge, and background), how the product is used (frequency of use, misuse, and user habits with the product), and what the product is used to do (a specific customer’s needs and the function the product is performing for that user). A number of authors

[29][73][74][75][76] have discussed these factors and have shown how user characteristics and behavior can influence the environmental impact of products by, for instance, altering the product’s performance and lifetime. 47

Many examples of how user characteristics and behavior affect the environmental impact of products have been discussed in literature. For example, the environmental impact of an electric kettle can be influenced by how attentive the user is – how promptly he or she turns off the kettle when it has reached the desired temperature and whether the user heats more water than is needed [73]. Similarly, the environmental impact of household refrigerators is affected by “consumer behaviours such as the frequency of shopping… door opening and food consumption,” the temperature the user sets for the refrigerator, the temperature of the food placed in the refrigerator, and how full the refrigerator is kept [77]. In addition, the primary factor in determining the environmental impact of a flooring material is its achieved lifetime, which is frequently ended prematurely by the consumer due to changes in taste [76]. Finally, important contextual factors for a washing machine and dryer include behavioral factors, such as the choice of wash temperature and how full the washing machine is at the time of use [8].

Importantly, certain user characteristics and behaviors can entirely negate the environmental benefits of ‘sustainable’ products and can actually harm the environment more than ‘unsustainable’ alternatives; ‘sustainable’ or ‘low-impact’ products or features may not achieve their intended environmental benefit if they are not used correctly, or if they are not used at all. For instance, programmable thermostats have the potential to help homeowners save energy on heating and cooling, but their efficacy is dependent on the occupants actively selecting “settings that result in savings” and is undermined when users of programmable thermostats are less inclined to turn their heating and cooling systems off entirely than they would be if they had a manual thermostat [78]. In addition, Derijcke and Uitzinger [79] studied sustainable housing projects, and found that many “residents did not 48

know that their toilet had a flush stop, and therefore did not use it” and that a misunderstanding of the markings on the ventilation system was held by more than 25% of the residents, causing “those residents… to use the ventilation at a higher level than necessary… wasting energy.” It is worth noting that the characteristics and behavior of someone other than the user of a product during the use phase may affect the environmental impact of a product.

For instance, the driving style of a truck driver will affect the energy efficiency of transit and the transportation impacts of all products that person transports. Similarly, the sorting practices of the operator of recycling equipment will affect the quantity and purity of the recycled material and, hence, the end-of-life impact of all products that person recycles. Hence, the variation in environmental impact caused by differences in user characteristics and behavior is not limited to the use phase of a product.

5.1.2 Usage Context

Another area of focus for researchers in LCA and sustainable design is how differences in usage context can affect the environmental impact of identical products. For the purposes of this work, ‘usage context’ includes “all aspects describing the context of product use that vary under different use conditions and affect product performance,” excluding user characteristics and behavior, product attributes [80], and differences in interacting technologies and infrastructure. There are numerous examples of important usage context factors that affect the environmental impact of designs. For instance, the environmental impact of household refrigerators is affected by whether the refrigerator is in direct sunlight or located near a heat source, as well as the ambient temperature of the room [77]. Similarly, the 49

environmental performance of a net zero energy building is influenced by a number of weather-related factors, such as the temperature (affecting the heating and cooling load) and the availability of solar and wind resources [81]. In addition, the environmental impact of a dryer is affected by the temperature at the location of use [8]. Also, more generally, “product lifetime can be influenced” by contextual factors during use, such as “the introduction of an alternative product with different or additional features” and “the environment in which the product is used (wet, dry, salty, hot, cold, acidic, basic, etc.)” [29].

The variability in environmental impact due to contextual factors has important implications for product designers. In some contexts, a particular design decision will be “highly beneficial,” but, in another, “the same decision may offer limited benefits or even penalties in terms of environmental performance” [73]. Previous work has used probabilistic graphical modeling to account for the effect of different usage scenarios and

“to estimate variable energy performance and identify types of users and situations that most exploit the proposed solutions” [73]. As in the section above, it is important to mention that the differences in usage context can affect the environmental impact of products outside of their use phase. For instance, the energy consumption of a refrigerated truck during its use phase is affected by the outdoor air temperature; consequently, this usage context factor will influence the environmental impact of all products shipped in the truck during their transportation phase.

Similarly, the availability of sunlight at the location of use significantly affects the amount of electricity generated by a solar PV panel during its use phase; if a PV panel and diesel generator together provide the electricity used to run manufacturing equipment, then the 50

local sunlight availability will influence the environmental impact of all products produced on this equipment during their manufacturing phase.

5.1.3 Available Technology and Infrastructure

The third source of variation in environmental impact of identical products that is discussed in the literature is the difference in available technology and infrastructure in locations throughout a product’s life cycle. Every location has a unique set of mining, manufacturing, transport, and waste disposal technologies available in it, something Reap et al. [5] refer to as “local technical uniqueness,” and this set of available technologies changes over time. The mix of technologies present in a location may arise as a result of financial realities, locally-available resources, or public policies promoting or banning certain options, for instance. Because the technology and infrastructure in different locations vary, the same product manufactured, used, transported, etc. in different locations or in the same location at different times may have very different environmental impacts;

“Differences in technology levels, existing at the same moment in the same country (or even at the same factory), can in some cases result in order of magnitude differences in emissions” [30]. These location-based technology (and impact) differences are more significant for some types of processes and products than others. For example, “electricity generation, road transportation, cement manufacturing, and agricultural production” have “continental, national, or even regional properties,” while “oil extraction in the Middle East or steel manufacturing in Asia” have far less variety in technology and process types used [11]. At any rate, it is possible for contextual technology and infrastructure differences to cause significant variations in the environmental impact of products in every life cycle 51

phase. Manufacturing technology, for instance, clearly can differ significantly in its environmental performance depending on location. A product made in a facility that gets most of its electricity from a coal power plant would have significantly higher GHG emissions impacts than if that same product were manufactured in a location that received most of its electricity from nuclear power. Similarly, the mercury emitted during PVC production is substantially different if chlorine produced “with mercury cells is compared to other technologies” [30]. In addition, certain modes of transport are not available in some locations due to financial or physical constraints (water bodies, mountains). This limits the modes of transportation that can be used and, consequently, alters the environmental impact of products whose shipping route passes through affected locations. For instance, two identical products that need to be shipped the same distance may have very different impacts if one is shipped via rail and the other is shipped via plane, and these shipping choices may be dictated entirely by the type of transportation infrastructure available between the origin and the destination. Also, different locations have different types of recycling and waste disposal infrastructure available. If no recycling system is in place near the location of use, it is not possible for the consumer to recycle a product even if he or she has the motivation to do so

[82], leading to differing environmental impacts for the same product used by the same user in different locations.

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5.1.4 Contextual Factors Can Affect the Amount of Impact in Every Life Cycle Phase – Solar PV Example

As discussed above, the amount of environmental impact generated by a design can be altered by user characteristics and behavior, the usage context, and the technology and infrastructure available in locations throughout the life cycle of a product. This section shows that contextual factors could significantly alter a design’s environmental impact in every life cycle phase. Below, relevant contextual factors in each phase of the life cycle of a solar PV panel are identified. For the sake of simplicity, only contextual factors that affect GHG emissions impacts will be discussed.

5.1.4.1 Materials Production

The amount of GHGs emitted during materials production depends on the location and time of extraction, due to variations in environmental laws and in the energy mix used to run extraction and processing equipment. One would expect, for instance, that the processing of silica sand into glass for PV panels would have much greater GHG emissions in a location that obtains a high percentage of its electricity from coal, as opposed to locales with a high percentage of nuclear energy.

5.1.4.2 Manufacturing

Similarly, the source of electricity used during manufacturing has a significant effect on the GHG emissions associated with PV panels. The largest source of GHG emissions during the life cycle of solar PV is the electricity used to manufacture the panel

[83]. Pacca et al. [84] found that manufacturing a KC120 multi-crystalline PV panel using only electricity generated from other KC120 multi-crystalline PV panels resulted in a 68% decrease in CO2 emissions, compared to manufacturing the panel using electricity from the 53

grid. In addition, Reich et al. [85] examined how the energy supply mix can affect the GHG emissions impact of crystalline silicon solar PV panel production and found that manufacturers’ electricity mix can add anywhere from 0 to 200 additional gCO2-eq/kWh to the GHG intensity, depending on whether the electricity to run the processes comes from solar PV or from coal, respectively. Also, the quality of the manufacturing equipment and processes affect the GHG emissions associated with solar PV during manufacturing. If manufacturing processes are poor, scrap rates will be higher and average lifetimes of panels produced may be lower.

GHG emissions associated with making these scrapped or prematurely-failed panels ought to be accounted for and averaged out over the other panels produced at the same manufacturing location. Consequently, manufacturing processes that have high scrap rates or result in poorly-made panels are likely to produce panels with higher GHG emissions.

5.1.4.3 Transportation

The magnitude of GHG emissions during transport is directly related to the geographic dispersion of the supply chain, i.e. the distances between the locations of material extraction, manufacturing, sales, use, and disposal. In addition, GHG emissions volumes depend on the modes of transportation available between these locations. Supply chains located in a small geographic area with energy efficient modes of transport are likely to release far fewer GHGs than the alternative.

5.1.4.4 Use

The GHG emissions benefit of a PV panel compared to other sources of electricity is entirely dependent on its performance in the use phase. The more electricity produced

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over the life of the panel, the fewer average emissions per kWh electricity produced, the greater the opportunity to avoid GHG emissions from the grid, and the greater the likelihood that the overall emissions balance will be favorable for PV. One of the critical contextual factors that determines PV panel production is the amount of solar irradiation a panel sees over its lifetime, which is dictated by the location of use and timing of other effects. The latitude, the time of year, weather effects such as cloudiness/dustiness, being shaded by a tree or building at certain times of the day, and propensity to be obstructed by snow, sap, leaves, dust, etc., together can significantly affect the solar irradiation seen by a panel. In a life cycle harmonization study conducted by NREL, for instance, estimates for solar irradiation ranged from 900-2,143 kWh/m2/year in the studies analyzed [86]. In addition, many other contextual factors affect the amount of electricity produced by a PV panel over the course of its lifetime, including the temperature at the location of use (affecting panel efficiency), the diligence with which the owner keeps the panel clean and well-maintained, and a wide range of factors that could reduce panel lifetime – such as tornadoes, fires, high winds, lightning, falling tree branches, and errant baseballs. In addition to the amount of electricity produced by a panel during its lifetime, the environmental benefit of a panel is determined by the type of electricity the PV electricity replaces. For instance, if a given amount of PV electricity displaces electricity generation from coal, the reduction of GHG emissions to the atmosphere is much greater (and the benefit of the PV panel is much greater) than if the PV electricity displaces generation from a nuclear plant. The type of electricity a PV panel displaces is dependent on a number of contextual factors, including the electricity generation mix on the grid at the location of 55

use, and the demand on the grid at times when the PV panel is producing electricity (which is affected by the time of day, time of year, and local weather conditions). Together, these two factors – PV panel production and the type of electricity the PV panel replaces – can cause enormous variability in the environmental benefit of a PV panel over its lifetime. For instance, Siler-Evans et al. [87] estimated “the combined health, environmental, and climate benefits from wind or solar” and found that these benefits differ for locations across the US by a factor of 10 as a result of the varying availability of sunlight or wind, as well as the type of marginal electricity emissions on the grid at the location of use.

5.1.4.5 End-of-Life

There are a number of disposal options for PV panels at their end of life. Ultimately, the method of disposal is dependent on the options available and on decisions made by the panel owner, which are influenced by local environmental regulations, existence (or lack) of local markets for recycled material, the cost of disposal, and the owner’s knowledge and beliefs about the options. If there is no market for materials that can be recycled from used solar panels, or if the salvage value of the panels is low, recycling programs may not exist. Furthermore, the cost (and likelihood) of dismantling and recycling the solar PV system changes with location. Fthenakis [88] estimates the cost of recycling CdTe PV modules to be approximately 4–5¢/W in areas where many panels are concentrated and approximately 12¢/W for dispersed PV installations. In addition, the GHG emissions impacts associated with each disposal option are dependent on the type of electricity or fuel consumed in the recycling plant and the efficiency of the recycling process.

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5.1.4.6 Further Reading

For further analysis and examples of how context can affect environmental impact, a conference paper on the topic [89] is provided in the Appendix. The paper illustrates the many ways context could affect the GHG emissions associated with solar PV systems and demonstrates the potential magnitude of the GHG emissions differences associated with using PV panels in different contexts. The first section of the paper presents an overview of GHG emission impacts associated with solar PV and discusses the factors that cause variability in GHG intensity estimates. The second section focuses on developing and using a simple analytical model of a residential-size solar PV system to study three contextual factors: (1) solar insolation levels in the location of use, (2) the type and GHG intensity of grid-based electricity that is replaced by electricity from the solar PV panel, and (3) the effect of the match between the magnitude and timing of electricity demand and solar PV generation for residential PV systems. This study identifies numerous contextual factors that can create substantial variation in GHG intensity estimates for electricity from solar PV panels and, similarly, can significantly affect the net GHG emissions balance for PV panels. For environmentally-conscious designers, the results of the study highlight the importance of understanding contextual issues and their overall influence on environmental impact. For policymakers, these results emphasize the importance of developing tailored policies related to sustainable technologies that may be more effective at reducing environmental impact because they take advantage of the contexts in which these technologies are most environmentally successful.

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5.2 THE AMOUNT OF DAMAGE CAUSED BY A GIVEN IMPACT DEPENDS ON CONTEXT

The previous section discussed how contextual factors can alter the environmental impact of products; this section addresses a separate, but related, issue: how the magnitude of damage a given impact inflicts on the environment can vary significantly depending on contextual factors. For instance, a given mass of toxic emissions may be more harmful to the environment if it is released in an ecologically sensitive area, as opposed to an ecologically-resilient area. It also may cause more damage if it is released into an area that already has a significant background concentration of the toxic chemical, and the new emissions cause the overall concentration to surpass a threshold beyond which negative environmental and health impacts occur. The two following sections discuss how the amount of damage caused by a given impact can change depending on how ecologically sensitive the local environment is and depending on chemical thresholds and background concentrations in the environment.

5.2.1 Some Environments are More Sensitive to Impacts than Others

“Each local environment is uniquely sensitive to the stresses placed upon it by a particular product system’s life cycle” [31], i.e. some local environments are more sensitive to certain types of environmental impacts than others. This section provides a number of examples. First, chemical releases in highly-populated areas do more human health damage than releases in sparsely-populated areas because more people are exposed. As a result, electric vehicles “may benefit public health by relocating air pollutants from urban centers… to rural areas where electricity generation and mining generally occur” [90], for instance. Similarly, the negative effects of “acidification, eutrophication, and smog” from 58

concrete manufacturing are significantly reduced when production occurs in northeastern U.S., as compared to elsewhere in the country, because “a significant share of the emissions are carried out to sea rather than across populated areas of the North American continent” [91]. Second, toxic chemical releases in areas with populations of endangered species are more damaging to the environment than releases in locations with only abundant species because the negative effects of emissions on endangered species could cause significant and irreversible biodiversity loss, in addition to the negative effects that any form of wildlife might experience as a result of the chemical exposure. Third, impacts in areas that are already experiencing a significant amount of environmental damage may be more sensitive than areas that are relatively unaffected. For instance, if a wind farm harms a bird population, it is important to know not just how many birds are killed by the windfarm and its associated infrastructure (new powerlines connecting the farm to the grid), but also how many birds in the area are already killed by other human impacts, and whether all these impacts together will threaten the population of a bird species. In the European Union, for instance, EIAs of some wind farm development projects are required to assess the cumulative impact of all human impacts in the area that affect bird populations [92].

Fourth, certain chemical impacts create more damage in some environments than others because of the chemical and physical situation present in the local environment.

Many examples are cited in the literature. For instance: calcareous areas are less sensitive to acidification than non-calcareous areas; emissions to agricultural soils are far more likely to penetrate the food chain than emissions to other soils; “compounds emitted to sandy 59

soils will leach much faster to groundwater than clay soils” [93]; “region-specific differences in terrestrial eutrophication and acidification potentials range up to 1.5 and 3.5 orders of magnitude, respectively” for locations in Europe [18]; and the impact of emissions of the heavy metal Cu2+ from landfills varies by four orders of magnitude, depending on the site of the landfill and the assumed level of background contamination [94].

Finally, the environmental damage caused by a given amount of resource extraction varies depending on the amount of natural resource present, with sustainable extraction rates varying for each type of resource in each location [95]. To account for the variability in damage caused by differences in environmental sensitivity on “local, regional and continental scales,” it is necessary to include contextual information in LCAs related to “differences in geology, topography, land cover (both natural and anthropogenic)… meteorological conditions” [31], the location of the impact

(i.e. the “region or country of the emission, urban vs. rural location, arctic versus tropical zone, into a lake versus a river, etc.”), and “the mode of entry of an emission into the environment (from a tall stack versus low-level dispersion, to air, to surface water, to sea water, etc.)” [12].

5.2.2 Chemical Thresholds and Dose-Response Effects Change the Amount of Damage Caused by Chemical Emissions in Different Environments

Another reason the amount of damage caused by a given amount of environmental impact can vary in different contexts is the existence of chemical threshold and dose- response effects.

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A threshold is a cutoff point corresponding to a certain concentration of a chemical in an environment that marks a change in how much damage an increase in chemical concentration would cause. For many chemicals, no negative impacts are anticipated below a certain no-effect threshold [96], increasingly negative impacts are expected above this threshold [97], and there is a higher threshold above which no increase in negative impacts is expected with increasing concentrations “because all sensitive species are already affected” [23]. A dose is the amount of a chemical that enters a system, such as a human body, over a certain period of time. A dose-response curve relates the concentration of a pollutant to the damage it causes to the health of humans or other organisms [23][98][99]. Along a similar vein as thresholds, dose levels are “not linearly related to its resulting impact, but this relation will typically reflect a sigmoid curve” [96]. Consequently, concepts pertaining to acceptable doses of a chemical are important in toxicology such as the ‘reference concentration’, which is “An estimate… of a continuous inhalation exposure to the human population… that is likely to be without an appreciable risk of deleterious effects during a lifetime” [100], with higher concentrations causing larger doses and more severe health effects. For this reason, toxic exposure indoors has a larger impact on human health than exposure outdoors because emissions in a small space cause higher concentrations of chemicals, and consequently higher doses, to arise and potentially affect human health [3][93][95]. Also, large doses experienced over short periods of time may produce very serious effects, but intake of the same amount of a chemical over a longer period of time may cause chronic effects or no negative effects at all [93][99].

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Because of threshold and dose-response effects, many contextual factors affect the amount of environmental damage caused by a given quantity of emission, including: the rate of emission release; the background concentration of the pollutant in the receiving environment; the presence of other chemicals in the receiving environment (affecting the types of reactions that might take place); the time of day of emissions (affecting the presence of light); the time of year of emissions (affecting temperature); and weather- related factors at the time of emission, such as wind speed [3][23][31][34][35][93][96]. It is important to note, however, that the threshold effect is experienced by many, but not all chemicals. For instance, “Genotoxic chemicals are believed to have no threshold amount below which they will NOT cause cancer” [99], and “For some impact categories (like the increased radiative forcing in global warming), the size of the impact is proportional to the size of the exposure” and does not have a no-effect threshold level [96]. For these substances, contextual factors at the location of emission are not important, or are less important, to account for when trying to predict or assess the damage caused by pollutants during LCA.

5.3 EXAMPLES OF CONTEXTUAL FACTORS TO CONSIDER WHEN ASSESSING THE ENVIRONMENTAL IMPACT OF PRODUCTS

This section presents examples of contextual factors that might be relevant for sustainable designers and eco-conscious consumers. Figure 2, below, organizes many of the examples of contextual factors provided in Sections 5.1 and 5.2. The contextual factors listed relate to technology and infrastructure, environmental factors, and users.

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Figure 2: Examples of contextual factors.

The user-related contextual factors are likely most relevant to eco-consumers; some of the technology and infrastructure and environmental factors that pertain to the use phase 63

of products and do not require technical knowledge to assess may be relevant as well. Eco- consumers need to consider the user-related contextual factors in relation to themselves and their characteristics. They need to think about their own background knowledge, habits, needs, preferences, and behaviors and how that might impact their environmental impact if they were to use the product in question. In addition, they should consider their personal timing in relation to other consumers and the general growth of the industry when assessing the consequences of an environmentally-motivated decision. However, eco- consumers are unlikely to have information to assess relevant differences in the technology and infrastructure-related contextual factors (geographic dispersion of supply chain, type of electricity used to manufacture the parts, etc.). In addition, some of the more technical environmental factors (concentration of chemicals in background environment) may be outside the realm of what an eco-consumer can be expected to assess. In contrast, designers need to consider contextual factors from all three areas. They need to think about how important contextual factors vary for the many products that will be produced with the same design and the distributions of these contextual factors over the population of products – the different conditions in which the design will be used, the different users of the design, and the different technology and infrastructure available throughout the product’s life cycle. While the needs and preferences of users are outside the direct control of the designer, a customer needs analysis should be conducted for a designer to have a broad sense of customers’ needs in aggregate and the general distribution of contextual factors that will be experienced by the users of their products. Designers are also better-equipped than users to assess the more technically-focused contextual details (such as background concentrations), and they are better-placed than users to understand 64

the implications of the supply chain dispersion and quality of the manufacturing equipment, for instance. In addition, designers may benefit from considering contextual factors pertaining to higher-level analyses conducted at the fleet scale or industry scale.

5.4 THE DIFFICULTY IN ACCOUNTING FOR CONTEXT IN PROSPECTIVE LCA

This section discusses the difficulty of accounting for contextual effects in prospective LCA. LCAs are prospective when they model future systems, such as in

“consequential LCA where the impacts of a future possible decision are assessed, or in attributional LCAs aiming at assessing future technologies or systems” [3]. For instance, if an LCA is conducted on a new design that has not yet been manufactured, the LCA is prospective since the entire lifespan of the product occurs in the future. Consequently, the practitioner must make assumptions about the availability of materials; the state of materials extraction, manufacturing, and recycling technology; the state of the environment; and the availability of recycling in the future, spanning the time from the beginning of proposed materials extraction to the end of the end-of-life for all products that will be manufactured according to the design. In addition, if an LCA practitioner is working to establish the environmental impact of a product currently being sold, the estimated impacts related to use, end-of-life, and a portion of transportation are prospective and based on assumptions about the future context and users. The accurate prediction of future environmental impacts is difficult, if not impossible, because “The future is inherently uncertain, and the actual future consequences of decisions are highly uncertain” [22]. The environment “is constantly changing, irrespective of any development under consideration” [101], technologies are constantly changing, and the needs of the users of a product are constantly changing as well. It is not 65

possible to know, for instance, what fuel will be used at a recycling plant in the future, what will happen to the wood that is ‘saved’ due to recycling [30], or whether a recycling system will be available near the product’s location of use at some point in the future. In addition, many contextual factors and data inputs to LCAs are inherently variable, further complicating attempts to predict future environmental impacts. For instance, in an LCA of a residential solar PV panel, sunlight availability and household electricity demand are inherently variable in the short term. Also, contexts and contextual factors can change over the long-term. For instance, an ‘optimized’ household solar PV system is unlikely to remain optimal if the family for whom the system was designed moves, changes their consumption patterns due to changes in family size, or if climate change causes long-term changes in sunlight availability where they live. Similarly, buildings have long lifetimes during which they may be renovated or repurposed, making their environmental impacts difficult to predict or control in advance [26].

In response to this challenge, LCA practitioners frequently “assume that the future is like the present and then model the present system. Sometimes this may be a good assumption. In other cases it may be more adequate to elaborate other future scenarios” [3]. Ekvall and Weidema [22] agree, stating that because technologies change with time and frequently become more energy efficient and less polluting, “it is not reasonable to assume that the environmental properties of the technologies in a future system are accurately described through the use of data that represent current technologies.”

As a consequence, LCA practitioners will sometimes perform an LCA a number of times with different sets of assumptions about the future, corresponding to different future scenarios. For instance, an LCA of paper products could have two different end-of-life 66

scenarios for the fleet of paper products corresponding to “100% incineration” and “70% closed-loop recycling and 30% incineration” to “reflect the situations of different future developments (more or less incineration and recycling capacity, new regulations, etc.)” [102].

5.5 DISCUSSION

5.5.1 LCAs Typically Do Not Account for Context

Beyond occasionally analyzing a few future scenarios, LCAs typically do not account for contextual factors and the resultant variability in environmental impact these factors create. For instance, LCAs typically explore the environmental tradeoffs of a design in an average use context for an average user and fail to account for the variability in environmental impact that arises due to differences in contextual factors during use; “In LCIs of most products, variability of product use is rarely considered, aside from the specification of one or two broad usage scenarios” [73]. Also, in sustainable design and

LCA, “There is very little data about the use phase except the designed energy and material consumption… information about the actual practice is not fed back for analysis” [75]. Consequently, there are many “gaps while calculating the actual environmental impact during use” [75]. In addition, LCAs frequently fail to account for differences in the technology and infrastructure available in different locations. Instead, it is common to use general scenarios for industries and average data, rather than tailor the LCA to the very specific contextual conditions experienced in practice. This becomes a problem when the “average or generic data or models are used to represent processes that significantly differ from the norm” [31].

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Finally, LCAs do not include contextual information for predicting the environmental damage from emissions, such as “the simultaneous emissions from other processes outside the product system, which expose the same ecosystem/human cohorts,” “the background concentration of other substances in the system” [3], “spatial, temporal, dose-response, and threshold information” [103], or “fate, background depositions, and ecosystem sensitivity” [18].

5.5.2 Why Context is Often Neglected in LCA

Contextual factors are rarely accounted for in LCA for a number of reasons. First, contextually-specific LCAs require more data and data that is more difficult to obtain. “Data collection costs can be prohibitively large;” data may be time-intensive to collect; and it may be inaccessible because it exists “outside of the LCA practitioner’s organization” [31]. Consequently, “Data collection and compilation are often the most work- and time-consuming steps in LCAs” [11], and accounting for context only makes this job more difficult. Since aggregated datasets are more readily available than context- specific ones [3], LCA practitioners are more likely to use databases with average data for different industries rather than context-specific data that may take much more time and energy to acquire. Second, accounting for contextual factors may significantly increase the complexity of the analysis. The more scenarios included in LCA, the more complex data collection becomes, as “data must be collected for each scenario” [102]. If identical products will be used in many contexts, it quickly becomes infeasible to do a separate LCA for the design in every possible context and for every user. Methods that analyze use context variability for a fleet of products and efforts to account for the variability in 68

environmental damage of emissions due to context – for instance, by using probabilistic graphical modeling techniques [73] or by accounting for the chemical composition of natural materials at the emission site – add a significant amount of complexity to the analysis as well. Other authors agree, stating that accounting for spatial differentiation in LCA “will increase the complexity of LCA, requiring more information in some cases about emissions and more differentiation in the impact assessment” [3] and that attempts to account for chemical thresholds in the environment are “not… applicable within a regular LCA due to the extensive need of additional data that are generally not accessible”

[96]. Finally, in some cases, elements of a product’s context are not known. LCA is a comprehensive tool that includes “hundreds of environmental stressors and thousands of processes that are located worldwide and take place in the past, present, or future” [104]. The specifics of the vast majority of these stressors and processes “are largely, or often completely, unknown” [12]. It is consequently infeasible to include detailed information for each of these LCA components related to the location and timing of impacts. To cope with this lack of information, practitioners will often select aggregated data when they do not know contextual specifics, or they will “address inventory data gaps by using assumptions or estimates” [103].

However, “the uncertainty of LCA results due to lack of local detail may be critical in some cases,” and it is recommended that practitioners use local data for parts of the product’s life cycle that are significant contributors to environmental impact and operate on regional scales [105].

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5.5.3 How This Limits LCA

Failing to account for context is a problem because each move toward more general, average, and agglomerated data means that the LCA results are less tailored to the specific environmental context of interest. If the focus of an LCA is to determine whether Company A should switch from offering plastic shopping bags to paper, or whether Household B should switch from 100% grid electricity to having part supplied by a solar panel, the more general the data is, the less relevant the results are for Company A and Household B, particularly if they are outliers compared to the average company or household. In addition, combining emissions data without accounting for contextual factors significantly overestimates local emissions impacts and undermines LCA’s ability to measure actual environmental impact. Ignoring contextual factors, such as “spatial, temporal, dose-response, and threshold information” [34], “fate, background depositions… ecosystem sensitivity” [18], and “local uniqueness and environmental dynamics” [31] in LCA can cause the results to be inaccurate [18][31][34][93]. Results pertaining to “local and/or transient biophysical processes,” “issues involving biological parameters, such as biodiversity, habitat alteration, and toxicity” [34], human health impacts [103], and “acidifying and eutrophying substances” [18] may be particularly problematic. This source of inaccuracy in LCA related to emissions impacts means that “LCA… does not predict or measure actual effects, quantitate risks, or address safety” [103]. Instead, LCA considers “all theoretically possible consequences or hazards,” and its results consequently “extend beyond a worst case scenario” [103]. The fact that LCA does not predict actual environmental impacts makes it more difficult to use LCA results “for strategic planning” and “public policy making” [104].

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Also, the fact that “the relationship between a product’s usage context and its environmental performance is rarely considered” makes it so that traditional design evaluations are unable to “differentiate between contexts for which design decisions are highly beneficial and contexts for which the same decision may offer limited benefits or even penalties in terms of environmental performance” [73]. It is possible that by accounting for the variability in usage context, different products could be designed to be the ‘sustainable’ option for different users and use contexts.

5.6 CONCLUSION

A product’s context is comprised of many different contextual factors, location- and time-specific elements of the setting or environment surrounding the product. Contextual factors have the potential to significantly influence a product’s environmental impact, meaning identical products manufactured or used, etc. in different contexts can have very different impacts; for instance, a product manufactured in a facility that receives its electricity from a coal-fired power plant will have much higher life cycle NOx emissions than one produced at a facility that runs on nuclear power. Section 1 provided many examples showing how contextual factors can cause identical products to have different environmental impacts as a result of differences in user characteristics and behavior, the usage context, and the technology and infrastructure available in a location at a specific point in time. In addition, it demonstrated how contextual factors can significantly affect the environmental impact of a product in every life cycle stage via an example examining the GHG emissions impacts of a solar PV panel. For a given amount of impact of a particular type, the local environment can experience very different levels of environmental damage as a result of contextual factors; for instance, 71

for a given amount of NOx emissions released over a set period of time, the harm to human health is much more severe if it is released in a highly-populated area where the smog generated can harm more people. Section 2 focused on how the magnitude of damage a given impact inflicts on the environment can vary significantly depending on local contextual factors, due to differences in the ecological sensitivity of the local environment and the existence of chemical thresholds and dose-response effects. Section 3 provided examples of contextual factors to consider when assessing the environmental impact of products. Section 4 dealt with the difficulty of accounting for context in prospective LCA and the problems inherent in accurately generating estimates of environmental impact of products in the always-uncertain future. Section 5 addressed the reasons contextual factors are often neglected in LCAs and how this limits LCA. Specifically, contextual factors are often not included because context-specific data is difficult to obtain, accounting for context increases the complexity of the analysis, and often LCA practitioners do not know the relevant contextual details. Failing to account for context is a problem because each move toward more general, average, and agglomerated data means that the LCA results are less tailored to the specific environmental context of interest. In addition, combining emissions data without accounting for contextual factors significantly overestimates local emissions impacts and undermines LCA’s ability to measure actual environmental impact. Understanding the effects of different contextual factors on the environmental impact of products and the environmental damage caused by certain types of impacts 72

makes it possible to design products, systems, and policies to take advantage of favorable contexts and to get an accurate estimation of the real-world variability in the environmental impacts of designs. The next chapter will discuss some of the implications of this variability in environmental impact due to context, and it will present some approaches sustainable designers can use to better consider this variability.

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Chapter 6: Implications of Variability in Environmental Impact Due to Context and Approaches for Sustainable Designers Moving Forward

This chapter discusses the implications of context-generated differences in environmental impact and what this means for LCA practitioners and individuals using LCA results to make more environmentally-friendly decisions, such as sustainable designers. The first section covers the implications of the variability in environmental impact caused by context. The second section presents a method for visualizing environmental impact in a manner that better accounts for different contextual scenarios and helps designers better understand the effects different contexts may have on the environmental impact generated by a product. The final section presents avenues for future work pertaining to better understanding and controlling the context-sensitivity of the environmental impact of products to help ensure that sustainable designs’ environmental impact reductions are realized.

6.1 IMPLICATIONS OF ENVIRONMENTAL IMPACT VARIATION DUE TO CONTEXT

This section covers the implications of the variability in environmental impact caused by context, namely: (1) that context changes with time, meaning the low-impact product or option may change with time as well, (2) that usage and consumption patterns vary widely, so general LCA results may not be particularly relevant for individuals trying to reduce their personal environmental impacts, and (3) that the lowest-impact product or decision is a function of both context and customer needs. Each of these implications will be discussed below.

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6.1.1 The Background System Changes over Time, Meaning the Low-Impact Option Changes as Well

When making a decision with environmental implications, it is common to assume the background context is static. However, this is often not the case. As a result, what constitutes a ‘good’ or ‘bad’ environmental decision can change over time. This section provides an overview of the many ways background contexts might change, how this could affect the relative environmental impacts of different products and decisions, and the implications for sustainable designers and eco-conscious consumers.

6.1.1.1 Context Changes over Time

Often, the context surrounding a design changes over time. For example, many factors in the background system of a solar PV panel could change due to: (1) normal variations in weather and climate change (altering solar availability and the likelihood that strong winds, storms, or fires might cause an early end to the panels, for instance); (2) electric grid changes altering the GHG intensity of avoided electricity (which could be caused by factors such as population change, cultural change affecting electricity consumption patterns, technology developments, and new energy policies); and (3) changes in household load (due to normal fluctuations in minute-by-minute consumption, changes in family size or in family members’ energy consumption patterns, and changes in electricity-consuming household appliances).

In general, changes to a design’s background context can occur as a result of external factors that alter the environment (the presence or absence of pollutants or endangered species, the population density, the climate, etc.), the existing infrastructure (presence of public transit options, high-density housing, etc.), and the economic balance

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between different options (available supply of recycled materials, or an increased demand for electricity). In addition, changes in the background system may occur if many individuals make decisions that are dependent on one another, as might happen, for instance, if the presence of a customer with a reusable shopping bag influences the perceptions and behavior of other customers in a manner that spurs others to bring reusable bags in the future. Also, a design itself may cause changes to the broader context, i.e. when a ‘sustainable’ decision is made, the background system may change in response.

6.1.1.2 Changes in Context Can Cause Changes in the Relative Environmental Impact of Alternatives

Changes in the background system can cause changes in the relative environmental impact of different design and decision alternatives. This can occur in a wide range of ways. Four such ways are discussed below with examples. First, when the background environment changes, it often alters the relative amount of damage caused by different types of impacts. As a result, the ‘best’ alternative for the environment may change as well. For instance, as climate change occurs, the environmental sensitivity of many areas may increase (more species become threatened or endangered), meaning one unit of human impact in those locations could cause much more environmental harm than it did before. Also, suppose an LCA shows that a gasoline- powered vehicle’s low-level emissions do not pose a significant health risk currently, allowing the vehicle to be considered to generate roughly the same amount of environmental damage as an electric vehicle in a given location for a certain driving scenario. However, in 5 years, when the population of the rapidly-growing city where the vehicle is located has doubled, the effect of more vehicles on the road and longer drive

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times as a result of congestion may cause a large increase in emissions, resulting in significant health-related threshold concentrations to be surpassed. Although presently the type of vehicle (gasoline-powered or electric) matters little, in the future, it would be much better for the environment if the vehicle were electric. Second, the relative impacts associated with different resources change as supply and demand change in the economy, leading to changes in the environmental benefits and damages associated with certain designs and decisions. For instance, if there is a large supply of unused recycled paper, incorporating this recycled material in a design may be associated with a significant environmental benefit over virgin paper. However, if demand for recycled paper surpasses supply, the environmental benefit of incorporating recycled paper in a design is reduced to zero, as all available recycled material would already be used in some design. In this case, using recycled paper in a particular design means another design will be manufactured using virgin paper instead of recycled and the overall environmental impact remains unchanged. Third, whether a particular option is beneficial for the environment depends on timing and the decisions other people make. For instance, as more people in a given area get residential solar PV panels, the type of grid electricity being displaced by the PV panels (and consequently the amount of environmental benefit associated with each panel) will change. At some point, additional PV panels will not be beneficial because the grid will already produce enough electricity from existing PV panels to meet the demands of all loads, meaning no non-PV electric generation would be displaced. This means that a customer’s decision to buy or not buy a PV panel for environmental reasons should be contingent on where that person falls on the ‘solar panel purchasing trend’. 77

Fourth, background changes to the environment can alter the performance of products, changing their relative environmental impacts. For instance, if severe storms and high winds become more common in a particular area in the future due to climate change, designs that would currently be considered ‘overdesigned’ because they needlessly have more material or stronger materials (resulting in a higher environmental impact) will be necessary, and today’s ‘sustainable’ designs (with no unnecessary material usage) will be more prone to fail (incurring increased environmental impact associated with their repair or early replacement). Similarly, there are areas where the installation of solar PV panels would currently be considered environmentally beneficial that, as a result of climate change, may become cloudier, reducing the performance of any panels installed in that area, and reducing the future environmental benefit conferred by the panels.

6.1.1.3 Considerations for Designers and Consumers

Because, as discussed above, background contexts change and these changes can affect the relative environmental impacts of different design alternatives, LCA practitioners and consumers making decisions with ramifications that last for long periods of time (whether to buy a gasoline-powered or an electric car, whether to get a solar PV panel for a home, etc.) ought to consider not just the current context, but also how that context might change over the life of the product, potentially amplifying or negating any anticipated environmental benefits. For instance, a PV system designer needs to understand to what extent changing contextual factors will influence the environmental impact of the panel in the future. The designer ought to consider questions such as: If it is good for a household to get a solar panel now, will it still be good for it to have the panel in 5 or 10 years when the family is a different size and has different electricity demands? Will it still be good if 78

the worst climate change scenarios in the household’s region occur, and sunlight availability decreases and/or the likelihood of high winds and severe storms that could damage the panel increases? What if the new nuclear plant being discussed in the area is finally opened, or what if the project is put on hold indefinitely (potentially altering the level of emissions the PV panel avoids)? If curtailment or voltage rise is a problem today in the household’s neighborhood, will it continue to be a problem over the life of the panel, potentially undermining the panel’s environmental benefits? By considering questions such as these pertaining to the changing context over a design’s lifetime, better long-term environmentally-focused decisions may be made.

6.1.2 Usage and Consumption Patterns Vary Significantly, Reducing the Usefulness of General LCA Results for Individuals

Different individuals and households have very different usage and consumption patterns. For instance, Jensen [106] found that consumption rates for similar types of houses with 4 residents each in the same neighborhood varied significantly “between lowest and highest household,” by approximately “a factor 7 for electricity, a factor 3 for heating, and a factor 6 for water.” In addition, consumers weigh economic tradeoffs differently, resulting in different environmental implications for purchasing the same product. For instance, a “consumer may choose to finance her extra expenditure on” an “eco-product by reducing consumption of some other good” that is either harmful to the environment (gasoline) or environmentally-beneficial (another eco-product) [104].

Consequently, how the consumer decides to balance her budget to account for the extra expense can significantly alter the overall change in environmental impact resulting from her purchase of an eco-product. For these reasons, and many others, it is clear that

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consumers need individualized advice for deciding which products are best for the environment. Other authors agree. Geppert and Stamminger [77] state, for instance, with regard to refrigerators, that “consumer behaviour is individual and dependent on innumerable factors. For this reason, it is appropriate to provide individual advice for sustainable use behaviour.” Consequently, LCA assumptions (and the corresponding LCA results) that may hold true for the average customer could be quite misleading for any given customer. Suppose an LCA shows, for instance, that for the average customer, it is better for the environment to choose paper grocery bags over plastic. However, a particular customer reuses plastic grocery bags as trash bags and recycles paper bags from the grocery store without reusing them. If he or she opts for paper over plastic based on the tradeoffs for the average customer, this person will now have one fewer trash bag and will need to acquire an additional trash bag elsewhere, in addition to the paper bag needed for transporting groceries. In this case, the customer’s propensity to reuse the plastic bag has significant implications on the ‘right’ environmental decision for the customer. The LCA results generated with the average customer in mind would provide misleading recommendations for this customer. Clearly, LCA practitioners cannot anticipate all scenarios for all potential customers, meaning general LCA can provide only limited guidance to customers and may provide misleading results on topics where consumption patterns vary greatly amongst individuals.

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6.1.3 The Lowest-Impact Option Is a Function of Both the Context and the Customer Need

Because of the variability in environmental impact of products due to the behavior of users and the usage context, eco-conscious users should not ask ‘Is product A or product B better for the environment?’ but instead ‘Is product A or product B better for the environment, given my current needs and situation?’ Take an example pertaining to disposable shopping bags. For simplicity, assume that the only environmental impact of concern is GHG emissions. 5 units of GHG emissions are released over the life cycle of a paper bag that holds 5 cubic units of groceries, and 3 units of GHG emissions are released over the life cycle of a plastic bag that holds 3 cubic units of groceries. At the store, customers should select the type of grocery bag to use based on the volume of groceries they have. For instance, a customer with 6 cubic units of groceries would be better off with 2 plastic bags (with 6 embedded GHG emissions) than 2 paper bags (with 10 embedded GHG emissions), for instance, but a customer with 5 units would be better off with 1 paper bag (with 5 embedded GHG emissions) instead of 2 plastic (with 6 embedded GHG emissions). Hence, the environmentally-preferable option may depend on the user’s needs and change from user to user. In addition, for a single user, the most environmentally- friendly option may change on a case-by-case basis, e.g. different trips to the store for the same person would have different environmentally-preferable bagging combinations.

6.2 METHOD FOR VISUALIZING ENVIRONMENTAL IMPACT SCENARIOS

This section presents a method for visualizing environmental impact in a manner that better accounts for different contextual scenarios and helps designers better understand the effects different contexts may have on the environmental impact generated by a

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product. Here, environmental impact is understood and visually depicted as a function of contextual factors and differing assumptions, and an LCA is considered a model of environmental impact that can be run many times over to correspond to different contexts and scenarios (different product lifetimes, use scenarios, transportation modes, disposal options, etc.). This method presents LCA results generated by a range of inputs corresponding to differing assumptions, contexts, and future scenarios, helping researchers visualize multiple LCA results together and enabling the effects of these assumptions, contexts, and scenarios to be compared. First, a method for analyzing different scenarios for one individual design over its lifetime is presented. Second, a method for examining different scenarios for a product fleet for a variety of fleet sizes is presented.

6.2.1 Individual Approach

This section presents a general framework for visualizing how the environmental impact of one design varies over the lifetime of the design and how it is affected by different contextual factors. This approach involves plotting the environmental impact of one design as a line that is a function of time and contextual factors. By plotting many lines on the same chart that correspond to different contextual scenarios, it becomes easier for LCA practitioners to understand the implications of different contextual factors, as well as to better communicate to readers the types of contextual scenarios that were considered in the study and their effects on the environmental impact of the design. The x-axis of the plot corresponds to time and spans the life of the product, running from the beginning of materials acquisition to the end of product disposal or recycling. The y-axis corresponds to the environmental impact, or the environmental impact in the impact category of interest (i.e. GHG emissions), of one design. One data point on these axes 82

represents the environmental impact of the design at a given point in time; for instance, one data point on the graph for a solar PV panel might represent the GHG emissions associated with year 3 of the use phase. The result of a typical LCA, based on a single set of assumptions and data, represents one line. The shape of the line is determined by different contextual factors, assumptions, and datasets and represents how the environmental impact of the product changes over time. For instance, the real-time GHG emissions associated with a solar PV panel are likely to be high during the early years of materials acquisition, manufacturing, and transportation, but relatively low during years corresponding to the use of the product. The specific LCA framework and calculation setup for a given design can be thought of as a model of environmental impact for the design. Different model inputs correspond to differing contextual factors, assumptions, and datasets and generate different lines to be graphed. Ideally, a representative sample of assumptions and contexts would be used to generate the equations for the set of lines using the most recent, exact, and plausible data available. For instance, if 75% of products of a given design are expected to be used at room temperature, and the other 25% are expected to be used at temperatures below freezing, the assumptions regarding operation temperature in the lines graphed should be distributed accordingly.

A hypothetical example plot for a car is shown in the figure below. The y-axis corresponds to the GHG emissions for the car in each year of its life cycle. In this plot, materials acquisition lasts 1 year and is associated with 4 units of GHG emissions. Next, manufacturing lasts 2 years and is associated with 2 units of GHG emissions each year. Afterwards, transportation to the point of use lasts 1 year and is associated with 1 unit of 83

GHG emissions. The use phase lasts 10 years. In the scenario depicted here, it is associated with 5 units of GHG emissions per year. Transportation at the end of life lasts 1 year and is associated with 1 unit of GHG emissions. Finally, disposal lasts 1 year and is associated with 4 units of GHG emissions.

Hypothetical LCA of a Car 6

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GHG GHG Emissions Impact (Units) 0 0 2 4 6 8 10 12 14 16 18 Time from Beginning of Materials Acquisition to End of Life (Years)

Figure 3: Hypothetical LCA of a car plotted from the beginning to the end of the product life cycle in terms of GHG emissions each year.

If the LCA practitioner considers many different use phase scenarios, the resultant plot may look like the one shown below in Figure 4. Blue represents the original scenario described above. However, now there are more lines in the use phase representing scenarios in which: (1) the car is driven more miles each year (green), (2) the car is driven in areas of greater congestion (blue), and (3) the efficiency of the car gradually decreases over time (purple).

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Hypothetical LCA of a Car with Multiple Use Phase Scenarios 8 7 6 5 4 3 2 1 GHG Emissions GHG Emissions (Units) Impact 0 0 2 4 6 8 10 12 14 16 18 Time from Beginning of Materials Acquisition to End of Life (Years)

Original More Driving More Congestion Less Efficient Over Time

Figure 4: Hypothetical LCA of a car with 4 different use phase scenarios plotted from the beginning to the end of the product life cycle in terms of GHG emissions each year.

This style of analysis helps identify the importance of different future scenarios – certain scenarios to try hard to avoid (by opposing certain policy-related changes) or design-around (make a solar panel that can be easily moved to a new house or one less likely to be damaged in high wind) and other scenarios that do not have a significant effect on environmental impact (whether you have a child move off to college, reducing household electricity demand, within a year or two of the end of the life of the PV panel).

This approach to time is fundamentally different from the approach currently used in LCA, where environmental impacts are frequently broken down by life cycle phase. In this method, assumptions related to time – such as assumptions about the length of the use

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phase of the product – are more explicitly depicted, allowing for contextual factors, assumptions, and uncertainty about the future to be more clearly highlighted and allowing for new types of insights to be gleaned pertaining to the relation between environmental impact and time. This method of visualization can be used to do a meta-analysis of LCAs in a manner somewhat the opposite of harmonization studies. Instead of controlling for contextual factors and differing assumptions, this method enables researchers to make sense of all available LCA results for a particular design, representing many different contexts and different sets of assumptions simultaneously. In the case where the different scenarios represent different types of contexts (i.e. a scenario for high and low solar insolation, or solar insolation for Phoenix and another for Anchorage), the results could aid researchers in identifying environmentally advantageous (and environmentally disadvantageous) contexts for a particular design.

6.2.2 Global Approach

This section presents a general framework for visualizing how the environmental impact of a product fleet varies with the number of designs in a fleet and with contextual factors. Throughout this section, the framework will be explained and presented using a hypothetical example looking at the environmental impact of a fleet of solar PV panels. The quantity of products of a single design can significantly affect the incremental environmental impact associated with each additional product. In some cases, there may be ‘environmental economies of scale’ associated with environmental benefits of mass production, for instance. In other cases, additional products may deplete a limited resource or exceed ecosystem absorption limitations, causing additional products to have 86

increasingly large environmental impacts. The timing of a consumer’s decision within the contextual changes in the world and the timing of other people’s decisions to adopt or not adopt a product can alter whether a consumer decision (to buy a solar PV panel, for instance) is good or bad for the environment. To visualize these effects, LCA results are plotted to depict different contextual factors and scenarios. The y-axis corresponds to the per-unit environmental impact (or the measure of the environmental impact category of interest) of a design, such as the GHG emissions associated with one additional unit of solar PV panel capacity. The x-axis corresponds to quantity, or the total number of units of the design in the world. A typical LCA based on a single set of assumptions and input data provides one data point to be graphed on these axes. This point can be extended into a line if the assumptions related to the total quantity of a design in the world are varied. When other contextual factors, datasets, and assumptions are changed, the results are represented as additional lines. For example, a plot of a hypothetical global solar PV fleet LCA is shown in Figure 5, below. The x-axis corresponds to the installed capacity of PV panels in generic units, and the y-axis to the environmental impact in generic units associated with each new unit of PV panel capacity. As one moves from left to right on the x-axis, each new unit of installed PV capacity has a different environmental impact from the last based on the total number of panels on earth, which affect, for instance, the environmental impact of the electricity that the new panel capacity displaces, whether the new panel benefits from environmental ‘economies of scale’ in manufacturing and disposal, where the materials to make the panel come from and how accessible they are, etc. These many contextual factors 87

and assumptions that are built into the fleet LCA based on the practitioner’s understanding of how the per-unit environmental impact is affected during the scale up of PV installation account for the different shapes of the line depicted.

Hypothetical Global Solar PV Fleet LCA 250

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0 50 100 150 200 Environmental Impact (Units)Impact Environmental Installed Capacity of PV Panels (Units)

Figure 5: Plot of a Hypothetical Global Solar PV Fleet LCA, displaying the environmental impact corresponding to each additional unit of installed PV capacity.

For instance, imagine a manufacturing system is set up and produces one PV panel with one unit of capacity, i.e. the fleet size is one. That panel would be expected to have a very large environmental impact because there are no economies of scale; for instance, 100% of the total impact associated with the equipment for manufacturing the entire fleet is attributed to a single panel. However, if the facility makes two panels, both panels split the ‘capital’ environmental impact associated with the equipment, and possibly other impacts as well related to special recycling equipment or shared transport of the panels.

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Hence, increasing the number of panels produced would be expected to significantly reduce the environmental impact of each panel for small fleet sizes and gradually make a negligible difference for per-unit impacts as fleet sizes become larger (until, of course, the number of panels necessitates higher-capacity manufacturing equipment or generates resource limitations). Consequently, in the graph above, the first few PV panels are shown to have high environmental impacts because manufacturing, transportation, and recycling systems are resource-intensive per unit when there is only a small total number of units, and as the number of units increases, environmental economies of scale are achieved, and each new panel has a reduced impact from the last. However, environmental economies of scale are likely to plateau at some point where, for instance, the available manufacturing plants are running at full capacity and new facilities must be built to attain increases in quantity. In the graph above, this plateau occurs at 100 units of installed PV capacity, where each additional unit of capacity is associated with 1 unit of environmental impact. When the quantity increases past this point, a large increase in per-unit impact is observed, as is shown in Figure 5 at 101 units of installed capacity. This jump in per-unit impact could be caused by the need to use a less-ideal manufacturing facility, or it could be caused by a number of other contextual factors. After all, as quantity increases many other issues related to technical constraints, resource limitations, and the inability of the environment to absorb further environmental damage may arise. Examples include instances where: (1) the maximum amount of solar PV without storage has already been installed on the grid, so any additional PV installations are higher-emission because the they necessarily are accompanied by some form of energy storage, (2) additional solar PV production exceeds the capacity of earth to provide 89

sufficient materials, so solutions such as interplanetary mining and asteroid mining must be used, and (3) space limitations on earth are exceeded by the panels, so the panels must be deployed in outer space and the energy beamed back to earth. The approach presented in this section encourages the designers to think through different contextual and scale-up scenarios. For instance, one could use this visualization method to consider how the per-unit environmental impact and total impact changes as the fleet size changes in two scenarios: (1) initially installing a high-capacity mass manufacturing system that can produce 1,000 units per day and later installing smaller- capacity systems of 50 units per day until the total anticipated manufacturing capacity has been reached and (2) installing only facilities that produce 50 units per day the entire time. This analysis could then be used to make manufacturing and design decisions that minimize the environmental impact in the most likely contextual scenarios. By plotting these scenarios in the manner presented in this section it may become easier for practitioners to communicate the scenarios studied, understand tradeoffs, and make better decisions based on the possible future contexts that might arise.

6.3 FUTURE WORK

This section presents avenues for future work pertaining to better understanding and controlling the context-sensitivity of the environmental impact of products to help ensure that sustainable designs’ environmental impact reductions are realized.

6.3.1 Minimizing the Context-Sensitivity of Designs’ Environmental Impacts

The sensitivity of a design’s environmental impact to contextual factors likely varies between different types of designs; some products have environmental impacts that

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are highly context-sensitive, but other similar products may have impacts that are relatively robust to changes in contextual factors. By switching the bulk of a design’s environmental impact from one life cycle phase to another or by adding certain types of design features, it may be easier to limit the context-sensitivity of a product’s environmental impact. Limiting the context-sensitivity of designs may be advantageous, for instance, when designing products to be used in a wide range of locations, for different purposes, or by people with very different habits; it can also be advantageous when designing products to be used in one location for one purpose by one person in a highly variable context. For instance, in the case of residential solar PV, sunlight availability is inherently variable on a variety of timescales. It can change on relatively short timescales due to a passing cloud and the time of day, and it can change on larger timescales as well due to the time of year, an El Nino year, and climate change. Consequently, future work may involve developing a variety of methods and tools to: (1) assess the context sensitivity of the environmental impact of a design, (2) identify the inputs to which the design’s environmental performance is most sensitive, and (3) generate designs with reduced context-sensitivity (perhaps by applying ‘design for robustness’ principles), thereby redesigning products to respond desirably in the presence of critical system inputs in whatever range they typically vary and making the environmental impact more easily predicted using LCA and more easily controlled by designers.

6.3.2 A Method to Group and Screen Contexts

Another area of future work is the development of a method for screening contexts for a particular design as ‘good’ or ‘bad’ for the environment based on past context-specific 91

LCAs. This method would identify contextual factors that contribute significantly to the environmental impact of a design, and similar contexts (i.e. similar sets of contextual factors, or contexts that cause the design to have a similar environmental performance) would be grouped based on how these contexts affect environmental performance. The method, for instance, may entail: (1) brainstorming a wide range of contextual factors that have theoretical support indicating that they might be important in determining environmental impact for a design, (2) conducting detailed LCAs for many panels in many different contexts and/or using the detailed results of context-specific LCAs found in the literature, and carefully tracking all context-related assumptions and data in the analysis, and finally (3) testing to see which contextual factors – and combinations of contextual factors – have a large influence on the overall environmental impact (though regression, self-learning networks, etc.) and determining justifiable “cutoff” points within each contextual factor to establish the borders of the different contexts.

For instance, it is highly likely that the latitude and the number of sunny days a year at the location of use are both important contextual factors that affect the environmental performance of solar PV panels. However, other factors, such as being located on a major bird migration route (resulting in increased bird droppings on the panels) are unlikely to significantly influence the environmental impact of PV panels. If the only two important contextual factors for solar PV were the ones mentioned above, researchers may be able to determine, for instance, that there are 3 meaningful groupings of latitude and sunny day contexts: (1) Latitudes within the tropics and more than 200 sunny days a year (corresponding to the best environmental performance); (2) Latitudes outside the tropics with more than 200 sunny days a year, and latitudes within the tropics with less than 200 92

sunny days a year (corresponding to moderate environmental performance); and (3) Latitudes outside the tropics with less than 200 sunny days a year (corresponding to poor environmental performance). Of course, this becomes far more complicated when there are 30 important contextual factors being analyzed, and when the cutoff points for each factor are not selected arbitrarily but are selected based on the environmental performance data from numerous context-specific LCAs.

The results from a study using this type of method would allow LCA practitioners to quickly identify contexts likely to result in positive and negative impacts for a given design, without having to run a detailed context-specific LCA. These results would allow different design options to be recommended for consumers in different contexts and ideal contexts that maximize the environmental benefits of a given design to be recommended, for instance, to companies or policymakers.

6.4 CONCLUSION

This chapter delved deeper into issues related to the variation in environmental impact for the same design caused by contextual differences. The first section discussed three implications of environmental impact variation due to context, namely, that: (1) the context of a product changes with time, meaning that the lowest-impact product or option also changes with time, (2) usage and consumption patterns vary significantly, so it is difficult to apply general LCA results to help guide individuals to make low-impact choices, and (3) the lowest-impact product or option depends not only on the product but also on the needs of the customer and the factors defining the use context.

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The second section presents a method for visualizing different environmental impact scenarios. It first presented an individual approach for plotting the impact of one product over its lifetime with regard to a number of assumptions or scenarios of interest. Next, an approach for plotting the impact of a fleet of products as the total number of products in the fleet increases was shown, demonstrating how incremental impact changes with quantity.

Finally, two avenues for future work in this area were presented, specifically: (1) the development of tools and methods to minimize the context-sensitivity of the environmental impact of designs so that designers can better predict and control the environmental impact of products, and (2) the development of a method for screening contexts for a particular design as ‘good’ or ‘bad’ for the environment based on past context-specific LCAs. The next chapter examines other environmental impact measurement frameworks and how they account for context to see what LCA and sustainable design practitioners might learn.

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Chapter 7: Learning from Other Environmental Impact Measurement Frameworks and How They Account for Context

Constructs and frameworks for accounting for environmental impact from other fields – such as environmental risk assessment (ERA), environmental impact assessment (EIA), and ecological impact assessment from biology – may account for some elements of context better than LCA and offer a potential learning opportunity for those trying to account for the contextual effects on the environmental impacts of products. These three frameworks and the manner in which they account for context are discussed below.

7.1 ENVIRONMENTAL RISK ASSESSMENT

Environmental risk assessment (ERA), also known as risk assessment or quantitative risk assessment, assesses the impact of chemical emissions on the environment and human health [23][107]. ERA seeks to estimate the absolute impact of emissions, rather than the impact relative to a functional unit. ERA produces results estimating the

“likelihood and severity of harm” associated with emissions and whether these risks are acceptable and justifiable, inherently assuming that some level of environmental impact is “permissible where the risks are small and/or the costs of further control are judged to be too high” [107]. ERA uses context-specific data pertaining to the location and timing of emissions, the background concentration of the chemical in the environment, the number of people affected, exposure pathways, the magnitude and duration of exposure, and the relationship between the dose and the expected response, for instance

[3][23][105][107][108]. These analyses focus entirely on the context in question – for example an ERA may examine the specific design of a coal power plant for a proposed location, accounting for background emissions of sulfur dioxide, the population, and the 95

likely impact of additional emissions on human health. Consequently, unlike LCA, ERA is able to more accurately predict the actual damage caused by chemical emissions and “is effective in local impact assessments” [105]. However, ERA is far less comprehensive than LCA [105], as it tends to focus on one emissions type [109] and does not deal with resource use throughout the life cycle of the product system [107]. As a result, some authors [105][110] have discussed the benefits of integrating ERA and LCA methods.

7.2 ENVIRONMENTAL IMPACT ASSESSMENT

Environmental impact assessment (EIA) examines proposed policies and projects “for their likely implications for all aspects of the environment” and develops responses to any issues that arise [111]. It is used globally by companies to meet government regulations [108] and legal requirements [111]. EIAs are typically used to assess the environmental impacts of facilities or large-scale projects, such as new roads [23][108], hazardous waste incinerators, dams, and the decommissioning of nuclear power plants [112]. EIAs document the impacts associated with both “regular activities, such as operation and maintenance of the facility,” as well as one-time activities, “such as construction and dismantling of the facility” [23], and they address “problems associated with climate change, loss of biodiversity, threats to freshwater sources and water quality, damage to marine areas and other forms of global environmental change” [111]. EIAs use context- specific data to predict a wide range of impacts at the project site, such as “noise, odour, landscape degradation” [23], natural resource consumption [108], and impacts on biodiversity. For instance, EIAs of offshore wind farms in Europe must assess the hazards the proposed project poses “to birds in terms of avoidance behaviour, habitat change and

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collision risk” so they can “account for predicted changes in the local abundance and distribution of avian species; and in local biodiversity” [92]. It is well-accepted that detailed EIAs tailored to the specific contexts encountered by designs are necessary to understand the environmental impact of large-scale facilities and projects. For instance, few would argue that the EIA results for a coal power plant in rural Kansas would be the same as a coal plant in downtown Los Angeles; even if the plant designs are the same, the effect on water, on human health, and on local species would be expected to be entirely different due to the differences in location. In this case, it is clear that EIA-level effort is needed to know what the environmental impact is of a large scale design. Likewise, there is no reason to think that this is any different for smaller-scale systems, such as consumer products, whose environmental impacts likely affect - and are affected by - the specifics of their contexts just as much as large scale systems. This raises the important question: If it is not sufficient to assume-away contextual factors in the assessment of the environmental impact of large-scale designs, is it really appropriate to do so in the assessment of the life cycle environmental impact of small-scale ones?

7.3 CONSTRUCTS OF ENVIRONMENTAL IMPACT FROM ECOLOGY

Although it is uncommon for sustainable designers and LCA practitioners to consider the environmental impacts of biological organisms, and especially the negative environmental impacts of biological organisms in the wild, this is rather common in the field of biology, and ecology in particular. By examining the constructs of environmental impact from biology, sustainable designers and LCA practitioners can learn some important lessons regarding methods and critical considerations when accounting for context when assessing environmental impact. 97

First, this section explores how environmental impacts are assessed in ecology and the importance that contextual factors play in this process. Second, the biological constructs of environmental impact are applied to human-engineered designs to outline a new framework for conducting LCA in a manner that better accounts for context.

7.3.1 How Environmental Impact is Accounted for in Ecology

7.3.1.1 Biological Organisms Can Have Both Positive and Negative Environmental Impacts

In ecology, the environmental impact of an organism is measured in terms of the magnitude of the change the organism causes in ecological processes [113][114], for instance, due to alterations the organism makes in the availability of resources in its environment [115][116]. The impacts of biological organisms can be considered positive or negative depending on contextual factors. If the environmental changes caused by biological organisms enhance “species richness and abundance”, the impact is considered ‘positive’; if instead the change hinders these traits by, for instance, causing habitat for an endangered species to be reduced, then the impact is considered ‘negative’ [116]. This means that the same organism can be deemed to have a positive environmental impact in one context (a beaver dams an area creating a habitat for an endangered species) but a negative impact in another (a beaver dams an area, flooding and destroying a habitat for an endangered species).

This ecological approach to understanding the environmental impact of organisms is interesting from a product design perspective because the same organism performing the same tasks can have very different environmental impacts – in terms of both size and the 98

‘goodness’ or ‘badness’ of the impact – depending solely on contextual factors and the other organisms in its environment. This is very different from a traditional LCA of products, where all products of a particular design are deemed to have an impact of a particular size and be ‘good’ or ‘bad’ for the environment, without consideration of the different contexts that will interact with each product individually.

7.3.1.2 Biologists Assess the Environmental Impact of Organisms within a Context

Biologists assess the environmental impact of organisms within a particular context. For instance, the environmental impact of invasive species and ecosystem engineers are assessed with a careful consideration of the specific physical, chemical, and biological conditions present in the location of study and the way in which other organisms interact with the organism of interest. For example, Gribben [117] states that “the effects of a habitat-forming invasive species are biomass dependent and… affect community components differently, suggesting that, globally, the impact of these types of invaders may be context dependent.” In addition, Wright and Jones [118] note that “the context dependency of ecosystem engineering” arises “from the underlying characteristics of the abiotic environment, from the way it is organismally modified, and from the response of other organisms to these abiotic changes.” Similarly, Ricciardi [114] discusses the “context dependency of impact” of nonnative species, specifically the “temporal and spatial variation in impact” and the fact that “the structure, diversity, and evolutionary experience of the recipient community” of a nonnative species are “general determinants of impact.”

Because environmental impacts of organisms in biology are context dependent, a number of authors emphasize the importance of not labelling species as inherently having positive or negative impacts, stating, for instance: “Much popular literature and some 99

scientific literature” incorrectly designate “native species as ‘good’ and introduced species as ‘bad.’ Species are neither” [113]. Instead, all changes species make to an environment are good for some organisms and bad for others. As Crooks [119] states:

Although it is tempting to characterize species like plants or macroalgae as habitat creators and grazing snails as habitat destroyers, in fact they both create one habitat type at the expense of another… Species able to live in the invader modified habitat type would be expected to benefit from the ecosystem engineering, while those living in the unmodified habitat might be inhibited.

Similarly, product designers may benefit from avoiding labelling some products as environmentally ‘sustainable’ and others as ‘unsustainable.’ Instead, they ought to consider sustainability as something that involves both a product and a context together, recognizing that different contexts will be affected by the same product in different ways and these effects may cause damage in some contexts but have environmental benefits in others.

7.3.1.3 Sustainability in Biology is about Preserving Biodiversity on a Global and Local Scale

Biologists conceive of environmental sustainability as being related to the preservation of biological diversity both locally and globally. For diversity to be preserved, it is necessary to maintain variety both in the types of environments present on earth and the types of biological organisms living. Having diverse organisms in diverse environments across the world helps to ensure that some organisms are likely to survive and reproduce in some locations in response to even significant changes to the global environment.

Hence, increases in both local and global species diversity improve the odds that life on earth will continue to survive. In local ecosystems it is good to have many species with significant genetic diversity to keep the ecosystem healthy and functioning and

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increase the likelihood that some species would survive in the event that the ecosystem is perturbed. Similarly, it is good to have high-functioning ecosystems in many different types of environments because it increases the odds that some ecosystems would survive in the event of a global environmental perturbation. However, even if all local ecosystems are diverse, this does not mean that global diversity has been achieved. For instance, the Hawaiian Islands have nearly the same number of bird species as they did before the arrival of humans, representing stable local biodiversity, but this translates to significantly-reduced global avian biodiversity because more than 50 now-extinct species were replaced by 50 species “common in their native ranges and widely established elsewhere” [113]. Hence, changes in local species diversity are not direct indicators of global species diversity. While there is no sustainable design analogue for the importance of diversity (no imperative to have diverse human-engineered designs locally or globally), it is beneficial to consider the importance of preserving biological diversity locally and globally when defining what it means to be a ‘sustainable’ design. LCA practitioners and sustainable product designers rarely translate the impacts of the designs they are assessing into impacts on biodiversity and almost never distinguish between local and global biodiversity issues. However, as noted here, biologists emphasize the importance of diversity in sustainability- related literature and view other environmental issues (climate change, toxic releases, etc.) in terms of their effects on diversity. It may be advantageous for the sustainable product designer to do the same.

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7.3.2 Applying Biological Constructs of Environmental Impact to Products / A New Ecology-Inspired LCA Framework

The purpose of this section is to apply the constructs of environmental impact developed in biological literature on ecosystem engineering [115][116] to human- engineered designs. It is hoped that doing so will provide a new lens through which to consider anthropogenic environmental impacts and better account for contextual effects in the environmental impact of products. An LCA framework based on biological constructs of ‘environmental impact’ is outlined below.

7.3.2.1 The New Framework

In their paper developing the concept of ecosystem engineers in biology, Jones et al. [115] present the following six criteria used to assess the size of the environmental impacts of biological organisms:

(i) Life time per capita activity of individual organisms.

(ii) Population density.

(iii) The spatial distribution, both locally and regionally, of the population.

(iv) The length of time the population has been present at a site.

(v) The durability of constructs, artifacts and impacts in the absence of the original engineer.

(vi) The number and types of resource flows that are modulated by the constructs and artifacts, and the number of other species dependent upon these flows.

This section draws analogies between biology and engineering to apply the six elements of this biology-based environmental impact measurement framework to engineered products. As many of these criteria are context-focused, the goal of this section 102

is to glean insights into how to better account for context in LCA and sustainable product design. To make the criteria listed above applicable to products, 'individual organisms,' 'the original engineer,' and 'constructs and artifacts' are all taken to mean one product, system, or functional unit with a particular design. In addition, a ‘population’ is taken to mean all products or systems with that same design in the same geographic area on a scale relevant to the environmental impact of interest. For instance, an individual coffeemaker is considered analogous to an individual organism, a fleet of coffeemakers of the same design is analogous to a species, and a group of coffeemakers in a particular geographic region (e.g. the global product fleet for GHG-related impacts, and a local stock of coffeemakers in use in one coffee shop for noise-related impacts) is a 'population'. When interpreted in this manner, LCA typically deals with three of Jones' criteria – (i), (v), and the first part of criterion (vi) – because, respectively: (i) LCAs account for the magnitude of impact of individual designs, i.e. the expected environmental impact of one car or one kWh of electricity from a power plant; (v) LCAs typically also consider the durability of the product and its wastes after the end of its useful life, e.g. when accounting for biodegradability, the influence of different disposal methods, and the times different types of GHGs persist in the atmosphere; and (vi) LCAs account for the number and type of resources that are changed as a result of a product's manufacture, transport, use, and disposal.

However, LCAs rarely, if ever, account for the other contextual aspects of environmental impact Jones presents – population density, population distribution, the

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length of time a population has remained at a site, and the dependence of other species on material flows. For instance, accounting for population density when determining the environmental impact of a design that produces chemical waste during use would likely reveal significant differences in impact if all products manufactured according to a particular design are used in one city, compared to a scenario where they are uniformly used across the world. This is particularly true for chemicals that have concentration thresholds above which significant negative impacts are expected and below which little to no impact is expected. Similarly, considering the spatial distribution of designs both locally and globally can reveal sustainability implications associated with the overall quantity of designs that challenge simplistic conceptions of environmentally 'good' and 'bad' technology. On one hand, just as a booming population of wolves in a particular area is considered unsustainable because the population cannot be maintained for lack of food, too many of any one engineering design – even one that is extraordinarily 'good' for the environment – in any impact area is unsustainable; for instance, the world cannot sustainably support a billion 400MW solar PV farms for lack of materials. On the other hand, even designs considered extraordinarily 'bad' for the environment may be sustainable if they are present in low enough quantities over a particular area; it is difficult to argue that the world cannot sustainably support one 400 MW coal power plant, for instance.

Likewise, examining the length of time a 'population' of products has remained at a particular geographic site has important implications for overall environmental impact. For example, the plastic wearing off the bottom of a shoe sole has greater impact on 104

bioaccumulation and toxicity thresholds if the ground is covered in 50 years' worth of plastic than if there is 1 year worth in areas where these shoes recently started being sold. Finally, accounting for species that may be dependent on resource flows in and out of a product could significantly affect environmental impact. For instance, waste heat emitted from a power plant could kill some local species while creating a habitat for others, potentially altering the biodiversity balance associated with the design, as has occurred in

California where the waste heat from power plants has created a habitat for sea turtles [120].

This approach from ecology considers the potential for higher-level environmental impacts than occur on the level of individual organisms. As Ricciardi et al. [114] note, environmental impact in biology can be assessed at a wide range of scales to provide insights into different types of environmental effects, including “the level of an organism (e.g., effects on individual mortality and growth), a population (abundance, genetics), a community (species richness, evenness, composition, trophic structure), an ecosystem (physical habitat, nutrient cycling, contaminant cycling, energy flow), or a region (species richness, beta diversity).” Similarly, the impacts of consumer products could be measured at higher orders of scale to reveal insights into environmental effects currently overlooked in the current paradigm focused on the scale of individual products.

The factors discussed above emphasize the importance of context on the environmental impact of a design from a high-level 'design population' perspective not frequently considered in the sustainable design community. The discussion of these factors highlights the value of developing a deeper understanding of the relationship between the product and its environment - the needs and vulnerabilities of organisms and ecosystems 105

potentially affected by the product, the existing human impacts at the site of manufacture, use, and end-of-life, for instance, and the expected total impact of all the individual products manufactured according to a particular design, accounting for the potential longevity of the design itself and the effect popularity of the design in one geographic area might have. Methods to account for many of these factors when analyzing the relative environmental impact of products have yet to be developed.

7.3.2.2 Discussion of Environmental Issues Raised by Using the New Framework

The newly-developed framework is different from existing LCA frameworks for a number of reasons. First, the new framework puts much greater emphasis on context; each analysis within the framework is focused solely on one particular context and considers a broader array of contextual issues than is typically accounted for in LCA, such as population effects, for instance. The new framework focuses on the context-product pairing, rather than solely on the product. In addition, the importance of each type of impact (toxic emissions, etc.) in this framework depends on context (the species present in the local environment and how sensitive they are to the relevant impacts, the amount and type of other toxic emissions that have already been released in the environment, etc.). The fact that products cannot be analyzed in this approach without regard to their context makes it far more difficult, if not impossible, to provide blanket environmental recommendations to an average consumer.

Second, because the product and its context are analyzed together within this approach, this method does not identify good or bad products for the environment, nor does it declare that certain types of environmental impacts are inherently good or bad. Instead, 106

this new framework explicitly acknowledges that some products or impacts are good for the environment in some contexts but that same products or impacts may be bad in other contexts. Consequently, it highlights the need to ask more specific questions related to the environmental impact of products. One should not ask: ‘Are electric vehicles better for the environment than gasoline-powered vehicles?’ but instead: ‘Are electric vehicles better for the environment in my specific community (which receives its electricity from a particular mix of fuels with a particular set of environmental impacts) and for someone with my driving habits?’

Third, the new framework accounts for the total quantity of products or functional units in an environment, a critical aspect of sustainability often neglected in LCA. Fourth, this approach weighs global and local impacts differently, with the awareness that an impact that harms a local environment could result in a benefit globally. Fifth, as opposed to LCA, which centers on minimizing environmental impacts, this framework is focused on maximizing species diversity.

7.4 CONCLUSION

This chapter provided an overview of some environmental impact measurement frameworks besides LCA and explained how they account for context and how LCA and sustainable design practitioners might benefit from studying them. First, the discussion of ERA highlighted the importance of considering the context- specific factors, such as the location and timing of emissions, and accounting for the absolute quantity of emissions or impact for a particular project, rather than focusing on the impact that corresponds to a functional unit. Accounting for these factors enables the prediction of actual environmental impacts. 107

Likewise, the section on EIA emphasized the importance of considering contextual factors in analysis, as it requires context-specific data to ensure accuracy of the environmental impact prediction, as well as the importance of accounting for the total quantity of impact. In addition, the discussion of ecological impact assessment from biology raised the point that the same organism or product performing the same tasks can have very different environmental impacts – in terms of both size and the ‘goodness’ or ‘badness’ of the impact – depending solely on contextual factors. Consequently, product designers may benefit from considering sustainability as something that involves both a product and a context together, recognizing that different contexts will be affected by the same product in different ways and these effects may cause damage in some contexts but have environmental benefits in others. Also, LCA practitioners and sustainable product designers may benefit from translating the impacts of the designs they are assessing into impacts on biodiversity and by distinguishing between local and global biodiversity issues. They may also benefit by accounting for higher-level elements of context considered in ecological assessments of environment impact, namely population density, population distribution, the length of time a population has remained at a site, and the dependence of other species on material flows.

Finally, a new LCA framework inspired by biological constructs of ‘environmental impact’ that better accounts for contextual effects was presented and discussed, with emphasis placed on explaining how the higher-level contextual factors considered in biology might be accounted for in an LCA focused on engineered products.

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This chapter concludes the section of this work examining context in LCA and sustainable design. Now, the focus shifts towards documenting the set of concepts that encompass the current paradigm of environmental sustainability (Chapter 8), so that problems in this paradigm can be identified (Chapter 9) and a new paradigm that avoids these problems can be proposed (Chapter 10).

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Chapter 8: Current Paradigm of Environmental Sustainability

In some sense, the underlying goal of those pursuing environmental sustainability is to avoid environmental problems caused by humans, such as acid rain, chemical releases, and climate change. While there are a wide range of perspectives within this community, environmental problems are frequently presented in the context of a greater story of human development, in which the industrial revolution profoundly changed human impact on the environment, new technology promoted the growth of the human population, and a culture of consumerism developed in wealthier regions, increasing the impact of individuals on the environment – all resulting in significant, human-caused environmental problems both locally and globally. These impacts have been deemed 'unsustainable' because, if the current relationship between humans and the environment continues, it threatens the viability of human life – and perhaps even life in general. Within the environmental dialogue, there is a sense that humans, technology, and their impacts are 'bad' and everything else is 'good.' Hence, the job of the sustainable product designer in this framework is to reduce human impacts and help humanity return to a 'sustainable' impact level, while still maintaining a high quality of life for people through the development of low-impact designs. Many common themes regarding environmental sustainability and environmental impact are referenced in the literature. This chapter presents and discusses these themes to outline the collection of ideas that encompass the existing environmental sustainability paradigm. First, conceptions of sustainability are discussed. Second, definitions of environmental impact are presented. Finally, the reductionist approach to environmental sustainability adopted by many LCA and sustainable design practitioners is examined, 110

along with the implications of adopting such an approach when defining what it means to be a sustainable product or person.

8.1 SUSTAINABILITY

Three conceptions of sustainability that are widely referred to in the literature on sustainable design are explained below: (1) the three pillar model of sustainability, (2) the idea that sustainability means preserving access to resources for future generations, and (3) the notion that sustainability entails ensuring the earth can continue to support human life.

8.1.1 Three Pillar Model of Sustainability

In the three pillar model, sustainability is understood as arising from the interplay of economic, social, and environmental factors. Authors who ascribe to this concept describe sustainability “as a three-legged table consisting of the environment, the economy, and society” [121] or “people, profit, and planet” [122]. Economic sustainability is associated fair prices for both producers and consumers; environmental sustainability concerns the preservation of the environment and maintaining a supply of natural resources; and social sustainability addresses the needs of society and how these needs are met by industry [123]. Within this model of sustainability, economic, environmental, and social factors are considered together to highlight the important relationships between them. It is important to understand, for instance, that lack of economic stability can promote environmental degradation by making wood collection or environmentally-damaging farming practices financially necessary. Similarly, developing a product that is environmentally sustainable is of no use if it does not fulfill a true social need or if it is too expensive. Consequently,

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those who use the three pillar model strive to understand all three aspects of sustainability as they relate to their product or issue of interest. However, the way each of these aspects of sustainability is achieved is quite different. For instance, very different methods are used to ensure a product is inexpensive, as opposed to ensuring a product will have a small environmental impact. Consequently, the tools that help engineers design environmentally sustainable products are often discussed in isolation of the other two pillars of sustainability, as is the case in this work.

8.1.2 Resources for Future Generations

Another interpretation of ‘sustainability’ deals with ensuring future generations have enough resources to meet their needs. A number of sources discuss sustainability in this manner. For instance, Our Common Future defines sustainable development as “development that meets the needs of the present without compromising the ability of future generations to meet their own needs” [124]. Others echo this sentiment, defining sustainability as “meeting the resource and services needs of current and future generations without compromising the health of the ecosystems that provide them” [121]; as “preserving the environment and sustainable use and management of natural resources” [123]; and as ensuring that “future generations… have access to the same resources as those that the present generation has at its disposal” [125]. Clearly, there is a global limit to the amount of resources humanity has at its disposal at any point in time. To preserve resources for future generations, present generations must live within the earth’s carrying capacity. When nonrenewable resources are consumed, future generations have fewer of these resources available to them. When renewable resources are consumed faster than they are produced, the resource base is 112

likewise threatened. To manage renewable resources in a sustainable way, “harvest rates should equal regeneration rates”; similarly, nonrenewable resources can be consumed “in a quasi-sustainable manner by limiting their rate of depletion to the rate of creation of renewable substitutes” [126]. Those striving to achieve this flavor of sustainability need to ask: can the current environmental trend of interest “keep going on in this way, on this scale, at this pace, without reducing the likelihood that future generations will live as prosperously and comfortably as ours has?” [36].

8.1.3 The Earth Can Continue to Support Human Life

The final concept of environmental sustainability presented here concerns preserving the ability of the earth to continue to support human life. Many sources discuss this view of sustainability, stating: “Achieving sustainability will enable the Earth to continue supporting human life” [127]; “a sustainable human civilization… can thrive for millennia without degrading the planet on which we all depend” [128]; and when we talk about the need “to shift toward a truly environmentally sustainable world that meets human needs,” “[w]e are talking about the survival of human civilization as we know it, and possibly of the species itself” [36]. This understanding of ‘sustainability’ is focused on ensuring that the environment is safe for people and that the resources we need from the environment to survive are available. Achieving this type of sustainability involves ensuring that human beings avoid destabilizing the environment so that life can continue to have the habitat and resources necessary for survival. For the earth to support human life, a number of conditions must be met. First, there must be clean air, water, and productive land [121] available in sufficient quantities to support the human population and the population of biological organisms 113

upon which human life depends. For these resources to be available, sudden change to the planet’s ecosystem must be avoided. Moore and Rees [129] warn that human impacts threaten to ‘flip’ the ecosphere “into an alternative stability domain that may not be amenable to human civilization,” and Rockstrom et al. [130] propose a set of ten planetary boundaries - related to climate change and biodiversity loss, for instance - that “must not be transgressed” if we want to avoid “unacceptable environmental change” that might make the earth less conducive to supporting human life.

8.2 ENVIRONMENTAL IMPACT

This section discusses issues pertaining to how ‘environmental impact’ is defined and addressed in literature on LCA and sustainable product design. First, it is established that authors typically emphasize the human connection when defining environmental impacts, problems, and issues. Second, the reasons for focusing on anthropogenic impacts are presented.

8.2.1 Environmental Impacts, Problems, and Issues are Typically Defined in Terms of Human Impacts

Environmental impacts, problems, and issues are generally defined in terms of human impacts. For instance: “the sum of current economic activity creates the sum of current environmental problems” [23]; “Environmental issues are harmful effects of human activity on the biophysical environment” [131]; “the collective sum of our individual actions… added to the effects of the societal structures we’ve created, lead to negative consequences for our environment” [132]; and “In general, environmental impact comes from (excessive) consumption of natural resources and emissions of pollutants to air, water, and land” [47] by humans. 114

Similarly, the environmental impact of something is measured against a previous state of the environment, or the expected state of the environment had a human activity not been undertaken. For instance: “the perception of impacts as an environmental problem is only influenced by the deviation from the natural situation, say, before the industrial era” [23]; and “The environmental impacts of a project are those resultant changes in environmental parameters… compared with what would have happened had the project not been undertaken” [101]. Ultimately, what constitutes an ‘environmental problem’ is subjective and is related to society’s value judgements and perception of the types of things that reduce environmental quality [23]. As a result, the “disappearance of birds or forests, household waste, depletion of the ozone layer, decrease in reproductivity of mammals, destruction of historic buildings by acid precipitation, and increase of the world population are all sometimes considered… environmental problems” [23].

8.2.2 Why Focus on Anthropogenic Impacts?

The focus of those concerned with achieving environmental sustainability is on reducing anthropogenic environmental impacts because humans arguably dominate the change in ecosystems happening across the world. As Vitousek et al. [133] state:

Between one-third and one-half of the land surface has been transformed by human action; the carbon dioxide concentration in the atmosphere has increased by nearly 30 percent since the beginning of the Industrial Revolution; more atmospheric nitrogen is fixed by humanity than by all natural terrestrial sources combined; more than half of all accessible surface fresh water is put to use by humanity… we live on a human-dominated planet.

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In other words, humans are the destabilizing force in the environment. Historically, humanity has caused many environmental problems, and our growing population amplifies the risk of environmental disaster; “we can anticipate that supplying food, fiber, and metals for a population even larger than today’s will have a profound (and destabilizing) effect on the global ecosystem under any set of technological assumptions” [134]. Humanity is exerting “enormous global forcings” that could cause a “global-scale state shift” in the biosphere “within decades to centuries” [135], potentially putting the ability of the earth to support human life in jeopardy [130]. Hence, those concerned with sustainability focus on reducing human impacts on the environment.

8.3 THE REDUCTIONIST APPROACH TO ACHIEVING SUSTAINABILITY IS TO MINIMIZE HUMAN ENVIRONMENTAL IMPACT ON SMALL SCALES

Many efforts to achieve environmental sustainability are focused on minimizing human environmental impacts on small scales, for instance, by minimizing the impact of consumer products, as occurs in sustainable design. This is a reductionist approach, in which the far-reaching problem of humanity’s collective environmental impact potentially jeopardizing resource availability and preservation of a habitat for humans on earth is reduced to billions of miniscule problems concerning a customer’s decision between a standard and an eco-friendly coffee maker, a homeowner remembering (or not remembering) to turn off lights when he leaves the room, and a commuter’s choice to either take the bus or drive on a given day.

Other authors make note of the prevalence of reductionist approach to sustainability as well, stating: “Even though sustainability is a macroeconomic problem… sustainable development is mainly promoted at the microeconomic level” [136]; it is commonly

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accepted “that sustainability can be achieved through a piecemeal… approach, with the aggregate of solutions to separate problems somehow adding up to a sustainable building or city” [137]; and “most research on… sustainable consumption has focused on” low- level “voluntary action-aimed informational strategies,” rather than higher-level structural strategies [82]. From an intuitive perspective, the reductionist approach appears correct; if the sum of human actions has generated the environmental issues we face, it makes sense that minimizing human environmental impacts on the level of individual human activities would fix the problem. This approach is also quite natural for scientists and engineers engaged in environmental sustainability efforts, as a reductionist approach is common in the natural sciences, where entities are frequently dissected into component parts and analyzed separately in depth. Many authors agree, stating, for instance: “the practice of science has become increasingly reductionist in seeking to understand phenomena by detailed study of smaller and smaller components” [138]; and the natural science model “for assessing ecosystems functions is to analytically dissect component parts of the whole into sub-components and functions rather than viewing them as mutually defining and interdependent” [139]. The reductionist approach has influenced research aimed at achieving environmental sustainability as well. Those working in sustainable design, sustainable consumption, LCA, and related fields tend to adopt the reductionist approach and focus on minimizing the environmental impact of small-scale functional units, products, and individual consumption activities. For instance, numerous product designers strive to make products with minimal impacts, and many eco-conscious consumers try to minimize the 117

environmental impact of their daily activities and lifestyles. A number of authors note the role the reductionist approach has in LCA, stating, for instance: “LCA was initially designed for micro-level applications that cause changes on a micro level” [104]; “Life- cycle assessment… focuses on individual products… The calculations… take a bottom-up approach to the environment” [140]. The influence of the reductionist approach can be seen in the many LCAs focused on minimizing the environmental impacts of low-level functional units. Although the functional unit under study in an LCA could theoretically be any size function, they are frequently selected on the scale of products [35] or smaller. The choice of low-level functional units appears reasonable for many types of problems in LCA and sustainable design. “After all, if an assessment suggests that one product is better than another product, then one would expect that the relative performance of a large number of these same two products should be consistent with the product-based analysis” [35].

The influence of the reductionist approach in LCA and sustainable design can also be observed through the emphasis placed on environmental individualism, i.e. the concept that environmental sustainability can be achieved through the personal lifestyle and product choices individual consumers make, a premise which underlies much of the work in sustainable design.

8.3.1 Sustainable Products

Product designers consider sustainability on a small scale when working to design sustainable products. The field focused on developing sustainable designs for products, processes, systems and services is referred to in this work as sustainable design, but it is known by many other names, including green design, ecodesign, and design for 118

environment. This section explores two commonly-discussed notions of what it means to be an environmentally sustainable product: (1) having no environmental impact, minimal impact, or a reduced impact, and (2) possessing environmentally friendly characteristics or features.

8.3.1.1 Having No Impact, Minimal Impact, or Having a Reduced Impact

In general, the sustainable design community associates environmental sustainability with the minimization or reduction of environmental impact, as demonstrated in numerous quotations to that effect from the literature: the “ultimate goal” of the sustainable design movement “is not only to reduce impact to the natural environment, but also to eliminate negative environmental impact completely through skillful, sensitive design” [141]; sustainability is about finding the global minima of environmental damage: “local minima of environmental damage… fall short of sustainability” [31]; “The emphasis and language of green design is largely one of reducing resource use and adverse environmental impacts” [142]; “green design is primarily directed at ‘doing less harm’ or, more generally, reducing the degenerative consequences of human activity on the health and integrity of ecological systems” [143]; and “The concept of 'ecodesign', 'green design', or 'life cycle design', concerns… the prevention of waste and emissions and the minimization of… environmental impact” [144]. More specifically, many researchers in sustainable design adopt a reductionist perspective, striving to reduce the environmental impact of designs on the low-level scale of products. Hence, many sustainable design researchers operating within this framework strive to design products with no, a low, or a reduced environmental impact compared to alternatives. Authors agree, stating, for instance: many people in sustainable design seek 119

“to solve individual problems with the objective of causing ‘less harm’ or even ‘net zero’ solutions that ‘minimize’ or ‘mitigate’ harmful human activities” [145]; “Products need to be developed that meet consumer requirements but have a minimum negative ecological… impact along the whole supply chain” [45]; “eco-design and design for environment” strive for products that “make the lowest possible environmental impact throughout the product’s life cycle” [9]; “Ecodesign involves a combination of strategies to minimise total environmental impacts over the whole life cycle of a product” [146]; “The general goal of environmentally conscious approaches to product design is the reduction of the negative environmental impact of a product throughout its life cycle” [47]; “reducing the environmental footprints associated with… products has critical importance in addressing the environmental sustainability challenge” [6]; and “Sustainable product development approaches… mainly focus on reducing the environmental impacts of products” [147]. Within the reductionist framework, a perfectly sustainable product is one that performs its function with no negative environmental impact – no material or energy consumption, no emissions, no waste. Since this goal is rather lofty, in practice, a sustainable product is generally regarded as one with a smaller environmental impact than a functionally-equivalent comparison product. Hence, a product is considered ‘sustainable’ if it has no measurable environmental impact or a reduced environmental impact compared to the original design or a functionally-equivalent product. Quotations to this effect are prevalent in both academic and popular literature. For instance: “A sustainable product… should… have a low-impact or no-impact on the environment” [148]; “A truly sustainable building is one that has no negative operational impact on the environment and few embodied ones” [141]; and “Manifestations of sustainable design… impact the 120

environment minimally” [149]. As a result, a significant amount of research in LCA and sustainable design is focused on reducing, minimizing, and avoiding environmental impact. For instance, there is much research in the area of net zero energy buildings, “highly energy-efficient buildings” that theoretically have “no adverse energy or environmental impact associated with its operation” [81]. As a result of this understanding that a product is sustainable if it has a lower environmental impact than a functionally-equivalent competing product, LCAs are frequently focused on answering the question: “Does product A have a larger or smaller impact than product B?” where the comparison is between fluorescent and incandescent light bulbs, paper and cotton diapers, or glass, plastic, and carton milk packaging, for instance [150]. The results of these LCAs are used to determine which product is lower- impact in an assumed scenario and is therefore, presumably, more sustainable. Sometimes, these results are used for marketing purposes; for instance, some companies list carbon footprints on packaging to allow customers to compare the environmental impact of products in stores [151].

8.3.1.2 Possessing Sustainable Design Characteristics or Features

Alternatively, some associate general design characteristics or features with sustainability. Sources state, for instance, that “designers can recognize environmentally friendly features for each concept and integrate them in an early design stage leading towards a sustainable product” [152], and “Different factors can be considered as measures of a sustainable product, including product attributes such as… shape and weight” and “production attributes such as manufacturability and ease of assembly” [148].

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Many types of features are believed to help a product be environmentally sustainable. The literature provides a variety of examples. For instance, “Manifestations of sustainable design require renewable resources” [149]; “An eco-design product has a cradle-to-cradle life cycle ensuring zero waste is created in the whole process” [153]; the criteria for an “environmentally friendly innovation” include reduced GHG emissions, “use of renewable resources,” and resource efficiency [154]. Other characteristics of this sort can be found in lists of sustainable design guidelines, such as the 76 design for environment guidelines from Telenko et al. [155].

8.3.2 Sustainable People

Another relatively small-scale approach to sustainability is to assess the sustainability of individuals and their lifestyles, as is commonly done in the field of sustainable consumption and is the basis for numerous sustainability efforts aimed at engaging the public. Within this context, the reductionist approach emphasizes the importance of environmental individualism, the idea that individuals’ efforts to reduce their personal environmental impact by buying low-impact products or making lifestyle changes lead to wider-scale environmental sustainability. Work in this area focuses on instilling in individuals a sense of responsibility to protect the environment and on public education initiatives concerning things individuals can do and change about their lifestyle to reduce their personal impact. Csutora states, for instance: “There are many popular calculators available for measuring the impacts of individual consumption patterns on the “ecological footprint”… They indicate tremendous potential for reducing the footprint through individual level efforts” [82].

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This section seeks to explain what it takes for a person to be considered environmentally sustainable. Three different views are discussed: (1) a sustainable person is an ethical consumer who purchases low-impact products, (2) a sustainable person gets educated and changes his or her lifestyle to reduce his or her environmental impact, and (3) a sustainable person uses only his or her share of earth’s resources.

8.3.2.1 Buying Low-Impact Products

Some maintain that a sustainable person is an ‘ethical consumer’ who buys low- impact products as a result of personal ethical inclinations. An “ethical consumer… perceives a… direct link between what is consumed and the social issue” [123]. Consequently, ethical consumers are more likely to buy products they believe are good for the environment – “such as organic and locally grown fruit and vegetables, recycled paper, alternative formulations for detergents, eco-friendly magazines or low-energy light bulbs” [156] – and avoid buying products they believe are harmful [157].

Many factors increase the likelihood a consumer will purchase low-impact products, including being strongly committed to helping the environment and having “good knowledge of the relevant environmental issues” [158]. Those who think ethical consumerism is an important part of achieving a sustainable society maintain that the key to achieving environmental sustainability is to instill a concern for the environment in all people so that more consumers will choose to buy low-impact products and to inform consumers via education initiatives about important environmental issues that are affected by personal consumption. There is some evidence that the general population accepts this idea of what it means to be a sustainable person. Through a survey, Jensen [106] found that “Generally… 123

environmental awareness is considered as something to be manifested through buying green or labelled products… rather than not buying or not using certain products.”

8.3.2.2 Making Sustainable Lifestyle Changes

Another related idea is that a sustainable person is one who is willing to get educated and make lifestyle changes to help the environment that go beyond purchasing green products and actually affect the behavior and actions of individuals. This concept is characterized by slogans like ‘reduce, reuse, recycle’ and is embodied in the wide range of self-help environmental sustainability resources, of which there are many. For instance, there have been numerous environmental campaigns encouraging individuals “to turn off the light when it is not being used, to buy energy-saving bulbs, to take the bicycle to the baker on Sundays, and… to reduce the stand-by consumption” [106]. In addition, the publication “100 Ways You Can Save the Earth” lists tips such as “Walk or ride a bike instead of using the car for short trips,” “Water lawns at night to limit evaporation,” and

“Start an organic garden” [159]. Also, the book The Consumer’s Guide to Effective Environmental Choices: Practical Advice from the Union of Concerned Scientists provides an array of advice on how to best act to protect the environment, including using a microwave rather than an electric oven whenever possible and “eating less beef” [160].

8.3.2.3 Using Only One’s Share of Earth’s Resources

Another popular view is that a sustainable person would live in a manner such that if all people currently living adopted the same general consumption patterns and lifestyle as this person there would be no risk of causing permanent, negative change to the environment. As Hertwich [10] states: “Sustainable consumption patterns can be defined

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as patterns of consumption that satisfy basic needs, offer humans the freedom to develop their potential, and are replicable across the whole globe without compromising the Earth’s carrying capacity.” A sustainable person would, for instance, consume only his or her fair share of the global resources available for human consumption, divided evenly amongst all people. For instance, Moore takes this approach when she defines sustainability “as one-planet living, which uses the ecological footprint as a metric to orient consumption to global ecological carrying capacity” [161]. Likewise, Moore and Rees [129] adopt this approach when they refer to 1.7 global hectares “to be each person’s equitable or “fair Earth-share” of global biocapacity,” i.e. they wager that each person on earth can sustainably use the resources generated by 1.7 hectares of biologically productive land and sea with average productivity each year. Similarly, a sustainable person would only be responsible for emitting GHG emissions equivalent to his or her share of the acceptable level of human-generated GHGs divided evenly amongst all people. Engelman [36] adopts this approach when he calculates

690 kg of carbon dioxide equivalent (CO2eq) emissions as the maximum any person could be responsible for in one year and still “claim that his or her lifestyle is atmosphere- sustainable,” based on an assumed global cap of 4.9 billion tons CO2eq per year.

8.4 CONCLUSION

This chapter examined the way in which the terms ‘sustainability’ and ‘environmental impact’ are discussed in the literature on LCA and sustainable design, as well as the reductionist approach authors in those fields typically take when establishing what it means to be a sustainable product or person. The topics addressed in this section outlined the collection of ideas that encompass the existing environmental sustainability 125

paradigm and provided insight into the assumptions commonly made by researchers in the field and the set of perspectives frequently adopted. First, three common conceptions of ‘sustainability’ were presented: (1) the three pillar (economic, environmental, and social) model of sustainability, (2) the idea that sustainability means preserving access to resources for future generations, and (3) the notion that sustainability entails ensuring the earth can continue to support human life. The three-pillar model is most easily applied to specific products and projects as a way to check if the entity being analyzed is environmentally and socially ‘good,’ and whether it is economically viable. In contrast, the other two conceptions of sustainability are higher- level ideas related, first, to equity and fairness regarding whether the lifestyles of currently- living people are depriving people in the future of resources, and, second, to avoiding a doomsday scenario in which the earth is no longer able to support human life. Second, the most typical understanding of what constitutes an environmental impact is provided, emphasizing the critical importance of the role of humans on this distinction. In the literature, environmental impacts, problems, and issues of interest to the LCA and sustainable design communities originate only from humans. As a result, negative impacts from other sources, such as other biological organisms, are neglected, and the focus of the field is on reducing and eliminating human-originated impacts. While such a perspective may be justifiable since humans are such an immense force for global environmental change, this perspective is not necessarily the only reasonable one to adopt.

Third, the reductionist approach to addressing environmental sustainability issues is presented, where low-level sustainability solutions are assumed to contribute to global sustainability. Within this framework, researchers and environmentalists maintain that if 126

every product were a ‘sustainable’ product (a low-, no-, or reduced-impact product or a product with ‘sustainable’ features) and if every person were a ‘sustainable’ person (and did their part by exclusively buying ‘sustainable’ products, adjusting their lifestyles to be more sustainable, or using only their fair share of earth’s resources), then global sustainability would be achieved. Hence, research into low-level, detailed solutions to small environmental problems (minimizing the environmental impact of a cup of coffee, or helping a particular individual minimize the environmental impact of her morning commute) are considered justified.

The next chapter challenges these views and presents many problems with the reductionist approach. In addition, Chapter 10 presents an alternative paradigm for thinking about sustainability and environmental impact that does away with many of the assumptions and perspectives presented here.

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Chapter 9: Problems with the Reductionist Approach

This chapter discusses a number of problems with applying the reductionist approach to issues related to sustainability and the minimization of environmental impact. First, it is difficult, if not impossible, to achieve the reductionist goal of minimizing impact on a small scale, and approaches to sustainable product design that focus on incrementally reducing the environmental impact of products are not drastic enough to achieve sustainability. Second, even if designers succeed at minimizing low-level impacts of product or individuals, doing so will not achieve sustainability because sustainability does not result from the sum of sustainable parts. There are many types of system-level effects – including network effects, scale effects, quantity-related effects, rebound effects, synergistic effects, and collective effects – that could undermine efforts on this front. Third, the reductionist approach neglects context and its significant influence on environmental impact. Fourth, the reductionist approach misses an important avenue to achieving sustainability: implementing systems-level, structural changes. Finally, trying to achieve sustainability via the reductionist approach may distract and prevent sustainable designers and eco-conscious consumers from making real progress towards sustainability by working to implement large-scale change.

9.1 IT IS DIFFICULT, IF NOT IMPOSSIBLE, TO ACHIEVE SMALL-SCALE SUSTAINABILITY

The reductionists’ goal of achieving sustainability by eliminating environmental impact on the scale of a single product or person is very difficult, if not impossible, to achieve.

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9.1.1 For Products, Minimizing Low-Level Impacts Is Not Enough

Attempts to achieve environmental sustainability by entirely eliminating environmental impact at the product level (i.e. designing a product with no environmental impact) face insurmountable constraints, as any use of materials or energy is associated with some type of environmental impact. Brower and Leon [160] explain, for instance, that “The use of… gasoline, whose burning emits air pollutants and… carbon dioxide, necessarily harms the environment. If we… are going to consume such materials, no conceivable technology can completely avoid environmental damage.” Without expanding the scale of analysis beyond the product itself, the goal of a sustainable product with no environmental impact can never be realized, as all products consume some energy and materials. Moreover, reductions currently seen in the environmental impact of ‘sustainable’ products are not enough to achieve global environmental sustainability. Instead, many sustainable design efforts more closely resemble product tweaks than system overhauls, with designers often focused on eliminating ‘unsustainable’ elements, as Kota et al. [75] note, rather than generating entirely new concepts for sustainable designs. For instance, an aluminum part may replace a steel one in a car, resulting in a slight increase in fuel efficiency, and environmental sustainability declared. Many authors agree, stating, for instance: “with so much labeled… sustainable, the term… at best indicat[es] a practice or product slightly less damaging than the conventional alternative” [37], and “Simply doing ‘better’ environmentally will not stop the unraveling of ecological relationships we depend on for food and health… vastly larger changes are needed than we have seen so far” [36]. Similarly, McLennan [141] states that “For many professionals a green building is

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something that… incorporates a few recycled products or has good windows”; however, this approach to sustainable design “is not nearly enough.” To make matters worse, incremental improvement in the impacts of consumer products can entrench high-impact technologies and approaches, potentially doing more harm than good when cleaner options are available [24]. Instead, approaches to reducing environmental impact on a broader scale are needed. Numerous authors echo these conclusions. For instance, Ceschin [162] argues that “innovations on a process and product level, although being fundamental and necessary, are not… sufficient to obtain the… radical shift” in production and consumption that is needed to achieve sustainability; instead, “there is a need to move from a focus on product improvements only, towards a wider systemic approach.” O’Rourke et al. [24] agree, stating that “although new approaches to design can realize incremental reductions in the environmental burden of products and processes,” sustainable design on this level “will not advance the larger technological and cultural shifts in industrial practice that we believe are necessary to achieve” environmental sustainability.

9.1.2 For Consumers, Minimizing Low-Level Impacts Is Not Enough

Similarly, it may not be possible to achieve a sustainable level of human consumption in wealthier parts of the world by focusing on reducing impact on the level of individuals alone, even if the individuals in question were to accept a massive lifestyle change to reduce their impact. For instance, Moore and Rees [129] discuss Moore’s [161] finding that:

[E]ven if average Vancouverites followed a vegan diet; avoided driving or flying and only walked, cycled, or used public transit; lived in a passive solar house that 130

used almost no fossil-based energy; and cut their personal consumption by half, they could only reduce their per capita Ecological Footprint by 44 percent (from 4.96 to 2.8 gha per capita). That seems like an impossible challenge already – and yet it is still a full global hectare beyond the one-planet threshold.

Other authors agree, stating: “individual consumption strategies may result in somewhat reduced environmental loads for committed consumers, but this reduction cannot offset the total impacts” which are dictated by economic factors, with higher- income consumers polluting more [82]; and “even if… we really do decrease our driving, stop littering, and refuse plastic… bags… the broader impacts are still negligible, since day-to-day individual actions do not contribute the bulk of today’s environmental harm” [163]. Furthermore, it is clearly impossible to convince all consumers to make eco- friendly choices consistently in all aspects of their lives. Not all consumers are interested in making eco-friendly choices, and those who are interested are faced with intellectual and time-related burdens (because they must analyze the environmental impact of their decisions), financial burdens (if the eco-friendly option is more expensive), and constraints due to the products and infrastructure available in their area. In addition, consumers are often not well-positioned to understand the environmental impacts of the products they buy; they are subject to marketing claims that may or may not be true, and they are unlikely to run their own analysis to understand their context and the impact the product would have for them. Consequently, the grassroots approach to achieving environmental sustainability can never achieve the same levels of environmental impact reduction that a more centrally- implemented environmental regulation or policy could.

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9.1.3 Conclusion

The goal of reductionist approaches to environmental sustainability – developing designs and methods to minimize the impact of individual products and consumers – is difficult, if not impossible, to achieve, and the progress that has been made in this area is nowhere near sufficient to stop the environmental damage that threatens our way of life. To achieve environmental sustainability, higher-scale environmental solutions must be sought.

9.2 MINIMIZING LOW-LEVEL IMPACTS MAY NOT LEAD TO DECREASED IMPACT OVERALL BECAUSE OF SYSTEM-LEVEL EFFECTS

This section discusses the reasons why working to minimize low-level impacts (e.g. those of functional units or individuals) may not lead to environmental sustainability and decreased environmental impact overall, namely network effects, scale effects, quantity- related effects, rebound effects, synergistic effects, and collective effects.

9.2.1 Low-Level Environmental Effects May Not ‘Ripple Up’ the Supply Chain

When making an environmental decision, consumers and LCA practitioners typically assume the rest of the system stays static, i.e. they assume that when someone chooses a paper bag over plastic, the ripple effect down the supply chain will cause one more paper bag to be produced and one fewer plastic bag, and everything else in the world will remain unchanged. Attributional LCAs assume that supply is totally elastic and that low-level environmental effects ripple up the supply chain and result in a small change globally, i.e. “The induced demand for one unit of product leads to the production and supply of one unit of product, with associated emissions and resource consumptions” [11].

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However, this may be an unfair assumption. Supply is not totally elastic in the real world. Consequently, “it is reasonable to expect that the assumption is invalid for products in general” [22]. As a result, small-scale impact minimization may have no effect on global environmental impact whatsoever – or it may increase the collective environmental impact – due to economic realities or other constraints. For instance, shopping bags are purchased in bulk by stores, so a customer’s decision to choose paper over plastic likely will only ripple up to the store level, causing the store to run out of paper bags one bag sooner than expected. If many people make this same choice in unison, perhaps this will cause a temporary paper bag shortage at the store, ultimately forcing a different customer to use a plastic bag because no paper bag is available, resulting in no net environmental benefit of the first customer’s paper choice. On the other hand, perhaps the store will re-order paper bags one bag sooner, allowing the effect to ripple up to the level of the paper mill. If the mill is already running at full capacity, it may not be possible to fill the order sooner, resulting in a temporary shortage and no net environmental benefit. Unless there is an immense increase in demand (enough to justify building a new paper mill or paper bag-making facility), there be no environmental change caused by the customer’s choice. The reality of these distorted or obstructed environmental effect ripples may be so important that environmentally-related decisions ought only to be made on high levels of scale, where the supply chain effects are more predictable (such as a grocery store deciding to only offer paper bags) as opposed to on the customer level, where the supply chain effect cannot be predicted, and general environmental guidelines such as ‘choose paper over plastic’ may lead to much bigger negative environmental impacts in some cases. 133

9.2.2 Network Effects

Network effects are one type of systems-level effect that prevents the reductionist approach to sustainable design and LCA from necessarily leading to decreased impact globally.

9.2.2.1 Basics of Network Effects

In LCA and sustainable design, network effects arise out of the environmental impact network surrounding a product or system of interest. By modeling environmental impact interactions that occur as a result of the supply chain, economy, or physical environment, for instance, as a network, dynamic interactions that occur on a larger scale or in different parts of the environmental impact network than might otherwise be considered in an LCA can be taken into account, such as the interactions between individuals participating in the economy or between companies participating in an eco- industrial park.

Modeling network effects as they pertain to the assessment of environmental impact is akin to greatly expanding the system boundary of an LCA and including more detailed contextual information in the model. This is very different from the assessment of the environmental impact of single-entities. In the single-entity analysis, the focus is on optimizing the environmental impact of the entity using a bottom-up approach in which “impact is divided per unit” [140]. In contrast, analysis performed on a network is focused “on finding a fair solution for the individual actor as part of the network” of interacting parties and a top-down approach is taken [140]. Consequently, consideration of a broader network in LCA can greatly affect the outcome deemed to be lowest-impact, with options

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such as eco-industrial parks only arising when the broader network is considered in the analysis. Network effects are often unpredictable and appear because seemingly-negligible differences in one portion of a network can generate significant differences in a region of the network one might otherwise expect to be relatively unaffected. The existence of network effects is worrisome because it means that low-level modifications aimed at reducing the environmental impact of a design (the outcome of the reductionist approach) may cause unforeseen problems in other areas of the environmental impact network, potentially mitigating any anticipated benefit. That is, seemingly environmentally-friendly decisions may have unintended effects that result in environmental harm. Similarly, a seemingly environmentally-unfriendly decision could have positive environmental impacts as a result of network effects. Consequently, an LCA that analyzes only one product – or even one industry – may miss important environmental implications.

9.2.2.2 Previous Work in LCA Related to Environmental Impact Networks

Some previous work in LCA adopts the idea of a causal chain or causal network when discussing environmental impact. For instance, consequential LCI models “chains of causal relationships,” beginning with a decision with environmental implications and showing both the direct and secondary effects of the decision, including, for instance, how the decision affects “the production of… intermediate products” and “the use of the intermediate products in other processes” [22]. In addition, Suh and Huppes [20] describe integrated hybrid LCA as a network of flows within the process LCA system and between the process system and the input-output LCA system. Also, Fuertes et al. [164] present an environmental impact causal model for a construction project, which consists “of a process- 135

oriented causal network of thirty-nine environmental impacts, forty-five causal factors and over two hundred causal relationships,” the purpose of which is to support “contractors and other decision-makers in the early identification of factors that are likely to lead to impacts or to exacerbate their consequences.” This approach emphasizes the importance of contextual factors in determining environmental impact. Finally, work in life cycle sustainability analysis (LCSA) considers environmental impact to take place in a causal network. LCSA accounts for “all three dimensions of sustainability” as well as “physical relations (including limitations in available resources and land), economic and behavioral relations” [150].

9.2.2.3 Examples of Environmental Impact Networks

Every product is part of a vast network with the potential to significantly affect its environmental impact. These networks are comprised of many types of relationships that influence the impact of the product in different ways. This section provides a number of examples illustrating the types of entities and relationships that might be relevant to include in an environmental impact network. In the case of a TV, for instance, the environmental impact network includes (1) “technological relationships: using a TV requires the existence and hence the production of a TV, electricity, and TV broadcasts,” (2) “behavioural relationships: using a TV may induce you to use a sofa, to eat popcorn, and to buy advertised articles,” (3) “economic relationships: using a TV implies spending less on other activities,” and (4) “legislative relationships: TVs are required by certain laws to possess certain safety measures, such as flame retardants and electric fuses” [165].

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Environmental impact networks may be far-reaching, as has been noted by other authors. For instance, Udo de Haes and Heijungs [39] discuss the environmental impact of transporting glass, which is influenced by “the fuel of the trucks… the production of the trucks and… the building of the factory in which the trucks were constructed,” and note that “There is always a process behind a process” [39]. Chapman [38] echoes these sentiments:

The production of a consumer product in the UK requires inputs from all the production processes in the country and, through international trade, from all the production processes in the world. For example, a loaf of bread requires wheat which has to be milled, cooked and transported. Transport requires fuel and vehicles, for which steel, rubber, copper and energy for fabrication are necessary. Shops and bakeries need bricks, steel, cement, wood and glass; wheat production must have tractors, fertilisers, insecticides etc.

The diagram below provides an example of the types of physical and economic interactions that may be relevant when calculating the environmental effect of a change in demand for a product using a network perspective. In this case, there is multifunctional process with two sub-processes that produce two different products.

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Figure 6: “Illustration of a theoretical multifunction process consisting of two separate sub-processes and of the activities that may be indirectly affected by a change in the production of product B” [7].

Ekvall and Finnveden [7] explain:

A significant change in sub-process 1 may affect the environmental burdens of sub-process 2, even when the sub-processes are physically separate. If the economic viability of the production site depends on the revenue from both of the products, a significant reduction in the demand for product A may result in the shutting down of the production site. If the production levels of both products are restricted due to, e.g., space limitations at the site, a significant reduction in the demand for product A may result in an increased production of product B.

In addition, the change in demand for product A could alter the demand for – and environmental impact associated with – product C and other products fulfilling the same function as product B. Authors discuss examples of economic networks of this type that have the power to influence the environmental impact of a product. For example, “particleboard… is manufactured from sawdust from a sawmill… The sawdust that is not used for particleboard production is sold… for fuel… the effect of an increased production of

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particleboard is likely to be that less sawdust is sold as fuel and that other fuels… will be used instead” [22]. Also, “The effect of recycling material from old products into the system might be that landfill or waste incineration is reduced or that less recycled material is used in other product systems” [22]. In addition, switching to energy-efficient manufacturing processes may reduce the amount of natural gas consumed by these processes, thereby reducing the price of natural gas, encouraging its use in plastics production, and ultimately reducing the use of a material competing with plastic [165].

9.2.2.4 Examples Demonstrating the Importance of Environmental Network Effects

Examples of network effects demonstrate how the standard sustainable design and LCA approaches can fall short. Typically, for instance, including greater amounts of recycled material in a design would be considered an environmental benefit. However, this could be an environmental detriment instead, if another product must use virgin material as a result and if the virgin material for that product has a larger environmental impact than the virgin material for the product being designed. Similarly, a reduction in sawdust from a sawmill would typically be seen as an environmental benefit; less waste is almost always considered better for the environment. However, if that sawdust has an alternate function and is used for particleboard or fuel, the reduction in sawdust may result in an increase in the use of other fuel types, for instance, that may have a larger environmental impact overall. Hence, it is necessary to study the physical and economic networks that a product is a part of to understand the environmental consequences of making a change to the product design or the method of manufacture. However, very little work in LCA explicitly demonstrates the importance of network effects. One exception is a paper from Oberg et al. [140] analyzing the 139

sustainability initiatives of three companies on both a company level and within the context of a broader network. They found that the plans that appeared most environmentally beneficial at the company level neglected to include indirect effects of the new initiative and that these initiatives in some cases resulted in increased environmental harm when network effects were taken into account [140]. For instance, a food wholesaling company streamlined their transportation through a central warehouse, resulting in better fill rates of their vehicles and lower transportation impacts on a company level [140]. However, when analyzed at the network level, it became clear that these changes had negatively affected the transport of the company’s suppliers, who now were forced to run vehicles with low fill rates [140]. This increase in negative environmental impacts for the suppliers’ transportation more than offset the gains made by streamlining transport at the company level [140]. In addition, a bread company in Northern Sweden proposed to move south to be closer to customers [140]. While the move would significantly reduce transportation impacts at the company level, network analysis revealed that the current method of transport is relatively low-impact, due to a transportation imbalance in Sweden, where approximately twice as many goods are shipped north than are shipped south [140]. Consequently, the bread company’s proposed move would not result in significantly reduced environmental impact overall because the trucks that ship their bread would simply run empty on their return trip south [140]. Oberg et al. [140] note that since LCA is focused on a product scale it is unlikely to take these seemingly-extraneous network-level effects into account, meaning its results would mislead decision makers into making environmentally-motivated choices that actually harm the environment overall.

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Many other examples of network effects potentially mitigating the expected environmental benefit of a seemingly-sustainable action. Six such examples are provided in the table below.

Table 1: Examples of how network effects might mitigate the expected environmental benefits of a seemingly-sustainable action.

1 Low demand for recycled material leads “to oversupply of separated waste,” making “it uneconomical for it to be recycled,” and causing efforts to separate recycling to have no environmental benefit [82]. 2 “[H]ydropower is a constrained production factor in the Nordic countries. An increase in the use of hydropower for aluminium production” – for instance, because of a special eco-friendly electricity contract – “is not likely to result in an increase in total hydropower production in these countries. Instead, less hydropower will be available for other processes” [22]. 3 A consumer may purchase a ‘sustainable’ product over an ‘unsustainable’ one, but the increased demand for the ‘sustainable’ product means more must be made and shipped. If local sources for the ‘sustainable’ product are overwhelmed, and it must be transported from a different country or continent, the environmental impact could increase dramatically, offsetting the original environmental benefit associated with the product. This could be true for fruits and vegetables, for example, which would be low impact as long as the amount consumed does not exceed the amount produced locally with non-intensive farming methods. In addition, Csutora provides the example of a consumer who switches to renewable pellet-fed boilers, but local supply of pellets is insufficient, and the pellets must be “transported over long distances at high ecological cost,” offsetting the gains associated with using a renewable energy source [82]. 4 A decision to ship a product by train rather than truck may cause the trucking industry to have a higher impact per unit of goods transported (if trucks now must run emptier), or that some other good that would have been transported by train will now be transported by truck because of the change in available capacity (and associated changes in cost of transit) for these two modes of transportation. 5 Assume a part is made out of aluminum instead of steel to reduce the weight of a car and save fuel. The increased use of aluminum could prompt a new aluminum manufacturing facility to be built in a country with minimal environmental restrictions, ultimately resulting in increased deaths due to chemical releases at the plant and mitigating any environmental benefit associated with decreased fuel consumption of the car. 141

Table 1, cont.

6 Assume the LCA of a newspaper recommends readers choose electronic delivery over paper for environmental reasons. If many people choose electronic delivery, the amount of waste paper available for recycling in the community decreases. As a result, companies in the area that previously purchased recycled paper pulp, such as cardboard box companies, are unable to do so. These companies instead must buy virgin paper pulp and, consequently, are responsible for the deforestation and other impacts previously attributed to the newspaper company. Also, edelivery of newspapers leads to an increase in electricity consumption and, ultimately, to an overall increase in global GHG emissions. In addition, LCAs and sustainable design efforts from the paper box companies cannot compensate for this change, i.e. there is no option to switch from physical to electronic cardboard boxes.

9.2.2.5 Where Network Effects Might Arise

As discussed previously, allocation is the process by which inputs and outputs are assigned to different products during LCA, for instance, in the case of a multifunctional process that produces more than one product. One method recommended by the ISO for dealing with allocation problems – “expanding the product system to include the additional functions related to the co-products” [25] – is related to network analysis because it involves expanding system boundaries of an environmental analysis to include relationships outside the product life cycle of interest that affect the environmental impact of the product via physical and economic relationships. Because building an environmental impact network is one means of system expansion in LCA, modeling environmental impact as a network helps deal with allocation problems. Cases where allocation problems occur are cases where network effects may be expected. Allocation problems occur, for instance, when a system has multiple outputs (e.g. “in mining and metal production where several metals are produced from the same raw

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material” [69].) These outputs could be produced independently, or production of one output may be dependent on demand for another output [22]. Depending on which case is in question, environmental interventions that change demand for one product may or may not also affect demand for another product from the same multifunctional process and, hence, its absolute environmental impact. Consequently, accounting for the relationships between products in a network can help LCA practitioners better understand product supply and demand tradeoffs, as well as the environmental consequences of making certain product-related decisions.

Along similar lines in the area of risk management, Hofstetter et al. [104] describe the ripple effect of decisions meant to lower risk of the west Nile virus and how these decisions may have unintended consequences causing new and greater risks to public health. For example, the use of larvicide to reduce mosquito populations that carry the virus may cause a number of harmful results, such as: (1) negative health effects on park visitors,

(2) occupational health risks during spraying, (3) the development of larvicide-resistant mosquitos, (4) manufacturing impacts associated with larvicides, and (5) traffic accidents and pollution caused by would-be park goers driving “to more distant recreational areas” to avoid the larvicide. In total, they “identify 10 types of ripples… direct, upstream, downstream, accidental risks, occupational risks, risks due to offsetting behavior, change in disposable income, macro-economic changes, depletion of natural resources, and risks to the manmade environment” [104]. These types of effects could all be potential sources of network effects with the potential to affect the environmental impact of a product or system.

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9.2.3 Scale Effects

Environmental impact can be studied using LCA on a wide range of scales [39][127][150][165][166], from a sub-product scale (e.g. one kWh of electricity generated or one ounce of coffee) to a global scale (e.g. global electricity generation or the entire coffee industry). This section examines scale-related effects of environmental impact that should be taken into consideration when working to make sense of efforts at different scales. Because of scale-related effects, achieving environmental impact reductions on a small scale provides no assurance that the product fleet or the industry making the products is doing so in a sustainable way that does not jeopardize life on earth.

9.2.3.1 Basics of Scale Effects

Scale effects occur as a result of the hierarchy in an environmental impact network and the relationship between sub-product functional units, products, companies, the economy, and the ecosphere. Scale effects can cause the environmental impact of a large scale functional unit to not equal the sum of the impacts of entities on smaller scales. For instance, the total environmental impact of a product fleet often is not equal to the environmental impact of a single product multiplied by the total number of products due to the nonlinearities that arise between different scales of analysis. Scale effects are important because they imply that decisions that appear to be environmentally beneficial on a small scale may be detrimental on a large scale and vice versa, i.e. many small low-impact environmental decisions made in silos might add up to a large, high-impact environmental effect overall and, conversely, there are likely cases where making a higher-impact choice on a small scale leads to a lower-impact outcome overall. Consequently, sustainability efforts implemented at different scales may be in 144

conflict with each other, and efforts to reduce impact at the product level may cause impact increases on the scale individuals or industries. This poses a problem for the fields of LCA and sustainable design (which typically analyze functional units on a product scale or lower) because it means that the results from these fields may be misleading and the changes implemented in response to these results may cause greater environmental harm rather than if no LCA or sustainable design initiative was begun.

9.2.3.2 Example of Scale Effects

Dale and Benson [167] provide an example of scale effects with regards to the energy balance of solar PV. They show that even though individual solar PV panels produce more electricity than they consume over their lifetimes, the total PV industry could be net energy consuming depending on the growth rate of the industry and the amount of electricity consumed and produced per panel [167]. This means that each panel appears to contribute to clean energy production (and therefore confer a positive environmental impact) when analyzed individually, but collectively, all PV panels in the industry could consume more energy than they produce, ultimately conferring a negative environmental impact. “A rapidly growing PV industry may… temporarily exacerbate the problem of GHG emissions if operating at a net energy loss, i.e. consuming more energy each year in manufacturing and installing PV systems than is produced by systems in operation” [167].

9.2.3.3 Consider Many Scales Together

Researchers have indicated that some scales may be more appropriate for assessing some types of sustainability-related questions than others. For instance, Wu [168] states:

[L]ocal ecosystem-based studies tend to be too small in spatial extent to incorporate the environmental, economic, and social patterns and processes most 145

relevant to sustainable development, whereas at the global scale, it is often impossible to assess essential mechanistic details necessary for guiding local policies.

Because of scale effects, individual LCAs of products need to be connected to larger-scale entities to see how these small effects will ultimately affect the global environment. Other authors make similar points, stating, for instance: linking “micro level choices to macro level sustainability requirements” would address one of the “main deficiencies and limitations” of LCA as presented by the ISO [165]. Odum and Barrett

[138] likewise emphasize the importance of considering the effects of both a higher and a lower scale when studying systems at a particular scale “because… some attributes are predictable from parts (collective properties), but others are not (emergent properties). Ideally, a system-level study is itself a threefold hierarchy: system, subsystem (next level below), and suprasystem (next level above).” In some cases, many scales of analysis may need to be considered together with different questions asked at each scale. For instance, if the goal is to compare different options for Swedish biofuel production:

[W]e can derive more limited or specific questions at the product level (which biofuel is environmentally, economically, and/or socially benign), at the meso- level (how is the food-sector affected by the biofuel sector), and even at the economy-wide level (what are the physical limits of land use for food, biomaterial, and biofuel production) [150].

Parker et al. [169] make a similar point with regard to analysis of the impacts of biological organisms, noting the benefit of analyzing the environmental effect of a biological invasion at many levels of scale simultaneously, as well as the different types of impact that can be seen on different levels of analysis.

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9.2.4 Quantity-Related Effects

Reducing the low-level environmental impact of a functional unit or individual does not necessarily lead to greater environmental sustainability due to quantity-related effects. There are two types: (1) effects related to the fact that lower per-unit impacts can add up to a higher overall impact if there are enough of them, and (2) environmental economies (or diseconomies) of scale. Both will be discussed below.

9.2.4.1 The Total Impact Matters

LCA practitioners and sustainable designers often focus solely on the impact of a low-level functional unit and give no thought to the total quantity of functional units consumed or the overall environmental impact generated by the total number of functional units. Numerous authors agree, stating: “LCA does… not normally address the number of products (or functions) used in society” [30]; “LCA provides no estimate of the absolute mass of releases” and “does not address or consider absolute quantities” [103]. Instead, assumptions regarding quantity are often buried in calculations and are not clearly reported with LCA results. However, total environmental impact is a function of both the per-unit impact and the total number of units, and achieving environmental impact reductions on a small scale provides no assurance that the product fleet or the industry making the products is doing so in a sustainable way; with a great enough quantity, even a negligible amount of resource consumption or emissions per functional unit could disrupt ecosystems and threaten life on earth. Conversely, an immense amount of resource consumption or emissions per functional unit could be environmentally acceptable and have little to no impact on ecosystems if the total quantity of such functional units were low. Consequently, to achieve 147

global sustainability, one must understand the total scale of human impact – the number of people and the absolute amount they consume, compared to the resources available on earth and the environment’s capacity to absorb that impact. This means it is necessary to consider quantity and absolute amount of impact in environmental analyses, not just the per-unit impact, as is standard in the reductionist approach. Numerous authors acknowledge that the total scale of consumption and quantity of products have a significant effect on the environmental well-being of the planet, stating, for instance: “A consumer demanding cleanly-produced products might feel good about his or her lifestyle choice, but it will take more than just consuming such products to initiate a change – it will require a decrease in consumption as well” [122]; “It is not enough to engineer cleaner… technologies” or “design greener… products”; although important, these things will not “ensure… that the scale of material throughput remains within ecological limits” [46]; “even when environmental awareness galvanizes green actions, it does not necessarily put a stop to increasing consumption” [82]; there could be “a growing number of… green consumers buying more and more ‘sustainable’ products produced by increasingly efficient production processes, and yet for the absolute scale of resource consumption – and the associated environmental impacts – to continue to grow” [170]. For these reasons, some methods other than LCA consider the absolute quantities of products or impacts. For instance, “risk assessment and risk management” calculate the absolute amount of environmental risk, so that the results “would vary dramatically” “when calculated for 1000, 10,000, or 100,000 widgets” [103]. In ecology, Parker et al. [169] account for the ‘abundance’ of invasive nonindiginous species when measuring their ecological impact. Similarly, work related to the IPAT equation, which equates impact with 148

population*affluence*technology, clearly highlights the importance of population when determining human impact. Here, “the scale of the economy (population times per capita resource use) must be within the carrying capacity of the region,” which implies “a limit on total scale of resource throughput” [126]. Consequently, “As population rises… the less of a share of any fixed resource, such as the atmosphere, is available for each of us to sustainably and equitably transform or consume… With a large enough population there is no guarantee that even very low levels of equitable per capita greenhouse emissions or resource consumption are environmentally sustainable” [36]. Finally, the threshold effect also clearly depends on the total quantity of pollutants in a given area: “Below a certain level of pollution trees will survive in smog. But, at some point… a small increment in smog” causes “living trees [to] become dead trees” [134]. Similarly, “Five hundred people may be able to… dump their raw sewage into [a] lake, and the natural systems of the lake will be able to break down the sewage.... Five hundred and five people may overload the system and result in a “polluted” or eutrophic lake” [134]. The fact that LCA does not consider the absolute level of chemical emissions is a problem because, as discussed previously, environmental damage from many types of chemical emissions occurs only as a result of surpassing threshold concentrations, i.e. exceeding a certain absolute mass of chemicals in a particular volume. This means that

LCA may needlessly strive to minimize chemical emissions when doing so would not result in any environmental gains (if, for instance, the concentration is already below the no- effect level). In addition, focusing only on emissions associated with functional units may cause practitioners to fail to see serious environmental problems that might arise from very low-level emissions (if, for instance, at the location of emissions there are many other 149

sources of low-level emissions surpassing emissions thresholds as a group, with each source contributing a seemingly-negligible amount [96]). Indeed, many serious environmental problems occur when thresholds are reached. For these concerns, it is necessary to consider the absolute amount of emissions coming from a product, product fleet, industry, or industrial sector – not just the emissions per functional unit. This allows analysts to determine whether the products or consumer behaviors are, in fact, contributing to – or detracting from – global environmental sustainability by either releasing emissions at a level consistent with the overall global limit – or exceeding their allowable share.

The total amount of impact matters in both in a static way (e.g. there is an enormous difference in environmental damage between manufacturing one product vs. one million products) and in a time-dependent way (e.g. manufacturing lots of products at once can result in higher emissions concentrations and more environmental damage than manufacturing the same number of products over a broader stretch of time). This highlights the inadequacies of reductionist efforts to reduce global environmental impact by minimizing the impact of small-scale functional units. Clearly, just because the environmental impact per functional unit decreases (i.e. environmental impact efficiency increases) does not mean environmental impact is being reduced overall, or that progress is being made towards environmental goals. Rather, an awareness of the quantity and the absolute amount of impact in relation to the absolute amount of resources available and the absolute amount of absorption capacity in the environment for relevant types of emissions and impacts is necessary to understanding the true environmental effects of a change.

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9.2.4.2 Environmental Economies (or Diseconomies) of Scale

Environmental economies (or diseconomies) of scale occur when there are nonlinear relationships between environmental impact and the quantity of items having an impact, i.e. there is a disproportional change in the overall environmental impact as the number of functional units changes. Environmental economies of scale exist when the environmental impact for one functional unit decreases as the total number of functional units increases, as might occur for instance, when an increase in the number of units manufactured from a factory results in more efficient use of capital equipment at that factory and a lower per-unit environmental impact. Alternatively, environmental diseconomies of scale occur when increasing quantity increases the per-unit environmental impact in a ‘diminishing returns’ scenario. This might occur, for instance, in cases where a larger quantity of a product or population is associated with a need to use less-accessible resources or more energy-intensive methods of resource extraction [134]. In addition, the environmental “cost of maintaining environmental quality at a given level escalates disproportionately as population size increases” [134]. This occurs, for instance, in the treatment of municipal sewage, where greater populations mean that a higher percentage of contaminants must be removed – using more intensive wastewater treatment processes that consume more resources per unit effluent – to maintain the same output water quality [134].

9.2.4.3 Problems That Arise When Quantity-Related Effects Are Not Considered in LCA

When quantity-related effects are not considered in LCA, those focused on minimizing environmental impact of a functional unit can be misled by their results to view

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higher consumption as an advantage when it generates environmental economies of scale. For instance, in cases where capital equipment is not used at full capacity or where larger- capacity equipment is more efficient, those focused on minimizing the environmental impact for each functional unit are likely to celebrate when overall consumption increases, because the per-unit impact likely decreases due to the capital environmental impact being spread across more functional units, or due to the increased efficiencies associated with larger-scale equipment. Take a plastics factory that has equipment capable of producing 5,000 water filters a day, but produces only 4,500 a day due to demand. If demand increases, and the equipment is run at maximum capacity, the ‘capital’ environmental impact associated with the machinery and the space in the factory will now be spread across more water filters, and the environmental impact per-filter will decrease. Similarly, if demand increases substantially, and the company is able to invest in a more efficient, higher capacity machine that makes 10,000 water filters a day, an increase in demand to that level will reduce the environmental impact per unit because of the higher-efficiency machinery. However, it is mistake to think that the reduction in impact per unit is an environmental win in cases like these; the increase in consumption needed to produce this per-unit reduction produces absolute impact that may totally overwhelm any per-unit reduction.

9.2.4.4 Does Achieving Sustainability Require a Reduction in Personal Consumption?

There is disagreement regarding whether environmental sustainability requires a reduction in personal consumption and associate lifestyle changes, or not: “While some definitions insist that sustainable consumption implies consuming less, others assert that it means consuming differently, and that it categorically does not mean consuming less” 152

[170]. This disagreement relates to reductionism and the quantity of consumption because those arguing that sustainability does not require lifestyle change believe that the current amount of global consumption can be maintained, or even increased in impoverished areas of the world, and sustainability can be achieved. In contrast, those who argue that a change in quality of life is necessary in wealthy regions of the world to achieve sustainability are appealing to the idea that efficiency and sustainable products are not enough and that the total quantity of products and the overall amount of consumption must be reduced to achieve sustainability.

Some maintain that sustainability does not require lifestyle change, just eco- efficiency. Eco-efficiency has to do with generating less environmental impact per unit output. This is precisely the approach used by those adopting a reductionist approach and assessing environmental impact on the level of low-level functional units. “Underpinning the eco- efficiency movement is the acceptance of finite resources and limited sink capacities. If continued economic growth is to meet the ever-expanding needs of human development in an equitable manner, then more must be achieved with less resources” [137]. Consequently, this approach emphasizes the “Efficient use and consumption of natural resources” [136]. Indicators for resource efficiency on an economy-wide scale and regional levels “are based on the idea to use less resource input per unit of economic output” [136]. This push for eco-efficiency is often the focus of those who maintain that sustainable consumption entails consuming products with a smaller environmental impact, but not consuming less, lowering one’s quality of life, or hindering economic growth. For instance, the United Nations Environmental Program explains: “sustainable consumption 153

is not necessarily about consuming less; it is about consuming better – i.e. more efficiently, with less risk to our health and environment” [171]. In addition, a speech from the UK’s former Secretary of State for Trade and Industry explains that environmental sustainability can be achieved with increased consumption: “consumption no longer has to cost the earth... We can enjoy more comfort… and more security without automatically increasing harmful and costly impacts on the environment. But it requires a re-thinking of business models to make more productive use of natural resources” [172]. This line of thinking jives with the reductionist approach to sustainability, which is focused on minimizing low-level environmental impacts. However, others maintain that sustainability requires less overall human consumption and lifestyle changes, at least for those living relatively opulent lifestyles. For instance, Clark et al. [122] state: “we can no longer afford to take our current consumption patterns for granted”; instead, we need to both choose “cleanly-produced products” and decrease overall consumption to realize environmental gains. Similarly, Assadourian [128] claims: “consumerism is not a viable cultural paradigm on a planet whose systems are deeply stressed and that is currently home to 7 billion people.” For some, ‘sustainable consumption’ is associated with reducing consumption, and adopting an attitude of anti- consumption is viewed as potentially enabling sustainable development [156]. In addition, the concept of ‘overconsumption’ implies that people living relatively-opulent lifestyles “need to reduce their consumption of goods and services across the board; they need to quell their materialistic lifestyle” and “accept a diminished standard of living” [160]. Unlike the reductionist approach to sustainability, this approach emphasizes the importance of reducing consumption and environmental impact more broadly, accounting 154

for the total quantity of impact, rather than simply minimizing the impacts of small-scale functions. Numerous authors describe the significant lifestyle change that they maintain is required to achieve environmental sustainability. According to Engelman [36], sustainable consumption levels “would undoubtedly be small fractions of what” people “in high- consuming countries” “take for granted today.” Achieving sustainability “may mean doing without a personal car or living in homes that are unimaginably small by today’s standard… With a large enough human population, however, even modest per capita consumption may be environmentally unsustainable” [36]. Similarly, Assadourian [128] argues that a sustainable lifestyle does not include “the celebrated entitlements of the high- income lifestyle – 79 kilograms of meat a year… air-conditioned homes, family pets, and… access to flights around the world… these luxuries will no longer be… accessible to the vast majority of people in a truly sustainable society.”

Hence, those that ascribe to this view would maintain that a sustainable person is one who minimizes his or her environmental impact through both the use of low-impact products as well as through conservation measures and significant lifestyle changes that minimize total amount of consumption on a broader scale.

9.2.5 Rebound Effects

Rebound effects occur when some type of efficiency results in an increase in overall consumption. They highlight the importance of not just looking at per-unit impacts but also considering how the total number of units demanded can change with efficiency improvements (such as reductions in environmental impact per unit).

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Psychological rebound effects occur when sustainable products are used to justify using more of that product or using a less-sustainable product elsewhere. People with a low per-unit environmental impact for a resource may be more prone to use that resource, resulting in a higher overall environmental impact. For example, “a hybrid or electric car may cause the driver to feel that driving is not polluting, thus encouraging extra mileage” [82], or someone with a solar panel may feel more carefree about wasting electricity.

Alternatively, a disposable cup with a reduced impact may limit the aversion of people who typically use nondisposable beverage containers for environmental reasons, thereby increasing total disposable cup consumption. Also, “[P]eople may decrease one environmentally destructive behavior with good intentions, only to offset the gains by increasing a different and more destructive activity” [163]; for instance, eco-conscious consumers who feel good about having a solar panel may be less prone to worry about driving more or flying frequently.

Economic rebound effects occur when a reduction in consumption produces a monetary savings or alters the economic tradeoffs between products, ultimately resulting in an increase in consumption overall. Two types of economic rebound effects are discussed below. First, direct rebound effects occur when increased efficiency leads “to a lower price of the service (or product or technology),” inducing “an increased use of this cheaper service” [104]. For example, “If energy efficiency of a car is increased… 100 km can be driven with less fuel and, therefore, at lower cost. Consequently, people may drive more and longer distances because mobility… has become cheaper” [173]. In addition, the development of energy-efficient light bulbs causes the cost of using a bulb to decrease, 156

encouraging “people… to use them more often. Thus, we see gardens which are populated with many “energy-efficient” lights” [165]. Second, indirect rebound effects occur when “the reduction of costs due to a particular efficiency” leads consumers to spend more on other goods [104]. For example, indirect rebound effects arise when people switch to a vegan diet, but then “substitute high- impact imported or exotic vegan foods like exotic fruits or humus for meat, offsetting most of the gains of their new diet” [82], or when an urban dweller “uses the thousands of dollars she saves each year from not owning a car to take an exotic far-off vacation, burning more carbon in one week than she would have in an entire year of driving” [163]. Conversely, if a consumer spends more money on an eco-product, he or she will have less money to spend on something else. Where that consumer makes his or her budget cut will affect the environmental impact of the decision to buy the eco-product [104]. This cut could help the environment more (if coal-fired electricity consumption is reduced) or less (if the consumer decides against replacing his or her energy-inefficient windows). Rebound effects “are not part of traditional LCA” [165], and sustainable designers do not typically account for them. However, the existence means that lowering the environmental impact of products does not guarantee environmental benefits overall. Consequently, efforts in sustainable product design to reduce low-level environmental impacts could unknowingly be thwarted by the rebound effect.

9.2.6 Synergistic Effects

Synergistic effects occur when two seemingly unrelated impacts affect one another and amplify or lessen the total environmental damage via feedback loops, essentially changing the context in which each type of impact occurs. For instance, synergistic effects 157

occur when cities expand into agricultural areas, causing the pollutants typical of each region to come into contact; the sulfur dioxide from the city paralyzes “the cleaning mechanisms of the lungs, thus increasing the residence time of potential carcinogens” from agricultural chemicals prevalent in the country, and “The joint effect may be much more than the sum of the individual effects” [134]. Synergistic environmental effects also are noted in the study of invasive species, where “the joint effect of two or more interacting species is greater than the sum of the effects of the species acting alone” [114].

9.2.7 Collective Effects

The collective effect occurs when many people need to make the same change together for a small-scale change made by an individual to have a positive impact. As a consequence of the collective effect, partial switches to a lower-impact technology may be worse for the environment than no change. For instance, building a new bike trail can be good for the environment if many people who were previously commuting via car now take the trail, but it can be bad for the environment if only a few people take the trail and the avoided car emissions do not offset the environmental impact associated with building the infrastructure of the trail in the first place [82]. This is also the case for recycling centers [82], where it is good for the environment if lots of would-be waste is recycled there, but is bad if not enough waste is recycled to counter the impact of the recycling center infrastructure. Similarly, introducing a higher-efficiency version of a product may be beneficial to the environment if all consumers switch and production volumes remain high, but it may be harmful if introducing the product would split the current market, requiring twice the production equipment for the same number of products to be built and reducing the efficiency of the production equipment for both products. 158

Conversely, there are cases where many people doing the same ‘sustainable’ thing could inadvertently increase everyone’s environmental impact. For instance, if too many people in the same area have heat pumps that use “groundwater… as heat source during winter operation and heat sink during summer operation” “to reduce… the primary energy required for heating and cooling” in their homes, “the performances of other heat pumps installed in the neighborhood” could be negatively affected [174].

9.2.9 Discussion

The systems-level effects discussed in this section are not necessarily theoretically separate. Some may be subsets of others, or two may be equally applicable to the same scenario. For instance, assume the LCA results from analyzing one building and a group of buildings in a neighborhood indicate that environmental impact does not scale linearly. This could be characterized as a scale effect because there is clearly an increase in scale of the functional unit between analysis of one building and analysis of one neighborhood.

However, this could also be characterized as a network effect, because analysis of a neighborhood is really an analysis of a network of buildings with their interactions. This same type of problem arises with the analysis of one company compared to the analysis of many companies; the difference in functional unit represents a change in scale, but also a consideration of the network and the nonlinear effects that arise as a result of interactions among entities in the network.

9.2.10 Conclusion

Minimizing small-scale impact is not a guaranteed road to sustainability. Even if sustainable designers and LCA practitioners using the reductionist approach succeed at

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reducing the low-level environmental impacts of products or individuals, they may not contribute to environmental impact reductions overall. This is because minimizing environmental impact on the scale of low-level functional units may have unintended, counter-productive consequences that arise because of a range of system-level effects – including network effects, scale effects, quantity-related effects, rebound effects, synergistic effects, and collective effects. Consequently, the sacrifices individuals make for the environment (e.g. buying more expensive ‘green’ products, walking instead of taking the bus) – which may negatively impact their quality of life – may not help the environment as much as expected, or they may actually harm the environment. As a result, sustainable designers should work to account for these systems-level effects. When there is an option, designers should select larger functional units corresponding to higher-level analyses so that systems-level effects are brought to the forefront of the analysis. Rather than focusing on designing low-impact consumer products, designers should create sustainable designs at higher levels of scale and instead study groups of companies and industries and seek avenues to achieve sustainability on these scales, for instance, by designing new infrastructure or designing eco-industrial parks from existing companies. LCA practitioners and eco-conscious consumers should ask higher- level questions regarding whether and how product choices and actions do or do not translate to global environmental benefits and what can be done on a larger scale to try to ensure global benefits are achieved. The focus of efforts should be on finding optimal solutions globally, not minimizing low-level environmental impacts. Finally, LCA practitioners and sustainable designers might benefit from studying environmental impact networks and better-relating detailed aspects of product LCAs to the larger environmental 160

picture, combining life cycle inventory models with economic models to better understand the environmental consequences of a decision.

9.3 THE REDUCTIONIST APPROACH NEGLECTS CONTEXT AND ITS SIGNIFICANT INFLUENCE ON OVERALL ENVIRONMENTAL IMPACT

Designers striving to minimize the low-level impacts of functional units or individuals nearly always deal with a large population of functional units or individuals that exist in very different contexts. For instance, a designer may estimate the life cycle environmental impact of a coffeemaker design, of which 20,000 will be manufactured, on the level of an individual coffeemaker or lower (ex. one cup of coffee). In this case, by focusing on the environmental impact of one individual coffeemaker, the average assumed coffeemaker is analyzed, despite the fact that each of the 20,000 coffeemakers will be used by different consumers for slightly different tasks in different locations (making full pots of coffee continuously every day in a diner in a tropical climate vs. making 2 cups of coffee once a week in a single family home in a cold climate), potentially changing the environmental impacts in large ways. Now, some may say that the coffeemaker design ought not be analyzed on the level of the coffeemaker, but instead on the level of one cup of coffee. After all, an eco-conscious café goer needs to be able to compare the impact of his cup of coffee from each café in his neighborhood, meaning that for an apples-to-apples comparison for a consumer, the analysis must be on the level of consumption, in this case, one cup of coffee. Alas, no context-free analysis exists for this consumer because any analysis performed on the level of one cup of coffee must make assumptions about the efficiency of the coffeemaker, for

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instance, assumptions which hide important contextual details regarding how often the coffeemaker is used, how and where it is used, how many cups of coffee it will produce over its lifetime, etc. The reality is, there is no accurate apples-to-apples comparison that can be made for this consumer that is not embedded in a specific context. Instead, as the unit of analysis becomes smaller, more contextual details become hidden in the assumptions about the typical usage patterns or the average user. For instance, by focusing on one functional unit at the level of the coffeemaker or below (ex. one cup of coffee), information about these contextual differences and their effect on the environmental impact of the coffeemaker are downplayed as the questions answered by the LCA become less relevant to the real-world context. For example, if a designer is conducting an LCA of a coffeemaker with the intention of reducing its environmental impact, he or she will focus on the design elements of a coffeemaker: How can electricity consumption during one brew cycle and during downtime be reduced? Can waste be eliminated by making a reusable filter or manufacturing the coffeemaker out of recyclable materials? This type of analysis is focused on reducing the environmental impact of the product in the average context for the average user. However, if a designer is conducting an LCA of a fleet of coffeemakers and is trying to reduce their impact, he or she will focus on the features of the fleet, which are inherently embedded in the real-world context: How can the company more efficiently distribute coffeemakers to the locations around the world where they will be purchased? How can the designer ensure that the energy-saving features that are helpful in warm climates and harmful in cold climates are used appropriately in each context? This type of analysis characterizes the distributions of contexts and users to minimize the environmental impact of the product fleet. 162

Consequently, adopting a reductionist approach and minimizing low-level impacts leads to a reduced emphasis of the role of context and contextual factors in LCA and sustainable design. Neglecting the role of context is problematic because failure to account for contextual factors can cause low-level, seemingly environmentally-beneficial decisions, behaviors, and products to not achieve their desired effect. Csutora [82] refers to this phenomenon as the behavior impact gap (BIG), which can be observed when sustainable behavior occurs, but the environmental impact is not, or is only slightly, reduced due to contextual factors and the ‘interfering behavior’ of others. For example, this would occur when people mistakenly put nonrecyclables in with recycling, lowering the value of all the recycled material in the bin and reducing the environmental benefit of the recyclable material or when a user has to drive a long distance to a recycling site, offsetting some of the environmental gains of recycling due to the increased transportation impact [82].

9.4 THE REDUCTIONIST APPROACH MISSES AN IMPORTANT AVENUE TO ACHIEVING SUSTAINABILITY: IMPLEMENTING SYSTEMS-LEVEL, STRUCTURAL CHANGES

Minimizing the environmental impact on the level of products or individual acts of consumption can only make so much headway towards achieving sustainability before a bigger, higher-level, structural change is needed. For instance, designers can make some environmental progress by designing a more fuel efficient car, but much greater improvement may be realized, instead, through the design of nicer and more convenient public transit systems, or the development of more appealing urban housing options that reduce travel distance. Educational initiatives to encourage people to be very waste- conscious and minimize their use of disposable beverage bottles may be beneficial, but

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more progress may be made if better recycling programs are established, or if laws are made forbidding the sale of beverages in disposable containers in certain contexts. Similarly, recycling waste from a manufacturing facility may result in a small decrease in the environmental impact of a product, but establishing an eco-industrial park with a number of other co-located companies to reuse waste within a network may result in a much greater decrease in the product’s impact. The types of systems-level solutions mentioned here would be missed using a reductionist approach; they are outside the purview of a typical product designer and are unlikely to be considered in a typical product- focused LCA. Many authors agree that systems-level changes are necessary to achieve environmental sustainability: only so “much of a reduction in carbon footprint can be achieved through merely increasing the environmental awareness of society without substantially affecting structural–contextual elements” [82]; “If our civilization is to transition to sustainability, many sectors of society will need to rethink their modes of operation” [132]; some believe “profound and radical changes to the structures of society” are necessary “for the Earth to remain fit for human habitation” [137]; in some cases, “the emphasis must be placed on changing the policies of governments and institutions rather than the habits of consumers” [160]; “perfecting our everyday individual choices is not the answer to creating a sustainable society… we need to implement new technologies, cultural norms, infrastructure, policies, and laws” [163]; and “we need… to focus upon integrated, system’s approaches for creating and re-creating buildings, neighborhoods, urban areas and regions” [145].

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A systems approach to sustainability may entail high-level changes to infrastructure (redesigning the electric grid, building rapid transit routes, not widening highways), housing (building energy efficient high-rises downtown rather than large homes in the suburbs), policy (instituting a carbon tax or cap and trade program, banning the use of particular substances in goods, or banning the use of plastic shopping bags), and supply chains (establishing an eco-industrial park).

Belief that higher-level, structural changes are likely to result in greater environmental benefits is also a main driver in the areas of industrial ecology, industrial symbiosis, eco-industrial parks, and related fields. These fields focus on the many economic and environmental benefits that can arise through the development of high-level structural changes in supply chains and waste streams between companies that allow the waste from one company to become a valuable input to another. Researchers in those areas maintain that this approach can provide greater environmental benefit collectively than would be possible if each company acted to independently reduce its environmental impact. Authors note, for instance, that “Arguably, by cooperation in an industrial ecosystems, the participants will achieve a greater waste reduction and/or material use efficiency than as isolated elements” [47]; “Webs of synergistic linkages emerging within IS networks can allow improvements in the efficiency and effectiveness by which different resources and capacities are utilised, going beyond that which can be achieved by fragmented pursuit of improvements in individual units” [56]; and “By working together, the community of businesses” that form an eco-industrial park “seeks a collective benefit that is greater than the sum of the individual benefits each company would realize if it optimized its individual performance only” [57]. 165

The lowest-impact solution overall may be one in which “one element of the system may actually produce more waste than before, as long as the other partners are capable of absorbing it and the overall waste output of the system is reduced” [47].This type of solution would not be found using a reductionist approach, as the increase in waste from this element would not be permitted.

9.5 FOCUSING ON SMALL-SCALE IMPACTS MAY DISTRACT FROM OPPORTUNITIES FOR LARGE-SCALE CHANGE

Attempting to minimize environmental impacts on a small scale – the goal of the reductionist approach – may distract sustainable designers and consumers, preventing them from seeing and addressing bigger-picture environmental issues. Consequently, opportunities to implement higher-level changes that could incur larger-scale environmental benefits may be missed. Suggestions for environmental improvement from sustainable designers are typically made on the basis of a single unit of a product and do not account for issues related to the product fleet, infrastructure systems, “the interrelations between the products and the infrastructure system (e.g. how consumers use the products considering the available infrastructure), the consumption response to income change, product improvements,” or policy resistance [8]. Instead, designers frequently focus more narrowly on design elements of a single product. For instance, “A team of design engineers may struggle for months over whether it is ‘preferable’ to use an aluminum or a plastic radiator- cap, while more fundamental questions about the sustainability of the gasoline-powered automobile are never raised” [24]. Engelman [36] discusses two further examples of airlines touting their sustainability initiatives – using a sustainable source for their

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cardboard and recycling three airplanes-worth of aluminum – and notes that neither initiative “sheds any light on whether the airlines’ overall operations—or commercial aviation itself—can long be sustained on today’s scale.” Arguably, these big-picture issues regarding the sustainability on the level of product types (ex. gasoline-powered cars), companies, and industries (ex. commercial aviation), for instance, should be considered and emphasized more in the sustainable design community. As Jackson [46] states, although “more efficient industrial processes” and the development of cleaner technologies are important, neither of these things “will ensure that consumers choose to buy… greener products or that the scale of material throughput remains within ecological limits.” Instead, broader systems-level changes are needed. Likewise, eco-conscious consumers typically focus on reducing their impacts on an individual level. Unfortunately, efforts to reduce individual consumption may serve as a distraction and an excuse not to push for wider-scale environmental change. If a consumer exhausts himself trying to achieve a net-zero personal environmental impact, for instance, he may not have motivation for the important work of environmentally-focused protesting and policymaking that is likely to result in a larger environmental benefit overall. Consequently, analysis of higher-level environmental effects should perhaps be emphasized more in sustainable design and LCA, rather than focusing only on low-level issues with products or individuals.

9.6 CONCLUSION

This chapter questioned the appropriateness of the reductionist approach to sustainability, arguing that low-level environmental impact reductions do not necessarily contribute to high-level impact reductions or environmental sustainability for five reasons. 167

First, it is difficult, if not impossible, to achieve the reductionist goal of minimizing impact on a small scale, and approaches to sustainable product design that focus on incrementally reducing the environmental impact of products are not drastic enough to achieve sustainability. Second, minimizing low-level impacts of product or individuals does not necessarily lead to greater environmental sustainability because there are a number of types of system-level effects, including network effects, scale effects, quantity-related effects, rebound effects, synergistic effects, and collective effects that could all undermine efforts on this front. Third, the reductionist approach neglects context and its significant influence on environmental impact, and contextual differences may affect equivalent functional units in different ways. Fourth, the reductionist approach misses an important avenue to achieving sustainability: implementing systems-level, structural changes. Finally, trying to achieve sustainability via the reductionist approach may distract and prevent sustainable designers and eco-conscious consumers from making real progress towards sustainability via large-scale change. The next chapter presents a new theoretical paradigm for thinking about environmental sustainability that aims to avoid the problems discussed in this chapter that occur in the current paradigm as a result of the reductionist approach adopted.

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Chapter 10: The New Paradigm of Environmental Sustainability as an Emergent Property of Complex Global Systems

This chapter presents a new theoretical paradigm for thinking about environmental sustainability. Compared to existing paradigms, this new paradigm:  Focuses on sustainability on a global scale  Focuses on context and its effects on environmental impact  Considers non-human environmental impacts

 Considers both the ‘positive’ and ‘negative’ environmental impacts of humans  Strives to preserve biodiversity and maintain a habitat for humans  Strives to ‘balance’ environmental impacts, not ‘minimize’ human impacts  Strives for broad-scale, systems-level solutions to environmental problems  Views environmental sustainability as an emergent property of a complex system

 Views environmental impact as a network The first section introduces the need for a new paradigm for conceptualizing environmental sustainability. The second section describes how environmental impact could be thought of as a network of energy and material flows from different components that have environmental impacts on each other. The third section presents a new conception of environmental sustainability wherein sustainability is an emergent property that arises out of a network of environmental impacts. The fourth section discusses the implications of the new paradigm for designers.

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10.1 THE NEED FOR A NEW PARADIGM

A new way of thinking about sustainability and environmental impact is needed that responds to four problems with the existing paradigm, discussed below.

10.1.1 Sustainability Is Not a Collective Property

Researchers who adopt a reductionist approach to sustainable design assume that sustainability is a collective property, i.e. a property of a whole system that is a summation

“of the behavior of individual components” and does “not involve new or unique characteristics resulting from the functioning of the whole unit” [138]. However, there is no reason to think that sustainability is a collective property of a system, and there is evidence to the contrary. For instance, the existence of systems-level effects discussed in Chapter 9, including network effects, scale effects, and quantity-related effects, indicate that overall environmental impact is more than just the sum of small-scale impacts. The existence of these effects means that minimizing human impact on a small scale will not necessarily lead to minimized human impact on a global scale. Hence, it represents a breakdown in the reductionist approach to environmental impact and environmental sustainability.

10.1.2 Sustainability Is Not a Design Attribute

Sustainability is not a design attribute, as it is normally assumed to be in sustainable design. As discussed in Chapter 8, reductionists consider designs ‘sustainable’ when they are found, via LCA, to be ‘low-impact’ compared to competing designs. Reap et al. [31] discuss the possibility of using weights “to assess whether, on a standalone basis, a product system is environmentally ‘good,’ ‘bad’, or even ‘sustainable’” using “an absolute, aggregate measure.” However, no such absolute measure for sustainability (or goodness or 170

badness) exists, and there is no such thing as an inherently sustainable design. Instead, any instantiation of a design could be either sustainable or unsustainable because systems-level effects and context play a critical role in determining the ultimate impact of a design. Both of these possibilities are discussed below. First, the existence of systems-level effects means that individual products that would be considered ‘low-impact’ or ‘sustainable’ in the reductionist paradigm could be

‘high-impact’ or ‘unsustainable’ when considered in total. Regarding quantity-related effects, for example, any product with a non-zero environmental impact can be a sustainability problem if too many are produced. Regardless of the design, there is a global limit beyond which a certain quantity of the design violates the energy and material limitations on earth. As this limit is approached, the ‘sustainable’ design would begin to be regarded as ‘unsustainable.’ Second, the existence of contextual effects that alter the environmental impact of the same design in different situations mean that sustainability is not a design attribute. Many authors note the difficulty in declaring products ‘sustainable’ or ‘low-impact’ as a result of contextual factors, stating: “Sustainability is inherently context-dependent” [168]; “while it has become common usage, it seems inappropriate to consider buildings as being ‘sustainable’. A building is an element set within wider human endeavours and is necessarily dependent on this context” [143]; and:

The idea of a “sustainable product” is misguided because the impact that any product has on the social and ecological environment depends as much on its use as on the technology it deploys. An axe, for example, can easily be made from recyclable steel, but it will still have a negative environmental impact if used to clear-cut a forest [175].

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Indeed, the context of a product plays a significant role in determining its environmental impact. Even products generally considered very sustainable can be unsustainable in certain circumstances. Solar PV, for instance, is generally regarded as a ‘sustainable’ technology, and researchers agree that PV panels can avoid an immense amount of GHG emissions in ideal contexts – such as when they are used in locations with high solar insolation in place of a GHG-intensive electricity source over a long period of time. But, when their entire life cycle is taken into account, PV panels could result in increased GHG emissions and be deemed ‘unsustainable’ if, for instance, the panels fail prematurely, are used in place of other lower-carbon electricity sources, or are used for an application that would not otherwise consume electricity. In conclusion, any instantiation of a design could be either sustainable or unsustainable because systems-level effects and context play a critical role in determining the ultimate impact of a design.

10.1.3 Impacts Are Not Inherently Good or Bad for the Environment

In the existing paradigm for sustainability, it is necessary to list impacts deemed ‘bad’ for the environment and then quantify the environmental impact of the product of interest in terms of those impacts. However, particular types of impacts are not inherently good or bad for the environment for at least two reasons. First, whether an impact is good or bad is determined by context. For example, depletion of fossil fuel resources is considered an important environmental problem.

Greater consumption is considered ‘bad’ for the environment and reduced consumption is considered ‘good’ – but this is only because human consumption of fossil fuels occurs at a much higher rate than new fossil fuels are generated. It is not that fossil fuel consumption 172

is inherently bad; if the rate the earth’s geologic process transformed organic matter into fuels were higher, or the rate of consumption of fossil fuels were lower, there would be no sustainability problem with consuming fossil fuels from a resource-limitation perspective. In addition, within the context of concerns about climate change, GHG emissions are seen as bad for the environment, and GHG sequestration is seen as good. However, if the current climactic situation were different (there were fewer anthropogenic GHG emissions, less solar radiation emitted by the sun, or significant global cooling caused by geological forces) and biological organisms were instead threatened by a cooling climate, additional

GHGs would be considered good, and carbon sequestration efforts considered bad. Second, whether an impact is bad or good is also determined by the arbitrary timing of events. For instance, imagine a world without the threat of climate change. If an enormous, high GHG-emitting machine were constructed, causing the concentration of GHGs in the atmosphere to rise perilously, this system machine and its impact would be deemed ‘bad’ for the environment. Then, if an equally-enormous GHG-sequestering machine were built, causing the concentration of GHGs in the atmosphere to return to its original state, this sequestration machine and its impact would be considered ‘good’ for the environment. However, if the sequestration machine were built first, and the atmosphere were losing GHGs too rapidly, causing perilous global cooling, this machine and its impact could instead be considered ‘bad’ for the environment. Likewise, in that case, the high- GHG-emitting system installed second would be considered ‘good.’

Consequently, the same entity with the same environmental impact could be considered either very good or very bad for the environment depending on context and the arbitrary timing of events. This result suggests that ‘goodness’ or ‘badness’ of an impact is 173

not an inherent property of the impact itself. In addition, it indicates an underlying problem in the current sustainability paradigm (which labels designs and their impacts as ‘good’ or ‘bad’ for the environment). Sustainability is instead related to whether a given design disturbs - or contributes to - system balance, and a specific type of environmental balance that maintains the earth in a state that is habitable for humans, as will be discussed below.

10.1.4 Large Impacts Are Not Inherently Unsustainable

As discussed in Chapter 8, reductionists consider designs ‘sustainable’ when they are found, via LCA, to be ‘low-impact’ compared to a competing design. Consequently, sustainable design initiatives typically focus on reducing the environmental impact of products, for instance, by making them more efficient, or redesigning them to use less material. However, environmental sustainability is not necessarily about having a small environmental impact; biology is filled with organisms that have enormous environmental impacts that have lasted eons without ending life on earth. Indeed, human life is dependent on many of the large environmental impacts of other organisms (e.g. the oxygen provided by photosynthetic organisms). This strongly indicates that large impacts are not necessarily bad and that some underlying assumptions in the current paradigm are flawed.

10.2 WHAT IS ENVIRONMENTAL IMPACT IN THIS PARADIGM?

Environmental impact is fundamentally tied to how a product or system interacts with ‘the environment,’ taken here to refer to anything outside of the product that affects, or is affected by, the product. Consequently, environmental impact has to do with the attribution of cause and effect to the entities in the environment of a product, and the factors

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that affect the environmental impact of a product are embedded in the system and context surrounding that product.

10.2.1 Environmental Impact is a Network

Within this paradigm, environmental impact is thought of as a network of impacts on a wide range of scales comprising a complex system. Impacts on a particular scale connect to each other, and small-scale impacts connect to large-scale impacts, forming a hierarchical network that ultimately connects all global impacts to one another. Here, a systems approach to environmental impact is adopted, “premised on the belief that the component parts of a system can best be understood in the context of relationships with each other and with other systems, rather than in isolation” [143] and emphasizing the benefit of including “the trans/cross-boundary impacts or interrelationships between and among the parts” when searching for globally optimal solutions to environmental problems [4].

For a single product, causes can be viewed as flowing towards the product in the form of a chain, from final causes to a series of proximate causes, to the effect of the environment on the product. Similarly, effects of the product on the environment flow away from the product. The many causal chains that relate to a product can ultimately be viewed as a “causal web” formed of many interweaving causal chains. In addition to the product’s causal web, all the other entities in the product’s environment have causal webs of their own. These entities affect – and are affected by – the other entities in the environment.

Together, these causal webs can be viewed as a network that describes the flows of materials and energy among entities.

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The entire network exists at one point in time. As time moves forward, the volume of materials and energy transported from one link to the next changes. In this way, the network accounts for the variability of contextual factors and environmental impact over time. The components in this network may be agents with decisions or events. If a component in a modeled network has no causes (if the causes are not known or are not of interest), then this component lies on the system boundary of the model.

Context in this paradigm is thought of as the collection of links in a network that connect to a design and the values of the flows on this network throughout the lifetime of the design – from the point in time when the design enters the network to the point in time when all its energy and material flows to other parts of the network and the design disappears. Consequently, contextual factors form the environmental impact network and are of the utmost importance in this paradigm. In addition, as a result of this new way of thinking about environmental impact, there is a sense in which ideas about ‘better accounting for contextual factors in LCA,’ ‘modeling the broader network,’ and ‘expanding system boundaries’ conceptually overlap. Here, better accounting for context is one and the same as modeling the environmental impact network in greater detail. Along similar lines, expanding system boundaries, which corresponds to accounting for relatively smaller flows of energy and materials in environmental impact models, also corresponds to more detailed modeling of the environmental impact network. However, ‘accounting for contextual factors’ typically deals with relating a generalized LCA to a specific context and specific location, whereas ‘expanding system boundaries’ typically pertains to modeling the generalized environmental impact of the design in more granular, but still generalized, way. 176

10.2.2 Biological Ideas of Environmental Impact Adopted

Many aspects of the concept of environmental impact from biology, discussed in Chapter 7, are adopted in this paradigm, with some modifications. Namely: (1) humans are viewed as one type of high-impact biological organism, rather than separate from biology; (2) biological organisms (including humans) and inanimate entities (e.g. volcanoes) are viewed as having significant environmental impacts; and (3) impacts are considered 'negative' when they harm humans or decrease biological diversity globally and locally, and 'positive' when they help humans or increase diversity. While the idea that humans are viewed as one type of biological organism is self-explanatory, the other two ideas and their implications are discussed in further detail below.

10.2.2.1 Non-Anthropogenic Impacts Are Considered

Numerous environmental problems are caused by natural entities and nonhuman biological organisms, such as toxic algal blooms, volcanoes, and meteor impacts. These non-anthropogenic environmental impacts are just as damaging to the environment as anthropogenic ones; for instance, one kg of methane emitted to the atmosphere from an electric plant has the same negative impact on the climate as one kg methane emitted from the digestive tract of ruminants. Likewise, excellent environmental solutions can come from the domain of all things non-anthropogenic, just as they can from the realm of anthropogenic activities. For example, in the face of climate change, disaster could be avoided by altering interstellar energy and material flows (setting up a screen to limit the amount of solar insolation reaching earth to reduce global warming) or altering the presence of biological entities

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(culling invasive, methane-emitting camels in the Australian outback), just as it could by intervening in human activities (shutting down coal-fired power plants). Consequently, it is important to adopt a more comprehensive view and consider non-anthropogenic entities when assessing environmental impact. Hence, the environmental impact network discussed here includes a broad range of entities and activities, such as astronomical entities (the sun, asteroids); geological entities (volcanoes, fault lines); biological and biologically-built entities (sea turtles, coral reefs), as well as anthropogenic entities (cities, coffee pots).

10.2.2.2 Both ‘Negative’ and ‘Positive’ Impacts Are Considered

In addition, within this new paradigm, impacts are considered 'negative' when they harm humans or decrease biological diversity (either directly or by contributing to imbalance in energy and material flows on earth, resulting in ecosystem destabilization). Impacts are considered 'positive' when they help humans or increase diversity.

Unlike previously, emphasis is on accounting for both positive and negative impacts. Examining only environmental harm associated with a product, as is currently done in sustainable design, is similar to considering only the expenses of a company when trying to determine whether it is financially sustainable. Sure, the cost to the company of producing one product may be $0.01 and the expenses of the company over some time period may be $1,000, both of which are considered ‘low’. But this information provides no assurance that the company is financially sustainable and not on the verge of bankruptcy. Similarly, just because a product has a low per-unit impact or because the company and all its products together have a ‘low’ negative environmental impact does not mean the product, or the company, is environmentally ‘sustainable.’ 178

Instead, the ways in which a design harms humans or biological diversity must be viewed in the context of the ways in which the design helps humans or enhances biological diversity. This is akin to efforts in LCA to compare the impact of functional units, which might represent the amount of environmental impact per unit of electricity produced, for instance, so that the impact is normalized with regard to the function provided (one unit of electricity). However, the approach discussed here takes this idea further.

Here, it is not the impact per unit of electricity that matters when assessing sustainability, but the impact per unit of the end product of the electricity consumption.

Only a very low per unit impact for electricity is acceptable from the perspective adopted here if that electricity is used for a frivolous purpose, such as decorative lighting; only a small amount of harm to humans and biodiversity is acceptable for an activity that results in only a small benefit to humans and biodiversity. Conversely, a very high per unit impact for electricity may be acceptable from the sustainability perspective adopted here if that electricity is used for a critical and beneficial purpose, such as powering a life support system in a hospital or a facility that aids endangered animals. Consequently, sustainable designers should focus not only on minimizing negative environmental impacts but also on maximizing beneficial environmental impacts. One way to do this is through the creation, preservation, or reclamation of microenvironments that can provide valuable habitat. For example, thermal waste from the cooling systems of two power plants on the San Gabriel River near Los Angeles has created a habitat that supports a population of green sea turtles [120], an endangered species [176]; artificial reefs can be constructed out of wrecked ships or waste dredged material [177]; and urban wildlife refuges can be established on the sites of old landfills [178]. 179

In conclusion, in this paradigm, designs in which the benefits to humanity and biology far outweigh the costs are preferred. This idea is quite different to the one emphasized in the reductionist approach to sustainable design in which a design is preferred if its environmental costs are considered ‘low’ or ‘lower than alternatives’, with no consideration of the legitimacy of the need for the design’s functionality.

10.3 WHAT IS ENVIRONMENTAL SUSTAINABILITY IN THIS PARADIGM?

10.3.1 Sustainability Is an Emergent Property of a Complex System

Environmental sustainability arises from thousands of insignificant decisions made by billions of people every day and has to do with how these decisions alter the system of energy and material flows on earth. These flows from both anthropogenic and non- anthropogenic sources form a hierarchical network, and sustainability is an emergent property that arises out of the network. Consequently, within this paradigm, sustainability is conceived of as an emergent property of a complex system, rather than a collective property of a system or an intrinsic characteristic of a design. An emergent property is a “nonreducible property- that is, a property of the whole not reducible to the sum of the properties of the parts” [138], and a complex system is one in which “the effects of fine details amplify so that small differences end up having large effects” [179]. “The hierarchical nature of complex systems requires that they be studied from different types of perspectives and at different scales” [40]. Some other authors also describe sustainability in this way, stating, for instance:

“Complexity models of living systems can… ground… models for sustainability as an emergent property” [44]; “Sustainability is not an aggregate of social–economic–

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technological solutions, but rather an emergent property arising from the interactions of all these systems” [137]; “sustainability issues cannot be discussed in isolation. They must always be examined within their broader context. Every system is a component of another system and is, itself, made up of systems” [40]; and the biosphere and “Human-dominated ecosystems and landscapes” are complex adaptive systems, whose sustainability is related to system resilience, i.e. the persistence of system function in the face of “change and disturbance” [168].

10.3.2 Sustainability Means Preserving Biodiversity and Maintaining a Habitat for Humans

The underlying goal of those trying to protect the environment is to ensure the success and survival of living organisms on earth, particularly humans. Consequently, in this paradigm, environmental sustainability is understood to be a state of the global environment in which there is sufficient habitat for humans and in which biodiversity more broadly is preserved. Biological diversity has this level of importance because functional and genetic diversity both globally and locally is an indicator of the ability of life to be resilient and survive in the face of environmental disasters, disease, and habitat change. (In some cases, these two goals of environmental sustainability may come into conflict, such as when a new virus develops that contributes to biodiversity on earth but threatens the existence or quality of human life. Eradicating this threat can be deemed ‘sustainable,’ or at least not ‘unsustainable.’)

Other authors promote similar conceptions of sustainability, stating, for instance, that sustainability is “a condition of balance, resilience, and interconnectedness that allows… society to satisfy its needs while neither exceeding the capacity of… ecosystems

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to… regenerate the services necessary to meet those needs nor by our actions diminishing biological diversity” [121], that sustainability is about stopping “the unraveling of ecological relationships we depend on for food and health,” stabilizing the atmosphere,” slowing “the falling of aquifers” and “the rising of oceans,” and returning “Arctic ice… to its pre-industrial extent” [36], and that “Ecological sustainability emphasizes… the importance of enabling natural systems to endure through the maintenance of their essential functions and processes, and retention of their biodiversity” [143].

10.3.3 Focus on Sustainability on a Global Scale

Within this new paradigm, sustainability is viewed as occurring on a global level, just as the survival of humanity and other living organisms occurs globally. Many other authors refer to the global nature of sustainability, stating that sustainability is “an overarching globally scaled, evolving aspiration” [143], “a global constraint” [6], a “macroeconomic problem” [136], and a “property of the world at large”

[44]. Similarly, numerous authors emphasize the importance of addressing environmental problems from a global perspective, stating, for instance, that “Problems of population size and growth, resource utilization and depletion, and environmental deterioration must be considered jointly and on a global basis” [134]. Changing the global environment – for instance, by changing the chemical makeup of the atmosphere through the release of GHGs – threatens many forms of life simultaneously, including humans. In contrast, localized environmental effects are easier to address because their sphere of influence is limited; people or endangered organisms can be moved out of the impact area, or the bad impacts can be moved to an area with few or no people. Consequently, avoiding global environmental changes is of the utmost 182

importance and is prioritized over avoiding local environmental impacts. However, the total amount of localized disruption that occurs in the world is also taken into consideration because it is not viable to have a large proportion of local ecosystems around the world to be disrupted and inhospitable to humans and other organisms. Hence, in the new paradigm, both total human impact and net human impact influence overall sustainability. Total human impact is the sum of all low-level individual impacts such that ‘positive’ and ‘negative’ environmental impacts both increase the total impact, e.g. carbon emissions and carbon sequestration both count as environmental impacts, just as natural resource extraction and waste disposal do. Total impact matters because it represents the extent to which local ecosystems are disrupted by humans. In contrast, net human impact considers the balance between positive and negative impacts, e.g. the net increase in carbon in the atmosphere over the last year. Net impact matters because it indicates how the environment changes on a global scale, providing insight into the large-scale buildup of pollutants, upcoming shortages of fossil fuels, etc. Hence, this approach considers both global change to the environment as well as the total amount of local environmental disruption occurring from a global perspective.

10.4 IMPLICATIONS OF THE NEW PARADIGM FOR SUSTAINABLE DESIGN

This new paradigm for environmental impact and environmental sustainability has a number of important implications for sustainable designers, six of which are discussed below.

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10.4.1 Sustainable Designers Should Work to Redesign Energy and Material Networks

Sustainable designers can achieve the goal of balance in energy and material networks by modeling the existing environmental impact network and designing human systems that fit into that network well. This approach encourages broad, system-level solutions to environmental problems via the redesign of these networks and the re-routing energy and material flows. In contrast, the reductionist approach focuses on reducing the amount of energy and materials flowing in the network, but leaves the connections and the shape of the network the same. Of course, it is clearly not feasible or advisable to try to model everything in the universe to understand environmental sustainability and answer everyday sustainability- related questions. In addition, it is important “to avoid any temptation” to implement “some massive central planning process in which we pretend to design the industrial system from the top down… because it is so clearly not possible” [43]. Instead, there may be benefit in thinking about environmental impact in this way, as an interconnected complex system, and modeling the components of the broader system where relevant.

10.4.2 Sustainable Designers Should Strive to ‘Balance’ Environmental Impacts, Not ‘Minimize’ Human Impacts

The goal of sustainable design in this new paradigm is to achieve balanced flows of materials and energy on earth so that the environment is stable enough to support human life and preserve global biodiversity. This amounts to striving for net-zero impact on a global scale, accounting both for anthropogenic and non-anthropogenic impacts. Here, sustainability is viewed as relating to the accumulation of materials in the environment (e.g. pollutants) and the removal of materials from the environment (e.g. fossil 184

fuel extraction). To be sustainable, there must be enough energy and materials to perform all functions required on earth (there is no desperate shortage), and there must be balancing components in the system that consume enough of the waste or pollution so that the rate of accumulation is slow enough to allow mammals and other slowly-evolving organisms to keep pace from an evolutionary standpoint, avoiding a mass extinction, preserving biodiversity, and ensuring the planet is able to continue to support human life.

This approach is quite different than the one adopted in the existing paradigm, where designers seek to minimize total human environmental impact or the impact of low- level components in the network, such as products.

10.4.3 Designers Should Continue to Strive for Efficiency

Eliminating unnecessary energy and materials consumption still has a place in the road to achieving sustainability. Sustainable designers should work to balance the environmental impact across the entire global system, striving to minimize waste on a small scale. This amounts to ensuring the total environmental impact on a local scale is within the scope of that area’s ability to absorb and process the impact. Maximizing efficiency on a small scale helps achieve the goal of minimizing total human impact and minimizing the disruption of local ecosystems.

10.4.4 The Focus of Sustainable Design Shifts to Protecting Humans and Preserving Biodiversity Globally

In response to this new view of sustainability, the focus of sustainable design shifts from 'reducing anthropogenic environmental impacts' to 'preserving biodiversity globally and maintaining a habitat for humans'.

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One implication of this shift is that human and non-human environmental impacts alike can be considered good or bad for the environment, depending on whether the impact promotes or hampers biological diversity globally. Impacts typically considered 'bad for the environment', such as the destruction of biological organisms and ocean dumping, could be considered 'good for the environment' in some contexts, such as when invasive species are destroyed or when wreckage in the ocean provides a structure on which a coral reef can grow. Also, because sustainability is assessed on a global scale in this paradigm, what might have been considered a negative environmental impact using the old paradigm

– because of negative local effects – might instead be considered a positive impact if it contributes to global biodiversity or an enhanced ability of humans to survive on earth. Negative environmental impacts that can be contained locally can be good in small quantities on a global scale, for instance, if they promote the evolution of new types of organisms capable of living in extreme conditions. For example, heat pollution from a power plant may kill local fish – reducing diversity locally – but provide a new habitat for endangered sea turtles or manatees, contributing to greater biodiversity globally. These observations highlight the need to pay additional attention to context in sustainable design. In addition, shifting the focus of sustainable design towards 'promoting biological diversity' emphasizes the need for greater consideration of endangered species in an impact area and the importance of avoiding broad-scale impacts with the potential to change the environment globally or regionally for many organisms at once, over avoiding small-scale impacts that change only the local environment.

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10.4.5 Designs Cannot be ‘Sustainable’ Because Sustainability Is an Emergent Property of a System

Examining the environmental impact of a design and declaring it “sustainable” or “unsustainable” is similar to looking at the behavior of a tiny piece of an immense and complex system out of context and making judgements about how this tiny piece plays into the broader network. By definition, an emergent property of a complex system cannot be attributed to a single component in the system. Similarly, ‘sustainability’ cannot be attributed to a single product or design.

10.4.6 For Sustainability, Size of the Impact of a Design Does Not Matter

Within the new paradigm, there is no sustainability advantage for components in the environmental impact network to have relatively small impacts. Instead, sustainability is a property of the network that arises when the inflows and outflows are in balance, such that the dynamic interactions between components still allow for the basic needs of humans and biology to be met on earth. This balanced network could have components that all have small impacts or components that all have large impacts. But no matter. It is the balance of flows that matters for ecosystem stability and the survival of life on earth, not the size of the impact of individual components. However, designs in which the environmental benefit provided by the design is significantly greater than the environmental toll the design takes on humans and biodiversity are preferred to designs where the environmental costs may outweigh the benefits.

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10.5 CONCLUSION

This chapter rejected the reductionist approach and presented a new paradigm for thinking about environmental impact and environmental sustainability. Here, sustainability is viewed as an emergent property arising out of a broad network of environmental impacts. The concept of environmental impact presented in this chapter emphasizes the importance of context and presents a case for shifting the focus of sustainable design away from ‘reducing anthropogenic environmental impacts’. Instead, the goal of sustainable design in this paradigm is to maximize species diversity and maintain a stable ecosystem capable of supporting human life. The next chapter presents a summary of practical findings from throughout this work that can guide LCA practitioners, sustainable designers, eco-consumers, and researchers based on the new paradigm presented here.

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Chapter 11: Summary of Findings, with Examples

This chapter provides a summary of practical advice to LCA practitioners, sustainable designers, eco-consumers, and researchers, based on the new paradigm presented in Chapter 10. This is a synthesis of the findings from all previous sections. For every recommendation, examples of hypothetical products, LCAs, and sustainable design projects are presented to demonstrate the theoretical points made in the work and provide insight into the practical implications of adopting the conceptions of sustainability and environmental impact discussed here. It should be noted, however, that any examples, models, or calculations presented below are meant only to illustrate concepts and demonstrate the plausibility of theoretical points. In addition, these recommendations are intended as strategies or options LCA practitioners, sustainable designers, eco-consumers, or researchers may benefit from considering. As such, some of these recommendations work towards the same goal in conflicting ways and cannot be used simultaneously, while others may be complimentary and generate greater benefit if used together. It is left to the LCA practitioner, designer, eco-conscious consumer, and researcher to determine which recommendation – or combination of recommendations – is most appropriate and effective to use for the task at hand.

11.1ADVICE TO LCA PRACTITIONERS

11.1.1 Consider consequential LCA.

The distinction between attributional and consequential LCA is not often discussed in sustainable design literature, and many may be unaware of this distinction and the possibility of using consequential LCA approaches to achieve their objective.

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Consequential LCA should be used when determining how to reduce future environmental impact and what the consequences of a change will be. In consequential LCA, practitioners model the context surrounding the product and ask: ‘What will happen in the environment if the proposed change is made? What will the consequences be of having more or less of this product on the environment?’ In contrast, in attributional LCA, practitioners model the life cycle of the product and ask: ‘How much environmental impact is this product responsible for? How much impact can be attributed to the product?’

11.1.1.1 Example:

Suppose there are 5 consumers on an electric grid each consuming 1 unit of electricity over a certain time period, as depicted in the center of Figure 7, below. This electricity (represented by the blue rectangles) is supplied by both a PV panel and a diesel generator. For the time period in question, the PV panel supplies 4 units of electricity and the diesel generator makes up the difference between demand and supply, generating 1 unit. This is represented in the leftmost column of Figure 7 in blue. To the right of this column, the life cycle GHG emissions associated with the 4 units of electricity generated by the solar PV panel and the 1 unit generated by the diesel generator are represented in yellow and red, respectively. An attributional LCA, which uses averages and evenly distributes environmental responsibility to entities based on the amount they consume, shows that each consumer is responsible for 1/5 of the GHG emissions associated with the grid. Consequently, in the second to the rightmost column in the figure above, each consumer is shown to be responsible for 1/5 of the GHG emission associated with the PV panel (in yellow) and 1/5 of the emissions associated with the diesel generator (in red). 190

Figure 7: Attributional vs. consequential LCA for an electric grid with 5 consumers.

In contrast, consequential LCA shows what difference an individual can make and how that person can change what happens in the environment. Consequently, in the rightmost column in the figure above, the first 4 consumers are shown to emissions impacts equal to 1/4th of the total of the electricity from the PV panel (in yellow), and the fifth consumer is shown to have emissions impacts equal to the emissions associated with the one unit of electricity produced by the diesel generator (represented by the red rectangle in the top right corner of the figure). If one person on the grid stopped consuming electricity, the marginal electricity generation (in this case, the electricity from the diesel generator) would be reduced. In addition, if one consumer doubled his or her electricity consumption, only marginal electricity generation (again from diesel) would be added.

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The change in impact calculated in consequential LCA may be larger (or smaller) than the amount of environmental impact that individual is responsible for, because the marginal electricity on the grid (ex. diesel electricity) may have a very different impact (represented by the red rectangle in the top-right corner of the figure) than the average grid electricity (represented by any one of the red and yellow combination rectangles in the second to rightmost column in the figure).

11.1.1.2 Related Sections:

For more on the distinction between attributional and consequential LCA, see Section 2.2.2.

11.1.2 Consider hybrid LCA or process LCA with network modeling.

Consider hybrid LCA or process LCA with network modeling to capture broader contextual and systems-level effects. Although the distinction between process, input- output, and hybrid LCA is frequently discussed in the field, few in sustainable product design use hybrid LCA, the most detailed and broad (but also most time consuming) approach. In addition, process LCA with network modeling is rarely, if ever, discussed.

11.1.2.1 Example:

For instance, Yue et al. [13] used hybrid LCA when assessing the GHG emissions impact of an ethanol supply chain in the UK. The authors used multi--objective optimization with the simultaneous goals of minimizing GHG emissions and minimizing cost. As shown in Figure 8, below, of ten supply chain designs they identified on the Pareto frontier, between 12.8% of total GHG emissions calculated (case 10) and 58.4% of total GHG emissions calculated (case 1) were attributed to the input-output portion of the hybrid 192

LCA. This means these emissions would not have been included in the analysis had only process LCA been undertaken, as is commonly the case in sustainable product design. Hence, the results highlight the advantage of conducting hybrid LCA over process LCA.

Figure 8: “Pareto profile with the total project cost and life cycle GHG emissions for 10 instances” [13]. This demonstrates the importance of the input-output portion of the LCA (in yellow), as it represents a significant proportion of the overall GHG impact for each of the 10 designs.

In addition to hybrid LCA – which is process LCA combined with input-output LCA – process LCA could instead be combined with network analysis, i.e. process LCAs could be combined with general models of global material flows based on engineering principles and environmental data (rather than economic data, as in input-output LCA). As will be discussed in Section 11.4.1.1, Bailey et al. [180] have taken an initial step towards this goal, through the development of a material flow analysis approach that models physical flows using the mathematics underlying economic input-output analysis.

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11.1.2.2 Related Sections:

For more on the differences between process, input-output, and hybrid LCA, see Section 2.2.1.

11.1.3 Select the scale of analysis and the functional unit to intentionally influence the focus of the study and the aspects of the product/fleet/industry/economy that are modeled in detail.

Small-scale analyses are more likely to have accurate data for low-level impacts and use approximations or make assumptions about high-level phenomena, whereas large- scale analyses are more likely to have accurate high-level data and use averages and assumptions to account for small-scale phenomena. Large-scale analyses are also more likely to account for systems-level effects. The conscious selection of the scale of the analysis is different from the current approach in LCA, where the scale and the size of the functional unit are selected more arbitrarily (as they are not expected to affect the results of the study, since all results scale linearly in attributional LCA). Choosing the right scale of analysis is important because it determines the types of environmental issues raised through the LCA and the types of solutions proposed.

11.1.3.1 Example:

An LCA analyzing the impact of one solar PV panel is likely to have more detailed modeling of the low-level technical aspects of the panel itself, the manufacturing process for the panel, assumptions about specific weather patterns, and detailed data related to the panel’s assumed performance, for instance, with general assumptions about equipment impacts that contain implicit assumptions about the total number of panels produced on the equipment. In contrast, an LCA analyzing the impact of a solar PV fleet is likely to have

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more detailed and well-supported assumptions about the total fleet size, the timing of the fleet production and its effect on manufacturing equipment impact, but perhaps less information and more assumptions regarding the technical details of the panels. Differences along these lines are reflected in work from Dale and Benson [167] comparing the energy balances of solar PV on the scale of a single PV electricity generation plant (shown below on the left) and the whole PV industry (depicted on the right).

Figure 9: Left: “Energy inputs and outputs to a single energy production system. Energy inputs (blue) are” below “the horizontal line, and energy production (yellow) is shown above the line”; Right: “Energy inputs and outputs for an energy production industry growing asymptotically to some upper limit. Gross output is shown as a bold line; net output is shown with the dashed line” [167].

The differences between these two analyses highlight the important differences that occur between environmental analyses performed on different scales. The single-plant analysis is focused on quantifying the amount of electricity produced by the PV panel over its lifetime, as well as the input energy to manufacture, maintain, and dispose of the panel.

In contrast, the industry-wide analysis focuses on bigger-picture, systems level phenomena, such as the energy balance across the whole industry and the industry growth

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rate. The industry-wide analysis shows that even though individual solar PV panels produce more electricity than they consume over their lifetimes, the total PV industry could be net energy consuming if the growth rate of the industry is high [167]. This means that each panel may appear to contribute to clean energy production (and therefore confer a positive environmental impact) when analyzed individually, but collectively, all PV panels in the industry could consume more energy than they produce, i.e. “A rapidly growing PV industry may even temporarily exacerbate the problem of GHG emissions if operating at a net energy loss, i.e. consuming more energy each year in manufacturing and installing PV systems than is produced by systems in operation” [167]. Panel-scale analysis asks: ‘Are PV panels individually net electricity producers?’, while an industry-scale analysis asks “Is the global PV industry a net electricity producer?” [167]. These two analyses are very different, requiring very different models of PV’s impact and arriving at different types of solutions.

11.1.3.2 Related Sections:

For more on the functional unit in LCA, see Section 2.3.1.2; for a summary of the basics of scale in LCA, see Section 3.1.1; for a discussion of the effect of scale on LCAs, see Section 3.1.2.; system-level effects, Section 9.2; and scale effects, Section 9.2.3.

11.1.4 When in doubt, select the highest relevant scale of analysis and largest relevant functional unit.

The higher the scale of analysis, the more likely large-scale contextual factors and systems-level effects will be captured. Moving up a level of scale means generating a hierarchical model of environmental impact for the design. Generating this type of model

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allows more system-level effects to be accounted for because system-level entities can be explicitly included in the model.

11.1.4.1 Example:

For instance, opt to conduct a fleet-scale solar PV analysis rather than an analysis of a 1 kW PV panel. Doing so will better account for large-scale contextual factors (as a fleet-scale analysis will have context-specific data related to the rate of production of the fleet or the actual number of panels in the fleet, for instance), whereas an analysis of a 1 kW PV panel is more likely to be an analysis of an ‘average’ panel, and the contextual factors driving many of the assumptions are unlikely to be highlighted. Choosing a larger- scale functional unit will also help include systems-level effects in the analysis, such as environmental economies of scale (stemming from more fully utilizing PV panel manufacturing capacity or having greater coverage of PV recycling facilities due to greater PV densities).

11.1.4.2 Related Sections:

For a summary of the basics of scale in LCA, see Section 3.1.1; for a discussion of the effect of scale on LCAs, see 3.1.2; for more on the problems with small-scale analyses and the benefits of large-scale analyses, see 3.1.3; for a discussion of systems-level effects, see 9.2.

11.1.5 Focus on larger environmental problems and perform LCAs on larger scales to make better use of the time and resources necessary to do LCA right.

When the problem (and the potential reduction in impact that might be achieved through sustainable design) is larger, it makes more sense to invest the time and resources

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to conduct a rigorous LCA and include many types of impacts, wide system boundaries (integrated hybrid LCA), modeling detail, and context-specificity.

11.1.5.1 Example:

Suppose an LCA practitioner has a week to assess the environmental impacts of solar PV and is going to create a model with 100 elements. The practitioner could either: (1) meticulously analyze the impact of one specific PV panel in a specific location with detailed data, or (2) meticulously analyze a company’s PV fleet. The time spent carefully analyzing a PV fleet will more likely result in a significant reduction in environmental impact than if that time were spent carefully modeling one specific PV panel and optimizing its environmental impact.

11.1.5.2 Related Sections:

For a summary of the basics of scale in LCA, see Section 3.1.1; for a discussion of the effect of scale on LCAs, see 3.1.2.; for more on the problems with small-scale analyses and the benefits of large-scale analyses, see 3.1.3.

11.1.6 Conduct uncertainty analysis and/or sensitivity analysis.

Uncertainty analysis “models uncertainties in the inputs to a LCA and propagates them to results,” whereas sensitivity analysis “helps to identify the most influential LCA inputs when their uncertainty has yet to be or cannot be quantified” [31]. ISO 14044 states that “An analysis of results for sensitivity and uncertainty shall be conducted for studies intended to be used in comparative assertions intended to be disclosed to the public” [25]. Uncertainty analyses may indicate that the results of an LCA are inconclusive because there is too much uncertainty in the inputs to the study. Consequently, it is 198

important to do this analysis, and accept an inconclusive result should it arise. In addition, some models of environmental impact are more sensitive to differences in assumptions, methods, and data than others. It is important to know if the results of an LCA will change if an assumed value is altered slightly, if a different method had been used, or if one dataset is selected over an equally-representative one.

11.1.6.1 Example:

Siler-Evans et al. [87] conducted an extensive sensitivity analysis for their study of the benefits of wind and solar generation, verifying that their conclusions (that “(i) the benefits of wind and solar energy vary widely depending on location, and (ii) the sites with the highest energy output are not necessarily the best for offsetting health and environmental impacts”) would not change had assumptions been altered. Specifically, they analyzed the effect of “(i) key assumptions in the Air Pollution and Emission Experiments and Policy (APEEP) analysis model, (ii) using average (rather than marginal) damages from electricity production, (iii) dividing the United States according to the eight regions of the North American Electric Reliability Corporation

(NERC) rather than the 22 eGRID subregions, and (iv) valuing displaced NOx and SO2 emissions using allowance prices” [87]. They found that “Results are most sensitive to the value of a statistical life, the social cost of CO2 emissions, and the dose–response function that relates mortality to concentrations of fine particulate matter,” but these sensitivities affect only the magnitude of the results, not the general conclusions [87].

The figure below, for instance, shows the result of 5 different cases exploring the health and environmental benefits of a 1-kW solar panel in 5 different locations, exploring the effects of different assumptions related to the value of a statistical life, and different 199

methods used. The important finding is that although the magnitude of benefits change for each case, the relative benefits remain the same for each region in each case, signaling that the conclusions are robust and reflect real relationships beyond those imparted by the subjective decisions made by the LCA practitioner related to assumptions, methods, and data.

Figure 10: “Sensitivity analysis for the health and environmental benefits from solar energy. Results present the average annual benefits from displaced SO2, NOx, and PM2.5 for solar panels within an eGRID subregion. Five cases are presented for 5 of the 22 eGRID subregions. The selected regions are: AZNM (Arizona and New Mexico), ERCT (Texas), MROE (Wisconsin), RFCW (Indiana, Ohio, and West Virginia), and SRMW (Missouri and Illinois)” [87].

11.1.6.2 Related Sections:

Subjectivity in LCA, Section 2.3.1; uncertainty in LCA, Section 2.3.2.1.

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11.1.7 Conduct contextual analysis.

Identify contextual factors that might alter the environmental impact of the design in every life cycle phase. Create a model relating these contextual factors to the design’s environmental impact. Find distributions for the values of the contextual factors, and run them through the model to get an estimate of the real-world variability in the environmental impacts of the design.

11.1.7.1 Example:

In the case of a solar PV panel, for instance, an LCA practitioner would brainstorm potential contextual factors that could affect environmental impact in every life cycle phase, generating the result depicted below.

Figure 11: A list of potential contextual factors in each life cycle phase that may alter the environmental impact of a solar PV panel.

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Since the use phase of a PV panel drives its GHG emissions balance, an LCA practitioner may decide to focus efforts there and develop a model that can account for contextual factors during use. A simple model of a PV panel relating sunlight availability at the location of use to the GHG emissions avoided is provided below. Model inputs include hourly data on solar panel production, accounting for both location and weather effects. The electricity generated by the panel replaces electricity that would have been provided by other sources on the electric grid, avoiding GHG emissions associated with these sources.

Figure 12: Model relating sunlight availability at the location of use to the GHG emissions avoided for a PV panel.

Next, an LCA practitioner could consider how solar insolation might vary during use. A map of the US showing annual average solar insolation for a panel tilted at an angle

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equal to the latitude is provided below, highlighting the locations of three cities receiving high, medium, and low solar insolation – Phoenix, Austin, and Seattle, respectively.

Figure 13: Annual average solar resource data for the US, shown for a solar collector tilted at an angle equal to the latitude. Adapted from Roberts [181].

Next, the LCA practitioner would run the model many times to determine the environmental effect of varying the contextual factor of interest – here, the solar insolation. Below, the results of calculations of the annual PV production for a 4kW panel, the GHG intensity of the electricity generated by the panel, and the lifetime avoided GHG emissions are provided for Phoenix, Austin, and Seattle, assuming a 30 year panel lifetime, embedded emissions for the panel of 6200 kgCO2-eq, and the GHG intensity of avoided electricity is

533 gCO2/kWh. These calculations, including justification for all assumptions, are presented in O’Rourke and Seepersad [89], which is reproduced in the appendix.

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Table 2: Annual electricity production, GHG intensity of electricity, and lifetime avoided GHG emissions estimates for a 4kW PV panel in three cities, assuming a 30 year panel lifetime, embedded emissions for the panel of 6200 kgCO2-eq, and the GHG intensity of avoided electricity is 533 gCO2/kWh.

Phoenix Austin Seattle Annual PV Production for 6,926 5,900 4,341 4kW Panel (kWh) GHG Intensity of Electricity Generated by the Panel 29.8 35.0 47.6 (gCO2-eq/kWh) Lifetime Avoided GHG 110,700 94,300 69,400 Emissions (kg CO2 avoided)

Over the course of a year, total PV electricity production varies significantly based on solar insolation at the location of use – from 6,926 kWh for the panel in Phoenix to 4,341 kWh in Seattle. The GHG intensities for electricity generated by the panel at each location likewise vary – with the GHG intensity of the electricity generated by the same solar PV panel almost 60% higher in Seattle than in Phoenix. For the 30 year life of the panel, the differences in solar insolation at the location of use resulted in substantial differences in avoided GHG emissions: 110,700 kg CO2 avoided by the panel in Phoenix;

94,300 kg CO2 by the panel in Austin, and 69,400 kg CO2 by the panel in Seattle. These results highlight the importance of solar insolation at the location of use for the lifetime GHG emissions impact of PV panels and provide insight to the LCA practitioner regarding the extent of the real-world variability in the GHG emissions impact of a panel.

11.1.7.2 Related Sections:

For more on how environmental impact is determined by contextual factors, see

Section 5.1; for discussion of how and why LCAs typically fail to account for contextual factors, see Sections 5.5.1 and 5.5.2. Appendix A5 provides further details for the

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calculations provided here, as well as further calculations exploring other ways the environmental impact of solar PV varies with contextual factors.

11.1.8 Include assessment of damage to biodiversity.

Include assessment of damage to biodiversity, distinguishing between local and global biodiversity issues, as is done in biological assessments of environmental impact. Consider including damages to the biotic environment or midpoint categories relating to effects on local endangered species, for instance.

11.1.8.1 Example:

Hernandez et al. [182] review work assessing the environmental impacts of utility scale solar PV on biodiversity, addressing issues such as habitat degradation on land used throughout the PV life cycle (due to vegetation removal at the PV installation site and the grading of land), landscape fragmentation preventing the movement of organisms, the importance of siting systems away from habitats for endangered species, and the effect of toxins in herbicides and chemicals used at the site to prevent dust buildup and rust. Stoms et al. [183] present research on siting solar energy projects to minimize biological impacts, by selecting land that is already degraded and is of low conservation value, for instance, as well as land that can easily be connected to existing infrastructure, minimizing the need to affect more land through infrastructure expansion.

11.1.8.2 Related Sections:

Section 2.1.2 on LCA phases, specifically ‘midpoint categories’ and ‘damages’ in life cycle impact assessment; Section 7.3.1.3 on how sustainability in biology is about preserving biodiversity on both a global and local scale; Section 10.3.2 on how 205

sustainability means preserving biodiversity and maintaining a habitat for humans; and Section 10.4.4 on how the focus of sustainable design in the new paradigm relates to preserving global biodiversity.

11.1.9 Explicitly account for the positive aspects of some human-caused environmental impacts.

Explicitly account for the positive aspects of some human-caused environmental impacts, rather than accounting only for the human-caused impacts that worsen environmental problems and generate environmental damage. What is considered an environmental benefit or environmental damage depends on context, with ‘positive’ aspects bringing the global system back into balance, and ‘negative’ aspects driving the global system into a greater state of imbalance.

11.1.9.1 Example:

For instance, heat pollution from a power plant has provided a habitat for endangered sea turtles in California [120], and this type of environmental benefit stemming from a human-caused impact should be accounted for in LCA. This may have further implications for LCAs of products where the function of the device is to protect human health or biodiversity, such as medical devices and incubators for endangered species.

11.1.9.2 Related Sections:

Section 10.1.3 on how impacts are not inherently good or bad for the environment; Section 10.2.2.2 on how both ‘negative’ and ‘positive’ impacts should be considered;

Section 10.4.4 on how the focus of sustainable design should be on protecting humans and preserving biodiversity globally.

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11.1.10 Conduct contextual analysis, and avoid labelling impacts as ‘good’ or ‘bad’ for the environment.

As in life cycle inventory analysis, conduct contextual analysis. The same impact may affect different environments in different ways, causing damage in some contexts but imparting benefits in others. Additionally, for one particular context, a given impact may confer harm to some organisms and benefit to others.

11.1.10.1 Example:

Chemical releases in highly-populated areas do more human health damage than releases in sparsely-populated areas because more people are exposed. For instance, the negative effects of “acidification, eutrophication, and smog” from concrete manufacturing are significantly reduced when production occurs in northeastern U.S., as compared to elsewhere in the country, because “a significant share of the emissions are carried out to sea rather than across populated areas of the North American continent” [91]. Bare et al. [91] develop and use the tool TRACI to do location-specific LCIA, relating impacts to actual environmental damage. Also, as mentioned previously, waste heat emitted from a power plant could kill some local species while creating a habitat for others, potentially altering the biodiversity balance associated with the design. This example shows how one impact in one context

(waste heat emissions at a particular site) can confer harm to some organisms and benefits to others.

11.1.10.2 Related Sections:

For more on how environmental damage caused by a given impact is determined by contextual factors, see Section 5.2; for discussion of how and why LCAs typically fail 207

to account for contextual factors, see Sections 5.5.1 and 5.5.2. A new ecology-inspired LCA framework, Section 7.3.2.; Quantity-related effects, the total impact matters, and LCA does not account for the total quantity of emissions and associated threshold effects, Section 9.2.4.1. Impacts are not inherently good or bad for the environment, Section 10.1.3.

11.1.11 Show your work, and emphasize the environmental impact model and assumptions in LCA publications.

When publishing the results of an LCA, present the model and assumptions explicitly. Provide a visual depiction of the system analyzed (for instance, with boxes used to represent elements in the model and arrows to represent flows of energy, materials, pollutants, etc.), along with a list of all assumptions. This is currently not done routinely in LCA research, as evidenced by the many studies thrown out by researchers conducting meta-analyses due to lack of information necessary for them to reproduce published models and generate new results using standard assumptions. (For instance, in their life cycle harmonization study of solar PV panels, both Kim et al. [184] and Hsu et al. [185] explicitly state that they had to throw out a number of studies that did not include the values they used for key parameters for PV life cycle GHG emissions.) Other researchers should be able to read an LCA and easily use the published model and accompanying calculations and modify the model to fit their own assumptions, data, and context to generate their own results.

11.1.11.1 Example:

The figure below shows an example of a detailed visual representation of an environmental impact model, clearly indicating the portions of the product’s life cycle that

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were considered by the analyst, complete with the type and amount of materials and energy flowing from one entity to the next.

Figure 14: “Process flow diagram with an internal commodity flow loop” [20].

This is in contrast to literature that fails to adequately describe environmental impact models, literature that describes impact models in text form, and literature that provides an overly-generic visual lacking detailed information pertaining to the modeling choices, assumptions, and data.

In addition, authors should provide details regarding all calculations and assumptions. For instance, the following equation, adapted from Hsu et al. [185], was used to harmonize the solar PV LCAs they analyzed:

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푊 퐺퐻퐺 = 퐼 ∗ 휂 ∗ 푃푅 ∗ 퐿푇 ∗ 퐴 Where:  GHG = the mass emissions of GHGs weighted by their global warming potential

per unit electricity generated by the solar panel (gCO2eq/kWh)  W = the global warming potential-weighted mass of the GHGs emitted over the

lifetime of the PV system (gCO2eq)  I = Irradiation (kWh/m2/year)  η = the lifetime average module efficiency (%)  PR = the performance ratio  LT = the system lifetime (years)  A = total module area (m2) Providing this equation, with a listing of all assumptions used in the calculations with justification (for efficiency, performance ratio, etc.) is necessary for other researchers to recreate results and adapt the model to other contexts, situations, designs, and environmental problems.

11.1.11.2 Related Sections:

For a discussion of the difficulty in comparing LCAs and applying the results to other problems, see Section 2.3.2.2. For two methods for visually depicting environmental impact scenarios, see Section 6.2.

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11.2 ADVICE TO SUSTAINABLE DESIGNERS

11.2.1 Work to balance the global environmental impact network, minimizing waste and optimizing flows between entities.

The goal of sustainable design in the new paradigm is to achieve balanced flows of materials and energy on earth so that the environment is stable enough to support human life and preserve global biodiversity. This amounts to striving for net-zero impact on a global scale, accounting both for anthropogenic and non-anthropogenic impacts. To do this, designers should strive to redesign the global network by re-routing energy and material flows (as in the design of industrial ecosystems) and by designing products and systems that help bring these flows back into balance.

11.2.1.1 Example:

The new paradigm equates sustainability with a state of balance in the energy and material flows on earth, where the values of sources, sinks, and flows are such that human life can be sustained and biodiversity is preserved. Because of this: (1) high-impact designs are not viewed as being at odds with sustainability and (2) low-impact designs are not viewed as guaranteeing sustainability. The following example networks illustrate why this is the case. First, designs with large impacts can be part of balanced, sustainable networks, as shown in the figure below.

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a)

b)

c)

Figure 15: Just because an impact is large does not mean it is ‘unsustainable’ or that the network is imbalanced.

For example, imagine a world in which global environmental impacts are in balance and there is no threat of either a cooling or warming climate. A large amount of GHG emissions from a large coal-fired power plant could be balanced with a large-scale reforestation project with a large amount of GHG sequestration. This scenario could be represented by the model depicted in Figure 15a, with the coal plant on the right and the reforestation project on the left. This network is viewed as being ‘sustainable’ because there is balance in the network; materials and energy are not accumulating (as waste) or being depleted (as a resource). However, implementing a large-scale carbon sequestration project in this world without countering it with a large-scale carbon emission project would be considered unsustainable, as would the reverse. Here, sustainability does not have to do with avoiding certain types of impacts (GHG emissions) or minimizing impacts (having a

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small coal-fired power plant with few emissions or a small carbon sequestration project removing a small number of GHGs from the atmosphere); it has to do with having a balanced system of energy and material flows on a global scale. Likewise, a small amount of GHGs from a small coal-fired power plant could be balanced with a small-scale reforestation project with a small amount of GHG sequestration, depicted in Figure 15b. In addition, many small coal fired power plants, each emitting a small amount of GHGs, but collectively emitting a large amount of GHGs, could be balanced with a large-scale reforestation project, depicted in Figure 15c.

Second, designs with small impacts can be part of unbalanced, unsustainable networks, as shown in Figure 16, below. For instance, if the atmospheric level of GHGs is in a balanced state, a small amount of additional GHG emissions from a diesel generator may be ‘unsustainable’; this small emissions imbalance combined with many other small emissions imbalances in the same direction may have a large and negative effect on the environment. The fact that the overall environmental impact of the diesel generator is small does not prevent it from contributing to an unsustainable environmental state. As shown in the figure below, many designs generating the same, small amount of waste (many tiny diesel generators emitting GHGs, for instance) could lead to large-scale, unsustainable accumulation of waste in a manner that is environmentally harmful. Similarly, many instances of consuming a small amount of a resource (one person takes one fish from a lake, for instance) could lead to large-scale, unsustainable depletion of the resource.

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Figure 16: Just because an impact is small does not mean it is ‘sustainable’ or part of a balanced network.

The takeaway here is that the term ‘sustainability’ refers to a state of balance in an environmental impact network and is unrelated to the size of the impact of individual components. Rather than focusing only on minimizing the environmental impact of their design per functional unit, sustainable designers need to consider the total quantity of units and the overall state of the environment with regards to the impact areas of their design.

Their true objective is to balance energy and material flows on earth through the design of products so that resources are not depleted and wastes are not accumulated at a rate that will significantly alter the environment. Minimizing environmental impact on a small scale is not the key to achieving sustainability through design; balancing the flows of energy and materials within a broad system, however, is. Consequently, designers may benefit from adopting approaches frequently used in the design of industrial ecosystems. They should assess the state of the broader system, including the wastes that are accumulating and the resources that are consumed. They should take this information and use it to develop ideas for changes to manufacturing

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processes at companies, for instance, so that companies can better make use of the wastes from their neighbors or avoid consuming resources that are being depleted in their area.

11.2.1.2 Related Sections:

Chapter 4, on network-related approaches to environmental assessment; Section 8.3 on how the reductionist approach is focused on minimizing human impact on small scales; Chapter 9 on problems with the reductionist approach, specifically Section 9.1.1 on how it is difficult, if not impossible, to achieve sustainability by minimizing the low-level impact of products, and Section 9.2 on how minimizing low-level impacts may not lead to decreased impact overall due to systems-level effects; Section 10.1.1 on how sustainability is not a collective property; Section 10.1.4 on how large impacts are not inherently unsustainable; Section 10.2.1 on how environmental impact is a network; Section 10.2.2.2 on how both ‘negative’ and ‘positive’ impacts should be considered; Section 10.3.1 on how sustainability is an emergent property of a complex system; Section 10.4.1 on how sustainable designers should work to redesign energy and material networks; Section 10.4.2 on how sustainable designers should work to ‘balance’ environmental impacts, not ‘minimize’ human impacts; and Section 10.4.6 on how, for sustainability, the size of the impact of a design does not matter.

11.2.2 Select the scale of the entity to design intentionally, with the awareness that the choice will influence the types of design solutions developed.

The types of sustainable design solutions found at different scales vary dramatically, and designers should be cognizant of these differences. Moreover, it may be advantageous to intentionally consider different scales of design solutions during concept generation, as doing so promotes greater exploration of the solution space. For instance, in 215

a brainstorming session with mindmapping, the first ring of structure in the mindmap could be set in advance to encourage the brainstorming of concepts on the product scale, fleet scale, company scale, and inter-company scale. Alternatively, care could be taken in the way the design problem is framed prior to 6-3-5 to avoid biasing the designers to think about design solutions only on one particular level of scale and to encourage designers to consider the possible solutions on multiple levels of scale.

11.2.2.1 Example:

For instance, consider a sustainable redesign effort to reduce the environmental impact of a cell phone. As shown below in Figure 17, very different design solutions could be developed on the scale of an individual phone (product scale), a fleet of phones (fleet scale), the electronics company designing and manufacturing the phone (company scale), and the group of companies co-located with the electronics company (inter-company scale), for instance. On the scale of an individual phone, design solutions could include using a more energy efficient screen technology to reduce energy consumption during use, selecting non-toxic materials and manufacturing processes, and specifying recyclable materials. On the scale of a fleet of cell phones, design solutions could include the optimization of the supply chain and distribution system of phones (through the modelling of the locations of suppliers, customers, and recycling centers and optimizing the placement of manufacturing facilities and product takeback locations to minimize the total mass-distance travelled, for instance). On a company scale, product take-back programs could be developed to collect the product at its end of life and enable the company to reuse, remanufacture, and recycle components from old phones. Finally, on an inter-company scale, designs for industrial ecosystems can be developed, matching the wastes of the phone 216

manufacturing company with the needs of a nearby company in an unrelated industry and generating plans for an optimized network of material and energy flows that collectively yields environmental impact reductions.

Figure 17: Mindmap of concepts to reduce the environmental impact of a cell phone on a product scale (an energy efficient mode), fleet scale (supply chain optimization), company scale (product takeback program), and inter- company scale (industrial ecopark). Image sources: [186][187][188][189].

Interventions on each of these scales could reduce the environmental impact of the cell phone in different ways. As discussed below, interventions on different scales could be complementary, independent, or they might work against each other.

Sustainable design solutions on different scales may be complementary, achieving greater reductions in environmental impact if solutions are implemented together than they would otherwise. For instance, on a product level, redesigning a product so that more 217

components are made out of recyclable material is likely to reduce its environmental impact. Similarly, on a company level, instituting a product takeback program is likely to reduce the impact of the product, as valuable, undamaged components can be recovered and used in remanufactured products. However, implementing these solutions together is likely to result in enhanced environmental benefits. The product takeback program on the company scale will increase the rate at which recyclable components in the product are actually recycled (the company’s efforts to retrieve products will decrease the number of products sent directly to landfills, and the specialization of the disassembly and remanufacturing effort may enable the company to recycle more specialized materials that could not be recycled in a general municipal recycling system). Also, the switch to more recyclable materials in the product means that a reduced percentage of the materials collected via the product takeback program will need to be landfilled (the components that are not reclaimed for remanufacturing efforts are more likely to be recycled by the company). Alternatively, design solutions on different scales may be independent. For instance, increasing the energy efficiency of a coffeemaker on the product scale, while also establishing a product takeback program to take advantage of remanufacturing opportunities, is unlikely to affect the benefits associated with either alternative.

Finally, the design solutions on different scales may work against each other. For instance, efforts on a company scale to reduce waste during manufacturing may prevent an industrial ecosystem from forming on an inter-company scale if the design for the industrial ecosystem is dependent on the availability of the large waste stream from the company.

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Consequently, an assessment must be done of the relative environmental merits of the conflicting sustainable redesign option operating at different levels of scale. Ultimately, it is advantageous for designers to consider potential low-impact design solutions on multiple levels of scale and to examine the effects potential combinations of such solutions might have.

11.2.2.2 Related Sections:

For a summary of scale in LCA, see Section 3.1; for how the reductionist approach neglects context and its significant influence on environmental impact (how the scale of the entity to redesign affects the focus of the study and how context is accounted for), see Section 9.3; for how the reductionist approach misses an important avenue to achieving sustainability: implementing systems-level, structural changes, see Section 9.4

11.2.3 Focus on designing big, high-level systems to make better use of the time and resources necessary to do sustainable design right.

It is impractical and infeasible to do a detailed analysis showing how a small-scale design helps and hurts humans and biodiversity, accounting for all relevant contextual factors. Sustainable designers would make more headway towards achieving environmental sustainability for the same amount of effort if they focused on larger-scale entities (such as groups of companies in the design of eco-industrial parks) rather than minor details of products.

11.2.3.1 Example:

Rather than having many households with residential PV panels, each of which is briefly designed and analyzed for its unique context, it may be better to have a larger, more

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centralized PV system of the same total capacity with much greater and more detailed environmental analysis performed so that the environmental advantages of the system are better assured. For instance, a designer with 1,000 hours to design a 1,000 kW PV system can better optimize the system for the local context if the entire capacity is cited in one location as one large-scale system, as opposed to designing 1,000 systems of 1 kW capacity. With little time to design each of the 1,000 systems, a designer would need to resort to using rules of thumb and generalized data, rather than developing optimized, context-specific solutions. Even simple guidelines, such as ‘set the angle of tilt of the panels equal to the latitude’ become extraordinarily time consuming if one is doing the analysis for many systems. In the time it takes one designer to find 1,000 angles of tilt for 1,000 1kW panels in 1,000 different locations, the same designer of a single 1,000 kW PV system could instead not only identify the angle of tilt for the panels, but also design a reduced-impact method of cleaning the panels based on the relative impacts of different cleaning technologies at the location of use (related to the local availability of freshwater, electricity generation mix on the local grid, and the expected impact of residue from the degradation of a self-cleaning panel coating on the local ecosystem, for instance.)

11.2.3.2 Related Sections:

For a summary of scale in LCA, see Section 3.1; benefits of conducting analysis on a high level of scale, see Section 3.1.3. Problems with the reductionist approach, see Chapter 9, specifically Section 9.1, on how it is difficult, if not impossible to achieve sustainability by minimizing low-level impacts, Section 9.2 on systems-level effects, and Section 9.2.1 on how low-level effects may not ‘ripple up’ the supply chain.

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11.2.4 Ask big-picture, fundamental questions that challenge the proposed focus of the sustainable design project, and adjust the scope accordingly.

Ask big-picture, fundamental questions that challenge the proposed focus of the sustainable design project - such as: ‘Does moving forward with this redesign entrench an environmentally-problematic technology?’ and ‘Is there a more dramatic solution to reduce environmental damage through structural changes, policy changes, or large-scale efficiency improvements, for instance? – and adjust the scope accordingly. Strive to design high level, structural changes to society and infrastructure, in the hope that doing so will generate greater environmental benefits than tweaking the impact of products.

11.2.4.1 Example: Old Scope Questions to Ask New Scope Design lower-impact coal Does redesigning coal Design lower-impact mining processes (more mining processes entrench electricity sources (lower- energy efficient, less acid a problematic technology carbon, more efficient) mine drainage) (coal-fired electricity)? Design a lower-impact car Are large numbers Design an electric vehicle, (choose between an gasoline-powered vehicles design nicer and more aluminum and plastic likely a part of a sustainable convenient public transit radiator cap, make a more future? systems, design appealing efficient engine) urban housing options that reduce travel distance Design a lower-impact Is the wide-scale use of Design initiatives to disposable beverage bottle disposable beverage bottles encourage use of reusable (use less material or use really necessary? Is it a bottles (installing water biodegradable material) good use of earth’s bottle filling stations, resources? allowing companies to fill personal mugs) Design a process for Is there a way that this Design an eco-industrial minimizing waste from a waste could instead be used park with co-located manufacturing facility as a resource? companies (adding a recycling system, reducing scrap rates)

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11.2.4.2 Related Sections:

For a discussion of benefits of conducting analysis on a high level of scale, see Section 3.1.3; on how the reductionist approach misses an important avenue to achieving sustainability: implementing systems-level, structural changes, see Section 9.4; on how focusing on small-scale impacts may distract from opportunities for large-scale change, see Section 9.5.

11.2.5 Generate novel concepts for products with significantly-reduced impacts using alternate ideation techniques during conceptual design.

Generate novel concepts for products with significantly-reduced impacts using alternate ideation techniques during conceptual design, rather than generating ideas for incremental reductions in environmental impact using standard techniques during detail design. The environmental impact of a design should be considered from the beginning of the design process, when designers have more freedom to explore innovative, impact- reducing approaches, rather than as an add-on during detail design, after many aspects of product architecture have been decided. For instance, conceptual designers working in the early phases of design may be able to develop an entirely new concept that has a significantly lower-impact architecture or functions with far less energy. In contrast, detail designers might be able to minimize the number of screws in product, saving a little material; or they might choose to have a component made out of aluminum rather than steel, lightening the product slightly and saving fuel, but with a far smaller impact reduction overall.

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11.2.5.1 Example:

Alternate concept generation methods, such as design-by-analogy and, more specifically, bioinspired design, help designers develop novel solutions to design problems [190]. If these efforts in ideation are focused on developing novel concepts for products with significantly-reduced environmental impacts, lower-impact designs may be achieved. One example of this is the design of the energy efficient passive cooling system in Eastgate Centre - a shopping center and office building in Zimbabwe - that was inspired by passive cooling in termite mounds [191]. The use of a passive cooling system resulted in a 50% reduction in energy consumption by the building compared to a similarly-sized office building with a standard air conditioner [192]. It is unlikely a redesign of a standard air conditioner involving product tweaks based on LCA results during detail design could arrive at a solution with such a significant environmental impact reduction.

11.2.5.2 Related Sections:

Section 9.1.1 on how it is difficult, if not impossible, to achieve sustainability by minimizing the low-level impact of products.

11.2.6 Avoid labelling designs ‘sustainable,’ ‘unsustainable,’ ‘high-impact,’ or ‘low- impact’.

In the old paradigm, designs are often considered ‘sustainable’ if they are ‘low- impact’ (or lower impact than functionally equivalent alternatives) and ‘unsustainable’ if they are ‘high-impact’ (or higher impact than functionally equivalent alternatives).

However, environmental impacts arise as result of a product and a context together (so designs by themselves cannot be ‘low-impact’ or ‘high-impact’). In addition, in the new

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paradigm, sustainability is viewed as an emergent property of a complex system, meaning it cannot be attributed to a single component in the system, such as a design.

11.2.6.1 Example:

For instance, designers should not claim ‘Our solar PV system design is low- impact’ or ‘Our solar PV system design is sustainable.’ Instead, statements regarding the environmental benefits of a design should be qualified and specific, more along the lines of: ‘Our solar PV system design is lower-impact than Company A’s solar PV system design in contexts where snowfall is less than one inch annually’ (perhaps because Company A’s panel involves a special energy- and chemical-intensive coating to promote snow removal, for instance.) The particular solar PV system design, like all PV system designs, is undoubtedly high-impact compared to other sources of electricity in locations where there is low solar insolation (in a cloudy region at high latitude, on a submarine that remains submerged in the deep sea most of the time, etc.), so it is not universally ‘low-impact.’

Also, while your design could be part of the road to a sustainable future (if it is used to help reduce GHG emissions from electricity and bring into balance the mass of GHGs going into and out of the atmosphere), it could also be part of the road to further unsustainability (if the production rate is too high, leaving the fleet in a net-energy negative (and net-GHG positive) space; if there are too many of the PV system design produced, causing resource shortages on earth (the world cannot sustainably support a billion 400MW solar PV farms, for instance); or if the systems are installed exclusively in ecologically sensitive locations, causing numerous extinctions.) These types of exceptions exist for all designs. Consequently, designs should not be labelled ‘sustainable,’ ‘unsustainable,’ ‘high-impact,’ or ‘low-impact.’ 224

11.2.6.2 Related Sections:

For a discussion of how context changes with time, so the lowest-impact option changes with time as well, see Section 6.1.1; on how biologists assess the environmental impact of organisms within a context, see Section 7.3.1.2; on applying biology-inspired context focused constructs of environmental impact to products, Section 7.3.2.; on how sustainability is not a design attribute, see Section 10.1.2; for a discussion of how sustainability is an emergent property of a complex system, see Section 10.3.1; on how designs cannot be sustainable because sustainability is an emergent property of a system, see Section 10.4.5.

11.2.7 Design products that benefit the environment.

Create designs that benefit the environment, not just designs that damage the environment less than alternatives. That is, maximize the ‘positive’ impacts of products (recognizing that the same impact can confer environmental benefits in some contexts and environmental damage in others), don’t just minimize the ‘negative’ impacts.

11.2.7.1 Example:

Designers could create, preserve, or reclaim microenvironments that can provide valuable habitat. For instance, artificial reefs can be constructed out of wrecked ships or waste dredged material [177], and urban wildlife refuges can be established on the sites of old landfills [178]. In addition, greenspaces in cities can be optimized to be maintenance- free (no need for herbicides, no lawn mower required), sequester maximum carbon

(through selection of plants that are carbon hogs and grow to varying heights to maximize the foliage density per square foot), remove maximum toxins in air (using a species mix that is ideal for air purification), and promote biodiversity (by using a diverse mix of rare 225

native plants), for instance. Alternatively, decorations for homes or offices could be made out of living plants and designed to create ambiance with minimal maintenance (low- watering through the use of cactus and succulents), while also sequestering carbon and purifying the air.

11.2.7.2 Related Sections:

See Section 10.2.2.2 on considering the benefit to society of the design.

11.2.8 Consider methods and approaches other than LCA to assess and reduce environmental impact.

Consider methods and approaches other than LCA to assess and reduce environmental impact, such as design for environment guidelines, industrial symbiosis, material flow analysis, environmental risk assessment, environmental impact assessment, and ecological impact assessment from biology.

11.2.8.1 Example:

Design for environment guidelines are preferable to LCA during conceptual design, as they can be used before data and knowledge about product details are available. Telenko et al. [155] present a compilation of design for environment guidelines and provide examples of how these guidelines can be used to develop new, lower-impact concepts for designs. In addition, O’Rourke and Seepersad [193] use design for environment guidelines to assess the relative impacts of nine designs and their functionally equivalent competitors. For example, the energy-efficient passive cooling system in Eastgate Centre was compared to a standard electric air conditioner for a similarly sized building using the guidelines. The environmental impact assessment using the guidelines allowed differences in the manner

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in which environmentally-related problems were solved in the two designs to be identified and compared without the need for large amounts of detailed data, as would be necessary in LCA.

11.2.8.2 Related Sections:

For a summary of the advantages of LCA and uses for LCA, see ‘LCA Basics’ Section 2.1.1; for challenges associated with implementing LCA, see Section 2.3; for network-related approaches to environmental assessment, see Chapter 4; for a discussion of how LCA is limited because it fails to account for context, see Section 5.5.3; for more on learning from other environmental impact measurement frameworks and how they account for context, see Chapter 7; for a discussion of quantity-related effects and how LCA does not account for quantity, see Section 9.2.4.1.

11.2.9 When identifying and assessing potential redesign avenues, consider the wider context surrounding a design, and model relevant interactions within the supply chain, economy, or physical environment, for instance.

Modeling the broader context surrounding a design helps account for systems-level effects and dynamic interactions that occur on a larger scale or in different parts of the environmental impact network than might otherwise be considered in an LCA. This approach to sustainable design is akin to greatly expanding the system boundary of an LCA. Consideration of the broader context can greatly affect the outcome deemed to be lowest-impact, with options such as eco-industrial parks only arising when the broader network is considered.

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11.2.9.1 Example:

For instance, Oberg et al. [140] analyzed a proposed sustainability initiative for a bread company in Northern Sweden that involved moving the company south to be closer to customers, reducing its transportation impacts.

Figure 18: Company-scale LCA of a bakery showing that transportation impacts would be reduced if the bakery moved south to be closer to customers.

While the move was shown to significantly reduce transportation impacts when the analysis was performed at the company level, consideration of the context on a broader scale revealed that the current method of transport is already relatively low-impact, due to a transportation imbalance in Sweden, where more goods are shipped north than are shipped south [140]. Consequently, the bread company’s proposed move would not result in significantly reduced environmental impact overall because the trucks that ship their bread would simply run empty on their return trip south [140], as shown in the figure below.

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Figure 19: Company-scale LCA with national-scale network analysis reveals a transportation imbalance in Sweden that would cause the proposed move of the bakery to have little overall environmental effect.

11.2.9.2 Related Sections:

For a discussion of network-related approaches to environmental assessment, see Chapter 4; for a discussion of how, in the current paradigm for sustainability, the reductionist approach is focused on minimizing human impact on small scales, see Section 8.3; for problems with the reductionist approach, see Chapter 9; for examples of environmental impact networks, see Section 9.2.2.3; for a discussion of how sustainability is not a collective property, see Section 10.1.1; and for a discussion of how environmental impact is a network, see Section 10.2.1.

11.2.10 Connect small-scale LCAs to larger-scale network models to account for systems-level effects.

Many insights can be gained if designers connect their detailed environmental impact models for designs developed in LCA to a broader network model. This is similar to hybrid LCA in that a process model is connected to a higher-scale model, but it is

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different in that this higher-level model is related to global energy and material flows, not national-level economic relationships, as is the case with input-output LCA.

11.2.10.1 Example:

Figure 20: Connect a detailed process LCA model to a generic network representing global energy and material flows. Image credits: Global model [194], process model [20].

11.2.10.2 Related Sections:

For more on systems-level effects, see Section 9.2, and specifically for examples demonstrating the importance of environmental network effects, Section 9.2.2.4; for a discussion of how environmental impact is a network, see Section 10.2.1.

11.2.11 Consider the likelihood that certain product scenarios will occur, and favor options for reducing impact that are within the designer’s control.

A smaller, certain reduction in impact may be preferable to a larger, uncertain reduction in some instances. Designers should consider the likelihood that certain product 230

scenarios will occur and favor environmental improvements that are guaranteed over those that are uncertain.

11.2.11.1 Example:

Designers often have significant control over the manufacturing impact of their companies’ products, but far less control of the use and end-of-life impacts. Consequently, designers may want to favor a proposed change that is guaranteed to make a modest reduction in manufacturing impact, over a change that might produce a more significant impact reduction during use if the designer’s assumptions about the use context ultimately prove true. For instance, consider the environmental tradeoffs that may occur in the design of a bracket that attaches a PV panel to a roof. Suppose these brackets will be used to install a fleet of 1 million PV panels. With a fleet of this size, the variability in the use context is significant. Certainly some of the 1 million panels will fail in high winds at some point in their 30 year expected lifetimes (some will be hit by hurricanes or tornados, for instance), and some of these failures may be attributed to the brackets. Failure of a PV panel in this way is likely catastrophic, resulting in the need for a full panel replacement and the loss of a significant amount of embedded GHG emissions (a 4kW solar PV panel was calculated to have approximately 6200 kg CO2-eq embedded GHG emissions in O’Rourke and Seepersad [89], also available in the appendix). The bracket designer must consider options for brackets that fall along a spectrum

– at some point, the bracket is so overdesigned that it will almost never fail (the roof or the PV panel itself will almost always fail first in high winds), and at another point the bracket is so underdesigned that it will almost always fail, even without wind (the bracket is made 231

of cardboard). When considering possible design options for brackets that fall along this spectrum, the designer ought to take into account the likelihood that wind at various speeds will occur in the lifetimes of some percentage of the panels. For instance, when considering whether to make the brackets thicker, use a stronger and more energy-intensive material for the brackets, or apply a corrosion-resistant coating to the brackets, designers should weigh the environmental impact changes associated with these interventions (e.g. increasing materials consumption, increasing energy during materials acquisition, and increased toxicity impacts, respectively) against the embedded emissions associated with the PV panels expected to be saved by this intervention. To weigh this tradeoff, designers must make models predicting where in the world the 1 million panels will ultimately be used and what the maximum expected wind speed over a 30 year period is in each of these locations, so that, for any bracket design, an estimate can be made of the number of panels that will be destroyed in high winds due to bracket failure.

Unfortunately, models of this type (weather models in the future and models of where future customers will choose to use their PV panels) contain a significant amount of uncertainty; many aspects of the product use context are outside the designer’s control and are difficult for the designer to predict. As a result, there will be a gray area where it will be unclear whether it is environmentally preferable for the brackets to be 1 mm thicker, for instance, increasing the material use slightly but decreasing the wind-related bracket failure rate slightly as well, or if the reverse is true. In these gray areas that result from the context- related uncertainty, it may be beneficial for designers to prefer those options that are within their control (such as manufacturing impact reductions) and are therefore guaranteed.

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11.2.11.2 Related Sections:

For a discussion of the difficulty in accounting for context in prospective LCA, given that contexts in the future are uncertain, see Section 5.4.

11.2.12 Identify environmentally favorable and unfavorable contexts for designs, and promote or discourage product adoption in these contexts accordingly.

Use the results of contextual analysis to identify environmentally favorable and unfavorable contexts for designs, and promote or discourage product adoption in these contexts accordingly. Environmental impact reductions may be achieved by advertising to consumers in beneficial contexts or by designing policies that encourage (or discourage) product use in environmentally favorable (or unfavorable) contexts.

11.2.12.1 Example:

For instance, contextual analysis could reveal areas of the world that are environmentally favorable for solar PV because they have both a high amount of solar insolation and a high GHG intensity of existing sources of electricity, and policies could be designed to incentivize solar PV adoption in those locations. Work from Siler-Evans et al. [87] does just that, estimating “the combined health, environmental, and climate benefits from wind or solar” and finding that these benefits differ for locations across the US by a factor of 10 as a result of the varying availability of sunlight or wind, as well as the type of marginal electricity emissions on the grid at the location of use. A graphic they developed of the human health benefits of solar PV throughout the US, accounting for both sunlight availability and type of avoided electricity on the grid is shown below. This type of study could be used to recommend the installation of PV panels (or develop policies to promote PV adoption) in favorable contexts, such as those that occur in Indiana and Ohio. 233

Figure 21: Performance of solar panels relative to annual health and environmental benefits from displaced SO2, NOx and PM2.5 emissions. “Sharp boundaries are due to the assumption that wind and solar only affect generators within the same eGRID subregion (i.e., imports and exports of electricity between regions are ignored). Monetary values are in 2010 dollars” [87].

11.2.12.2 Related Sections:

For more on how environmental impact and environmental damage are determined by contextual factors, see Chapter 5; for discussion of how and why LCAs typically fail to account for contextual factors, see Sections 5.5.1 and 5.5.2; for sensitivity studies of contextual factors, see Appendix A.5.

11.2.13 Identify contexts to focus on during redesign to minimize the impact of the entire product fleet.

Individual products in a fleet will each be used in different contexts, causing each to have different environmental impacts. Some of these contexts will be particularly 234

problematic, causing products in these contexts to disproportionately increase the environmental impact of the fleet. Designers should use the results of contextual analysis to identify these problematic contexts so that they can be the focus of redesign efforts.

11.2.13.1 Example:

If some percentage of PV panels in a fleet are expected to have unusually high environmental impacts (for instance, because they will be used in contexts with high winds where they will be damaged), it may be environmentally preferable to make a design change for all the products in the fleet to avoid the problem (by adding material to make the panel more durable). While this design change would likely increase the impact of the PV panel in the average context (the impact of the panel in the standard, low-wind context would be slightly higher because of the additional material needed to increase durability), the overall impact of the fleet when contextual effects are taken into account could, in some cases, be lower (if the increase in overall impact across the product fleet associated with the additional durability is less than the impact associated with replacing the panels that would otherwise have failed).

11.2.13.2 Related Sections:

For more on how environmental impact and environmental damage are determined by contextual factors, see Chapter 5; for two methods to use to visually depict the environmental impact scenarios analyzed, see 6.2.

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11.2.14 Consider segmenting the market and designing different products optimized to have low environmental impacts in different contexts.

If the results of the contextual analysis indicate wide variation in environmental impact in different contexts, consider segmenting the market and designing different products optimized to have low environmental impacts in different contexts.

11.2.14.1 Example:

For example, Telenko and Seepersad [73] used probabilistic graphical modeling to study contextual effects and found that lightweighting vehicles results in high energy savings in “Scenarios with large families… especially if the vehicle is used for commuting or stop-and-go traffic conditions.” However, “vehicles targeted at senior citizens, who typically drive shorter distances and do not commute, offer some of the least significant benefits from lightweighting and may benefit more from strategies, such as drag reduction, that exploit their usage conditions” [73]. This type of information could be used to generate two separate vehicle designs, one for each use context, optimized using the two different environmental impact reduction strategies – lightweighting and drag reduction.

11.2.14.2 Related Sections:

For more on how environmental impact and environmental damage are determined by contextual factors, see Chapter 5; for two methods to use to visually depict the environmental impact scenarios analyzed, see 6.2.

11.2.15 Redesign products to minimize the context sensitivity of environmental impact.

The sensitivity of a design’s environmental impact to contextual factors varies between different types of designs; some designs have environmental impacts that are

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highly context-sensitive, but other designs’ impacts are relatively robust to changes in contextual factors. By switching the bulk of a design’s environmental impact from one life cycle phase to another, or by adding certain types of design features, it may be easier to limit the context-sensitivity of a design’s environmental impact, allowing the designer to control the environmental impact more easily.

11.2.15.1 Example:

For example, Barroso and Holzle [195] discuss how server power usage and energy efficiency correspond to the utilization level of the servers. They note that even energy efficient servers are not very efficient at the low end of the typical operating region for servers, as shown in the figure below.

Figure 22: “Server power usage and energy efficiency at varying utilization levels, from idle to peak performance. Even an energy-efficient server still consumes about half its full power when doing virtually no work” [195].

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Consequently, they advocate designing energy-proportional servers, which have better efficiencies in the typical operating region, as depicted in the figure below. These energy-proportional servers would have less fluctuation in environmental impact due to contextual factors that affect total server utilization because their energy efficiency is less variable in the typical server operating range.

Figure 23: “Power usage and energy efficiency in a more energy-proportional server. This server has a power efficiency of more than 80 percent of its peak value for utilizations of 30 percent and above, with efficiency remaining above 50 percent for utilization levels as low as 10 percent” [195].

11.2.15.2 Related Sections:

For more on how environmental impact and environmental damage are determined by contextual factors, see Chapter 5; for discussion of how and why LCAs typically fail to account for contextual factors, see Sections 5.5.1 and 5.5.2.

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11.2.16 Consider how context might change over the life of the product, potentially amplifying or negating any anticipated environmental benefits.

When making decisions with ramifications that last for long periods of time, consider how context might change over the life of the product, potentially amplifying or negating any anticipated environmental benefits. This is in contrast to the current approach to sustainable design, where practitioners use a set of assumptions related to the present context.

11.2.16.1 Example:

Suppose a PV system designer is designing a residential PV system for a family and assessing the environmental benefits of this system compared to grid electricity over the life of the panel. Using the new framework for sustainable design, he or she might ask: If it is good for a household to get a solar panel now, will it still be good for it to have the panel in 5 or 10 years when the family is a different size and has different electricity demands? Will it still be good if the worst climate change scenarios in the household’s region occur, and sunlight availability decreases and/or the likelihood of high winds and severe storms that could damage the panel increases? Will it still be good if the electricity generation mix of the grid the home is connected to changes, altering the GHG intensity of avoided electricity? In contrast, a PV system designer using the old framework might ask simply: ‘Is it good for a household of a particular size with particular electricity demands to get a PV panel, given the sunlight availability in their home’s location and the current expected lifetime of the panel?’ without considering the possibility that this context could change over time.

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Along similar lines, suppose an LCA shows that a gasoline-powered vehicle’s low- level emissions do not pose a significant health risk currently, allowing the vehicle to be considered to generate roughly the same amount of environmental damage as an electric vehicle in a given location for a certain driving scenario. However, in 5 years, when the population of the rapidly-growing city where the vehicle is located has doubled, the effect of more vehicles on the road and longer drive times as a result of congestion may cause a large increase in emissions, resulting in significant health-related threshold concentrations to be surpassed. Although presently the type of vehicle (gasoline-powered or electric) matters little currently, in the future, it may be much better for the environment if the vehicle were electric.

11.2.16.2 Related Sections:

For a discussion of the difficulty in accounting for context in prospective LCA, given that contexts in the future are uncertain, see Section 5.4; for a discussion of how context changes with time, so the lowest-impact option changes with time as well, see Section 6.1.1.

11.3 ADVICE TO ECO-CONSCIOUS CONSUMERS

11.3.1 Avoid unnecessary consumption, even if it has a low per-unit impact.

Non-consumption, or conservation, is better for the environment than low-impact consumption. For every product for which there is a lower-impact option, it is important to remember that using no product at all is also a choice. When deciding what to conserve,

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eliminate those applications with a high impact per unit of the end function (rather than high impact per functional unit) first.

11.3.1.1 Example:

For instance, avoid unnecessary international work travel by using video conference calling instead. Avoid purchasing a car and instead walk, bike, bus, and use car-sharing service in the few instances where a car is really necessary. Reduce the temperature setting on your home’s thermostat and instead wear warmer clothes. Avoid the use of fertilizer, herbicides, and water by filling your garden with hearty native plants. Use a snow shovel instead of a snow blower. When choosing what to conserve, focus efforts on applications with a high impact per unit of the end function. For instance, a very high per unit impact for electricity may be acceptable if the electricity is used for a critical and beneficial purpose, such as powering a life support system in a hospital. In contrast, only a very low per-unit impact may be acceptable for electricity if the electricity is used for a frivolous purpose, such as decorative lighting; only a small amount of harm to humans and biodiversity is acceptable for an activity that results in only a small benefit. Consequently, conservation efforts should focus on the latter types of applications.

11.3.1.2 Related Sections:

For a discussion of quantity-related effects, underscoring the point that the total impact matters, see Section 9.2.4.1.; for a discussion of whether achieving sustainability requires a reduction in personal consumption, see Section 9.2.4.4.

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11.3.2 Focus on protesting, lobbying, changing company policies, and other, large- scale environmental efforts.

Focus on protesting, lobbying, changing company policies, and other, large-scale environmental efforts, rather than on minimizing personal consumption or striving for net- zero impact on a small scale. For an individual, an immense amount of effort must be put forth to achieve a slight impact reduction, with questionable environmental benefit overall. However, that same amount of effort could instead be invested in finding higher-scale solutions to environmental problems. These higher-scale solutions are more likely to confer environmental benefit because larger-scale analyses are more likely to be context-specific and account for systems-level effects.

11.3.2.1 Example: Problem #1: An eco-conscious consumer is concerned about waste generated from food packaging. He is especially concerned because he lives in an apartment complex that does not offer recycling. Old Paradigm: Using the reductionist New Paradigm: Using the new paradigm, approach from the old paradigm, this the eco-conscious consumer could instead consumer might focus on minimizing his focus his efforts on getting a recycling personal food packaging impact – by program started at his apartment complex driving his recyclables to the local – by starting a petition for residents to sign community center once a week, bringing in support of such a change, speaking to his personal ceramic mug to the coffee apartment management, and writing letters shop to avoid using a disposable cup, and to local government officials requesting buying bulk foods in minimal packaging policies to be put in place to mandate rather than pre-portioned, snack-sized recycling programs in housing complexes options, for instance. such as his, for instance.

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Problem #2: An eco-conscious consumer is concerned about wasting electricity. She is especially concerned because she lives on an island that gets a significant amount of electricity from diesel generators. Old Paradigm: Using the reductionist New Paradigm: Using the new paradigm, approach from the old paradigm, this the eco-conscious consumer could instead consumer might focus on minimizing her focus her efforts on a larger scale, spending personal electricity-related impact – by her time talking to local politicians and the drying dishes by hand instead of using the electric company about starting a solar PV ‘heated dry’ feature of her dishwasher, initiative in her area, planning pro-solar removing all ‘unnecessary’ lighting from demonstrations, and encouraging her local her house (Christmas lights, nightlights, elementary school to invest in a more the LED clock on her microwave), and energy-efficient air conditioner, for replacing her self-propelled corded electric instance. mower with a mechanical push mower.

In both examples, the efforts of the eco-conscious consumer using the reductionist approach from the old paradigm would be expected to reduce that individual’s impact. However, that same amount of time could instead be used to reduce many people’s impacts on a broader scale. While the benefits of working on a larger problem may be less obvious and less instantly gratifying, if successful, these efforts would make a more substantial difference to the environment.

11.3.2.2 Related Sections:

Section 9.1.2 on how it is difficult, if not impossible, to achieve sustainability by minimizing the low-level impact of individual consumption; Section 9.4 on how the reductionist approach misses an important avenue to achieving sustainability: implementing systems-level, structural changes; and Section 9.5 on how focusing on small- scale impacts may distract from opportunities for large-scale change.

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11.3.3 Focus eco-consumption and conservation efforts on occasions when the marginal environmental impact is larger than the average impact.

Marginal differences in environmental impact may be significantly larger or smaller than average impact per unit. Consequently, the same eco-consumption or conservation efforts may make a significant difference to the environment at some times and make far less of a difference at other times. As a result, eco-conscious consumers should concentrate their efforts at times when these efforts will be most effective at helping the environment, i.e. when the marginal environmental impact is larger than the average impact.

11.3.3.1 Example:

If a consumer conserves electricity when electricity from pulverized coal is on the margin and elects not to conserve when electricity from natural gas is on the margin, the environment is better off than if the reverse were true, even though the sacrifice on the part of the individual is the same. This is the case because the median life cycle emissions for electricity from pulverized coal are 820 grams carbon dioxide equivalent per kilowatt hour

(gCO2eq/kWh), whereas they are 490 gCO2eq/kWh for electricity from natural gas [196]. Consequently, when electricity from pulverized coal is on the margin, one kWh of electricity conserved results in 820 gCO2eq not emitted to the atmosphere, whereas when electricity from natural gas is on the margin, one kWh of electricity conserved result in only 490 gCO2eq avoided.

11.3.3.2 Related Sections:

For more on attributional vs. consequential LCA, see Section 2.2.2.

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11.3.4 Assess the extent to which the environmental impact of the product you are purchasing is context-dependent.

Ask yourself: ‘Will the environmental impact of this product change significantly in different contexts?’ If no, LCA results from a study of an average product for an average user in an average context likely adequately represent the environmental tradeoffs faced by any consumer, including you. If yes, a more detailed assessment of context is warranted.

11.3.4.1 Example:

For instance, for a given application, it is a safe bet that an LED lightbulb will be better for the environment than an incandescent bulb, as the efficiency of LEDs is much greater than incandescent bulbs, and the contextual effects that might alter the impact of either bulb during use are the same for bulb types. In contrast, having a solar PV panel on a house may be advisable in some cases but not advisable in many others, as the impact of PV panels are highly sensitive to contextual factors, such as sunlight availability at the location of use.

11.3.4.2 Related Sections:

For more on how environmental impact and environmental damage are determined by contextual factors, see Chapter 5.

11.3.5 Consider how your context may affect the product’s impact. Ask: ‘Is product A or product B better for the environment, given my needs and situation?’

If purchasing a context-sensitive product, consider how your context may affect the product’s impact. Don’t ask ‘Is product A or product B better for the environment?’ but instead: ‘Is product A or product B better for the environment, given my needs and situation?’ ‘Will this product’s impact be higher or lower in the likely context in which I 245

will use it?’ ‘Is the context in which I will use the product unusually sensitive to the impacts generated (because the location of use is home to an endangered species, near a childcare center, already heavily polluted, etc.)?’

11.3.5.1 Example: Questions eco-conscious Questions eco-conscious consumers ask in the new consumers asked in the old paradigm paradigm Is residential solar PV or Is residential solar PV or grid electricity better for me, grid electricity better for the given that I live on a sunny island near the equator that environment? gets its grid electricity from a diesel generator (or given that I live in a cloudy location far from the equator that gets its grid electricity from hydropower)? Are electric vehicles better Are electric vehicles better for the environment in my for the environment than community, which receives its electricity predominantly gasoline-powered vehicles? from coal, and for someone with my driving habits? Are paper or plastic Are paper or plastic shopping bags better for the shopping bags better for the environment, given that I need help carrying X cubic environment? units of groceries, and given that I would reuse any plastic bags and recycle any paper bags I take home?

11.3.5.2 Related Sections:

For more on how environmental impact and environmental damage are determined by contextual factors, see Chapter 5; for a discussion of how general LCA results are of limited use for individuals because usage and consumption patterns vary significantly, see 6.1.2; for a discussion on how the lowest-impact option is a function of both the product and the customer need, see Section 6.1.3; for an alternative ecology-inspired LCA framework, see Section 7.3.2; and for a discussion of the idea that sustainable products have no impact, a low impact, or a reduced impact, see Section 8.3.1.1.

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11.3.6 Consider how your pro-environmental behavior may affect your own consumption (and impact) via rebound effects.

Consider the impact of your pro-environmental behavior on your psychology and your pocketbook via rebound effects. When you buy a product with a low per-unit environmental impact, you may be prone to use more of that resource, resulting in a higher overall environmental impact, or use a higher-impact product elsewhere.

11.3.6.1 Example:

If you have a solar PV panel on your house, make sure that that knowledge is not leading you to be more carefree about wasting electricity or about having a greater environmental impact in other areas of your life, for instance, by driving more or flying frequently. If you buy a more energy efficient vehicle, make sure the money you are saving on fuel is not encouraging you to drive more, or is not being spent on other high-impact activities (e.g. on additional red meat or air travel).

11.3.6.2 Related Sections:

For a discussion of rebound effects, see Section 9.2.5.

11.3.7 Consider how your pro-environmental behavior may work with – or against – the pro-environmental behavior of others via collective effects.

Consider whether it is more worthwhile to engage in the same pro-environmental strategy as others, or whether it would be better for the environment for you to do something different. There are cases where many people need to engage in the same pro- environmental behavior together for environmental benefit to be achieved, and there are

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other cases where many people engaging in the same pro-environmental behavior together inadvertently increase everyone’s environmental impact.

11.3.7.1 Example:

Building a new bike trail can help reduce GHG emissions if many people who were previously commuting via car now take the trail, but it can increase global emissions levels if only a few people take the trail and the avoided car emissions do not offset the environmental impact associated with building the infrastructure of the trail in the first place [82]. Consequently, many people must switch from driving to biking to make the construction of a trail worthwhile. Conversely, if too many people in the same area install heat pumps that use “groundwater… as heat source during winter operation and heat sink during summer operation” for energy efficiency purposes, “the performances of other heat pumps installed in the neighborhood” could be negatively affected [174], i.e. too many people using the same pro-environmental strategy may lower the environmental benefit of each individual’s efforts.

11.3.7.2 Related Sections:

For a discussion of collective effects, see Section 9.2.7.

11.3.8 Be wary of environmental product claims. However, when the environmental tradeoffs of a product have been thoroughly studied by many different researchers, trust the results.

Be wary of environmental product claims. General LCA can provide only limited guidance to customers and may provide misleading results on topics where consumption patterns vary greatly amongst individuals. This is because LCA practitioners cannot

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anticipate all scenarios for all users. In addition, all LCAs are based on a wide range of subjective decisions, meaning their results are not objective and can be skewed by companies to defend decisions that may cause environmental harm. However, when the environmental tradeoffs of a product have been thoroughly studied by many different researchers, trust the results. In these types of cases, consumers have relative assurance that the environmental differences anticipated by nearly all analysts likely correspond to them and their context as well.

11.3.8.1 Example:

If a company advertises elaborate decorative lighting as ‘sustainable’ or as an ‘eco- design’ because it can be charged using an included solar PV panel, in addition to being plugged into a wall socket, question the claim. Ask: ‘Will the ‘environmentally friendly’ features of this product (the solar panels) generate enough environmental benefit in my context to be worthwhile (or do I live in a location with low solar insolation and low- emission grid electricity)?,’ and ‘Is this company advertising the potential for solar power to be used as a way to convince me that this product is eco-guilt-free and not a waste of electricity? Is non-consumption a better alternative?’ – for instance. However, if you are deciding between using a solar PV panel or a diesel generator to power a given application, it is a safe bet that solar PV is better for the environment. For most situations where both technologies are technically and financially feasible (i.e. there is a decent level of solar insolation at the location of use), the electricity coming from a PV panel is better for the environment than the electricity coming from a diesel generator. Although there are undoubtedly some far-flung exceptions, the massive number of LCAs

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using different models of impact, combinations of assumptions, and datasets that all arrive at the same conclusion speaks volumes.

11.3.8.1 Related Sections:

For a discussion on the subjectivity in LCA, see Section 2.3.1; for a discussion of how companies can use LCA defensively, see Section 2.3.2.3.

11.3.9 When available, use results from context-specific consequential LCAs to guide environmentally-motivated decisions.

11.3.9.1 Example:

Suppose you are an eco-consumer at the grocery store pondering your answer to the enduring question ‘paper or plastic?’ (Assume non-consumption is not possible because you have too many items to carry everything in your hands, you have forgotten your reusable bags at home, and you walked to the store so you cannot use a cart-trunk combo solution.) The advantages of a context-specific consequential LCA with wide system boundaries (as opposed to a general, attributional LCA) are that the following factors would be considered: (1) the volume of groceries you are purchasing on this shopping trip (as opposed to the ‘average’ amount of groceries, or simply considering the impact with respect to a small-scale functional unit that represents some volume of groceries, ex. plastic bags have 1 unit of impact per cm3 bag volume while paper bags have .999 units of impact per cm3, etc.), (2) whether and how you might reuse or recycle the bags (Do you use plastic bags as bathroom trash bags? Do you use them to clean up after your dog on walks? Do you use paper bags as wrapping paper? Do you recycle plastic or paper bags?), and (3)

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whether and how your choice will ripple up the supply chain (Will choosing paper ultimately increase the number of paper bags the grocery store orders in the future, or will it mean that the grocery store will run out of paper bags sooner, forcing other customers to use plastic?), for instance.

11.3.9.2 Related Sections:

For more on the distinction between attributional and consequential LCA, see

Section 2.2.2; for more on how environmental impact and environmental damage are determined by contextual factors, see Chapter 5; and for a discussion of how general LCA results are of limited use for individuals because usage and consumption patterns vary significantly, see 6.1.2.

11.4 ADVICE TO SUSTAINABLE DESIGN AND LCA RESEARCHERS

11.4.1 Develop tools and methods to generate models of environmental impact networks, analyze these models, and redesign these networks to achieve environmental goals.

Tools and methods could be developed to identify the most environmentally- optimal point in a network to place a new design or to identify alternate network configurations that are associated with lower amounts of waste. For instance, a method could be developed for connecting a model of the environmental impact of a design to a broader environmental impact network of resource sources, sinks, and flows. A tool could be created that would analyze the model and produce a layout of an alternate network with optimal placement of the design. This result could indicate where to source materials, where to send wastes, alternate uses of pollutants,

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etc., for the design. For example, a detailed model of the material and energy flows through a manufacturing facility could be connected to a broader network model of an industrial ecosystem. Then, an optimization tool could analyze the network and determine how material and energy flows should be re-routed to minimize waste overall (which companies should send which material and energy surpluses to which other companies). In addition, a tool could be made to optimize the network to generate minimal environmental disruption (where the total flow of all energy and materials on the network is minimized) or minimal environmental impact (where the change in the amount of resource depletion and resource accumulation at nodes is minimized).

11.4.1.1 Example:

In two papers, Bailey et al. [180][193] developed a method that is an initial step in this direction. Their method, called ecological input-output analysis, models physical flows in industry using the mathematics behind economic input-output analysis. The results are then connected to environmental objectives. They used their model to study material flows through the life cycle of a carpet, as shown in Figure 24, below. This figure illustrates the types of entities included in the model (materials and energy that make up the product, materials and energy that are used to manufacture the product, the product itself, and wastes) and the types of relationships included (the flow of energy and materials from one life cycle phase to the next, or out of the system altogether).

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Figure 24: Interface carpet flow analysis model. “Flows and processes with asterisks involve only… materials that are not primary inputs to the final product (in this case, carpet). For example, nylon and PVC are product materials, whereas water and natural gas are process materials” [180].

Bailey et al. [180] were able to use their model and analysis to draw conclusions about the environmental impact of different recycling options. Related techniques need to be developed that that are dynamic and allow for nonlinearities, for instance. Creating a related method using a modeling approach more like that described in Beyeler et al. [198] including stocks and changes in time, for instance, is one next step.

11.4.1.2 Related Sections:

For more on how environmental impact and environmental damage are determined by contextual factors, see Chapter 5.

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11.4.2 Develop tools and methods to minimize the context-sensitivity of the environmental impact of designs.

Products of the same design are often used in vastly different contexts, and the context in which a single product is used often changes over its lifetime. Consequently, minimizing the context-sensitivity of the environmental impact of designs is advantageous because it would allow designers to better predict and control these impacts. Efforts in this area may benefit from drawing from work in ‘design for robustness’ and ‘design for resiliency.’

11.4.2.1 Example:

For instance, researchers might apply ‘design for robustness’ approaches, focusing on making the environmental performance of designs ‘robust’ to external factors. Similarly, ‘design for resiliency’ methods may be adapted to make the environmental performance of designs ‘resilient’ to disruptions and long-term contextual changes. Alternatively, concept generation methods may be created to help designers identify potential design solutions that would reduce the context-sensitivity of environmental impact, such as including a battery on a grid with electricity supplied by a PV panel and a diesel generator (thereby reducing reliance on the diesel generator and causing the environmental impact of each unit of electricity to be less sensitive to short-term variations in sunlight availability).

11.4.2.2 Related Sections:

For more on how environmental impact and environmental damage are determined by contextual factors, see Chapter 5, specifically, for discussion of how and why LCAs

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typically fail to account for contextual factors, see Sections 5.5.1 and 5.5.2; for more on minimizing the context-sensitivity of designs’ environmental impacts, see Section 6.3.1.

11.4.3 Develop a method for screening contexts and matching designs with contexts to achieve environmental goals.

Develop a method for screening contexts for a particular design as ‘good’ or ‘bad’ for the environment based on past context-specific LCAs.

11.4.3.1 Example:

One such method applied to a design for a PV panel could entail: (1) brainstorming a wide range of contextual factors with theoretical support indicating that they might be important in determining environmental impact for the panel design, (2) conducting detailed LCAs for panels in many different contexts and/or using the detailed results of context-specific LCAs found in the literature, (3) testing to see which contextual factors – and combinations of contextual factors – have a large influence on the overall environmental impact (through regression, self-learning networks, etc.), and (4) determining justifiable “cutoff” points within each contextual factor to establish the borders of the different contexts. In this way, contexts can be grouped (put in bins) with others that are equally suitable for the product, so that region A and region B are identified as being equally beneficial for solar PV, but for very different reasons (region A has high solar insolation and moderate GHG intensity of grid electricity, while region B has moderate solar insolation and high GHG intensity of grid electricity.) These groupings could be made based on, for instance, the results of 100 context-specific LCAs used to train a network to

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predict whether the context in question is likely in an area of high, medium, or low impact for a particular design based on contextual factors, without needing to do an LCA. For instance, it is highly likely that the latitude and the number of sunny days a year at the location of use are both important contextual factors that affect the environmental performance of solar PV panels. However, other factors, such as being located on a major bird migration route (resulting in increased bird droppings on the panels) are unlikely to significantly influence the environmental impact. If the only two important contextual factors for solar PV were the ones mentioned above, researchers may be able to determine, for instance, that there are 3 meaningful groupings of latitude and sunny day contexts: (1) Latitudes within the tropics and more than 200 sunny days a year (corresponding to the best environmental performance); (2) Latitudes outside the tropics with more than 200 sunny days a year, and latitudes within the tropics with less than 200 sunny days a year (corresponding to moderate environmental performance); and (3) Latitudes outside the tropics with less than 200 sunny days a year (corresponding to poor environmental performance). Of course, this becomes far more complicated when there are 30 important contextual factors being analyzed, and when the cutoff points for each factor are not selected arbitrarily but are selected based on the environmental performance data from numerous context-specific LCAs.

11.4.3.2 Related Sections:

For more on how environmental impact and environmental damage are determined by contextual factors, see Chapter 5; for two methods to use to visually depict the environmental impact scenarios analyzed, see Section 6.2; for more on developing a method to group and screen contexts, see Section 6.3.2. 256

11.5 THE NEW APPROACH IN PRACTICE, COMPARED TO THE OLD APPROACH

This section summarizes the findings discussed above for LCA practitioners, sustainable designers, eco-conscious consumers, and researchers in sustainable design and LCA. The tables below compare the new framework presented here to the old framework for each of these groups.

11.5.1 Life Cycle Assessment

Table 3: Life Cycle Assessment – New Approach vs. Old Approach

# New Approach Old Approach Goal and Scope Definition 1 Consider consequential LCA. Use attributional LCA as default. 2 Consider hybrid LCA or process LCA Use process LCA as default. with network modeling. 3 Select the scale of analysis and the Select the scale of analysis and the functional unit to intentionally influence functional unit arbitrarily. the focus of the study and the aspects of the product/fleet/industry/economy that are modeled in detail. 4 When in doubt, select the highest Select the scale of analysis and the relevant scale of analysis and largest functional unit arbitrarily. relevant functional unit. 5 Focus on larger environmental problems Take the environmental problem as and perform LCAs on larger scales to given, and scope the study to fit within make better use of the time and time and resource constraints. resources necessary to do LCA right. Life Cycle Inventory Analysis 6 Conduct uncertainty analysis and/or Do not conduct uncertainty analysis or sensitivity analysis. sensitivity analysis because of time considerations and the possibility it will render the study inconclusive. 7 Conduct contextual analysis. Conduct the analysis using a set of assumptions corresponding to the average context and user.

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Table 3, cont.

Life Cycle Impact Assessment 8 Include assessment of damage to Select impact categories based on needs biodiversity. and interests. 9 Explicitly account for the positive Consider all human-caused aspects of some human-caused environmental impacts as damaging to environmental impacts. the environment. 10 Conduct contextual analysis, and avoid Do not consider how the same labelling impacts as ‘good’ or ‘bad’ for environmental impact could result in the environment. different levels of environmental damage in different contexts. Interpretation 11 Show your work, and emphasize the Emphasize the data gathered and environmental impact model and numerical results in LCA publications. assumptions in LCA publications.

11.5.2 Sustainable Design

Table 4: Sustainable Design – New Approach vs. Old Approach

# New Approach Old Approach The Objective 1 Work to balance the global Work to minimize the environmental environmental impact network, impact of small-scale products. minimizing waste and optimizing flows between entities. 2 Select the scale of the entity to design Take the entity to be designed or intentionally, with the awareness that redesigned as given. the choice will influence the types of design solutions developed. 3 Focus on designing big, high-level Take the focus of the sustainable design systems to make better use of the time project as given. This often involves and resources necessary to do minimizing the impact of low-level sustainable design right. designs. 4 Ask big-picture, fundamental questions Take the focus of the sustainable design that challenge the proposed focus of the project as given. sustainable design project, and adjust the scope accordingly. 258

Table 4, cont.

5 Generate novel concepts for products Incrementally redesign products, with significantly-reduced impacts slightly decreasing impact with each using alternate ideation techniques iteration, using LCA during detail during conceptual design. design. 6 Avoid labelling designs ‘sustainable’ or Refer to designs with low ‘unsustainable.’ environmental impacts (or lower impact than functionally equivalent alternatives) as ‘sustainable’. 7 Design products that benefit the Design products that damage the environment. environment less than alternatives. Methods and Approaches 8 Consider methods and approaches other Use LCA to assess the environmental than LCA to assess and reduce impact of designs. environmental impact. 9 When identifying and assessing Adopt a reductionist approach and potential redesign avenues, consider the model environmental impact on a small wider context surrounding a design, and scale using attributional LCA, honing in model relevant interactions within the on specific aspects of the design itself. supply chain, economy, or physical environment, for instance. 10 Connect small-scale LCAs to larger- Limit the scope of sustainable design scale network models to account for projects, and do not account for the systems-level effects. possibility of systems-level effects. Context 11 Consider the likelihood that certain Do not consider whether options for product scenarios will occur, and favor reducing impact are within the options for reducing impact that are designers’ control. Favor options that within the designers’ control. are associated with the greatest reduction in impact, regardless of the consistency with which those reductions are likely to occur. 12 Identify environmentally favorable and Take the context for a design as given, unfavorable contexts for designs, and and design the lowest-impact product promote or discourage product adoption for this context. in these contexts accordingly. 13 Identify contexts to focus on during Design the lowest-impact product for an redesign to minimize the impact of the average context; don’t design a product entire product fleet. fleet for an extreme context. 259

Table 4, cont.

14 Consider segmenting the market and Design one low-impact product for an designing different products optimized assumed context. to have low environmental impacts in different contexts. 15 Redesign products to minimize the Do not consider the context sensitivity context sensitivity of environmental of environmental impact. impact. 16 Consider how context might change Use a set of assumptions related to one over the life of the product, potentially specific context, and do not account for amplifying or negating any anticipated change in context over time. environmental benefits.

11.5.3 Eco-conscious Consumers

Table 5: Eco-conscious Consumers – New Approach vs. Old Approach

# New Approach Old Approach Where to Focus Efforts 1 Avoid unnecessary consumption, even Focus on consuming ‘sustainable’ if it has a low per-unit impact. products with a low per-unit impact. 2 Focus on protesting, lobbying, changing Strive to be an eco-perfectionist. Buy company policies, and other, large-scale only ‘sustainable’ products. Work to environmental efforts. make your personal environmental impact net-zero. 3 Focus eco-consumption and Eco-consume whenever possible. conservation efforts on occasions when the marginal environmental impact is larger than the average impact. Context 4 Assess the extent to which the Do not consider how the environmental environmental impact of the product impact of products might vary with you are purchasing is context- context. dependent. 5 Consider how your context may affect Do not consider how the environmental the product’s impact. Ask: ‘Is product A impact of products might vary with or product B better for the environment, context. Ask: ‘Is product A or product B given my needs and situation?’ better for the environment?’ 260

Table 5, cont.

Systems-Level Effects 6 Consider how your pro-environmental Focus on engaging in pro- behavior may affect your own environmental behavior, and do not consumption (and impact) via rebound consider systems-level effects. effects. 7 Consider how your pro-environmental Focus on engaging in pro- behavior may work with – or against – environmental behavior, and do not the pro-environmental behavior of consider systems-level effects. others via collective effects. Finding Good Information 8 Be wary of environmental product Focus on purchasing products that make claims. However, when the environmental claims. environmental tradeoffs of a product have been thoroughly studied by many different researchers, trust the results. 9 When available, use results from Follow guidelines for ‘sustainable’ context-specific consequential LCAs to technologies and behaviors, often based guide environmentally-motivated on attributional LCAs for average decisions. contexts.

11.5.4 Sustainable Design and LCA Researchers

Table 6: Sustainable Design and LCA Researchers – New Approach vs. Old Approach

# New Approach Old Approach 1 Develop tools and methods to generate Focus on minimizing the impact of the models of environmental impact design itself, not on matching a design networks, analyze these models, and to a context. redesign these networks to achieve environmental goals. 2 Develop tools and methods to minimize Do not attempt to minimize the context- the context-sensitivity of the sensitivity of environmental impact. environmental impact of designs. 3 Develop a method for screening Do not consider context-sensitivity of contexts and matching designs with environmental impact, or consider only contexts to achieve environmental a few scenarios. goals. 261

11.6 SUSTAINABILITY STRATEGIES FOR DESIGNERS IN OLD AND NEW PARADIGMS

The table below compares the sustainability strategies (with examples) sustainable designers typically use in the old paradigm with those available in the new paradigm presented in this work. Here, in addition to minimizing small-scale impacts of products, sustainable designers can work to find a low-impact context in which to place a given product, to maximize positive environmental impacts, and to redesign large-scale environmental impact networks.

Table 7: Comparison of strategies in the old and new paradigm for sustainability that designers can use to restore balance in global material and energy flow networks that are consistently out of balance.

Sustainability Strategies (with Examples) Old Paradigm New Paradigm Minimize Small-Scale Impact  Use energy-efficient manufacturing  Use energy efficient transport (trains over trucks) X X  Run manufacturing equipment on electricity from PV  Avoid chemical X  Recycle Find Right Context for Product  Study contextual factors for PV and install PV X in some locations but not others Maximize Good Impacts  Design a carbon sequestration project X  Design endangered species habitat protection Redesign Networks for Efficiency  Grid redesign X  Industrial ecopark design including a manufacturing company

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11.7 FLOWCHART SUMMARIZING THE NEW SUSTAINABLE DESIGN PROCESS

The findings in this work related to sustainable design pertain to different strategies for sustainable design, as discussed above. Figure 25, below, presents a flowchart for the sustainable design process based on these findings and strategies. First, sustainable designers identify the environmental problem or problems of concern they want their designs to address, such as climate change, fossil fuel depletion, and human health hazards caused by toxic chemicals.

Next, the energy and material flows that need to be maintained or balanced to address this environmental problem are identified. For instance, atmospheric GHG levels need to be stabilized to prevent climate change; the consumption and supply of fossil fuels globally need to be brought into balance to prevent resource depletion; and the concentration of a chemical that causes health problems for humans needs to be maintained at a level below or equal to the no-effect threshold. For each flow, ask: ‘Is the flow balanced?’ or, in other words, ‘Is the state of the system consistently in balance or out of balance one way or the other? If the system is consistent, it is possible to chart the pathway forward for sustainable designers more clearly. If not, further assessment is required.

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Figure 25: Flowchart summarizing the sustainable design approach presented in this work.

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First, there are cases where the energy and material flows are already in balance. For instance, assume the global logging industry initiated a new and highly effective environmental program that managed to keep the flow of wood in balance from the global supply of land for logging. For a given amount of land, lumber is harvested at the same rate it is grown so the availability of the resource in the future is assured. In this case, the lumber-availability-related impacts of the logging company would be in a balanced state, i.e. the amount of lumber available as a resource would not be decreasing with time. From a net environmental impact perspective, things are great, and the system is already in a balanced state. In this type of case, the goal of a sustainable designer would be, as in the current paradigm of sustainability, to reduce total flows in the system. That is, it would be to reduce the total amount of lumber demanded, or the amount of land that the trees need to grow, to increase the amount of land that is left as wilderness and make headway towards improving things on a total environmental impact perspective.

Second, there are cases where the system is sometimes balanced, sometimes unbalanced one way, and sometimes unbalanced the other way. In these cases it is not universally clear if more of the flow is better, worse, or neutral for the environment. Consequently, a contextual analysis should be completed to better understand the specifics of the case. For instance, emissions of a particular chemical harmful to humans in high concentrations may be very damaging to the environment if they are released in an area with already-high concentrations and a large human population, but they will not generate any environmental damage if they are released in an area producing very low concentrations that are below the no-effect threshold, in areas where no humans live.

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Finally, there are cases that are consistently out of balance. Consider the case of GHG emissions. Currently, the earth is in a state where the atmosphere has an excess of GHG emissions. This has been the case for many years, and will continue to be the case for many years to come, i.e. it is ‘never’ the case that the system is in balance. This imbalance is consistently true for every location and instance on earth, as all of earth is affected by GHGs emitted anywhere on the planet. Consequently, it is true that any GHG emissions are associated with environmental damage (the consistency and the global nature of the imbalance preclude the need to do a contextual analysis of the type described in LCA

#10), and it is safe to focus efforts on reducing GHG emission. For these types of problems, where the energy and material flows are out of balance in a consistent way, there are a few options sustainable designers have at their disposal. If the imbalance is due to resource accumulation (as with GHGs accumulating in the atmosphere), designers can work to remove the excess (by creating designs that sequester

GHGs) or redesign existing products to have reduced inputs of the resource (redesigning products to have reduced GHG emissions). However, if the imbalance is due to resource depletion (such as the depletion of fossil fuels), designers can work to add to depleted stores by creating designs that generate more of that resource (create designs that generate biofuels, for instance), or they can redesign existing products to reduce their consumption of that resource (and conserve fossil fuels). This boils down to either maximizing positive environmental impacts, for instance, through the creation of a design where the function of the design is to produce the desired impact, or minimizing negative environmental impacts of a design. In either case, designers

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ought to do context-specific analysis at this point, model the broader network, consider systems effects, and do as high a scale of analysis as possible. If one is taking the path of minimizing negative impacts, it is best to conserve (not consume at all), and it is second-best to increase efficiency.

11.8 CONCLUSION

This chapter provided a summary of practical advice to LCA practitioners, sustainable designers, eco-consumers, and researchers, with examples, based on the new paradigm presented in Chapter 10. This is a synthesis of the findings from all previous sections. The next chapter concludes, summarizing the topics addressed in this document, the major contributions of this work, and opportunities for future work.

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Chapter 12: Conclusion

This chapter provides an overview of this work, summarizes the major contributions, discusses opportunities for future work based on this research, and concludes.

12.1 SUMMARY OF DISSERTATION

12.1.1 Introduction and Literature Review

Chapter 1 introduced and outlined this work. Chapter 2 provided an overview of LCA, various approaches to LCA, and challenges associated with implementing LCA. Chapter 3 discussed how the scale of analysis and choice of system boundaries affects the focus and results of LCAs. Chapter 4 provided an overview of five existing approaches to reducing the environmental impact of designs that use network-related concepts.

12.1.2 Context in LCA and Sustainable Design

Chapter 5 addressed context and its effect on the environmental impact of products and the environmental damage caused by certain types of impacts. Chapter 6 discussed the implications of context-generated differences in environmental impact and what this means for LCA practitioners and individuals using LCA results to make more environmentally- friendly decisions. Chapter 7 provided an overview of some environmental impact measurement frameworks besides LCA and presented a new LCA framework inspired by biological constructs of ‘environmental impact’ that better accounts for contextual effects.

12.1.3 The Current, Reductionist Paradigm for Sustainability

Chapter 8 discussed common themes regarding environmental sustainability and environmental impact to outline the collection of ideas that encompass the existing 268

environmental sustainability paradigm. Chapter 9 explained the mechanisms by which the reductionist approach to sustainability fails and by which these emergent sustainability- related properties arise.

12.1.4 The New Paradigm for Sustainability and Practical Recommendations

Chapter 10 presented a new paradigm for sustainability. Chapter 11 summarized the findings of the dissertation in a list of recommendations based on the new paradigm to

LCA practitioners, sustainable product designers, eco-conscious consumers, and LCA and sustainable design researchers, with examples of how these recommendations can be applied in practice.

12.2 MAJOR CONTRIBUTIONS

This work critically examined the existing paradigm for sustainability in light of a number of serious problems that undermine efforts to address environmental issues via sustainable design. Specifically, it addressed the context-dependency of environmental impact and damage, and the scale-dependency of LCA results. The major contributions of this work are: 1. A new paradigm for environmental sustainability and environmental impact, presented in Chapter 10, that addresses the problems with the current, reductionist

paradigm. 2. A set of practical recommendations for LCA practitioners, sustainable designers, eco-conscious consumers, and LCA and sustainable design researchers based on

this new paradigm, provided in Chapter 11. 3. Sustainable design and LCA frameworks and methods, including:

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a. A new method for visualizing environmental impact that depicts the effect of contextual factors, discussed in Chapter 6, b. A new LCA framework inspired by biological constructs of environmental impact that better accounts for contextual effects, presented in Chapter 7, and c. A new method for conducting hybrid LCA using a generalized, global

network model of energy and materials on earth, outlined in Section 11.4.1.

12.3 THE VALUE OF THE NEW PARADIGM AND WHAT SUCCESS LOOKS LIKE

In the previous paradigm, numerous products that pose serious environmental problems were incorrectly identified as being ‘sustainable’. For instance, a design for a building might be deemed ‘sustainable’ if it has triple pane windows rather than single pane windows, due to the expected increase in energy efficiency. However, the overall energy consumption of the building may, in fact, increase as a result of the rebound effect.

This may occur, for example, if designers opt to include more windows in the design than they otherwise would in response to the increase in energy efficiency of the triple pane window over the single pane window. The new paradigm presented in this work is an improvement from the previous one because it has greater explanatory power and helps designers, LCA practitioners, and eco- consumers better avoid these failures in conventional analysis. Within the new paradigm, there are fewer observational outliers (designs that should be ‘sustainable’ according to the paradigm, but are harmful to the environment and vice-versa). This new paradigm consequently has more instrumental value for designers, LCA practitioners, and eco- conscious consumers; it is a better guide for these actors and will help them arrive at better 270

choices for the environment by avoiding the sustainable design failures discussed throughout this work. For instance, in the case of the building design discussed above, thinking in terms of the new paradigm may prompt designers to assess the environmental impact of the building on a systems scale. Doing so may help designers identify the possibility of the rebound effect and the potential for an overall increase in energy consumption in response to the use of more energy-efficient, triple pane windows.

Success in this new paradigm relates to the paradigm being useful – helping designers, LCA practitioners, and eco-conscious consumers avoid thorny problems that could lead them to make recommendations using the old paradigm that are ultimately environmentally harmful (such as unwittingly favoring designs with small environmental impact on small scales, but increased impact on larger scales due to the rebound effect). Consequently, success in this new paradigm involves changing the way people frame environmental problems and helping them achieve design and decision outcomes for the environment. Success is also achieved if people use this new paradigm to address environmental problems using strategies that might not otherwise be considered. For instance, as depicted in the flowchart presented in Figure 25, the new paradigm points to new directions in the sustainable design research space that have been neglected: maximizing positive environmental impacts, considering context and systems-level effects, and designing systems-level solutions to environmental problems via network modeling.

12.4 FUTURE WORK

Numerous avenues for future work exist based on this research.

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First, it would be valuable to generate specific and practical environmental impact modeling approaches based on concepts discussed in Chapter 10 using existing work in complex systems. This would involve describing environmental impact networks in terms of complex systems phenomena and terminology, developing the mathematical foundation for understanding environmental sustainability as a network effect or emergent property of a complex system, and generating modeling methods that allow for the reengineering of environmental impact networks and the creation of industrial ecosystems. Second, future work also includes developing design tools and methods along the lines of those presented in Sections 6.3 and 11.4 aimed at (1) generating models of environmental impact networks, analyzing these models, and redesigning these networks to achieve environmental goals; (2) minimizing the context-sensitivity of the environmental impact of designs so that designers can better predict and control the environmental impact of products; and (3) screening contexts for a particular design as

‘good’ or ‘bad’ for the environment based on past context-specific LCAs and matching designs with contexts to achieve environmental goals. More specifically, a software tool could be developed and used by researchers, undergraduate students, or others to perform a hybrid LCA with network modeling of the sort discussed in Sections 11.1.2, 11.2.10, and 11.4.1. This would entail the development of a background flow model with nodes and edges that represents the major material and energy flows on earth in a relatively static manner. This model could initially be very generalized and simplistic. It could then be made more detailed as data is acquired and more complicated relationships between smaller-scale entities are captured. The model could eventually be structured hierarchically, relating high-level impacts to low-level 272

impacts. This model would then be attached to a process LCA model that details the flows of energy and material inputs to the system of interest to analysts (including materials used to build the product, electricity used to run manufacturing equipment, emissions from the product, and waste materials at the end-of-life). Input and output flows from the process LCA would connect to nodes from the broader, generalized network (with flows of materials used to make a product connecting to nodes representing general natural resource stores, specific mines, or sources of recycled materials; or with the flow of electricity used to run manufacturing equipment connected to a node that represents global electricity generation, generation on a particular electric grid, or generation from a particular electric generator, for instance). Once constructed, tool users would input information related to their specific process LCA and the origins of materials used in their product, as well as the fate of the emissions and other waste products in their product (i.e. identifying the nodes in the more general model to which product energy and material flows should attach). Users should also input information about the broader context – the expected fleet size, for instance. Then, the model could be run to see how that particular design is likely to affect the stores of energy and material resources, as well as the level of waste, at different nodes over time. Finally, future work could involve making the recommendations presented in

Chapter 11 more accessible to sustainable designers and undergraduate engineering students learning sustainable design methods. For instance, a set of cards could be made listing each recommendation and a related example to stimulate thinking on different sustainability-related issues. Designers could be encouraged to develop at least one concept during brainstorming for each card. In addition, for sustainable design #2 – Select the scale 273

of the entity to design intentionally, with the awareness that the choice will influence the types of design solutions developed – designers could use the basic framework of the mindmap shown in Figure 17 to encourage the development of sustainable design concepts on the product scale, fleet scale, company scale, and inter-company scale.

12.5 CONCLUDING REMARKS

Sustainability occurs when the system of energy and material flows on earth is in balance in a state that provides ample habitat and resources for humans and a wide range of other organisms. The idea – widely accepted by sustainable designers, eco-consumers, LCA practitioners, and researchers – that this type of sustainability can be achieved by reducing the environmental impact of small-scale human activities is misleading. Instead, as discussed in Chapter 9, reductionism and the minimization of environmental impact on small scales may ultimately lead to increases of environmental impact on larger scales via systems-level effects.

In addition, working to minimize environmental impact on small scales comes with an opportunity cost. For designers, time spent tweaking product designs to slightly reduce impact (e.g. redesigning incandescent light bulbs to use slightly less glass) is time not spent reducing the impact of large-scale infrastructure (redesigning the electric grid to accept larger inputs of solar and wind power) or developing novel concepts for products with huge environmental impact reductions (designing/inventing the LED or other disruptive, low- impact technology). Similarly, for eco-conscious consumers, time spent determining whether paper or plastic is lower-impact, or whether it is better to drive recyclables to a faraway recycling center or to throw them away for nearby disposal, is time not spent on

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fighting for the EPA to ban pesticides that harm brain development, or time not spent campaigning for a political candidate who supports carbon legislation. Finally, the idea that sustainability is achieved through the reduction of human impact is not the whole story. Yes, it is important to reduce absolute human impact globally to some threshold (it cannot be ideal for humans to constantly disturb all ecosystems on the planet: surely, having some relatively unaffected areas is good). However, a more important consideration is the net environmental impact (or the change in the environment – the accumulation of wastes and pollutants, and the depletion of resources), regardless of whether this change is caused by humans or not. High net environmental impacts on a global scale destabilize ecosystems, threatening all forms of life on earth, including humans. Consequently, the goal of sustainable design should be to minimize net environmental impacts and balance energy and material flows on earth. This work has made headway towards identifying problems in sustainable design and LCA related to the current, reductionist paradigm of environmental sustainability. It has presented a new paradigm that helps address and avoid these problems, along with practical advice for LCA practitioners, sustainable designers, eco-conscious consumers, and researchers. It is hoped that the findings of this work will help guide those working in the field in their efforts to protect the environment, helping them invest their time more wisely and achieve greater progress towards environmental goals.

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Appendix: The Importance of Contextual Factors in Determining the Greenhouse Gas Emission Impacts of Solar Photovoltaic Systems1

A.1 ABSTRACT

Small-scale residential solar photovoltaic (PV) systems are becoming increasingly common. In some cases, governments or individual homeowners promote PV technology because of concerns about climate change and a desire to reduce global greenhouse gas emissions (GHGs). While solar PV directly emits no GHGs during use, the panels are associated with a significant amount of embedded GHG emissions, resulting from the manufacturing of the panels, for instance. A review of relevant literature reveals that the life cycle GHG emissions of solar PV panels are significantly influenced by contextual factors, such as the location of the panels during use. The purpose of this paper is to illustrate the many ways context could affect the GHG emissions associated with solar PV systems and to demonstrate – via calculations from a simple analytical model – the potential magnitude of the GHG emissions differences associated with using PV panels in different contexts.

A.2 INTRODUCTION

Given the rising atmospheric concentrations of greenhouse gases (GHGs) and the potentially catastrophic effect they may have on the climate, low-GHG emitting energy technologies are needed. Displacing electricity generation from fossil fuels by increasing

1 J. M. O’Rourke and C. C. Seepersad, “The Importance of Contextual Factors in Determining the Greenhouse Gas Emission Impacts of Solar Photovoltaic Systems,” in ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2015, DETC2015-46471.

J.M. O’Rourke conducted the literature review, performed the analysis, and wrote this paper. C.C. Seepersad advised this research and provided feedback on the writing of this paper. 276

generation from low-emitting renewable sources is a key approach for reducing GHG emissions and mitigating climate change. Within this context, solar photovoltaics (PV) are promising; they have no direct GHGs emissions during use and have the additional benefit of consuming free solar energy. While researchers agree that solar PV emits fewer GHGs than many competing electricity generation technologies, such as coal-fired generation, questions remain regarding the effect of context on the overall GHG emission impacts of solar panels. The purpose of this paper is to illustrate the many ways context could affect the GHG emissions associated with solar PV systems and to demonstrate – via calculations from a simple analytical model – the potential magnitude of GHG emissions differences associated with using the panel in different contexts. First, this paper presents the background and motivation for this work, detailing the sources of GHG emissions and avoided emissions over the life of a PV panel, as well as discussing the significant variability – and causes of this variability – in GHG intensity estimates for solar PV. Section A.3 identifies and examines a number of important contextual factors that could lead to this variability in GHG intensity. Finally, Section A.4 applies a simple model of residential solar PV GHG emissions to investigate the sensitivity of emissions to solar insolation during use, type of electricity avoided, and the timing of household load. Throughout this paper, the phrase ‘embedded GHG emissions’ is used to refer to the GHG emissions associated with a solar panel itself that are emitted throughout its life cycle as a result of manufacture, transport, and recycling, for instance. Similarly, ‘avoided GHG emissions’ refers to GHGs that are never emitted as a result of the PV panel, such as 277

those from displaced grid electricity; ‘net GHG emissions’, to the difference between the embedded and avoided GHG emissions over the life of the solar panel; and ‘GHG intensity’, to the embedded GHG emissions divided by the total electricity production from the PV panel over the course of its lifetime.

A.3 BACKGROUND AND MOTIVATION

A.3.1 Basics of Life Cycle GHG Emissions for Solar PV

This section provides a brief overview of the factors that affect the GHG emissions balance of solar PV. Materials extraction, manufacturing, and transport of PV panels all cause the release of GHGs, due to either the burning of fuels in these stages or to the consumption of electricity. Specifically, materials extraction and manufacturing have been estimated to be responsible for 71.3% of all GHG emissions associated with PV panels [199]. During use, solar PV systems do not directly emit GHGs; however they do have small quantities of indirect emissions associated with cleaning, preventative maintenance, and replacement of damaged parts [185][199][200]. In addition, there may be significant avoided emissions during use if, for instance, electricity generated by the panel replaces electricity that would have otherwise been supplied by a diesel generator. At a solar panel’s end-of-life, it can meet one of three potential fates: (1) burial in a landfill, (2) incineration in a municipal waste plant, or (3) recycling. Each of these options is likely associated with small volumes of GHG emissions due to land use change or electricity consumption at the disposal facility. In addition, end-of-life may also be

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associated with avoided GHG emissions if, for instance, recycled materials are put to use in another product.

A.3.2 Variation in GHG Intensity Estimates

Multitudes of GHG intensity estimates for solar PV technology are available in the literature. However, the results of these studies vary significantly. For instance, Nugent and Sovacool [199] conducted a review of 23 studies that contained 57 estimates of GHG intensity for different types of solar PV panels in different conditions. The estimates they considered ranged from 1 gram of carbon dioxide equivalent per kWh electricity produced by the PV panel (gCO2eq/kWh), which corresponds to systems manufactured without F- gasses using electricity exclusively from renewable sources, to 218 gCO2eq/kWh, for panels produced with F-gases using electricity from coal, with an average value of 49.9 gCO2eq/kWh [199]. Significant variability in GHG intensity estimates has also been found in a number of other meta-analyses of solar PV life cycle assessments (LCAs), including those from Hsu et al. [185], the United States’ (US) National Renewable Energy Laboratory (NREL) [86], Sherwani et al. [201], and Kim et al. [184]. Variation in GHG intensity estimates for electricity from solar PV can be attributed to a wide range of technical, methodological, and contextual factors. Differences between these three types of factors are discussed in the corresponding sections below.

A.3.2.1 Technological Factors

Technological factors that influence GHG emissions intensity include: (1) the type of solar PV used (mono-crystalline, thin film, etc.); (2) type of mounting (fixed, single-axis tracking, etc.); (3) module efficiency, “the percentage of… solar energy converted to direct

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current [DC] electricity by the module” [185]; and (4) the performance ratio, “the ratio of… alternating current [AC] electricity actually produced by the PV system, after accounting for system losses, to the electricity calculated based on the DC-rated module efficiency and irradiation” [185]. In response to the variability in GHG intensity caused by technical factors, a number of authors provide separate estimates for different technologies or different sets of technical assumptions. For instance, Sherwani et al. [201] analyzed 19 GHG intensity estimates for amorphous, mono-crystalline, and poly-crystalline solar cells and found that the estimates ranged from 15.6–50, 44–280 and 9.4-104 gCO2/kWh, respectively. While this approach may be able to provide some insight into the relative GHG intensity effects of different technological alternatives, the large GHG ranges in the results from Sherwani et al. and others who have conducted similar studies indicate that many other factors also have a significant role to play in determining GHG intensity.

A.3.2.2 Methodological Factors

It is well-known that LCA results are dependent on the methods, data, and assumptions used in the study. The choice of functional unit, system boundaries, and values used to weigh the tradeoffs between different types of environmental impacts all could significantly alter an LCA [5][31]. Zhai and Williams [202] present calculations for the GHG intensity of a multi-Si PV system, using both a process LCA (a bottom-up LCA method where material and energy inputs and outputs are quantified in all stages of the product life cycle) as well as a hybrid LCA (which includes economic input-output data in addition to process information). They estimate the system embodies 24 g of carbon/kWh using the process method, but 32 g of carbon/kWh using the hybrid method. Hence, this 280

study demonstrates the significant impact that the choice of LCA method can have on the final results. Like technological factors, methodological factors are within the control of designer conducting the LCA, and they have the power to significantly influence the GHG intensity estimates. However, unlike technological factors, methodological factors have no effect on the real-world GHG intensity of solar PV panels; the actual effect of a solar PV panel on the climate has absolutely nothing to do with the LCA method, assumptions, or data used to develop the GHG estimate. Consequently, methodological factors help to explain variability in GHG intensity estimates, but the variability caused by these factors does not transfer to the real world.

A.3.2.3 Contextual Factors

In contrast, contextual factors have the power to generate significant differences in real-world GHG intensities, and they are outside of the designer’s direct control - as they are driven by the location of manufacture, location of use, and personal inclinations of the PV system owner, for instance. Understanding the effect of different contextual factors on real-world GHG intensity is critical to being able to design solar PV systems and policies to take advantage of favorable contexts and to get an accurate estimation of how the adoption of solar PV will likely affect the climate. Numerous studies [86][184][185] control for contextual factors or ‘harmonize’ GHG intensity estimates by rerunning calculations using a standard set of assumptions related to solar insolation and system lifetime, for instance. However, few studies, if any, have estimated the significant real- world variability in the GHG intensity of electricity from solar PV that arises as a result of different contextual factors. The remainder of this paper is devoted to taking the initial 281

steps to making such estimates by identifying and analyzing contextual factors that may significantly influence the GHG intensity of solar PV systems and modeling their effects in different contexts.

A.4 IDENTIFYING CONTEXTUAL FACTORS THAT AFFECT THE GHG EMISSION IMPACT OF SOLAR PV

This section identifies and examines a number of contextual factors that could significantly affect the ultimate environmental impact of solar PV panels in each life cycle stage.

A.4.1 Materials Extraction

GHG emissions impacts associated with materials extraction and processing are likely to be highly dependent on the location where extraction takes place, due to the differences in the energy mix used to run extraction equipment and differences in environmental laws in that location. One would expect, for instance, that the processing of silica sand into glass would have much greater GHG emissions in countries that obtain a high percentage of their electricity from coal, as opposed to countries with a high percentage of renewable energy.

A.4.2 Manufacturing

Two contextual factors that affect the GHG emissions associated with manufacturing PV panels – the electricity mix at the location of manufacture and the quality of manufacturing – are discussed in this section.

The largest source of embedded GHG emissions for solar PV is associated with the electricity used to manufacture the panels [83]. Pacca et al. [84] found that manufacturing

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a KC120 multi-crystalline PV panel using only electricity generated from other KC120 multi-crystalline PV panels resulted in a 68% decrease in CO2 emissions, compared to manufacturing the panel using electricity from the grid. In addition, Reich et al. [85] examined the effect differences in the energy supply mix have on GHG emissions impact during the production of crystalline silicon solar PV panels and found that the manufacturers’ electricity mix can add anywhere from 0 to 200 additional gCO2-eq/kWh to the GHG intensity, depending on whether the electricity to run the processes comes from solar PV or from coal, respectively. Typically, LCA practitioners assume an average energy mix for a manufacturing area [83][203]. However, as Hsu et al. [185] note, China is the largest producer of silicon feedstock and PV modules and has coal-intensive electricity, but few if any studies explicitly account for impacts associated with manufacturing PV modules in China. Additionally, the quality of the manufacturing equipment and processes affect the embedded GHG emissions associated with solar PV. If the manufacturing processes are poor, scrap rates will be higher and average lifetimes of panels produced may be lower. GHG emissions associated with making these scrapped or prematurely-failed panels ought to be accounted for and averaged out over the other panels produced at the same manufacturing location. Consequently, manufacturing processes that have high scrap rates or result in poorly-made panels are likely to produce panels with higher embedded GHG emissions.

A.4.3 Transportation

The magnitude of GHG emissions during transport is directly related to the geographic dispersion of the supply chain, i.e. the distances between the locations of 283

material extraction, manufacturing, sales, use, and disposal. In addition, GHG emissions volumes depend on the modes of transportation available between these locations. Supply chains located in a small geographic area with energy efficient modes of transport are likely to release far fewer GHGs than the alternative.

A.4.4 Use

The amount of electricity produced during use of the solar panel very closely relates to the GHG intensity, the avoided GHG emissions, and the net GHG emissions associated with the panel. The more electricity produced over the life of the panel, the fewer average emissions per kWh, the greater the opportunity to avoid GHG emissions from the grid, and the greater the likelihood that the overall emissions balance will be favorable for the PV panel. Two contextual factors that affect PV panel production – (1) solar irradiation and (2) cleaning and maintenance diligence – are discussed below. One of the critical factors that determines PV panel production is the amount of solar irradiation that the panel sees over the course of its lifetime. Solar irradiation is “the average energy flux from the sun” [185] and can be measured in kWh/m2/year. NREL’s life cycle harmonization study [86] identified differences in solar irradiation assumptions as the main driver for differences between GHG intensity estimates for solar PV. Estimates for solar irradiation ranged from 900-2,143 kWh/m2/year in the studies NREL analyzed [86]. Irradiation is a purely environmental factor dictated by the location of the panels during use. The latitude of the geographic region, the time of year, weather effects such as cloudiness/dustiness, being shaded by a tree or building at certain times of the day, propensity to be obstructed by snow, sap, leaves, dust, etc., the angle of tilt, and the N-S

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orientation of the panel all are factors in determining the actual solar irradiation seen by a panel. Because of the importance of physical conditions at the installation site that might prevent the solar panel from receiving the expected theoretical irradiance – such as dust, snow, leaves, or other vegetation – the user’s commitment to cleaning, repairing, and maintaining the panels could have a significant effect on total electricity produced over the life of the panel. The more diligent the panel’s owner is in keeping it free from obstruction, the greater the expected lifetime electricity generation from the panel. However, as noted earlier, these activities are also associated with a small amount of indirect GHG emissions.

A.4.5 End-of-Life

Two contextual factors that affect the GHG intensity and net GHG emissions of solar PV panels are system lifetime and the disposal scenario selected. Both of these factors are discussed below.

The GHG intensity of PV panels is significantly affected by the lifetime of the system since most GHG emissions occur before the use phase. For instance, if a solar panel is destroyed in a tornado 1 year after installation, the electricity produced over its lifetime would be expected to have approximately a 30x greater GHG intensity than if it had lasted 30 years. If median GHG intensity values from the IPCC [196] are used – with solar PV for a rooftop installation at 41 gCO2eq/kWh and coal electricity associated with 820 gCO2eq/kWh - this would put the GHG intensity of the solar panel that survived only 1 year to 1230 gCO2eq/kWh, well above the GHG intensity associated with electricity from coal. In addition to tornadoes, the lifetime of panels may be shortened by being located in areas prone to high winds, lightning, falling tree branches, errant baseballs, etc. Similarly, 285

minor differences in manufacturing, damage to the panels during transport or use, and contamination within the panels could all reduce panel lifetime. As mentioned previously, there are a number of different disposal options for PV panels. Ultimately, the method of disposal is dependent on the options available and on decisions made by the panel owner, which are in turn influenced by local environmental regulations, existence - or lack - of local markets for recycled material, the cost of disposal, and the owner’s knowledge and beliefs about the options. If there is no market for materials that can be recycled from used solar panels, or if the salvage value of the panels is low, recycling programs may not exist. Furthermore, dismantling and recycling the solar PV system may be associated with a significant economic cost. According to the manufacturer of the 2.7 kWp PV system analyzed by Kannen et al. [200], the cost of dismantling of the system is approximately US$750. Similarly, Fthenakis [88] estimates the cost of recycling CdTe PV modules to be approximately 4–5¢/W in areas where many panels are concentrated and approximately 12¢/W for dispersed PV installations. In addition, the GHG emissions impacts associated with each disposal option are dependent on contextual factors, such as the type of electricity or fuel consumed in the recycling plant and the efficiency of the recycling process, for instance.

A.5 SENSITIVITY STUDIES OF CONTEXTUAL FACTORS

As discussed above, the GHG emissions impact associated with electricity from solar PV is highly dependent on a wide range of contextual factors. This section develops a simple model of a residential PV system that accounts for important contextual factors and is capable of generating estimates of the net and avoided GHG emissions - as well as the GHG intensity - associated with solar panels in different contexts. Specifically, the 286

effects of varying levels of solar insolation, different GHG intensities of avoided electricity, and differences in the timing of household demand and PV production are considered here. These contextual factors are included in this modeling effort because it is hypothesized that each could introduce significant variability in values of different GHG emissions metrics within the realm of reasonable PV usage scenarios. In addition, these three factors are all interrelated and pertain to avoided GHG emissions during the use phase of PV panels. The results from this section can be used to inform eco-conscious consumers and policymakers and help them purchase or incentivize solar PV designs in contexts that are associated with lower GHG emissions.

A.5.1 Model Framework

A simple model of a house with a solar panel was developed in Excel. Model inputs include hourly data on both solar panel production and the house’s electricity demand. When electricity is available from the solar panel to meet household demand, it is used.

The house receives backup electricity from the grid to make up the difference. It is assumed that the solar PV system has no form of energy storage and that the home does not sell excess electricity generated from the PV panel to the grid, as would occur if a feed-in-tariff were in place. Hence, any production from the solar PV panel beyond the amount demanded by the home is wasted. This model accounts for a number of contextual factors that can affect net GHG emissions associated with the household’s electricity, including: (1) the magnitude and timing of solar insolation at the location of use, which includes both location and weather effects, (2) the magnitude and timing of household electricity demand, accounting for differences among low-, base-, and high-consumption households and for differences in 287

the typical loads experienced by households in different geographic locations with different weather patterns, type of building structure, and type of appliances typically installed, and (3) differences in the type of grid-based electricity available.

A.5.2 Input Data

Four types of input data are used in the model: (1) PV production data, (2) household demand data, (3) GHG intensity data for avoided electricity from the grid, and

(4) data on the embedded GHG emissions associated with the PV panel. Each of these inputs is discussed below. First, NREL’s PVWatts tool [204] was used to generate annual production on an hourly basis from a residential solar panel for a 365-day year. The tool accounts for differences in the amount of solar insolation seen by the panel due to both location on the earth’s surface and weather effects; it allows users to specify the location of the panel, as well as the source of weather data. In addition, many of the design features of the solar panel, including panel type, size, efficiency, and installation type can be specified in the tool to simulate different PV technologies and system designs. The third version of the tool released September 8, 2014 was used in this study. Second, household load profile data was downloaded from OpenEI, a website that provides open-access energy information. They provide one load profile for TMY2 locations, as well as a ‘high’, ‘low’, and ‘base’ load profile for typical residences in all TMY3 locations in the US. TMY stands for ‘typical meteorological year.’ TMY2 data is available for 239 locations from 1961-1990 [205]. The load profile data is based on the Building America House Simulation Protocols [206].

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Third, when grid electricity is used as a backup for solar PV, the solar electricity typically displaces different types of electricity generation depending on the electricity mix on the grid and the timing. As demand on the grid changes throughout the day, different electricity generators are used. Hence, solar PV displaces whichever type of electricity is on the margin of production and would be ramped up if the panel were not producing. Data on GHG intensities of different types of grid electricity comes from a 2014 IPCC report

[196] and is provided in the table below. Median values are used in this study.

Table 8: Median GHG Intensities of Backup Electricity, Adapted from the IPCC [196].

Electricity Source Median GHG Intensities (gCO2eq/kWh) Coal – Pulverized Coal 820 Natural Gas – Combined Cycle 490 Biomass – dedicated 230 Solar PV – utility 48 Geothermal 38 Concentrated Solar Power 27 Hydropower 24 Nuclear 12 Wind offshore 12 Wind onshore 11

Finally, in this section, it is assumed that the total embedded GHG emissions associated with the 4kW solar PV panel are 6200 kg CO2-eq. A justification for this value is provided in the Appendix.

A.5.3 Test Case

As a test case, the model is used to estimate the net GHG emissions over the 30 year life of a home electricity system with a 4kW solar PV panel in various contexts. For the solar panel production data, all of the default system settings were used in the PVWatts

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tool, with the following two exceptions: (1) the ‘array type’ was set to ‘fixed (roof mount)’, as opposed to open rack or tracking options, and (2) an angle of tilt equal to the latitude at the location. The default settings specify a 4 kW DC system size, a standard module type (as opposed to premium or thin film), 14% system losses, 180 degree azimuth (an optimistic assumption that the panels, which are all analyzed for locations in the northern hemisphere, will face directly south towards the equator), a 1.1 DC to AC size ratio, 96% inverter efficiency, and a 0.4 ground coverage ratio. TMY2 weather data was selected and used for all calculations. To be consistent with the solar PV production data, TMY2 data was also used to specify the home electricity demand. The roof mount option was selected because this study is focused on residential solar PV systems in the US; here, residential PV systems are typically installed on roofs, whereas ground-mount and tracking options are more common for utility-scale PV [207]. In addition, the calculation of the total embedded GHG emissions associated with the solar

PV panel, presented in Appendix A, is based on the work from Hsu et al. [185]. Nearly three quarters of the studies Hsu et al. used to generate a median harmonized GHG intensity value for solar PV were estimates for rooftop-mounted PV systems [185], meaning choosing a roof mount option to generate PV production data helps maintain consistent assumptions for the inputs to the model.

Solar PV panels should be angled towards the sun to maximize the amount of solar energy they receive. For panels that are fixed mounted and do not have their installed angle change over the course of the year, it is generally accepted that the optimal angle for tilt is approximately equal to the latitude of the location where the panels are installed with the panels facing the equator [208]. Compared to other approaches in which tracking systems 290

are used to follow the sun throughout the day, or where the tilt of the fixed-mounted panel is adjusted biannually or monthly, for instance, using one angle of tilt for the entire year is the simplest approach to implement, although it does not produce the largest possible amount of solar electricity. Consequently for this study, it was assumed that the solar panel was installed with a tilt equal to the latitude. A graph of the annual average solar resource (in kWh/m2/day) in the US for a solar collector installed with the angle of tilt equal to the latitude is shown below, based on data from 1998-2005.

Figure 26: Annual average solar resource data for the US, shown for a solar collector tilted at an angle equal to the latitude. Adapted from Roberts [181].

In this section, four sets of calculations are made using the model that lend insight into the relative importance of different contextual factors that affect the use phase of solar PV panels.

A.5.3.1 The Effect of Differences in Solar Insolation during Use

This section examines the impact of differences in availability of solar insolation at the location of use on the GHG intensity of the electricity generated by the panel over its 291

life cycle. For this study, 3 locations – Phoenix, Arizona; Austin, Texas; and Seattle, Washington – were selected, corresponding to a high, medium, and low annual average solar resource of >6.5, 5.0-5.5, and 3.5-4 kWh/m2/day, respectively, for a latitude-tilt collector in the continental US. For each location, NREL’s PVWatts tool was used to estimate the hourly solar production for a 4kW solar PV panel installed with a tilt equal to the latitude at the TMY2 data station located in that city. Phoenix is located at 33.43 degrees north; Austin at 30.30 degrees north; and Seattle at 47.45 degrees north.

The total annual PV panel AC system output was calculated for the panel in each location. Over the course of the year, 6926 kWh electricity was produced by the PV panel in Phoenix, 5900 kWh in Austin, and 4341 kWh in Seattle. The GHG intensity of solar electricity was then calculated for the panel at each location, assuming that the panel would provide the annual output of electricity calculated above every year for its 30 year lifetime (an optimistic assumption), that all electricity generated by the panel will be used, and that the embedded GHG emissions associated with the panel amount to 6200 kgCO2-eq. The GHG intensities calculated were: 29.8 gCO2- eq/kWh for electricity generated by the 4kW solar PV panel in Phoenix, 35.0 gCO2-eq/kWh for Austin, and 47.6 gCO2-eq/kWh for Seattle. These results, along with the results of the following section, are also provided in Table 9. When compared to the values listed in Table 8, all of these GHG intensities are within a typical range for low-carbon electricity and are an order of magnitude lower than the GHG intensity of electricity from natural gas and coal.

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However, while always relatively low, the GHG intensity of the electricity generated by the same solar PV panel in different locations differs significantly; it is almost 60% higher in Seattle than in Phoenix. Section A.5.3.2 was designed to help understand the implications of this difference for the climate, in terms of net GHG emissions.

A.5.3.2 GHG Intensity vs. Net GHG Emissions

This section calculates the avoided GHG emissions associated with the electricity from the solar PV that replaces grid electricity in the three cities of interest over the course of the 30 year life of the panel. It also provides insight into net GHG emissions levels when the level of avoided GHG emissions is compared to the embedded emissions associated with the panel (6200 kg CO2-eq). According to the EIA, the US electric power industry produced a total of 4.048 billion MWh of electricity in 2012 [209], which is associated with the emissions of 2.157 billion metric tons of CO2 [210]; this works out to an average GHG intensity for electricity generated in the US in 2012 to be 533 gCO2/kWh. For the 30 year life of the panel, the following avoided GHG emissions are estimated: 110,700 kg CO2 avoided by the panel in Phoenix; 94,300 kg CO2 by the panel in Austin, and 69,400 kg CO2 by the panel in Seattle. These results highlight the fact that seemly small differences in GHG intensity that all are within the ‘good’ range for the climate can have large differences in the avoided GHG emissions associated these technologies. These results, along with the results from the previous section, are summarized in Table 9, below.

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Table 9: Annual electricity production, GHG intensity of electricity, and lifetime avoided GHG emissions estimates for a 4kW PV panel in three cities, assuming a 30 year panel lifetime, embedded emissions for the panel of 6200 kgCO2-eq, and the GHG intensity of avoided electricity is 533 gCO2/kWh.

Phoenix Austin Seattle Annual PV Production for 6,926 5,900 4,341 4kW Panel (kWh) GHG Intensity of Electricity Generated by the 29.8 35.0 47.6 Panel (gCO2-eq/kWh) Lifetime Avoided GHGs 110,700 94,300 69,400 Emissions (kg CO2 avoided)

In all cases, the mass of avoided GHG emissions is significantly greater than the estimated 6200 kg embedded GHG emissions. Even for the PV panel in Seattle, the upfront emissions associated with the panel only amount to 9% of the GHG emissions avoided over the lifetime of the panel, highlighting the importance of understanding and controlling the use-phase contextual factors that influence the net GHG emissions – such as the location of the panel during use – rather than trying to shave emissions off the manufacturing of the panels, for instance, when trying to maximize the environmental benefit of solar PV.

A.5.3.3 Complexities of Type and Timing of Backup Generation

Assuming that [the avoided GHG emissions associated with a PV panel] equal [the quantity of electricity produced by the solar PV panel over the course of its 30 year life] times [the average GHG intensity of a kWh of electricity in the US] – as was done above – is a significant simplification for many reasons that will be discussed below. The difficulty in understanding the GHG intensity of backup electricity generation from the grid arises because the mix of types of electricity generation – the relative proportions of coal, natural gas, and utility-scale solar – on a grid varies depending on location. In a

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particular location, the mix of sources actually generating electricity varies with time, depending on both the total demand on the grid and the relative cost of all available electricity generators, as can be seen by looking at a dispatch curve. A hypothetical dispatch curve is shown in Figure 27.

Figure 27: Hypothetical dispatch curve for summer 2011 from the EIA [211] demonstrating how the electricity generation mix depends on electricity demand and the cost of different types of generators.

To meet the required electricity demand – which varies with time of day and time of year – grid operators dispatch a set of electricity generators that has the same system capacity needed to meet the demand (horizontal axis of Figure 27), but with the lowest operating cost (vertical axis). This means that the GHG intensity of grid-based electricity a solar panel is displacing at any moment is not the average intensity of all generators on the grid, but is the intensity associated with the type of electricity generation that would otherwise have been used if the solar PV panel had not reduced demand on the grid. For the dispatch curve shown in Figure 27, electricity from a solar panel in operation in the early morning when the demand on the grid is 67 GW would be replacing electricity from a natural gas – combined cycle power plant. Later in the day, when the demand is 114 GW 295

on the grid, electricity from the solar panel would instead be replacing a natural gas – other generator. Similarly, if the demand on the grid were significantly lower – around 20 GW, for instance – the panel would instead replace hydropower; if demand were significantly higher on the grid – around 130 GW for instance – the panel would be replacing electricity from petroleum generators. Hence, the makeup of grid-based electricity in a particular location and the specific context that dictates demand on the grid at any particular moment in time can have a profound effect on the avoided GHG emissions associated with a solar PV panel.

To get a sense of this effect, the calculation performed in Part 2 is repeated here for the case of a solar PV panel in Austin, but instead of assuming electricity with the US average GHG intensity is replaced, different potential types of displaced grid power are instead considered, assuming their GHG intensity is the median value given for it by the IPCC, as shown in Table 8. The results of these calculations are provided in Table 10.

These results show an extreme example of how significantly the avoided GHG emissions associated with a 4kW solar PV panel in Austin could differ if grid electricity were supplied by only the source listed in the ‘backup electricity source’ column for the 30 year life of the panel. In cases where the grid electricity avoided comes from high-GHG emitting sources, such as coal, the avoided GHG emissions associated with the panel are significantly greater than the 94,300 kgCO2 value found in Section A.5.3.2 using average emissions intensities for the US. Also, as the 4kW panel was estimated to release

6200 kgCO2eq over the course of its life cycle, it can be shown that there is a breakeven point, where if most of the displaced electricity on a grid is coming from low-emitting

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sources, such as concentrated solar power, hydropower, nuclear, or wind, the 4kW solar panel actually causes an increase in net GHG emissions to the environment.

Table 10: Mass of avoided GHG emissions (kgCO2eq) associated with the use of a 4kW solar PV panel in Austin over 30 years, assuming 100% of the electricity from the panel offsets electricity that would have been generated from the ‘backup electricity source’ listed.

Backup Electricity Source Avoided GHG Emissions (kgCO2eq) Coal – Pulverized Coal 145,000 Natural Gas – Combined Cycle 86,700 Biomass – dedicated 40,710 Solar PV – utility 8,496 Geothermal 6,730 Concentrated Solar Power 4,780 Hydropower 4,250 Nuclear 2,120 Wind offshore 2,120 Wind onshore 1,947

These calculations highlight the unlikely finding that contextual issues related to the electric grid serving a particular area – the types of generators on the grid, their relative cost, and the timing of demand on the grid – can greatly influence the net GHG emissions benefit – or detriment – associated with incorporating additional solar PV.

A.5.3.4 Accounting for Timing of Demand and PV Production

Another contextual factor related to timing that has the potential to significantly affect the net GHG balance associated with a solar PV panel is how well-aligned the timing and magnitude of electricity demand is with solar PV production. To this point in Section A.5.3, it has been assumed that 100% of the electricity produced by the solar PV panel will displace electricity from the grid. In some cases, such as when PV panels are part of a solar PV utility directly feeding into an electric grid, this assumption may hold true. However,

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when a 4kW solar PV panel is attached to a typical home that does not have an energy storage system and does not have the option to sell excess electricity back to the grid, this assumption does not hold. This section explores the effect a timing mismatch between solar PV production and electricity demand could have on the net GHG emissions of a PV panel in this context. As shown in Figure 28, the timing and magnitude of solar PV production is not always aligned with the timing and magnitude of household demand.

4kW PV Production and Home Electricity Demand for 4 Days in Phoenix 5000

4000

3000

2000

Electricity(Wh) 1000

0 February 1st & 2nd August 1st & 2nd AC Solar PV Production Base Home Electricity Demand

Figure 28: The timing and magnitude of the AC electricity production from a 4kW panel in Phoenix, compared to electricity demand of a typical home in Phoenix, for February 1st and 2nd and August 1st and 2nd.

This figure shows the hourly electricity demand for a typical home in Phoenix (in terms of electricity consumption patterns), as well as the solar PV production of a 4kW PV panel in Phoenix for the first two days of February and August for a TMY2 year. 298

Electricity demand at the house varies hourly as well as seasonally, with demand much greater in August than in February, presumably as a result of increased air conditioning loads. The amount of electricity produced by the solar PV panel also varies hourly as well as seasonally; however, little weather and seasonal effects happen to appear in the 4 days that are graphed in Figure 28. This is not unexpected because Phoenix is a very sunny location, making it less likely to see dips in the PV production on an hourly basis due to clouds. Additionally, the at-latitude tilt of the panel has likely mitigated some of the seasonal variation in production between February and August. However, the graph does show that during midday on February 1st and 2nd, the solar panel production significantly exceeds the household’s electricity demand; without an energy storage system or the ability to sell the electricity back to the grid, this excess electricity from the solar PV panel is wasted. Hourly solar PV production data for the panel in Phoenix, including the data graphed above, for one full year was compared to annual hourly household electricity demand data for a typical house in Phoenix, to better understand the impact this timing mismatch could have for the net GHG emissions associated with the 4kW solar PV panel. Over the course of the year, the house in Phoenix demands 12,043 kWh of electricity, and 6,926 kWh are generated by the solar PV panel. This means that if timing were not a factor, roughly 58% of the household’s electricity demand could be supplied by the solar PV panel. However, when the solar PV production is considered relative to household demand, much of this electricity goes to waste because it is generated at a time when it is not needed.

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To understand of the impact of the timing issue, the difference between household demand and solar panel production was calculated for each hour over the course of the year. The results indicate that 2,589 kWh of electricity generated by the panel is wasted annually because the panel sometimes produces more electricity than is required by the house during a particular hour. This means that only 4,337 kWh of household demand is met by the solar PV panel, or similarly that 4,337 kWh of electricity produced by the solar panel over the course of the year is actually useful. The 2,589 kWh of wasted electricity corresponds to 37% of the total produced by the panel over the course of the year, meaning that quantity of grid-based electricity avoided over a year, or over the life of the panel, would also decrease by 37%. This represents a significant decline in the avoided GHG emissions associated with the panel. These calculations were also performed for a 4kW panel in Austin and Seattle, with the results for all three cities presented in Table 11, below.

Table 11: Summary of calculations estimating the effect timing and magnitude of household demand and solar electricity production from a 4kW PV panel have on the annual useful electricity produced by the panel, assuming no energy storage system and no option to sell excess electricity to the grid.

Phoenix Austin Seattle Annual Electricity Demand 12,043 15,670 7,862 for Base House (kWh) Annual PV Production for 6,926 5,900 4,341 4kW Panel (kWh) PV Electricity Wasted Annually Due to Timing 2,589 1,379 2,121 Mismatch (kWh) Percentage of PV Electricity Production Wasted Due to 37% 23% 49% Timing Mismatch

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In the case of all three cities, the percentage of electricity generated by the solar PV panel that goes to waste as a result of timing considerations is significant: 23% of the electricity produced by the panel in Austin is wasted, 37% in Phoenix, and 49% in Seattle. Consequently, these calculations demonstrate the importance of accounting for the timing and magnitude of solar availability and electric load for residential solar PV systems, to ensure that the electricity produced by the PV panel actually is used to offset grid electricity. A mismatch in the timing of demand and solar electricity production will result in wasted solar electricity, meaning that the GHG intensity of solar PV for useable electricity would increase. If this mismatch is significant it could defeat the purpose of installing solar PV from a climate change perspective. To get the most environmental benefit out of a given solar PV panel and avoid issues associated with timing mismatches, it may be advisable to encourage small PV panels to be attached to consistently large loads – so that the solar electricity produced is likely to always be less than that demanded by the load. For instance, policymakers could incentivize adoption of solar PV technology by electric utilities or by owners of large commercial buildings with significant electricity demand around midday, rather than incentivizing PV adoption at residences. The presence of feed-in-tariffs or the inclusion of an energy storage system in the residential solar PV system design would minimize or eliminate the issues discussed in this section associated with the mismatch in the timing and magnitude of solar PV production and household electricity demand. However, the electronics and metering systems needed to enable bidirectional flow on the grid, as well as the batteries and electronics needed for an energy storage system for a residential solar PV system, are both presumably associated 301

with a significant amount of GHG emissions. Calculating these emissions impacts and weighing the tradeoffs associated with these systems is a tasked saved for future work.

A.5.4 Future Work

Future research directions include: (1) assessing the GHG intensity impacts of incorporating energy storage, such as batteries, into solar PV systems; (2) analyzing the GHG intensity impact of a feed-in-tariff on solar PV systems, which would require new grid infrastructure in exchange for maximizing the use of the electricity generated from the panels; (3) incorporating hourly data of the GHG impact of electricity from electric grids in different locations; (4) expanding the analysis presented here for more cities to better identify geographic areas where solar PV is likely to have a large reduction in net GHG emissions; (5) assembling more complex models of grid networks that include solar PV at the neighborhood, city, grid, and national levels; and (6) incorporating economic and reliability metrics into the model.

A.6 CONCLUSION

A wide range of contextual factors are important in determining the life cycle GHG emission impact of solar PV systems. The first section of this paper presented an overview of GHG emission impacts associated with solar PV and discussed the factors that cause variability in GHG intensity estimates. In particular, numerous contextual factors that affect the GHG emission impact of solar PV were discussed, including the type of electricity used to manufacture the PV panels, the amount of solar energy the panel will see during use, and the manner in which the panels are cleaned and maintained. The second half of this paper focused on developing and using a simple analytical model of a

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residential-size solar PV system to study three different contextual factors: (1) solar insolation levels in the location of use, (2) the type and GHG intensity of grid-based electricity that is replaced by electricity from the solar PV panel, and (3) the effect of the match between the magnitude and timing of electricity demand and solar PV generation for residential PV systems. For all calculations, a roof-mounted, 4kW panel installed with a tilt equal to the latitude at the installation site was considered. When location was an important factor in the analysis, calculations were made using data for the cities of Phoenix, Arizona; Austin, Texas; and Seattle, Washington.

This study identified numerous contextual factors that can create substantial variation in GHG intensity estimates for electricity from solar PV panels and, similarly, can significantly affect the net GHG emissions balance for PV panels. For environmentally-conscious designers, the results of this study highlight the importance of understanding contextual issues and their overall influence on environmental impact. For policymakers, these results can help inform the development of tailored policies related to solar PV that may be more effective at reducing net GHG emissions because they take advantage of the contexts in which solar PV is most environmentally successful – i.e. when the life cycle emissions associated with manufacturing, transporting, recycling the panel are low; when the quantity of electricity produced by the panel is high; and when the electricity the solar electricity is replacing is GHG-intensive.

A.7 ACKNOWLEDGMENTS

Julia O'Rourke has been supported by a Powers Fellowship from the University of Texas at Austin and a National Science Foundation Graduate Research Fellowship. The

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authors would also like to thank the many researchers, colleagues, and friends who helped inspire this work.

A.8 APPENDIX

This section describes the manner in which the estimate for embedded GHG emissions associated with the 4kW panel analyzed in this study was determined. None of the many sources consulted in this work reported embedded emissions values associated with solar panels. By far the most common way to report LCA results of solar PVs was in terms of the GHG intensity of the electricity generated by the panels. Unfortunately, the sources consulted also did not provide estimates of the amount of electricity expected to be produced by the solar panel over the course of its life. Because the size of the solar panel system may have an effect on overall emissions intensity of the electricity produced – the so-called GHG ‘economies of scale’ – data from LCAs of residential-scale solar PV panels (approximately a 4kW rating) was desired.

Hsu et. al [2] provide the following equation that was used to harmonize the solar PV LCAs they analyzed:

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푊 퐺퐻퐺 = 퐼 ∗ 휂 ∗ 푃푅 ∗ 퐿푇 ∗ 퐴 Where:  GHG = the mass emissions of GHGs weighted by their global warming potential

per unit electricity generated by the solar panel (gCO2eq/kWh)  W = the global warming potential-weighted mass of the GHGs emitted over the

lifetime of the PV system (gCO2eq)  I = Irradiation (kWh/m2/year)  η = the lifetime average module efficiency (%)  PR = the performance ratio  LT = the system lifetime (years)  A = total module area (m2)

The median harmonized GHG value associated with all c-Si PV panels calculated by Hsu et al. – 45 g CO2eq/kWh – were used along with assumed values for the other variables based on Hsu et al.’s harmonization assumptions and technology-related assumptions – to calculate W for a 4 kWh solar panel. Specifically, Hsu et al.’s harmonized values for solar irradiation (1,700 kWh/m2/year), system lifetime (30 years), and performance ratio (0.75 for a rooftop mounted system) were used.

Hsu et al. provide two possible options for lifetime module efficiency: (1) 13.0% for monocrystalline modules with an initial efficiency of 14.0%, and (2) 12.3% for multicrystalline modules with an initial efficiency of 13.2%. The PVWatts tool, which was used to generate the solar PV production data in the case study, has three options for ‘Module Type’: (1) standard crystalline silicon, associated with a 15% efficiency; (2) 305

premium crystalline silicon, with a 19% efficiency; and (3) thin film, with a 10% efficiency. For the PV production data, the ‘standard’ module with a 15% efficiency was selected. Consequently, we chose the 13.0% efficiency value for the calculation of W because it was the highest value considered by Hsu et al. and the closest to the value for the module used to produce our solar PV production data. Finally, a value of 30 m2 was assumed for the module area for a 4 kW solar panel.

This value was based on the following range of estimates associating solar panel area with peak panel production:

 The PV Watts tool ‘help’ section [212] under ‘System Size (DC kW)’ provides the following equation: 푘푊 푆푖푧푒 (푘푊) = 퐴푟푒푎(푚2) ∗ 1 ∗ 푀표푑푢푙푒 퐸푓푓푖푐푖푒푛푐푦 (%) 푚2 Which, for a 4kW panel with an efficiency of 13%, gives an area of 30.7 m2.  According to the EcoExperts, a UK-based solar panel comparison website, a typical

4kW system takes up 28m2 of roof space, assuming a south-facing roof in the UK at a 35 degree angle with little to no shade [213].  According to California Solar Electric Company’s website [214], each DC nameplate kW of PV installed will require approximately 85 ft2, meaning a 4kW panel would require 340 ft2, or 31.6 m2.

Putting the assumed values into the equation from Hsu et al. gives estimates of the total life cycle embedded emissions W for a 4kW panel gives 6173 kgCO2eq, associated with the median harmonized emissions value 45 gCO2-eq/kWh. For simplicity, we use

6200 kgCO2-eq, a rounded version of the value associated with the median harmonized estimate. 306

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