Exhibit EG – 1

Exhibit EG-1

Emily Grubert Assistant Professor School of Civil and Environmental Engineering

CONTACT INFORMATION Mason Building 4140C [email protected] School of Civil and Environmental Engineering 404.894.3055 Georgia Institute of Technology emilygrubert.org Atlanta, GA 30332 ORCID: 0000-0003-2196-7571

TABLE OF CONTENTS I. EARNED DEGREES ...... 1 II. EMPLOYMENT HISTORY ...... 1 III. HONORS AND AWARDS ...... 2 IV. RESEARCH, SCHOLARSHIP, AND CREATIVE ACTIVITIES ...... 2 V. EDUCATION ...... 17 VI. SERVICE ...... 19

I. EARNED DEGREES

PhD , Environment and Resources, 2017 Dissertation: Improving Life Cycle Assessment as a Decision Support Tool Using Empirical Data for Multicriteria Prioritization Co-advisors: Adam Brandt, Mark Algee-Hewitt MS The University of at Austin, Environmental and Water Resources Engineering, 2011 Thesis: Freshwater on the Island of Maui: System Interactions, Supply, and Demand Advisor: Michael Webber MA The University of Texas at Austin, Energy and Earth Resources, 2010 Thesis: Maui’s Freshwater: Status, Allocation, and Management for Sustainability Advisor: Michael Webber BS Stanford University, Mathematics (Honors), Atmosphere/Energy Engineering (Honors), Biological Sciences (Minor), 2009

II. EMPLOYMENT HISTORY 2019- Georgia Institute of Technology, Assistant Professor, Civil and Environmental Engineering and, by courtesy, Public Policy; Computational Science and Engineering program faculty member 2018 University of California, Berkeley, Lecturer, Civil and Environmental Engineering 2017-18 University of California, Berkeley, Postdoctoral Scholar, Civil and Environmental Engineering Supervisor: Arpad Horvath 1 of 20 Grubert Curriculum Vitae Exhibit EG-1

2011-13 Business Analyst and Junior Engagement Manager, McKinsey & Company

III. HONORS AND AWARDS A. INTERNATIONAL OR NATIONAL AWARDS 2020 Trusted Reviewer (reflecting “exceptionally high level of peer review competency”), Institute of Physics 2017 Reviewer of the Year, Environmental Research Letters

B. INSTITUTE OR SCHOOL AWARDS 2020-21 Diversity and Inclusion Fellow, Georgia Institute of Technology 2019-20 Class of 1969 Teaching Fellow, Georgia Institute of Technology

IV. RESEARCH, SCHOLARSHIP, AND CREATIVE ACTIVITIES *: performed at Georgia Tech bold: indicates supervised student or postdoc co-author

A. PUBLISHED BOOKS, BOOK CHAPTERS, AND EDITED VOLUMES

A1. Refereed Book Chapters [2] Grubert, E. 2020. “Social Science and Energy Policymaking: The Need for Social Scientists in Developing Social Life Cycle Assessment.” In: Energy Impacts: A Multidisciplinary Exploration of North American Energy Development. Eds: J. Jacquet, J. Haggerty, and G. Theodori. Utah State University Press. [1] Haya, B., A. Strong, E. Grubert, and D. Cullenward. 2015. “Carbon Offsets in California: Science in the Policy Development Process.” In: Communicating Climate Change and Natural Hazard Risk and Cultivating Resilience: Case Studies for a Multi-disciplinary Approach. Eds: Yekaterina Kontar et al. Springer.

A2. Other Parts of Books [1] Lovins, A. and Rocky Mountain Institute. September 2011. Reinventing Fire: Bold Business Solutions for the New Energy Era. Chelsea Green Publishing Company, Vermont. (E. Grubert as research contributor, natural gas and coal systems)

B. REFEREED PUBLICATIONS AND SUBMITTED ARTICLES

B1. Published and Accepted Journal Articles [35] *Grubert, E. Fossil electricity retirement deadlines for a just transition. Accepted, Science. [34] *Krieger, J. and E. Grubert. Life cycle costing for distributed stormwater control measures on the gray-green continuum: A planning-level tool. Accepted, Journal of Sustainable Water in the Built Environment (ASCE). [33] *Grubert, E. Same-plant trends in capacity factor and heat rate for US power plants, 2001-2018. IOP SciNotes. DOI: 10.1088/2633-1357/abb9f1.

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[32] *Grubert, E., J. Stokes-Draut, A. Horvath, and W. Eisenstein. Utility-specific projections of electricity sector greenhouse gas emissions: A committed emissions model-based case study of California through 2050. Environmental Research Letters. DOI: 10.1088/1748-9326/abb7ad. [31] *Haya, B., D. Cullenward, A. Strong, E. Grubert, R. Heilmayr, D. Sivas, and M. Wara. Managing Uncertainty in Carbon Offsets: Insights from California’s Standardized Approach. Climate Policy. DOI: 10.1080/14693062.2020.1781035. [30] *Grubert, E., E. Rogers, and K. Sanders. 2020. Consistent Terminology and Reporting are Needed to Describe Water Quantity Use. Journal of Water Resources Planning and Management (ASCE). DOI: 10.1061/(ASCE)WR.1943- 5452.0001241. [29] *Grubert, E. 2020. At scale, renewable natural gas systems could be climate intensive: The influence of methane feedstock and leakage rates. Environmental Research Letters. DOI: 10.1088/1748-9326/ab9335. [28] *Tarroja, B., R. Peer, K. Sanders, and E. Grubert. 2020. How do non-carbon priorities affect zero-carbon electricity systems? A case study of freshwater consumption and cost for SB100 compliance in California. Applied Energy. DOI: 10.1016/j.apenergy.2020.114824. [27] *Meng, M., E. Grubert, R. Peer, and K. Sanders. 2020. Spatially allocating life cycle water use for US coal-fired electricity across producers, generators, and consumers. Energy Technology. DOI: 10.1002/ente.201901497. [26] *Grubert, E. and J. Stokes-Draut. 2020. Mitigation Life Cycle Assessment: Best Practices from LCA of Energy and Water Infrastructure That Incurs Impacts to Mitigate Harm. Energies. DOI: 10.3390/en13040992. [25] *Grubert, E. 2020. Conventional Hydroelectricity and the Future of Energy: Linking National Inventory of Dams and Energy Information Administration Data to Facilitate Analysis of Hydroelectricity. The Electricity Journal. DOI: 10.1016/j.tej.2019.106692. [24] *Peer, R., E. Grubert, and K. Sanders. 2019. A Regional Assessment of the Water Embedded in the US Electricity System. Environmental Research Letters. DOI: 10.1088/1748-9326/ab2daa. [23] *Grubert, E. 2019. Every Door Direct Mail in US survey research: An anonymous census approach to mail survey sampling. Methodological Innovations. DOI: 10.1177/2059799119862104. [22] *Greer, F., J. Chittick, E. Jackson, J. Mack, M. Shortlidge, and E. Grubert. 2019. Energy and Water Efficiency in LEED: How Well are LEED Points Linked to Climate Outcomes? Energy and Buildings. DOI: 10.1016/j.enbuild.2019.05.010 [21] *Grubert, E. and A. Brandt. 2019. Three Considerations for Modeling Natural Gas System Methane Emissions in Life Cycle Assessment. Journal of Cleaner Production. DOI: 10.1016/j.jclepro.2019.03.096 [20] Bell, C., K. Spahr, E. Grubert, J. Stokes-Draut, E. Gallo, J. McCray, and T. Hogue. 2018. Decision-making on the Grey-green Stormwater Infrastructure Continuum. Journal of Sustainable Water in the Built Environment (ASCE). DOI: 10.1061/JSWBAY.0000871

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[19] Grubert, E. 2018. Relational Values in Environmental Assessment: The Social Context of Environmental Impact. Current Opinion in Environmental Sustainability. DOI: 10.1016/j.cosust.2018.10.020 [18] Grubert, E. 2018. The Eagle Ford and Bakken Shale Regions of the United States: A Comparative Case Study. The Extractive Industries and Society. DOI: 10.1016/j.exis.2018.09.011 [17] Grubert, E. and K. Sanders. 2018. Water Use in the United States Energy System: A National Assessment and Unit Process Inventory of Water Consumption and Withdrawals. Environmental Science & Technology (ACS). DOI: 10.1021/acs.est.8b00139 [16] Grubert, E. and M. Cook. 2017. Communication Science for Science Communication: Water Management for Oil and Natural Gas Extraction. Journal of Water Resources Planning and Management (ASCE). DOI: 10.1061/(ASCE)WR.1943-5452.0000842 [15] Grubert, E. and W. Skinner. 2017. A Town Divided: Community Values and Attitudes Towards Coal Seam Gas Development in Gloucester, New South Wales. Energy Research and Social Science. DOI: 10.1016/j.erss.2017.05.041 [14] Drummond, V. and E. Grubert. 2017. Fault Lines: Seismicity and the Fracturing of Energy Narratives in Oklahoma. Energy Research and Social Science. DOI: 10.1016/j.erss.2017.05.039 [13] Grubert, E. and M. Algee-Hewitt. 2017. Villainous or Valiant? Depictions of Oil and Coal in American Fiction and Nonfiction Narratives. Energy Research and Social Science. DOI: 10.1016/j.erss.2017.05.030 [12] Grubert, E. 2017. The Need for a Preference-based Multicriteria Prioritization Framework in Life Cycle Sustainability Assessment. Journal of Industrial Ecology (ISIE). DOI: 10.1111/jiec.12631 [11] Grubert, E. 2017. How to Do Mail Surveys in the Digital Age: A Practical Guide. Survey Practice. [10] Grubert, E. 2017. Implicit prioritization in Life Cycle Assessment: Text mining and detecting metapatterns in the literature. International Journal of Life Cycle Assessment. DOI: 10.1007/s11367-016-1153-2 [9] Grubert, E. 2016. Water Consumption from Hydroelectricity in the United States. Advances in Water Resources. DOI: 10.1016/j.advwatres.2016.07.004 [8] Grubert, E. and A. Siders. 2016. Benefits and applications of interdisciplinary digital tools for environmental meta-reviews and analyses. Environmental Research Letters. DOI: 10.1088/1748-9326/11/9/093001 (selected for September 2016 monthly highlights) [7] Lukacs, H., N. M. Ardoin, and E. Grubert. 2016. Beyond formal groups: neighboring acts and watershed protection in Appalachia. International Journal of the Commons. DOI: 10.18352/ijc.578 [6] Grubert, E. and M. E. Webber. 2016. Synthetic flows for engineered systems with nonstationary parameters: A study of Maui’s Wailoa Ditch. Journal of Hydrologic Engineering (ASCE). DOI: 10.1061/(ASCE)HE.1943-5584.0001468

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[5] Grubert, E. 2016. Rigor in Social Life Cycle Assessment: Improving the scientific grounding of SLCA. International Journal of Life Cycle Assessment. DOI: 10.1007/s11367-016-1117-6 [4] Grubert, E. and M. E. Webber. 2015. Energy for water and water for energy on Maui Island, Hawaii. Environmental Research Letters. DOI: 10.1088/1748- 9326/10/6/064009 [3] Grubert, E., A. Stillwell, and M. E. Webber. 2014. Where does solar-aided desalination make sense? A method for identifying sustainable sites. Desalination. DOI: 10.1016/j.desal.2014.02.004 [2] Grubert, E., F. Beach, and M. E. Webber. 2012. Can switching fuels save water? A life cycle quantification of freshwater consumption for Texas coal- and natural gas-fired electricity. Environmental Research Letters. DOI: 10.1088/1748- 9326/7/4/045801 [1] Grubert, E. 2012. Reserve reporting in the United States coal industry. Energy Policy. DOI: 10.1016/j.enpol.2012.01.035

B2. Conference Presentation with Proceedings (Refereed) [13] *Burns, D., and E. Grubert. May 2020. Attributing Natural Gas Production to Natural Gas Users: A Geospatial Approach. Proceedings of the World Environmental and Water Resources Congress 2020. DOI: 10.1061/9780784482964.030 [12] Cook, M., and E. Grubert. April 2017. Water Use in the Oil and Gas Industries: An Evaluation of Best Practices for Communicating with Scientists, Policymakers, and the Public. Proceedings of the Society of Petroleum Engineers Health, Safety, Security, Environment, & Social Responsibility Conference-North America. DOI: 10.2118/184431-MS [11] Grubert, E., D. Kelly, B. Rumbelow, and J. Wilson. May 2015. Improving Produced Water Management: A Case Study of Designing an Inland Desalination Pilot Project. Proceedings of the World Environmental and Water Resources Congress 2015. DOI: 10.1061/9780784479162.052 [10] Grubert, E., B. Parks, E. Schneider, and S. Sekar. December 2011. Pebble Bed Modular Reactors Versus Other Generation Technologies: Costs and Challenges for South Africa. Proceedings of GLOBAL 2011. Paper 391144 [9] Grubert, E., C. King, and M. E. Webber. November 2011. Water for Biomass- based Energy on Maui, Hawaii. Proceedings of the ASME 2011 International Mechanical Engineering Congress and Exposition. DOI: 10.1115/IMECE2011- 63199 [8] Grubert, E. and M. E. Webber. August 2011. Water, Energy, and Land Use Planning on Maui Island, Hawaii: Estimating Surface Water Supply. Proceedings of the ASME 2011 5th International Conference on Energy Sustainability. DOI: 10.1115/ES2011-54332 [7] Grubert, E. May 2011. Lifecycle Water Impacts of Coal Use in the United States. Proceedings of the World Environmental and Water Resources Congress 2011: Bearing Knowledge for Sustainability. DOI: 10.1061/41173(414)344 [6] Grubert, E. May 2011. Modeling Maui’s Freshwater System to Inform Water Resource Management. Proceedings of the World Environmental and Water 5 of 20 Grubert Curriculum Vitae Exhibit EG-1

Resources Congress 2011: Bearing Knowledge for Sustainability. DOI: 10.1061/41173(414)105 [5] Phillips, R. and E. Grubert. May 2011. Water and Deforestation in Brazil: Future Challenges for Policy Implementation. Proceedings of the World Environmental and Water Resources Congress 2011: Bearing Knowledge for Sustainability. DOI: 10.1061/41173(414)129 [4] Grubert, E. February 2011. Energy Resource Extraction, Water Resources, and a Human Right to Water in the West. “Implementing the Human Right to Water in the West: Conference Report.” Willamette Law Review. Volume 48:1. [3] Grubert, E. September 2010. Mining-related Environmental Impacts of Carbon Mitigation: Coal-based Carbon Capture and Sequestration. Proceedings of the World Energy Congress. [2] Grubert, E. May 2010. Centralized Transportation Fuel Planning: Leveraging Californian Refineries as Transportation Utilities. Proceedings of the ASME 2010 4th International Conference on Energy Sustainability. DOI: 10.1115/ES2010- 90027 [1] Grubert, E. and M. E. Webber. May 2010. Water Impacts of the American Clean Energy and Security Act Renewable Portfolio Standard on Texas. Proceedings of the ASME 2010 4th International Conference on Energy Sustainability. DOI: 10.1115/ES2010-90029

B3. Other refereed material [3] Grubert, E. 2018. Civil engineering’s internal skepticism on climate change. Journal of Professional Issues in Engineering Education and Practice. DOI: 10.1061/(ASCE)EI.1943-5541.0000370 (Editor-refereed) [2] Grubert, E. 2016. Response to “Discourse over a contested technology on Twitter: A case study of hydraulic fracturing” – Word choice as political speech. Public Understanding of Science. DOI: 10.1177/0963662515626310 (Editor- refereed) [1] Emerging Leaders in Science and Society (ELISS) Fellows*. December 2015. Reimagining Epidemic Communications. Domestic Preparedness Journal. (*equal contributions by R. Erion, E. Grubert, S. Mosbah, M. Munyikwa, B. Paul, and C. Tran) (Editor-refereed)

B4. Submitted Journal Articles [3] *Grubert, E. Long-run greenhouse gas and water intensity of hydrogen: The influence of methane leakage and zero carbon electricity mixes. Submitted August 2020, Elementa: Science of the Anthropocene. [2] *Amekudzi-Kennedy, A., S. Labi, B. Woodall, G. Marsden, and E. Grubert. Role of Socially Equitable Economic Development in Creating Resilient and Sustainable Systems: COVID-19-Related Reflections. Submitted June 2020, Sustainability: The Journal of Record. [1] *Grubert, E. Is energy still useful as a sustainability proxy? Learning from water to propose a ‘yellow, red, brown’ energy footprint. In revision, Joule (Cell Press).

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C. OTHER PUBLICATIONS AND CREATIVE PRODUCTS

C1. Software [3] *Grubert, E. and J. Krieger. May 2020. “Integrated Decision Support Tool (iDST) Life Cycle Costing Module for Distributed Stormwater Control Measures (SCMs).” Life cycle cost model. [2] *Grubert, E. January 2019. “US power plants by capacity, age, and fuel.” Web map. [1] Grubert, E. (contributor). October 2015. Energy Policy Simulator. Web model.

C2. Other Creative Products [11] *Davis, S. and C. Bataille (leads) with Bazilian, M., Brouwer, J., Doig, S., Fennell, P., Gielen, D., Grubert, E., and D. Tong (contributors). “5.3 Accelerating Net-Zero Emissions Industry in the U.S.” In: SDSN 2020. Zero Carbon Action Plan. New York: Sustainable Development Solutions Network (SDSN). [10] *Grubert, E. July 2020. ‘Renewable’ natural gas may sound green, but it’s not an antidote for climate change. The Conversation. [9] *Amekudzi-Kennedy, A., S. Labi, B. Woodall, G. Marsden, and E. Grubert. April 2020. Role of Socially-Equitable Economic Development in Creating Resilient and Sustainable Systems: COVID-19-Related Reflections. Preprint (preprints.org). [8] *Haya, B., D. Cullenward, A. Strong, E. Grubert, R. Heilmayr, D. Sivas, and M. Wara. August 2019. Managing Uncertainty in Carbon Offsets: Insights from California’s Standardized Approach. Stanford Law School Environmental & Natural Resources Law and Policy Program Working Paper. Stanford, CA. [7] Grubert, E. 2018. Analyzing the Energy Sector for California Climate Investments: Literature Review of Energy Documents and GHG Electricity Emission Factors. California Air Resources Board. Berkeley, CA. [6] Rogers, L. and E. Grubert. 2017. Terraforming: Art and Engineering in the Sacramento Watershed. Green Library, Stanford University, Stanford, CA. (Co- curator, library exhibition) [5] Grubert, E., C. King, and M. E. Webber. August 2013. “Maui’s Complicated Relationship With Water.” Earth Magazine. [4] Grubert, E. August 2011. “Why Business-as-Usual Coal Consumption Could Mean Dramatic Changes.” Scientific American Guest Blog: Commentary invited by editors of Scientific American. [3] Grubert, E. and S. Kitasei. December 2010. How Energy Choices Affect Fresh Water Supplies: A Comparison of U.S. Coal and Natural Gas. Worldwatch Institute Briefing Paper. Worldwatch Institute: Washington, D.C. [2] Grubert, E. January 2010. “Beat a Dead Horse or Breed Immortal Ones.” Solutions. National Council for Science and the Environment. [1] Grubert, E. Over 60 published print columns, The Stanford Daily (January – June 2009), The Daily Texan (August 2009 – December 2010). Additional web columns for Americans for Energy Leadership and Elmrox (2010 – 2011).

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D. PRESENTATIONS D1. Keynote Addresses and Plenary Lectures [4] Energy Policy Research Conference. September 2018. “Water-Energy Nexus in the West, Plenary Session & Lunch.” Boise, Idaho. (Plenary moderator) [3] Resources for Future Generations. June 2018. “Keynote: Estimating water usage for the US energy system: Suggestions for improving data collection and reporting.” Vancouver, British Columbia. (Co-author with R. Peer, K. Sanders) [2] Convent of the Sacred Heart. June 2017. Commencement Address. Greenwich, Connecticut. (Individual) [1] Texas Leadership Society Luncheon. April 2010. Keynote Address. Austin, Texas. (Individual)

D2. Invited Conference and Workshop Presentations [8] American Geophysical Union Fall Meeting. December 2019. “Conventional Hydroelectricity and Near-zero Emission Energy Systems.” San Francisco, CA. (Individual) [7] INFORMS Annual Meeting 2019. October 2019. “How do we reconcile priorities during the energy transition?” Seattle, Washington. (Individual) [6] Solar Power and Energy Storage Mountain West. April 2019. “The Energy System is Changing.” Aurora, Colorado. (Individual) [5] Southeastern Energy Conference. March 2019. “Global Electrification.” Atlanta, Georgia. (Panel) [4] Data Science for Sustainability Meetup. October 2018. “The Water-Energy Nexus: Water Use for Energy Systems.” San Francisco, CA. (Individual) [3] South by Southwest Eco. October 2013. “New Global Models: Real-Time and Local.” Austin, Texas. (Panel) [2] Society of Women Engineers 12th Annual Conference for Women Engineers. November 2012. “Understanding the Water Implications of our Energy Choices.” Houston, Texas. (Panel) [1] International Student Energy Summit. June 2011. “Global Energy Dynamics: The Nexus between Energy and Water.” Vancouver, Canada. (Panel)

D3. Conference and Workshop Presentations [54] *Grubert, E. May 2021. “The Climate Implications of Renewable Natural Gas.” World Environmental and Water Resources Congress. Milwaukee, WI. (Oral) [53] *Grubert, E. May 2021. “Decarbonization and facility closures: planning for a just transition away from fossil fuels.” World Environmental and Water Resources Congress. Milwaukee, WI. (Oral) [52] *Gallo, E., K. Spahr, E. Grubert, and T. Hogue. December 2020. “Optimizing between green and grey stormwater infrastructure using hydrologic modeling, life cycle costs, and a benefit analysis.” American Geophysical Union Fall Meeting. Online due to COVID-19. (Oral) [51] *Tarroja, B., R. Peer, K. Sanders, and E. Grubert. December 2020. “Assessing the influence of freshwater consumption priorities on zero-carbon electricity 8 of 20 Grubert Curriculum Vitae Exhibit EG-1

planning: A case of Senate Bill 100 compliance in California.” American Geophysical Union Fall Meeting. Online due to COVID-19. (Poster) [50] *Maxim, A. and E. Grubert. December 2020. “Assessing Impacts of Climate Change and Climate Migration on Urban Infrastructure Resilience.” American Geophysical Union Fall Meeting. Online due to COVID-19. (Oral) [49] *Mulrow, J. and E. Grubert. December 2020. “Environmental Implications of the EV Cyber-Physical System.” American Geophysical Union Fall Meeting. Online due to COVID-19. (Poster) [48] *Grubert, E. December 2020. “Beyond Carbon in Socioenvironmental Assessment for Zero Carbon Systems.” American Geophysical Union Fall Meeting. Online due to COVID-19. (Poster) [47] *Grubert, E. August 2020. “Conventional Hydroelectricity and the Grid.” American Water Resources Association Spring Conference. Austin, TX. (Virtual due to COVID-19) [46] *Grubert, E. July 2020. “Life Cycle Cost and Environmental Assessment: Distributed Stormwater Control Measures.” Integrated Decision Support Tool Beta Testing for Stormwater Practitioners Workshop. International Low Impact Development Conference. Web. (Virtual due to COVID-19) [45] *Grubert, E. July 2020. “Socioenvironmental priorities in resource-producing communities: Case studies from US and Australian communities hosting fossil fuel and solar production.” International Symposium on Society and Resource Management. Cairns, Queensland, Australia. (Virtual due to COVID-19) [44] *Maxim, A. and E. Grubert. June 2020. “How could open data standards affect energy and water sustainability in agriculture?” International Symposium for Sustainable Systems and Technology. Pittsburgh, PA. (Virtual due to COVID-19) [43] *Ha, S. and E. Grubert. May 2020. “Understanding the Public Attitudes towards the Clean Power Plan Using Natural Language Processing and Deep Learning.” Duke University Energy Data Analytics Symposium. Durham, NC. (Postponed due to COVID-19) [42] *Kirkman, R. and E. Grubert. February 2020. “Rethinking Relational Values for Environmental Assessment.” 2020 Annual International Conference of the Association for Practical and Professional Ethics. Atlanta, GA. (Oral) [41] *Kirkman, R. and E. Grubert. January 2020. “Rethinking Relational Values for Environmental Assessment.” Workshops on Original Policy Research (WOPR). Georgia Institute of Technology. Atlanta, Georgia. [40] *Grubert, E. December 2019. “Phasing Out Fossil Fuels: Socioenvironmental Priorities and Just Transitions for Extraction Communities.” American Geophysical Union Fall Meeting. San Francisco, CA. (Oral) [39] *Meng, M., K. Sanders, and E. Grubert. December 2019. “Resolving the life cycle water consequences of U.S. coal-fired electricity: A challenge of data availability, spatial attribution, and consumer accountability.” American Geophysical Union Fall Meeting. San Francisco, CA. (Oral) [38] *Gallo, E., C. Bell, A. Beziou, K. Spahr, E. Grubert, and T. Hogue. December 2019. “Development of a new integrated decision support tool (i-DST) for optimizing the benefits and tradeoffs of greener to greyer stormwater

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infrastructure.” American Geophysical Union Fall Meeting. San Francisco, CA. (Poster) [37] *Ravikumar, A., E. Grubert, and D. Sanchez. December 2019. “An Introduction to the Green New Deal and its Implications for Climate Policy.” American Geophysical Union Fall Meeting. San Francisco, CA. (Oral—Session Chair, The Green New Deal: From Resolution to Reality) [36] *Grubert, E. September 2019. “Conventional Hydroelectricity and the Future of the Grid.” Energy Policy Research Conference. Boise, ID. (Oral) [35] *Grubert, E. August 2019. “Modeling Regionalized Life Cycle Cost Ranges for Stormwater Infrastructure.” Operation & Maintenance of Stormwater Control Measures. Minneapolis, MN. (Oral) [34] *Grubert, E. June 2019. “What can public comments on the Clean Power Plan tell us about public attitudes toward climate-oriented regulation of the electricity system? A computational analysis.” International Symposium on Society and Resource Management. Oshkosh, WI. (Oral) [33] *Peer, R., E. Grubert, and K. Sanders. May 2019. “A High-resolution Geospatial Assessment of Water for the US Energy System.” World Environmental and Water Resources Congress. Pittsburgh, PA. (Oral) [32] *Grubert, E. May 2019. “A Life Cycle Cost Model of United States Green Stormwater Infrastructure Including Monetized Environmental Costs.” World Environmental and Water Resources Congress. Pittsburgh, PA. (Oral) [31] *Grubert, E. April 2019. “Energy in Atlanta: Regional Priorities and Governance.” Atlanta Studies Symposium. Atlanta, Georgia. (Oral) [30] Sanders, K. and E. Grubert. December 2018. “Estimating the water usage of the US energy system within the context of change.” American Geophysical Union Fall Meeting. Washington, D.C. (Oral) [29] Stokes-Draut, J., and E. Grubert. December 2018. “Unraveling the Water- Energy-Carbon Nexus for California’s Urban Water Future.” American Geophysical Union Fall Meeting. Washington, D.C. (Oral) [28] Hogue, T., C. Bell, E. Gallo, K. Spahr, E. Grubert, J. Stokes-Draut, and J. McCray. December 2018. “Advancing tools for holistic management of water resources: Development of an integrated decision support tool (i-DST) for grey and green infrastructure implementation.” American Geophysical Union Fall Meeting. Washington, D.C. (Oral) [27] Peer, R., E. Grubert, and K. Sanders. December 2018. “A Geospatial Assessment of the Water Consumed and Withdrawn for US Fossil Fuel Production.” American Geophysical Union Fall Meeting. Washington, D.C. (Poster) [26] Gallo, E., T. Hogue, C. Bell, K. Spahr, E. Grubert, and J. Stokes-Draut. December 2018. “Application of a new integrated decision support tool (i-DST) for urban water infrastructure: Analyzing water quality compliance pathways in Ballona Creek Watershed in Los Angeles, California.” American Geophysical Union Fall Meeting. Washington, D.C. (Poster) [25] Grubert, E. June 2018. “Socioenvironmental priorities and experiences in the Eagle Ford and Bakken Shale regions of the United States: A comparative case

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study.” International Symposium on Society and Resource Management. Salt Lake City, Utah. (Oral) [24] Groenke, A., E. Grubert, J. Stokes-Draut, and A. Horvath. May 2018. “Analysis of California water conservation programs for low-income communities: Decision support systems for utility planning.” Re-Inventing the Nation’s Urban Water Infrastructure (ReNUWIt) Spring Meeting. Stanford, California. (Poster) [23] Grubert, E. May 2018. “Developing Social Elements of Life Cycle Assessment.” World Environmental and Water Resources Congress. Minneapolis, Minnesota. (Oral) [22] Webber, M. and E. Grubert. December 2017. “Thirst for Power: Energy, Water, and Human Survival.” American Geophysical Union Fall Meeting. New Orleans, Louisiana. (Oral) [21] Grubert, E. December 2017. “Water Use for Unconventional Energy Development: How Much, What Kind, and to What Reaction?” American Geophysical Union Fall Meeting. New Orleans, Louisiana. (Poster, Invited) [20] Traer, M., R. Haupt, and E. Grubert. December 2017. “Stop saving the planet! Carbon accounting of superheroes and their impacts on climate change.” American Geophysical Union Fall Meeting. New Orleans, Louisiana. (Poster) [19] Wang, J. and E. Grubert. November 2017. “Perceived variability in attribute outcomes, moral attributes, and compromise.” Society for Judgment and Decision Making Annual Meeting. Vancouver, British Columbia. (Poster) [18] Grubert, E. November 2017. “Integrating Water Quantity to Life Cycle Assessment: A US-based Energy Water Nexus Case Study.” American Water Resources Association Annual Conference. Portland, Oregon. (Oral) [17] Suganuma, J. and E. Grubert. July 2017. “Community Response to Unconventional Oil and Gas Development in North America.” Energy Impacts Symposium 2017. Columbus, Ohio. (Oral) [16] Grubert, E. and K. Sanders. June 2017. “A National Assessment of the Water Withdrawn and Consumed for the US Energy Economy.” 2017 Joint Conference of the International Society for Industrial Ecology and International Symposium on Sustainable Systems and Technology. Chicago, Illinois. (Oral) [15] Grubert, E. and M. Cook. May 2017. “Communicating Controversial Scientific Issues: Water Use for Oil and Natural Gas.” World Environmental and Water Resources Congress. Sacramento, California. (Poster) [14] Grubert, E. and K. Sanders. December 2016. “Water for Energy: Quantifying Water Use in the United States Energy Economy as of 2014.” American Geophysical Union Fall Meeting. San Francisco, California. (Oral) [13] Jagdeo, J., A. Ravikumar, E. Grubert, and A. Brandt. December 2016. “A Holistic Assessment of Energy Production: Environmental, Economic, and Social Impacts of Hydraulic Fracturing in Williams County, North Dakota.” American Geophysical Union Fall Meeting. San Francisco, California. (Poster) [12] Melby, G., E. Grubert, and A. Brandt. December 2016. “Perceptions of Shale Gas Development: Differences in Urban and Rural Communities.” American Geophysical Union Fall Meeting. San Francisco, California. (Poster)

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[11] Drummond, V., E. Grubert, and A. Brandt. December 2016. “Fault Lines: Seismicity and the Fracturing of Energy Narratives in Oklahoma.” American Geophysical Union Fall Meeting. San Francisco, California. (Poster) [10] Grubert, E. May 2016. “The Dynamic Water Intensity of Hydroelectricity.” World Environmental and Water Resources Congress. West Palm Beach, Florida. (Oral) [9] Cook, M. and E. Grubert. May 2016. “Water Use in the Oil and Gas Industries: Communicating with Scientists, Policymakers, and the Public.” World Environmental and Water Resources Congress. West Palm Beach, Florida. (Poster) [8] Grubert, E. April 2016. “The Water Intensity of Coal Mining in the United States: A Basin Level Evaluation.” American Water Resources Association Spring Specialty Conference. Anchorage, Alaska. (Oral) [7] Grubert, E. December 2015. “Social Priorities as Data.” American Geophysical Union Fall Meeting. San Francisco, California. (Poster) [6] Grubert, E. December 2015. “Empowering Graduate Students to Lead on Interdisciplinary Societal Issues.” American Geophysical Union Fall Meeting. San Francisco, California. (Oral) [5] Grubert, E. and A. Brandt. October 2015. “Methane Leakage in LCA: Quantifying the Effect of Fugitive Methane Emissions on Greenhouse Gas Inventories.” American Center for Life Cycle Assessment LCA XV. Vancouver, Canada. (Oral) [4] Grubert, E. February 2015. “Hearing the Unspoken: Using Text Mining to Investigate Social and Environmental Priorities.” American Association for the Advancement of Science Annual Meeting. San Jose, California. (Poster) [3] Grubert, E. March 2015. “Evaluating Produced Water as a New Source in the United States.” American Water Resources Association Spring Specialty Conference. Los Angeles, California. (Oral) [2] Grubert, E. August 2011. “Modeling Water Supply and Demand on Maui: Forests as a Land Use Category.” Hawaii Conservation Conference. Honolulu, Hawaii. (Oral) [1] Grubert, E. October 2010. “Air Impacting Water: How Carbon Emissions Standards Could Impact West Virginia Water.” West Virginia Water Conference: West Virginia’s Water Resources: Threats and Opportunities. Morgantown, West Virginia. (Oral)

D4. Invited Seminar Presentations [15] Georgia Institute of Technology. GeoSeminar. October 2020. “Decarbonization and a Just Transition in the United States Energy Sector.” Atlanta, GA. (Individual; remote) [14] University of California, Santa Barbara. October 2020. “Energy, Water, and Facilitating Infrastructure Decisions Under Climate Change.” Santa Barbara, CA. (Individual; remote) [13] Stanford University. September 2020. “Macro-Energy Systems: Toward a New Discipline.” Stanford, CA. (Panel; remote)

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[12] Stanford University. May 2020. “Renewable natural gas and climate: The influence of feedstock and methane leakage.” Stanford, CA. (Individual; remote) [11] University of Southern California. February 2020. “Conventional Hydroelectricity and the Energy Transition.” Los Angeles, CA. (Individual) [10] University of Illinois Urbana-Champaign. February 2020. “Conventional Hydroelectricity and the Energy Transition.” Urbana, IL. (Individual) [9] North Carolina State University. November 2019. “Conventional Hydroelectricity and the Grid.” Raleigh, NC. (Individual) [8] North Carolina State University. November 2019. “Power Shift: The Future of Energy and the Women Shaping It.” Raleigh, NC. (Panel) [7] Carnegie Institution for Science Department of Global Ecology. October 2019. “The Energy System is Changing: Industrialization, Deindustrialization, and Adapting What We Have.” Stanford, CA. (Individual) [6] NextProf Nexus. October 2019. “Preparing for the Interview.” Atlanta, Georgia. (Panel) [5] Georgia Institute of Technology. Environmental Engineering Seminar. October 2019. “The Energy System is Changing: Industrialization, Deindustrialization, and Adapting What We Have.” Atlanta, Georgia. (Individual) [4] American Center for Life Cycle Assessment and the International Society for Industrial Ecology. February 2018. “The Need for a Preference-Based Multicriteria Prioritization Framework in Life Cycle Sustainability Assessment.” LCSA Webinar Series. (Individual) [3] Energy Impacts Research Coordination Network. February 2017. “New Voices in Energy Impacts Research: Graduate Research Highlights.” Webinar. (Panel) [2] Yale Climate and Energy Institute, Yale University. February 2013. “Fuel Switching Can Save Water: Freshwater Use for Coal Versus Natural Gas Extraction and Power Generation in Texas.” New Haven, Connecticut. (Individual) [1] Rocky Mountain Institute. January 2011. “The Role of Coal in the United States: Reserves and Externalities.” Boulder, Colorado. (Individual)

D5. Other Presentations [19] Grubert, E. October 2020. “Exploring Civil and Environmental Engineering.” School of Civil and Environmental Engineering, Executive Advisory Board Meeting. Atlanta, Georgia. (Remote) [18] Grubert, E. September 2020. “Life Cycle Assessment.” ENVE 555. San Diego State University. San Diego, California. (Remote)

[17] Grubert, E. June 2020. “Beyond CO2: Water and Methane as Relevant Indicators in a Decarbonizing World.” ZERO Lab. Princeton University. Princeton, New Jersey. (Remote) [16] Grubert, E. May 2020. “Life Cycle Assessment: Sustainability Assessment for Decision Making.” Envres 240. Stanford University. Stanford, California. (Remote)

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[15] Grubert, E. May 2020. “The Powder River Basin Story.” Ad hoc online seminar. Web. [14] Grubert, E. May 2020. “Conventional Hydroelectricity and the Energy Transition.” Emmett Interdisciplinary Program in Environment and Resources Alumni Seminar. Web. [13] Grubert, E. April 2020, July 2020, September 2020. “Coal.” CEE 107A/207A/Earthsys 103. Stanford University. Stanford, California. (Remote, 3x) [12] Grubert, E. April 2020. “How Environmental Policy Opened a Coal District.” EH 590R. Emory University. Atlanta, Georgia. (Remote) [11] Grubert, E. March 2020. “Exploring Civil and Environmental Engineering: Engaging Freshmen Early” (Poster). Celebrating Teaching Day. Georgia Institute of Technology. Atlanta, Georgia. [10] Grubert, E. January 2020. “Life Cycle Assessment: Sustainability Assessment for Decision Making.” ME 4801. Georgia Institute of Technology. Atlanta, Georgia. [9] Grubert, E. October 2019. “Studying Energy Transitions with Geographic Information Systems.” CP 6541. Georgia Institute of Technology. Atlanta, Georgia. [8] Grubert, E. March 2019. “Social Life Cycle Assessment.” ISyE 8803-THO. Georgia Institute of Technology. Atlanta, Georgia. [7] MAP. March 2016. “Water Intensity of Energy Systems: A Major Emerging Policy Issue.” Palo Alto, California. (Individual) [6] United World College USA. February 2016. “Triple Bottom Line Policy Making: How Do We Balance Priorities?” Montezuma, New Mexico. (Individual) [5] United World College USA. February 2016. “Implementation and Activism: Being Effective While Advocating.” Montezuma, New Mexico. (Individual) [4] MAP. March 2015. “The Future of the Energy Industry.” Palo Alto, California. (Panel) [3] Texas Natural Gas Regulatory Modernization Initiative. June 2013. “Natural gas, coal, and water in Texas.” Austin, Texas. (Individual) [2] Grubert, E., A. Fraser, and E. Holland. September 2012. “Thermal Coal Vision 2030: United States Coal.” McKinsey Basic Materials Knowledge Day. Las Vegas, Nevada. [1] Amarillo Area Foundation and Texas Energy Forum. April 2010. “Energy and Water.” Amarillo, Texas. (Individual)

E. GRANTS AND CONTRACTS

E1. AS PRINCIPAL INVESTIGATOR [3] Title of Project: What Can Grids Expect from Conventional Hydroelectricity? Sponsor: Carnegie Institution of Washington Total Dollar Amount: $200,301 Role: PI Collaborators: n/a Period of Contract: 1/1/2020 – 12/31/2022 Candidate’s Share: 100% ($200,301) 14 of 20 Grubert Curriculum Vitae Exhibit EG-1

[2] Title of Project: CPS: Medium: Dynamic Pricing for Optimal Design of Sustainable Transportation Systems Agency/Company: National Science Foundation Total Dollar Amount: $1,018,602 Role: PI Collaborators: Samuel Coogan (Co-PI), Omar Asensio (Co-PI) Period of Contract: 10/1/2019 – 9/30/2022 Candidate’s Share: ~33% ($335,449) [1] Title of Project: What do public comments on environmental regulations reveal about social inequality? A computational analysis Agency/Company: Russell Sage Foundation Total Dollar Amount: $7,668 Role: PI Collaborators: none Period of Contract: 8/1/2019 – 7/31/2020 Candidate’s Share: 100% ($7,668)

E2. AS CO-PRINCIPAL INVESTIGATOR [4] Title of Project: Life Cycle Comparative Study of Pavements from Modified Sulfur Binder Agency/Company: Uberbinder Total Dollar Amount: $114,259 Role: Co-PI Collaborators: Kimberly Kurtis (PI), Francesca Lolli (Co-PI) Period of Contract: 6/15/2020 – 12/15/2021 Candidate’s Share: $12,062 (~10%) [3] Title of Project: Recommendations for Future Specifications to Ensure Durable Next Generation Concrete Agency/Company: Georgia Department of Transportation Total Dollar Amount: $325,000 Role: Co-PI Collaborators: Kimberly Kurtis (PI) Period of Contract: 8/15/2020 – 8/14/2023 Candidate’s Share: $196,500 (60%) [2] Title of Project: FW-HTF-RL: Cultivating Capacities for Responsible Hacking, Creating, and Making the Future of Work in Agriculture Agency/Company: National Science Foundation Total Dollar Amount: $1,996,465 Role: Co-PI Collaborators: Jacqueline Tidwell (PI), Don Edgar (Co-PI) Period of Contract: 10/1/2019 – 9/30/2023 Candidate’s Share: ~20% ($426,144) [1] Title of Project: Designing “Introduction to Civil and Environmental Engineering” Agency/Company: Georgia Institute of Technology (Serve-Learn-Sustain Course Development Funds) Total Dollar Amount: $4,000 Role: Co-PI Collaborators: Kevin Haas (Co-PI) Period of Contract: 4/1/2019 – 6/30/2019 15 of 20 Grubert Curriculum Vitae Exhibit EG-1

Candidate’s Share: 100% ($4,000)

E3. AS SENIOR PERSONNEL OR CONTRIBUTOR [2] Title of Project: IUSE/PFE: RED A&I: Adapting and Implementing Interactive Problem-Driven Learning, Professional and Computational Skills Development for Early and Vertically-Integrated Engagement Agency/Company: National Science Foundation Total Dollar Amount: $1,000,000 Role: Investigator Collaborators: Don Webster (PI), et al. Period of Contract: 9/1/2021 – 8/31/2036 Candidate’s Share: n/a [1] Title of Project: An Integrated Decision Support Tool (i-DST) for Life-Cycle Cost Assessment and Optimization of Green, Grey, and Hybrid Stormwater Infrastructure Agency/Company: Environmental Protection Agency Total Dollar Amount: $1,949,462 Role: subawardee Collaborators: Terri Hogue (PI), Mengistu Geza (co-PI), Christopher Higgins (co- PI), Arpad Horvath (co-PI), John McCray (co-PI), Rob McDonald (co-PI), Jennifer Stokes-Draut (co-PI) Period of Contract: 1/1/2019 – 3/31/2020 Candidate’s Share: ~6% ($110,000)

F. OTHER SCHOLARLY AND CREATIVE ACCOMPLISHMENTS [2] ASCE Plot Points, Season 4, Episode 8: Are Civil Engineers Doing Enough to Combat Climate Change? (Podcast guest) [1] Hames, Mat (Director). 2018. Thirst for Power. Documentary. http://www.imdb.com/title/tt9032352/. (Featured interviewee)

G. SOCIETAL AND POLICY IMPACTS

G1. SELECTED PUBLIC COMMENTS [2] Cullenward, D., M. Mastrandrea, E. Grubert, and A. Strong. March 2016. Use of 20-year GWPs in the Draft Aliso Canyon Methane Leak Climate Impacts Mitigation Program. Comment to the California Air Resources Board. (Written) [1] Grubert, E. April 2014. Testimony Regarding the Mine Methane Capture Carbon Offset Protocol. Meeting of the State of California Air Resources Board. (Oral)

G2. SELECTED PRESS COVERAGE Los Angeles Times (“Boiling Point”), Forbes, ClimateNexus, The Climate Pod, Huffington Post, Resources Radio (Resources for the Future), KQED, MIT Technology Review, Platts, Natural Gas Intel, Houston Chronicle, Scientific American, Environmental Research Web, Eos, Montgomery Herald, Mountain West News Bureau, Tonopah Times-Bonanza, We Are Engineers, The Alcalde, Texas Clean Energy Coalition, Washington Post

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G3. SELECTED PRESS QUOTES Los Angeles Times, National Geographic, E&E News, DeSmog Blog, Gizmodo, Salon, Mashable

G4. SELECTED USE OF RESEARCH IN POLICY Comment Re: Formal Case No. 1142 by the Apartment and Office Building Association of Metropolitan Washington

H. OTHER PROFESSIONAL ACTIVITIES 2020-presEnvision Sustainability Professional (ENV SP) (#35373) 2020 Project Consultant, CarbonPlan, San Francisco, California 2016, 18 Project Consultant, Lineage Logistics, Irvine, California 2014-15 Project Consultant, SandRidge Energy, Oklahoma City, Oklahoma 2013-14 Project Consultant, Energy Innovation, San Francisco, California 2013 Project Analyst, Pacific Gas and Electric 2011-presEngineer-in-Training, Environmental Engineering (#45743) 2009-presLeadership in Energy and Environmental Design (LEED) Accredited Professional, Building Design and Construction

V. EDUCATION

A. COURSES TAUGHT

A1. Georgia Tech Fall, 2020 CEE 2803 Exploring CEE 48 Spring, 2020 CEE 8813 Sustainable Buildings 14 Fall, 2019 CEE 2803 Exploring CEE 24

A2. Berkeley Spring, 2018 CE 268s Buildings and Sustainability 25

A3. Stanford Fall, Spring, 2015-18 CEE 107a/207a Understanding Energy 30-150 Summer, 2014-17 CEE 107s Energy Resources: Fuels and Tools 20-40 Winter, 2017 Envres 340 E-IPER PhD Writing Seminar 8 Fall, 2016 Envres 276 Water Resources: 6 Culture and Context Winter, 2015 Envres 275 The Practice of Mining and its 10 Social and Environmental Context

B. INDIVIDUAL STUDENT GUIDANCE

B1. Ph.D. Students Cohen, Abigail. Spring 2020-present. Graduation date: Spring 2023 (expected). Project: TBD. Co-advisor: Yongsheng Chen. 17 of 20 Grubert Curriculum Vitae Exhibit EG-1

Maxim, Alexandra. Fall 2019-present. Graduation date: Spring 2023 (expected). Project: TBD. Recipient: Robert Wood Johnson Foundation Health Policy Research Scholar Fellowship, Sloan Foundation Fellowship. Dean, Victoria. Summer 2019-present. Currently on leave. Project: The Development of Localized Social Life Cycle Assessment Indicators in Relation to Childhood Health and Education to Inform Future Atlanta Beltline Development. Recipient: Robert Wood Johnson Foundation Health Policy Research Scholar Fellowship. Ha, Sooji. Spring 2019-present. Graduation date: Spring 2021 (expected). Project: Detecting Behavioral Failures in Emerging Electric Vehicle Infrastructure Using Supervised Text Classification Algorithms. Co-advisor: Omar Asensio.

B2. M.S. Students Lyford, Kelsey. Fall 2019-present. Thesis: no. Descartes, Jamen. Fall 2019-present. Thesis: no. Burns, Diana. Fall 2019-present. Project: How Different are US Natural Gas Basins? Spatially Resolved Life Cycle Greenhouse Gas Emissions from Natural Gas. Thesis: yes. Recipient: Georgia Power Fellowship. Krieger, Jennifer. Spring 2019-Fall 2019. Project: Life Cycle Costing for Green Stormwater Infrastructure for the integrated Decision Support Tool (iDST). Thesis: yes.

B3. Undergraduate Students Molnar, Clara. Spring 2021. Undergraduate Research Assistant, Georgia Institute of Technology. Zacarias, Mathias. Summer 2020-present. Undergraduate Research Assistant, Georgia Institute of Technology. Gali, Manasi. Spring 2020; Fall 2020. Undergraduate Research Assistant, Georgia Institute of Technology. Gardner, Anna. Fall 2019. Undergraduate Research Assistant, Georgia Institute of Technology. Brown, Robert. Spring/Summer 2019. Undergraduate Research Assistant, Georgia Institute of Technology. Groenke, Alexa. Spring 2018. Undergraduate Research Assistant, University of California, Berkeley Drummond, Virginia. Summer 2016. Undergraduate Research Assistant, Stanford University Melby, Grayson. Summer 2016. Undergraduate Research Assistant, Stanford University Suganuma, Jade. Summer 2016. Undergraduate Research Assistant, Drake University Herring, Noelle. 2015-2016. Undergraduate Research Assistant, Stanford University Rey, Lindsey. 2010-2011. Undergraduate Research Assistant, The University of Texas at Austin 18 of 20 Grubert Curriculum Vitae Exhibit EG-1

B4. Service on thesis or dissertation committees Santoyo, Cesar. Graduation date: Expected Fall 2021. Project: Probabilistic analysis and control methods for electric vehicle charging. Advisor: Sam Coogan. Broesicke, Osvaldo. Graduation date: Expected Spring 2022. Project: Multidisciplinary design optimization for energy systems design: Evaluating the trade-offs between a centralized and distributed energy infrastructure for cities in the United States. Advisor: John Crittenden. Francisco, Abigail. Graduation date: Summer 2020. Project: Urban Energy Informatics: Improving the Usability of Building Energy Data for Community Energy Efficiency. Advisor: John Taylor. Samuels, Rachel. Graduation date: Summer 2020. Project: Identifying, Defining, and Utilizing Sociospatial Variances in Social Media Usage to Improve Crisis Response and Urban Resilience. Advisor: John Taylor. Jin, Qingxu. Graduation date: Fall 2019. Project: “Fundamental Understanding of NOx Sequestration Capacity and Pathways in Nano-TiO2 Engineered Cementitious Materials.” Advisor: Kim Kurtis.

B5. Mentorship of postdoctoral fellows or visiting scholars Mulrow, John. 2020-2021.

VI. SERVICE

A. PROFESSIONAL CONTRIBUTIONS 2020-pres. Editorial Board Member, Environmental Research: Infrastructure and Sustainability 2020-pres. Associate Editor, Journal of Environmental Studies and Sciences 2020 Steering Committee Member, Macro-Energy Systems Workshop 2020-2021 Vice Chair, Sustainability Committee, Interdisciplinary Council, Environmental and Water Resources Institute of the American Society of Civil Engineers 2020 Panel Reviewer, National Science Foundation, Directorate for Computer and Information Science and Engineering (CISE) 2019-pres. Editorial Board Member, IOP SciNotes (IOPSN) 2019-2020 Secretary, Sustainability Committee, Interdisciplinary Council, Environmental and Water Resources Institute of the American Society of Civil Engineers 2018-pres. Advisory Board Member, Environmental Research Letters 2018-2019 Program Committee, International Conference on Sustainable Infrastructure (ICSI) 2019: Sustainable Cities for an Uncertain World, American Society of Civil Engineers 2016-pres. Member, Environmentally Responsible Energy Production (formerly Hydraulic Fracturing) Technical Committee, Interdisciplinary Council,

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Environmental and Water Resources Institute of the American Society of Civil Engineers ongoing Journal Referee, Science, Environmental Science & Technology, Environmental Research Letters, Water Resources Research, Journal of Industrial Ecology, Energy Research and Social Science, Society and Natural Resources, Journal of Water Resources Planning and Management, others

B. INSTITUTE CONTRIBUTIONS 2020-pres. Civil and Environmental Engineering Committee on Diversity and Inclusion Faculty Representative (School Level) 2020 College of Engineering Dean Search Committee Member (College level) 2019-pres. Construction and Infrastructure Systems Engineering Representative, Undergraduate Committee (School level) 2019 OceanVisions2019 Session Co-chair (School level)

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Exhibit EG – 2

Exhibit EG-2

Date of Request: October 1, 2020 Request No. SC-011 Due Date: October 12, 2020 NMPC Req. No. NM-999

NIAGARA MOHAWK POWER CORPORATION d/b/a NATIONAL GRID Case Nos. 20-E-0380 and 20-G-0381 Electric and Gas Rates

Request for Information

FROM: Sierra Club, Joshua Berman

TO: National Grid, Future of Heat Panel

SUBJECT: Future of Heat

Request:

Note: The following information request pertains to the gas filings for 20-G-0381.

11. Referring to the Future of Heat Panel testimony’s discussion of RNG, has the Company conducted any analysis of the lifecycle greenhouse gas emissions associated with the various forms of locally sourced RNG? If so, please provide all such analyses.

Response:

RNG represents a renewable energy source with a low or net negative emissions factor depending on the feedstock and the GHG accounting framework. GHG emissions accounting becomes complex when an assessment includes various feedstocks across various sectors and various scopes of emissions. To understand the issues and complexities associated with GHG protocols and accounting frameworks, the Company was part of a national industry effort that hired ICF to assess the availability of RNG by feedstock in each region of the country and how to think through emission accounting of RNG. The American Gas Foundation released the study in December 2019. A copy of the study is included in Attachment 1.

More work in this area is still required, and the Company is committed to developing a methodology over time to quantify emissions associated with RNG.

Name of Respondent: Date of Reply: Donald Chahbazpour October 9, 2020

Form 103 Niagara Mohawk Power Corporation d/b/a National Grid Exhibit EG-2 Cases 20-E-0380 and 20-G-0381 SC-011 Attachment 1 Page 1 of 80

December 2019

RENEWABLE SOURCES OF NATURAL GAS: SUPPLY AND EMISSIONS REDUCTION ASSESSMENT

An American Gas Foundation Study Prepared by:

Niagara Mohawk Power Corporation d/b/a National Grid Exhibit EG-2 Cases 20-E-0380 and 20-G-0381 SC-011 Attachment 1 Page 2 of 80

Legal Notice This report was prepared for the American Gas Foundation, with the assistance of its contractors, to be a source of independent analysis. Neither the American Gas Foundation, its contractors, nor any person acting on their behalf: § Makes any warranty or representation, express or implied with respect to the accuracy, completeness, or usefulness of the information contained in this report, or that the use of any information, apparatus, method, or process disclosed in this report may not infringe privately-owned rights, § Assumes any liability, with respect to the use of, damages resulting from the use of, any information, method, or process disclosed in this report, § Recommends or endorses any of the conclusions, methods or processes analyzed herein. References to work practices, products or vendors do not imply an opinion or endorsement of the American Gas Foundation or its contractors. Use of this publication is voluntary and should be taken after an independent review of the applicable facts and circumstances. Copyright © American Gas Foundation, 2019.

American Gas Foundation (AGF) Founded in 1989, the American Gas Foundation (AGF) is a 501(c)(3) organization focused on being an independent source of information research and programs on energy and environmental issues that affect public policy, with a particular emphasis on natural gas. When it comes to issues that impact public policy on energy, the AGF is committed to making sure the right questions are being asked and answered. With oversight from its board of trustees, the foundation funds independent, critical research that can be used by policy experts, government officials, the media and others to help formulate fact-based energy policies that will serve this country well in the future.

ICF ICF (NASDAQ:ICFI) is a global consulting services company with over 7,000 full- and part-time employees, but we are not your typical consultants. At ICF, business analysts and policy specialists work together with digital strategists, data scientists and creatives. We combine unmatched industry expertise with cutting-edge engagement capabilities to help organizations solve their most complex challenges. Since 1969, public and private sector clients have worked with ICF to navigate change and shape the future. Learn more at icf.com.

Niagara Mohawk Power Corporation d/b/a National Grid Exhibit EG-2 Cases 20-E-0380 and 20-G-0381 SC-011 Attachment 1 Page 3 of 80 Renewable Sources of Natural Gas: Supply and Emissions Reduction Assessment

Table of Contents Executive Summary ...... 1 Introduction ...... 6 RNG Production Technologies ...... 6 RNG Feedstocks ...... 7 Resource Assessment Scenarios ...... 7 Review of Previous Work ...... 7 Regional RNG Resource Assessment ...... 9 Summary of RNG Potential ...... 10 RNG: Anaerobic Digestion of Biogenic or Renewable Resources ...... 16 RNG: Thermal Gasification of Biogenic or Renewable Resources ...... 29 Renewable gas from MSW ...... 36 RNG from P2G/Methanation ...... 38 Greenhouse Gas Emissions of RNG ...... 44 GHG Accounting Framework and Methodology ...... 44 GHG Emissions from RNG Resource Assessment ...... 46 RNG Cost Assessment ...... 50 RNG from Anaerobic Digestion ...... 52 RNG from Thermal Gasification ...... 56 RNG from Power-to-Gas / Methanation ...... 57 Combined Supply Curves ...... 60 GHG Cost-Effectiveness ...... 61 Key Findings ...... 62 Appendix A—Resource Assessment by State ...... 64 Appendix B—GHG Emissions using Lifecycle Analysis Approach ...... 70

i

Niagara Mohawk Power Corporation d/b/a National Grid Exhibit EG-2 Cases 20-E-0380 and 20-G-0381 SC-011 Attachment 1 Page 4 of 80 Renewable Sources of Natural Gas: Supply and Emissions Reduction Assessment

List of Tables Table 1. Summary of Feedstocks Considered for RNG Production ...... 7 Table 2. Summary of RNG Potential from 2011 AGF Study in units of tBtu/year ...... 8 Table 3. Summary of Feedstock Utilization in the Low and High Resource Potential Scenarios ...... 11 Table 4. Low Resource Potential for RNG in 2040, tBtu/y ...... 13 Table 5. High Resource Potential for RNG in 2040, tBtu/y ...... 14 Table 6. Technical Resource Potential for RNG in 2040, tBtu/y ...... 15 Table 7. Landfill Gas Constituents and Corresponding Upgrading Technologies ...... 16 Table 8. Number of Candidate Landfills by Census Region ...... 17 Table 9. Landfill to Energy Projects and Candidate Landfills by Census Region ...... 17 Table 10. Annual RNG Potential from Landfills in 2040, tBtu/y ...... 19 Table 11. Key Parameters to Determine Animal Manure Resource for RNG Production ...... 20 Table 12. Summary of AgStar Projects at Farms using AD Systems, by Census Region ...... 21 Table 13. Annual RNG Production Potential from Animal Manure in 2040, tBtu/y ...... 22 Table 14. Number of WRRFs by Census Region ...... 23 Table 15. Total Flow (in MGD) of WRRFs by Census Regions ...... 24 Table 16. WRRFs with Anaerobic Digesters, by Census Regions ...... 24 Table 17. Annual RNG Production Potential from WRRFs in 2040, tBtu/y ...... 26 Table 18. Annual RNG Production Potential from Food Waste in 2040, tBtu/y ...... 28 Table 19. Heating Values for Agricultural Residues ...... 30 Table 20. Annual RNG Production Potential from Agricultural Residues in 2040, tBtu/y ...... 31 Table 21. Heating Values for Forestry and Forest Product Residues ...... 32 Table 22. Annual RNG Production Potential from Forestry and Forest Product Residues, tBtu/y ...... 34 Table 23. Heating Values for Energy Crops ...... 34 Table 24. Annual RNG Production Potential from Energy Crops, tBtu/y ...... 35 Table 25. Heating Values for MSW Components ...... 36 Table 26. Annual RNG Production Potential from MSW, tBtu/y ...... 37 Table 27. Renewable Share of Electricity Generation in RPS-Compliant Run using IPM ...... 41 Table 28. Annual H2 and RNG Production (in tBtu /y) from P2G using Dedicated Renewable Electricity Generation, 2025-2040 ...... 43 Table 29. GHG Emission Reductions (in MMT) for RNG in the Low Resource Potential Case ...... 48 Table 30. GHG Emission Reductions (in MMT) for RNG in the High Resource Potential Case ...... 49 Table 31. Illustrative Cost Assumptions Developed to Estimate RNG Production Costs in 2040 ...... 50 Table 32. Cost Consideration in Levelized Cost of Gas Analysis for RNG from Landfill Gas ...... 52 Table 33. Cost Consideration in Levelized Cost of Gas Analysis for RNG from Animal Manure ...... 54 Table 34. Cost Consideration in Levelized Cost of Gas Analysis for RNG from WRRFs ...... 54 Table 35. Cost Consideration in Levelized Cost of Gas Analysis for RNG from Food Waste ...... 55 Table 36. Average Tipping Fee by Region ...... 56 Table 37. Cost Consideration in Levelized Cost of Gas Analysis for RNG from Thermal Gasification ...... 57 Table 38. Low Resource Potential for RNG in 2040, tBtu/y, by State ...... 64 Table 39. High Resource Potential for RNG in 2040, tBtu/y, by State ...... 66 Table 40. Technical Resource Potential for RNG in 2040, tBtu/y, by State ...... 68 Table 41. Range of Lifecycle GHG Emission Factors for RNG from Different Feedstocks and Regions (in units of g/MJ) ...... 72 Table 42. GHG Emission Reductions (in MMT) for RNG in the Low Resource Case ...... 73 Table 43. GHG Emission Reductions (in MMT) for RNG in the High Resource Case ...... 74 ii

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List of Figures Figure 1. Estimated Annual RNG Production, Low Resource Potential Scenario, tBtu/y ...... 3 Figure 2. Estimated Annual RNG Production, High Resource Potential Scenario, tBtu/y ...... 3 Figure 3. Average Annual CO2 Emissions (in MMT) from Natural Gas Consumption, 2009-2018 ...... 4 Figure 4. U.S. Census Regions ...... 9 Figure 5. Estimated Annual RNG Production, Low Resource Potential Scenario, tBtu/y ...... 10 Figure 6. Estimated Annual RNG Production, High Resource Potential Scenario, tBtu/y ...... 11 Figure 7. RNG Technical Resource Potential vs Average Domestic Natural Gas Consumption in Different End Uses, 2009-2018 (in tBtu/y) ...... 12 Figure 8. RNG Production Potential from Landfill Gas, Low Resource Potential Scenario, in tBtu/y ...... 18 Figure 9. RNG Production Potential from Landfill Gas, High Resource Potential Scenario, in tBtu/y ...... 19 Figure 10. RNG Production Potential from Animal Manure, Low Resource Potential Scenario, in tBtu/y ...... 22 Figure 11. RNG Production Potential from Animal Manure, High Resource Potential Scenario, in tBtu/y ...... 22 Figure 12. RNG Production Potential from WRRFs, Low Resource Potential Scenario, in tBtu/y ...... 26 Figure 13. RNG Production Potential from WRRFs, High Resource Potential Scenario, in tBtu/y ...... 26 Figure 14. RNG Production Potential from Food Waste, Low Resource Potential Scenario, in tBtu/y ...... 28 Figure 15. RNG Production Potential from Food Waste, High Resource Potential Scenario, in tBtu/y ...... 28 Figure 16. RNG Production Potential from Agricultural Residue, Low Resource Potential Scenario, in tBtu/y 31 Figure 17. RNG Production Potential from Agricultural Residue, High Resource Potential Scenario, in tBtu/y ...... 31 Figure 18. RNG Production Potential from Forestry and Forest Product Residues, Low Resource Potential Scenario, in tBtu/y ...... 33 Figure 19. RNG Production Potential from Forestry and Forest Product Residues, High Resource Potential Scenario, in tBtu/y ...... 33 Figure 20. RNG Production Potential from Energy Crops, Low Resource Potential Scenario, in tBtu/y ...... 35 Figure 21. RNG Production Potential from Energy Crops, High Resource Potential Scenario, in tBtu/y ...... 35 Figure 22. RNG Production Potential from Non-Biogenic MSW, Low Resource Potential Scenario, in tBtu/y . 37 Figure 23. RNG Production Potential from Non-Biogenic MSW, High Resource Potential Scenario, in tBtu/y 37 Figure 24. Supply-Cost Curve for Dedicated Renewable Electricity for P2G Systems, 2025-2040 ...... 41 Figure 25. Assumed Efficiency for Electrolysis and Methanation, 2020-2040 ...... 42 Figure 26. Scopes for categorizing emissions under the GHG Protocol (GHG Protocol 2019)...... 45 Figure 27. Overview of GHG Accounting Frameworks for RNG ...... 46 Figure 28. Average Annual Carbon Dioxide Emissions (in MMT) from Natural Gas Consumption in the U.S. 2009-2018 ...... 47 Figure 29. Supply-Cost Curve for RNG from Landfill Gas ($/MMBtu vs tBtu) ...... 53 Figure 30. Installed Capacity Cost of Electrolyzers, $/kW, 2020-2040 ...... 58 Figure 31. Installed Capacity Cost of Methanator, $/kW, 2020-2040 ...... 59 Figure 32. Assumed Efficiency for Electrolysis and Methanation, 2020-2040 ...... 59 Figure 33. Estimated RNG costs from P2G / Methanation ($/MMBtu) as a function of installed capacity of P2G systems ...... 60 Figure 34. Combined RNG Supply-Cost Curve, less than $20/MMBtu in 2040 ...... 60 Figure 35. Summary of carbon intensities for transportation fuels across life-cycle stages (ANL 2019)...... 70 Figure 36. Life-cycle carbon intensity for RNG grouped by different GHG Protocol scopes using GREET results...... 71

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Executive Summary Renewable natural gas (RNG) is derived from biomass or other renewable resources, and is a pipeline-quality gas that is fully interchangeable with conventional natural gas. The American Gas Association (AGA) uses the following definition for RNG:

Pipeline compatible gaseous fuel derived from biogenic or other renewable sources that has lower lifecycle carbon dioxide equivalent (CO2-eq) emissions than geological natural gas. ICF conducted an assessment to outline the potential for RNG to contribute meaningfully and cost- effectively to greenhouse gas (GHG) emission reduction initiatives across the country. The report serves as an update and expansion to a 2011 report published by the American Gas Foundation (AGF) entitled The Potential for Renewable Gas: Biogas Derived from Biomass Feedstocks and Upgraded to Pipeline Quality. Building upon the previous work, this report is focused on assessing a) the RNG production potential from various feedstocks, b) the corresponding GHG emission reduction potential, and c) the estimated costs of bringing RNG supply on to the system. ICF developed production potential estimates by incorporating a variety of constraints regarding accessibility to feedstocks, the time that it would take to deploy projects over the timeline of the study (out to 2040), the development of technology that would be required to achieve higher levels of RNG production, and consideration of likely project economics—with the assumption that the most economic projects will come online first. ICF developed low and high resource potential scenarios by considering RNG production from nine (9) feedstocks and three production technologies. The feedstocks include landfill gas, animal manure, water resource recovery facilities (WRRFs), food waste, agricultural residues, forestry and forest product residues, energy crops, the use of renewable electricity, and the non-biogenic fraction of municipal solid waste (MSW).1 These feedstocks were assumed to be processed using one of three technologies to produce RNG, including anaerobic digesters, thermal gasification systems, and power-to-gas (P2G) in combination with a methanation system. It is important to note that ICF’s analysis is not meant to be prescriptive, rather illustrative in terms of how the market for RNG production potential might evolve given our understanding of the feedstocks that can be used and the current state of technology development. Consider for instance that many anaerobic digester projects use a combination of animal manure and agricultural residues as feedstocks—the analysis presented here only considers the anaerobic digestion of animal manure and the thermal gasification of agricultural residues. ICF recognizes that these type of multi- feedstock considerations will continue to exist in the market; however, we needed to make simplifying distinctions for the purposes of the resource assessment. ICF estimated low and high resource potential scenarios by considering constraints unique to each potential RNG feedstock—these constraints were based on factors such as feedstock accessibility and the economics of RNG production using the feedstock. These constraints were then used to develop low and high utilization assumptions regarding each feedstock. The resource potential reported is also a function of the conversion efficiency of the production technology to which each

1 ICF notes that the non-biogenic fraction of MSW does not satisfy AGA’s definition of RNG; however, this feedstock was included in the analysis. The results associated with RNG potential from this non-biogenic fraction of MSW are called out separately throughout the report for the sake of transparency. 1

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feedstock is paired. ICF also presents a technical resource potential, which does not consider accessibility or economic constraints. The resource assessment was conducted using a combination of national-, state-, and regional-level information regarding the availability of different feedstocks; and the information is presented using the nine (9) U.S. Census Regions. In the low resource potential scenario, ICF estimates that about 1,660 trillion Btu (tBtu) of RNG can be produced annually for pipeline injection by 2040 (see Figure 1 below). That estimate increases to 1,910 tBtu per year when including the potential for the non-biogenic fraction of MSW. In the high resource potential scenario, ICF estimates that about 3,780 tBtu of RNG can be produced annually for pipeline injection by 2040 (see Figure 2 below). That estimate increases to 4,510 tBtu per year when including the potential for the non-biogenic fraction of MSW. For the sake of comparison, ICF notes that the 10-year average (2009 to 2018) for residential natural gas consumption nationwide is 4,846 tBtu; this is shown as the black-dotted line in Figure 1 and Figure 2 below. Ultimately, market conditions, technology development, and policy structures will determine the extent to which each of the feedstocks considered can be utilized. For the sake of reference, ICF also reports a technical resource potential scenario of nearly 13,960 tBtu—a production potential intended to reflect the RNG production potential without any technical or economic constraints. The reported RNG resource potential estimates reported here are 90% and 180% increases from the comparable resource potential scenarios from 2011 AGF Study. These changes are largely attributable to improved access to data regarding potential feedstocks for RNG production and are generally not attributable to more aggressive assumptions regarding feedstock utilization or conversion efficiencies. Furthermore, the analysis presented here includes estimates for RNG production from P2G systems using dedicated renewable electricity. While there are multiple studies regarding P2G technology and its uses, we believe this is the first study to quantify RNG production potential nationwide from P2G. A diverse array of resources can contribute to RNG production—there is a portfolio of potential feedstocks and technologies that are or will be commercialized in the near-term future that will help realize the potential of the RNG market. Figure 1 and Figure 2 below demonstrate the diversity of RNG resource potential as a GHG emission reduction strategy. On the technology side, most RNG continues to be produced using anaerobic digestion paired with conditioning and upgrading systems. The post-2025 outlook for RNG will increasingly rely on thermal gasification of sustainably harvested biomass, including agricultural residues, forestry and forest product residues, and energy crops. The long-term outlook for RNG growth will depend to some extent on technological advancements in power-to-gas systems.2

2 The RNG potential for P2G/methanation is shown as a pattern fill in Figure 1 and Figure 2 because of the way ICF estimates likely project economics for P2G. In reality, however, the low and high resource potential for P2G using dedicated renewable electricity will be constrained by more factors that could be considered in this report; and it is conceivable that the RNG resource potential from P2G is considerably higher than considered here. 2

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Figure 1. Estimated Annual RNG Production, Low Resource Potential Scenario, tBtu/y

5,000 P2G/Methanation

4,500 MSW

4,000 Energy Crops 3,500 Forest Residue 3,000 Ag Residue 2,500 Food Waste 2,000 WRRF 1,500 Animal Manure

Annual RNG Production(tBtu/y) 1,000 Landfill Gas 500

0 NG Residential Consumption, 2025 2030 2035 2040 10-yr avg

Figure 2. Estimated Annual RNG Production, High Resource Potential Scenario, tBtu/y

5,000 P2G/Methanation

4,500 MSW

4,000 Energy Crops 3,500 Forest Residue 3,000 Ag Residue 2,500 Food Waste 2,000 WRRF 1,500 Animal Manure

Annual RNG Production(tBtu/y) 1,000 Landfill Gas 500

0 NG Residential Consumption, 2025 2030 2035 2040 10-yr avg

The potential for power-to-gas systems as a contributor to RNG production could be significant. Power-to-gas (P2G) is a form of energy technology that converts electricity to a gaseous fuel. Electricity is used to split water into hydrogen and oxygen, and the hydrogen can be further processed to produce methane when combined with a source of carbon dioxide. If the electricity is sourced from renewable resources, such as wind and solar, then the resulting fuels are carbon neutral. In this study, ICF made the simplifying assumption that all hydrogen produced via P2G would be methanated for pipeline injection. This assumption should not be viewed as a determination of the best use of hydrogen as an energy carrier in the future; rather, it was a 3

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simplifying assumption to compare more easily P2G to other potential RNG resources evaluated in this study. ICF generally finds that the potential for RNG deployment could exceed the estimated high resource potential scenario because we opted to employ moderately conservative assumptions regarding the expected utilization of various feedstocks. These assumptions manifest themselves as constraints on the availability of supply for each feedstock, recognizing there will likely be competition for each feedstock. It is important to note that ICF did not make any assumptions regarding a specific policy or incentive framework that would favor RNG production over some other energy source (e.g., liquid biofuels). Excluding cost considerations, the deployment of P2G systems for RNG production requires assumptions across a variety of factors, including but not limited to access to renewable electricity, the corresponding capacity factor of the system given the intermittency of renewable electricity generation from some sources (e.g., solar and wind), co-location with (presumably affordable) access to carbon dioxide for methanation, and reasonable proximity to a natural gas pipeline for injection. ICF’s analysis did not seek to address all of these project development considerations; rather, we sought to understand the potential for P2G systems assuming access to dedicated renewable electricity production, meaning that these are purpose-built renewable electricity generation systems that are meant to provide dedicated power to P2G systems. ICF did not explicitly consider renewable electricity that could be curtailed from over-supply of renewable electricity as a result of compliance with Renewable Portfolio Standards (RPS). Ultimately, the issue of curtailment is a complicated one, and exploring it in detail was beyond the scope of this analysis. However, ICF’s initial assessment indicates that P2G systems running on curtailed renewable electricity will play an important transitional role in helping to deploy the technology and achieve the long-term price reductions that are required to improve the viability of P2G as a cost- effective pathway for RNG production. Despite the importance of curtailed renewable electricity as part of the transition towards more cost-effective P2G systems, ICF’s analysis does focus more on the opportunity for, and associated costs of RNG production using P2G systems with dedicated renewable electricity generation. It is important that this assumption by ICF is recognized as a limitation of our analysis, rather than a commentary on how the market will ultimately develop for P2G systems. ICF estimates that RNG deployment could achieve 101 to 235 million metric tons (MMT) of GHG emission reductions by 2040. The GHG emission reductions were calculated using IPCC guidelines stating that emissions from biogenic fuel Figure 3.Average Average CO AnnualEmissions CO2 Emissions(MMT) from (in MMT) sources should not be included when accounting from Natural Gas2 Consumption, 2009-2018 Natural Gas Consumption, 2009-2018 for emissions in combustion. This accounting Residential approach is employed to avoid any upstream Electric Gen 248 “double counting” of emissions that occur in the 466 agricultural or land-use sectors per IPCC guidance. Generally speaking, biogenic carbon in combustion is excluded from carbon accounting Commercial 170 methodologies because it is assumed that the carbon sequestered by the biomass during its lifetime offsets emissions that occur during Industrial combustion. Figure 3 shows the 10-year average 392 (2009-2018) of carbon dioxide (CO2) emissions from natural gas consumption across multiple sectors; and most notably that the residential 4

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energy sector on average emitted about 248 MMT of CO2 emissions nationwide over the 10-years considered. GHG emission reductions attributable to RNG can be a complicated issue driven by different accounting systems. Although we focus on the GHG emission reductions potential using IPCC guidelines in this report, many stakeholders are likely familiar with the lifecycle accounting approach for GHG emissions that is used by California’s Low Carbon Fuel Standard (LCFS) program. In that accounting system, the GHG emissions from production and processing to combustion are accounted for—and fuels like RNG sourced from animal manure generally have a negative emissions factor, which reflects the upstream “crediting” of capturing methane that would have otherwise been vented to the atmosphere. ICF addresses these various accounting systems, and reviews the GHG emission reductions under a lifecycle accounting framework in an appendix. ICF estimates that the majority of the RNG produced in the high resource potential scenario is available in the range of $7-$20/MMBtu, which results in a cost of GHG emission reductions between $55/ton to $300/ton in 2040. ICF evaluated the potential costs associated with the deployment of each feedstock and technology pairing, and made assumptions about the sizing of systems that would need to be deployed to achieve the RNG production potential outlined in the low and high resource potential scenarios. ICF reports that RNG will be available from various feedstocks in the range of $7/MMBtu to $45/MMBtu. These costs are dependent on a variety of assumptions, including feedstock costs, the revenue that might be generated via byproducts or other avoided costs, and the expected rate of return on capital investments. ICF finds that there is potential for cost reductions as the RNG for pipeline injection market matures, production volumes increase, and the underlying structure of the market evolves. As noted previously, the opportunity of RNG from P2G systems (and paired with methanation units) warrants further consideration; however, ICF’s analysis demonstrates that the combination of production potential and potential cost reductions for P2G systems is promising. With respect to RNG from P2G, the three main drivers for the production costs include: a) the electrolyzer, b) the cost of renewable electricity, and c) the cost of methanation. ICF finds that there is significant cost reduction potential in the P2G market, as the installed capacity (measured in GW, for instance) for electrolyzers increases over the next 10-15 years. ICF assumed that dedicated renewable electricity systems, co-located with P2G systems, could provide electricity at a levelized cost in the range of $10 to $55 per MWh. Lastly, there is significant cost reduction potential for methanation paired with P2G systems.

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Introduction Renewable natural gas (RNG) is derived from biomass or other renewable resources, and is a pipeline-quality gas that is fully interchangeable with conventional natural gas. The American Gas Association uses the following definition for RNG: Pipeline compatible gaseous fuel derived from biogenic or other renewable sources that has lower lifecycle carbon dioxide equivalent (CO2e) emissions than geological natural gas. The primary objective of this report is to characterize the resource and economic potential for RNG as a greenhouse gas (GHG) emission reduction strategy. Further, this report seeks to improve policy makers’ understanding of the extent to which delivering RNG to all sectors of the economy can contribute to broader GHG emission reduction initiatives. The following sub-sections introduce the RNG production technologies and corresponding feedstocks. ICF assessed the production potential for renewable gas into three categories: 1) RNG from renewable feedstocks using anaerobic digestion (AD) and thermal gasification (TG), 2) RNG derived from municipal solid waste (MSW),3 and 3) RNG produced via combination power-to-gas (P2G) and methanation. For each resource and production technology pairing, ICF estimated the production cost and corresponding range of GHG emissions. RNG Production Technologies RNG is produced over a series of steps–namely collection of a feedstock, delivery to a processing facility for biomass-to-gas conversion, gas conditioning, compression, and interconnection and injection into the pipeline. § The most common way to produce RNG today is via anaerobic digestion, whereby microorganisms break down organic material in an environment without oxygen. In the context of RNG production, the process generally takes place in a controlled environment, referred to as a digester or reactor. When organic material is introduced to the digester, it is broken down over time (e.g., days) by microorganisms, and the gaseous products of that process contain a large fraction of methane and carbon dioxide, sometimes referred to as biogas. The biogas is subsequently upgraded and conditioned to yield biomethane, and injected into the common carrier pipeline. § The thermal gasification of biomass also produces RNG—this includes a broad range of processes whereby a carbon containing feedstock is converted into a mixture of gases referred to as synthetic gas or syngas, including hydrogen, carbon monoxide, steam, carbon dioxide, methane, and trace amounts of other gases. This process generally occurs at high temperatures and varying temperatures (depending on the gasification system). § Lastly, this assessment considers RNG produced using renewable electricity (as a feedstock) to generate hydrogen via electrolysis, which is methanated for subsequent injection into the pipeline—this process is referred to as power-to-gas (P2G).

3 Gas produced from the thermal gasification of MSW does not satisfy AGA’s definition of RNG because it is not from a biogenic or renewable source; however, it does have lower lifecycle CO2e emissions than geological natural gas. As a result, MSW as a resource was assessed in this study, but is presented separately from the other feedstocks considered. 6

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RNG Feedstocks RNG can be produced from a variety of renewable feedstocks, as described in Table 1 below. More information about each feedstock and its corresponding contribution to the RNG resource potential is included in Section 0. Table 1. Summary of Feedstocks Considered for RNG Production Feedstock for RNG Description

The anaerobic digestion of organic waste in landfills produces a mix of Landfill gas (LFG) gases, including methane (40-60%).

Manure produced by livestock, including dairy cows, beef cattle, swine, Animal manure sheep, goats, poultry, and horses. Wastewater consists of waste liquids and solids from household, Water Resource Recovery commercial, and industrial water use; in the processing of wastewater, a Facilities (WRRF) sludge is produced, which serves as the feedstock for RNG.

Anaerobic digestion Commercial food waste, including from food processors, grocery stores, Food waste cafeterias, and restaurants, as well as residential food waste, typically collected as part of waste diversion programs. The material left in the field, orchard, vineyard, or other agricultural setting Agricultural residue after a crop has been harvested. Inclusive of unusable portion of crop, stalks, stems, leaves, branches, and seed pods.

Biomass generated from logging, forest and fire management activities, Forestry and forest and milling. Inclusive of logging residues, forest thinnings, and mill product residue residues. Also materials from public forestlands, but not specially designated forests (e.g., roadless areas, national parks, wilderness areas). Inclusive of perennial grasses, trees, and some annual crops that can be Energy crops grown specifically to supply large volumes of uniform, consistent quality feedstocks for energy production. Thermal Gasification Refers to the non-biogenic fraction of waste that would be landfilled after Municipal solid waste diversion of other waste products (e.g., food waste or other organics), (MSW) including construction and demolition debris, plastics, etc.

Renewable electricity (presumably excess generation thereof) serves as Renewable electricity feedstock for P2G technologies. P2G produces hydrogen, which can then P2G be blended directly into the pipeline or methanated.

Resource Assessment Scenarios ICF developed three scenarios for each feedstock—with variations between a low resource and high resource scenario regarding utilization of the feedstock, and a technical resource potential based on the energy content of the resource under consideration. This is substantially similar to the AGF study completed in 2011 regarding RNG, as noted below. Review of Previous Work In 2011, the American Gas Foundation (AGF) published The Potential for Renewable Gas: Biogas Derived from Biomass Feedstocks and Upgraded to Pipeline Quality, a study aimed at assessing the

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resource potential of renewable gas which included three scenarios, as described here, and the resource potential results are shown in Table 2 below.4 § Non-Aggressive Scenario: This represented a low level of feedstock utilization, with utilization levels reportedly depending on feedstock, with a range from 15%-25% for feedstocks that were converted to renewable gas using anaerobic digestion technologies. The utilization rates of feedstocks for thermal gasification in the non-aggressive scenario ranged from 5-10%. § Aggressive Scenario: This scenario represented a higher level of feedstock utilization, with utilization levels reportedly depending on feedstock, with a range from 40%-75% for feedstocks that were converted to RNG using anaerobic digestion technologies. The utilization rates of feedstocks for thermal gasification in the aggressive scenario ranged from 15-25%. § Maximum Scenario: This represents an “absolute upper bound” regarding the energy production potential and was used for illustrative purposes. Table 2. Summary of RNG Potential from 2011 AGF Study in units of tBtu/year RNG Production Potential, tBtu/y Feedstock Non-Aggressive Aggressive Landfill Gas 182 364 Animal Manure 148 493 WRRF 4 13 Food Waste N/A N/A Sub-Total, AD 335 871 Ag Residue 401 1,002 Forestry and Forest 82 206 Residue Energy Crops 80 200 MSW 69 207 Sub-Total, TG 632 1,614 Totals 967 2,485

4 Note that the 2011 RNG assessment did not consider P2G. 8

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Regional RNG Resource Assessment There are more than 85 projects producing RNG for pipeline injection today, compared to less than a half-dozen in 2010 when AGF first assessed the potential for RNG. In the following sub-sections, ICF outlines the potential for RNG for pipeline injection, broken down by the feedstocks presented previously, and considering the potential for RNG growth over time with 2040 being the final year in the analysis. ICF presents a low and a high RNG potential, varying both the assumed utilization of existing resources, as well as the rate of project development required to deploy RNG at the volumes presented. The resource potential is presented on a national-level and broken down by the nine (9) U.S. Census Regions, as shown in the figure below: New England, Middle Atlantic, East North Central, West North Central, South Atlantic, East South Central, West South Central, Mountain, and Pacific. Figure 4. U.S. Census Regions

The RNG potential is based on assessment of resource availability—in a competitive market, that resource availability will be a function of factors including, but not limited to demand, feedstock costs, technological development, and the policies in place that might support RNG project development. The intent of ICF’s estimates is to outline the RNG potential that could be realized given the right market considerations (without explicitly defining what those are), and then capture the corresponding costs and GHG emissions reductions associated with our production estimates. For the RNG market more broadly, ICF assumed that the market would continue to grow to 2025 at a compound annual growth rate slightly higher than we have seen over the last 5 years—at a rate of

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about 35%.5 This rate is reflective of existing investments in at least 40 new domestic RNG projects coming online, and other announcements that have not yet been made. Based on this assumption, we assume that the potential for RNG injected into the pipeline will be on the order of 220 to 240 tBtu in 2025. For RNG production potential post-2025, ICF used a logistic function to approximate the growth trajectory, whereby the initial stage of growth is approximated as an exponential, and thereafter growth slows to a linear rate, and then approaches a plateau (or limited to no growth) at maturity. Summary of RNG Potential The figures below illustrate ICF’s estimates for the low and high potential scenario across each feedstock, reported in units of trillion Btu per year (tBtu/y). Figure 5. Estimated Annual RNG Production, Low Resource Potential Scenario, tBtu/y

5,000 P2G/Methanation

4,500 MSW

4,000 Energy Crops 3,500 Forest Residue 3,000 Ag Residue 2,500 Food Waste 2,000 WRRF 1,500 Animal Manure

Annual RNG Production(tBtu/y) 1,000 Landfill Gas 500

0 NG Residential Consumption, 2025 2030 2035 2040 10-yr avg

5 ICF estimates that there were about 17.5 tBtu of RNG produced for pipeline injection in 2016 and that there will be about 50 tBtu of RNG produced for pipeline injection in 2020—this yields a compound annual growth rate of about 30%. 10

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Figure 6. Estimated Annual RNG Production, High Resource Potential Scenario, tBtu/y

5,000 P2G/Methanation

4,500 MSW

4,000 Energy Crops 3,500 Forest Residue 3,000 Ag Residue 2,500 Food Waste 2,000 WRRF 1,500 Animal Manure

Annual RNG Production(tBtu/y) 1,000 Landfill Gas 500

0 NG Residential Consumption, 2025 2030 2035 2040 10-yr avg

ICF estimates that the low and high resource potential scenarios will yield about 1,910 tBtu/y and 4,510 tBtu/y of RNG production by 2040. For the sake of comparison, the United States has consumed on average 15,850 tBtu of natural gas over the last ten years (2009-2018) in the residential (4,846 tBtu), commercial (3,318 tBtu), transportation (36 tBtu), and industrial sectors (7,652 tBtu).6 ICF sought to utilize reasonable, and in most cases, conservative assumptions regarding the utilization of different feedstocks. Table 3 below summarizes the utilization of the different feedstocks that ICF used in the analysis. Table 3. Summary of Feedstock Utilization in the Low and High Resource Potential Scenarios RNG Feedstock Low Resource High Resource LFG • 40% of the LFG facilities that have • 65% of the LFG facilities that have collection systems in place collection systems in place • 30% of the LFG facilities that do not have • 60% of the LFG facilities that do not have collections systems in place collections systems in place • 50% of EPA’s candidate landfills • 80% of EPA’s candidate landfills Animal manure • 30% of technically available animal • 60% of technically available animal manure manure WRRF • 30% of WRRFs with a capacity greater • 50% of WRRFs with a capacity greater than than 7.25 million gallons per day 3.3 million gallons per day Food waste • 40% of the food waste available at • 70% of the food waste available at $70/dry ton $100/dry ton Agricultural residue • 20% of the agricultural residues available • 50% of the agricultural residues available at at $50/dry ton $50/dry ton

6 Based on data reported by the Energy Information Administration, available online at https://www.eia.gov/dnav/ng/ng_cons_sum_dcu_nus_a.htm. 11

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RNG Feedstock Low Resource High Resource Forestry and forest • 30% of the forest and forestry product • 60% of the forest and forestry product product residue residues available at $30/dry ton residues available at $60/dry ton Energy crops • 50% of the energy crops available at • 50% of the energy crops available at $50/dry ton $70/dry ton Municipal solid • 30% of the non-biogenic fraction of MSW • 60% of the non-biogenic fraction of MSW waste (MSW) available at $30/dry ton available at $100/dry ton P2G • 50% capacity factor for dedicated • 80% capacity for dedicated renewables renewables

Ultimately, market conditions, technology development, and policy structures will determine the extent to which each of the feedstocks considered can be utilized. For the sake of reference, ICF also reports a technical resource potential scenario of nearly 13,960 tBtu—an estimate intended to reflect the RNG production potential without any technical or economic constraints. Figure 7 below shows how the RNG technical resource potential compares to the domestic consumption of natural gas in different end uses.7 Figure 7. RNG Technical Resource Potential vs Average Domestic Natural Gas Consumption in Different End Uses, 2009-2018 (in tBtu/y)

RNG Technical Resource

Vehicle 2018

- Industrial

Commercial

Residential Average U.S. Natural Gas Natural U.S. Average Consumption, 2009 Consumption, Trillion Btu per year

The tables below summarize ICF’s resource assessment for low, high, and technical resource RNG production potential in 2040, broken down by Census Region and by feedstock, reported in units of tBtu per year (tBtu/y). The last row in each table also includes the amount of natural gas consumed in the residential, commercial, transportation, and industrial sectors broken down by Census Region in 2018 for the sake of reference.

7 The technically achievable RNG production potential excludes P2G as a source. 12

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Low Resource Potential Scenario Table 4. Low Resource Potential for RNG in 2040, tBtu/y RNG Potential: Low Scenario (in tBtu/y) East West East West Feedstock New Mid- South North North South South Mountain Pacific Total England Atlantic Atlantic Central Central Central Central RNG from biogenic or renewable resources Landfill Gas 13.3 57.5 106.2 28.6 88.4 35.7 65.3 38.3 95.2 528.4

Animal Manure 8.0 12.1 30.3 44.5 31.7 18.9 36.0 28.7 21.0 231.2

WRRF 1.1 4.5 5.5 1.3 3.4 1.0 2.0 1.2 4.0 24.0

Food Waste 1.8 5.0 5.7 1.9 6.0 0.8 1.4 0.9 5.6 29.2

Sub-Total, AD 24.2 79.1 147.8 76.3 129.5 56.4 104.7 69.1 125.8 812.8

Ag Residue 0.0 3.7 57.0 144.4 10.0 2.9 10.7 10.9 14.9 254.6 Forestry and 3.6 4.8 9.7 6.5 37.6 20.6 16.3 2.7 6.8 108.6 Forest Residue Energy Crops 0.2 2.2 1.5 35.4 18.1 9.3 56.5 0.2 0.0 123.4

Sub-Total, TG 3.8 10.7 68.2 186.3 65.7 32.8 83.5 13.8 21.7 486.6 Renewable gas from MSW MSW 14.4 40.6 45.9 17.7 56.9 11.2 15.3 8.8 45.4 256.2 RNG from P2G / Methanation P2G / 357.7 Methanation Totals 42.3 130.5 261.8 280.4 252.1 100.3 203.4 91.7 192.9 1,913.2

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High Resource Potential Scenario Table 5. High Resource Potential for RNG in 2040, tBtu/y RNG Potential: High Scenario (in tBtu/y) East West East West Feedstock New Mid- South North North South South Mountain Pacific Total England Atlantic Atlantic Central Central Central Central RNG from biogenic or renewable resources Landfill Gas 21.7 94.3 173.8 47.3 145.0 59.1 106.2 32.9 155.2 865.6

Animal Manure 16.0 24.2 60.6 88.9 63.4 37.7 71.9 57.5 42.1 462.3

WRRF 1.6 6.3 6.6 2.0 5.1 1.6 3.1 1.7 5.5 33.5

Food Waste 3.1 8.8 9.9 4.1 13.1 4.2 8.0 2.9 9.8 63.9

Sub-Total, AD 42.4 133.6 250.9 142.3 226.6 102.6 189.2 125.0 212.6 1,425.3

Ag Residue 0.1 9.2 142.6 361.0 26.9 7.3 28.8 27.3 37.3 640.5 Forestry and 7.3 9.7 19.3 13.0 75.2 41.3 37.1 19.3 13.6 235.8 Forest Residue Energy Crops 0.5 9.4 64.4 260.0 77.3 91.6 330.5 3.9 0.0 837.6

Sub-Total, TG 7.9 28.3 226.3 634.0 179.4 140.2 396.4 50.5 50.9 1,713.9 Renewable gas from MSW MSW 32.4 91.6 103.4 46.1 136.3 43.2 83.2 50.1 108.5 694.8 RNG from P2G / Methanation P2G / 678.7 Methanation Totals 80.5 245.2 569.4 819.4 532.0 283.5 658.1 222.5 359.4 4,512.6

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Technical Resource Potential Table 6. Technical Resource Potential for RNG in 2040, tBtu/y RNG Potential: Technical Potential (in tBtu/y) East West East West Feedstock New Mid- South North North South South Mountain Pacific Total England Atlantic Atlantic Central Central Central Central RNG from biogenic or renewable resources Landfill Gas 32.5 143.4 259.1 70.3 211.7 84.0 154.0 92.0 233.2 1,280.2

Animal Manure 88.9 99.3 285.2 602.7 316.5 207.7 453.5 340.5 178.1 2,572.4

WRRF 4.0 14.4 18.1 5.6 12.3 4.7 7.6 4.5 12.2 83.2

Food Waste 17.7 50.1 56.6 23.5 74.5 23.6 45.5 16.5 56.0 364.1

Sub-Total, AD 143.1 307.2 619.0 702.1 615.0 320.0 660.6 453.5 479.5 4,300.0

Ag Residue 0.3 42.1 623.8 1,405.1 93.8 38.7 123.3 115.1 126.3 2,568.5 Forestry and 18.6 24.9 49.5 33.4 192.9 105.8 106.7 85.5 34.7 652.0 Forest Residue Energy Crops 3.0 84.3 872.5 1,508.1 357.1 460.8 1,266.4 48.7 0.0 4,600.9

Sub-Total, TG 21.9 151.3 1,545.8 2,946.6 643.8 605.3 1,496.4 249.3 161.0 7,821.4 Renewable gas from MSW MSW 85.8 242.7 274.0 122.2 361.2 114.6 220.5 133.1 287.5 1,841.6 RNG from P2G / Methanation P2G / N/A; dependent on market developments beyond scope of study Methanation Totals 250.8 701.2 2,438.8 3,770.9 1,620.0 1,039.9 2,377.5 835.9 928.0 13,963.1

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RNG: Anaerobic Digestion of Biogenic or Renewable Resources Landfill Gas The Resource Conservation and Recovery Act of 1976 (RCRA, 1976) sets criteria under which landfills can accept municipal solid waste and nonhazardous industrial solid waste. Furthermore, the RCRA prohibits open dumping of waste and hazardous waste is managed from the time of its creation to the time of its disposal. Landfill gas (LFG) is captured from the anaerobic digestion of biogenic waste disposed of in landfills and produces a mix of gases, including methane, typically with a methane content ranging from 45-60%. The landfill itself acts as the digester tank—a closed volume that becomes devoid of oxygen over time, leading to favorable conditions for certain micro- organisms to break down biogenic materials. The composition of the LFG is dependent on the materials in the landfill, and other factors, but is typically made up of methane, carbon dioxide (CO2), nitrogen (N2), hydrogen, carbon monoxide (CO), oxygen (O2), sulfides (e.g., hydrogen sulfide or H2S), ammonia, and trace elements like amines, sulfurous compounds, and siloxanes. RNG production from LFG requires advanced treatment and upgrading the biogas via removal of CO2, H2S, siloxanes, N2, and O2 to achieve a high Btu content gas for pipeline injection. Table 7 below summarizes landfill gas constituents, the typical concentration ranges in LFG, and commonly deployed upgrading technologies in use today. Table 7. Landfill Gas Constituents and Corresponding Upgrading Technologies LFG Constituent Typical Concentration Range Upgrading Technology for Removal • High-selectivity membrane separation • Pressure swing adsorption (PSA) Carbon dioxide, CO2 40-60% systems • Water scrubbing systems • Amine scrubbing systems • Solid chemical scavenging Hydrogen sulfide, • Liquid chemical scavenging 0-1% H2S • Solvent adsorption • Chemical oxidation-reduction • Non-regenerative adsorption Siloxanes <0.1% • Regenerative adsorption Nitrogen, N2 2-5% • PSA systems Oxygen, O2 0.1-1% • Catalytic removal (O2 only)

To develop the RNG potential from LFG, ICF extracted data from the Landfill Methane Outreach Program (LMOP) administered by the U.S. Environmental Protection Agency (EPA)—which included more than 2,000 landfills. ICF considered only landfills that are either open or were closed post- 2000. This constraint was imposed to account for the fact that the phase during which the decomposition of waste in a landfill produces sufficient methane concentrations lasts about 20-25 years, and this is the period during which waste-to-energy projects are most viable.8 While landfills continue to emit methane for 50 years or more, this constraint limits the potential for the assessment to over-estimate the production from older landfills with a decrease methane

8 US EPA Landfill Methane Outreach Program, LFG Energy Project Development Handbook, Chapter 1, Available online at https://www.epa.gov/sites/production/files/2016-07/documents/pdh_chapter1.pdf 16

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emissions concentration. This constraint reduces the number of candidate landfills to just over 1,500 landfills. The table below includes the number of candidate landfills considered in each Census region. Table 8. Number of Candidate Landfills by Census Region9 East West East West Landfill New Mid- South North North South South Mountain Pacific England Atlantic Atlantic Status Central Central Central Central Closed 33 16 51 21 54 19 25 24 58 (post-2000) Open 25 79 173 121 221 107 160 162 166

The US EPA’s LMOP database shows that there are about 620 operational LFG to energy projects nationwide, however, only 60 (10%) of them produce RNG, and only 52 of those actually inject RNG into the pipeline. Most of the projects capture LFG and combust it in reciprocating engines to make electricity (72%) or have a direct use (18%) for the energy (e.g., thermal use on-site). Moreover, the EPA currently estimates that there are 480 candidate landfills that could capture LFG for use as energy—the EPA characterizes candidate landfills as one that is accepting waste or has been closed for five years or less, has at least one million tons of waste-in-place (WIP), and does not have an operational, under-construction, or planned project. Candidate landfills can also be designated based on actual interest by the site. The table below includes LFG to Energy projects and candidate landfills broken down by Census Region. Table 9. Landfill to Energy Projects and Candidate Landfills by Census Region10

LFG to East West East West New Mid- South North North South South Mountain Pacific Energy England Atlantic Atlantic Project Type Central Central Central Central Electricity 28 64 105 23 101 20 19 18 71

Direct 1 12 26 17 31 6 10 1 5

RNG 1 9 13 5 4 4 19 1 4 Candidate 8 14 62 46 88 60 95 57 43 Landfills

ICF developed resource potentials for RNG production at landfills in a low and high scenario, considering the potential at LFG facilities with collection systems in place, without collection systems in place, and at candidate landfills identified by the US EPA. § In the low scenario, ICF assumed that RNG could be produced at 40% of the LFG facilities that have collection systems in place, 30% of the LFG facilities that do not have collections systems in place, and at 50% of the candidate landfills. Combined, ICF’s estimates in the low resource potential scenario represent about 425 of the more than 2,000 landfills included in the US EPA LMOP database.

9 Based on data from the Landfill Methane Outreach Program at the US EPA (updated February 2019). 10 Ibid. 17

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§ In the high scenario, ICF assumed that RNG could be produced at 65% of the LFG facilities that have collection systems in place, 80% of the LFG facilities that do not have collections systems in place, and at 80% of the candidate landfills. Combined, ICF’s estimates in the low resource potential scenario represent about 750 of the more than 2,000 landfills included in the US EPA LMOP database. To estimate the amount of RNG that could be injected from LFG projects, ICF used outputs from the LandGEM model—which is an automated tool with an MS Excel interface developed by the US EPA to estimate the emissions rates for landfill gas and methane based on user inputs like waste- in-place, facility location (and climate conditions), waste received per year, etc.. The estimated LFG output was estimated on a facility-by-facility basis. About 1,150 facilities report methane content; for the facilities for which no data were reported, ICF assumed the median methane content of 49.6%. The figures below show the low and high RNG resource potential from landfill gas between 2025 and 2040. The table that follows includes the total annual RNG production potential (in units of tBtu/y) for 2040 in the low, high, and technical resource potential scenarios. Figure 8. RNG Production Potential from Landfill Gas, Low Resource Potential Scenario, in tBtu/y

120 New England

100 Mid-Atlantic East North Central 80 West North Central 60 South Atlantic East South Central 40 West South Central 20 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

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Figure 9. RNG Production Potential from Landfill Gas, High Resource Potential Scenario, in tBtu/y

175 New England 150 Mid-Atlantic

125 East North Central West North Central 100 South Atlantic 75 East South Central 50 West South Central 25 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

Table 10. Annual RNG Potential from Landfills in 2040, tBtu/y RNG Potential from Landfills, tBtu/y RNG Potential East West East West New Mid- South Scenario North North South South Mountain Pacific England Atlantic Atlantic Central Central Central Central Low Resource 12.2 52.2 97.6 27.0 83.4 35.2 60.6 36.2 86.0 High Resource 20.9 89.8 166.8 46.5 141.8 60.0 102.1 61.8 146.8 Technical Resource 32.5 143.4 259.1 70.3 211.7 84.0 154.0 92.0 233.2

ICF estimates that between 528 and 866 tBtu/y of RNG could be produced at the national level by 2040 in the low and high scenarios, respectively from LFG facilities. Animal Manure The US EPA lists a variety of benefits associated with the anaerobic digestion of animal manure at farms as an alternative to traditional manure management systems, including but not limited to:11 § Diversifying farm revenue: The biogas produced from the digesters has the highest potential value. But digesters can also provide revenue streams via “tipping fees” from non- farm organic waste streams that are diverted to the digesters; organic nutrients from the digestion of animal manure; and displacement of animal bedding or peat moss by using digested solids. § Conservation of agricultural land: Digesters can help to improve soil health by converting the nutrients in manure to a more accessible form for plants to use and help protect the local water resources by reducing nutrient run-off and destroying pathogens. § Promoting energy independence: The RNG produced can reduce on-farm energy needs or provide energy via pipeline injection for use in other applications, thereby displacing fossil or geological natural gas.

11 More information available online at https://www.epa.gov/agstar/benefits-anaerobic-digestion. . 19

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§ Bolstering farm-community relationships: Digesters help to reduce odors form livestock manure, improve growth prospects by minimizing potential negative impacts of farm operations on local communities, and help forge connections between farmers and the local community through environmental and energy stewardship. The main components of anaerobic digestion of manure include manure collection, the digester, effluent storage (e.g., a tank or lagoon), and gas handling equipment. There are a variety of livestock manure processing systems that are employed at farms today, including plug-flow or mixed plug-flow digesters, complete-mixed digesters, covered lagoons, fixed-film digesters, sequencing-batch reactors, and induced-blanked digesters. Most dairy manure projects today use the plug-flow or mixed plug-flow digesters. ICF considered animal manure from a variety of animal populations, including beef and dairy cows, broiler chickens, layer chickens, turkeys, and swine. Animal populations were derived from the United States Department of Agriculture’s (USDA) National Agricultural Statistics Service. ICF used information provided from the most recent census year (2017) and extracted total animal populations on a state-by-state basis. ICF estimated the total amount of animal manure produced based on the animal population, the total wet manure produced per animal, an assumed moisture content, and the energy content of the dried manure. The values in the table below are taken from a California Energy Commission report prepared by the California Biomass Collaborative.12 Table 11. Key Parameters to Determine Animal Manure Resource for RNG Production Technical Total Wet Manure Moisture Content HHV Animal Type Availability (lb/animal/day) (% wet basis) (Btu/lb, dry basis) Factors Dairy Cow 140 87 7,308 0.50 Beef Cow 125 88 7,414 0.20 Swine 50 88 7,161 0.20 Poultry, Layer Chickens 10 91 6,839 0.50 Poultry, Broiler Chickens 0.2 75 6,663 0.50 Poultry, Turkeys 0.22 74 6,839 0.50

For the technical resource potential for RNG production, ICF did not account for the technical availability factors included in the table above. The US EPA AgStar database indicates that there are nearly 250 operational digesters at farms— more than 90% of which produce electricity or use the biogas for cogeneration. Only 5 of the projects (2%) currently inject gas into the pipeline.

12 Williams, R. B., B. M. Jenkins and S. Kaffka (California Biomass Collaborative). 2015. An Assessment of Biomass Resources in California, 2013 – DRAFT. Contractor Report to the California Energy Commission. PIER Contract 500-11-020. Available online here. 20

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Table 12. Summary of AgStar Projects at Farms using AD Systems, by Census Region East West East West New Mid- South North North South South Mountain Pacific AgStar Projects England Atlantic Atlantic Central Central Central Central Project Status Operational 22 62 69 16 20 5 4 16 34 Construction 2 3 3 7 2 -- -- 3 14 Project Type Electricity / Cogen 22 57 64 10 19 5 3 15 34 Flared -- 8 10 6 -- -- 2 2 Pipeline ------3 1 ------1 Animal Type Dairy 22 55 61 8 6 1 -- 11 34 Swine -- 4 2 7 12 1 4 5 -- Poultry -- 1 1 -- 2 3 ------Multiple -- 2 5 1 ------

ICF developed resource potentials for RNG production from the anaerobic digestion of animal manure in a low and high scenario. § In the low scenario, ICF assumed that RNG could be produced from 30% of the animal manure, after accounting for the technical availability factor. Generally speaking, this represents the share of animal manure that would be recoverable from the larger farms (e.g., dairy farms with more than 1,000 head of cattle and hog farms with more than 5,000 hogs). § In the high scenario, ICF assumed that RNG could be produced from 60% of the animal manure, after accounting for the technical availability factor. Generally speaking, this share of the animal manure represents the resources that could be recoverable from the medium to large farms (e.g., dairy farms with more than 500 head of cattle and hog farms with more than 5,000 hogs). In many cases, anaerobic digesters at dairy farms co-process other substrates (or feedstocks) to boost gas production—the co-digestion of substrates is used to help balance the carbon-to- nitrogen ratio for more favorable anaerobic digestion conditions.13 The figures below show the low and high RNG resource potential from animal manure between 2025 and 2040. The table that follows includes the total annual RNG production potential (in units of tBtu/y) for 2040 in the low, high, and technical resource potential scenarios.

13 US EPA, Increasing Anaerobic Digester Performance with Codigestion, September 2012. Available online: https://www.epa.gov/sites/production/files/2014-12/documents/codigestion.pdf. 21

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Figure 10. RNG Production Potential from Animal Manure, Low Resource Potential Scenario, in tBtu/y

45 New England 40 Mid-Atlantic 35 East North Central 30 West North Central 25 South Atlantic 20 East South Central 15 West South Central 10 5 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

Figure 11. RNG Production Potential from Animal Manure, High Resource Potential Scenario, in tBtu/y

90 New England 80 Mid-Atlantic 70 East North Central 60 West North Central 50 South Atlantic 40 East South Central 30 West South Central 20 10 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

Table 13. Annual RNG Production Potential from Animal Manure in 2040, tBtu/y RNG Potential from Animal Manure, tBtu/y RNG Potential East West East West New Mid- South Scenario North North South South Mountain Pacific England Atlantic Atlantic Central Central Central Central Low Resource 8.0 12.1 30.3 44.5 31.7 18.9 36.0 28.7 21.0 High Resource 16.0 24.2 60.6 88.9 63.4 37.7 71.9 57.5 42.1 Technical Resource 88.9 99.3 285.2 602.7 316.5 207.7 453.5 340.5 178.1

ICF estimates that between 231 and 462 tBtu/y of RNG could be produced in the low and high scenarios, respectively from animal manure by 2040.

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Water Resource Recovery Facilities Wastewater is created from residences and commercial or industrial facilities, and it consists primarily of waste liquids and solids from household water usage, from commercial water usage, or from industrial processes. Depending on the architecture of the sewer system and local regulation, it may also contain storm water from roofs, streets, or other runoff areas. The contents of the wastewater may include anything which is expelled (legally or not) from a household and enters the drains. If storm water is included in the wastewater sewer flow, it may also contain components collected during runoff: soil, metals, organic compounds, animal waste, oils, solid debris such as leaves and branches, etc. Processing of the influent to a large water resource recovery facility (WRRF) is comprised typically of four stages: pre-treatment, primary, secondary, and tertiary treatments. These stages consist of mechanical, biological, and sometimes chemical processing. § Pre-treatment removes all the materials that can be easily collected from the raw wastewater that may otherwise damage or clog pumps or piping using in treatment processes. § In the primary treatment stage, the wastewater flows into large tanks or settling bins, thereby allowing sludge to settle while fats, oils, or greases rise to the surface. § The secondary treatment stage is designed to degrade the biological content of the wastewater and sludge, and is typically done using water-borne micro-organisms in a managed system. § The tertiary treatment stage prepares the treated effluent for discharge into another ecosystem, and often uses chemical or physical processes to disinfect the water. The treated sludge from the WRRF can be landfilled, and during processing it can be treated via anaerobic digestion, thereby producing methane which can be used for beneficial use with the appropriate capture and conditioning systems put in place. ICF reviewed more than 14,500 wastewater treatment facilities surveyed as part of the Clean Watersheds Needs Survey (CWNS) conducted in 2012 by the US EPA, an assessment of capital investment needed for wastewater collection and treatment facilities to meet the water quality goals of the Clean Water Act. ICF further distinguished between facilities based on location, and facility size as a measure of average flow (in units of million gallons per day, MGD). ICF also reviewed more than 1,200 facilities that are reported to have anaerobic digesters in place, as reported by the Water Environment Federation. The tables below summarize the key data points from the survey of WRRFs in the United States, broken down by Census Region. Table 14. Number of WRRFs by Census Region14 East West East West Facility New Mid- South North North South South Mountain Pacific Size (MGD) England Atlantic Atlantic Central Central Central Central <0.02 33 70 169 581 94 46 127 107 32 0.02-0.07 58 255 495 1,125 222 191 362 263 137 0.07-0.18 83 289 607 602 291 224 380 217 145 0.18-1.00 176 555 838 552 569 391 459 308 293 1.01-3.30 109 234 324 160 267 177 178 126 162

14 Based on data from CNWS 2015. 23

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East West East West Facility New Mid- South North North South South Mountain Pacific Size (MGD) England Atlantic Atlantic Central Central Central Central 3.31-7.25 46 91 122 53 137 68 88 39 78 7.26-34.05 35 67 116 36 112 30 58 36 88 34.05+ 5 30 24 9 21 8 15 7 24

Table 15. Total Flow (in MGD) of WRRFs by Census Regions15 East West East West Facility New Mid- South North North South South Mountain Pacific Size (MGD) England Atlantic Atlantic Central Central Central Central <0.02 0 1 2 6 1 0 1 1 0 0.02-0.07 2 10 20 40 9 8 14 10 5 0.07-0.18 9 33 68 66 33 26 42 24 16 0.18-1.00 84 255 380 228 261 170 201 139 135 1.01-3.30 201 440 632 292 511 338 323 238 304 3.31-7.25 231 461 576 259 678 323 439 198 394 7.26-34.05 535 1,009 1,734 569 1,645 424 863 552 1,320 34.05+ 494 3,438 3,651 717 1,686 536 1,086 586 2,580

In other words, these tables tell us that despite the more than 14,500 WRRFs nationwide, nearly 45% of the wastewater is being processed at 142 of the facilities, or just 1% of the total WRRFs for which ICF was able to identify data. Furthermore, more than 70% of the wastewater is being processed at just 5% of the facilities. The table below shows the distribution of the more than 1,250 WRRFs with installed AD systems. Table 16. WRRFs with Anaerobic Digesters, by Census Regions16 West West New Mid- East North South East South North South Mountain Pacific England Atlantic Central Atlantic Central Central Central AD Facilities 34 231 309 125 133 47 74 82 233

The three tables above illustrate the challenges and opportunities associated with deploying AD systems at WRRFs: Most of the wastewater in the U.S. is treated at a small number of facilities. And of the facilities that already have an AD system installed, they tend to be the larger facilities. However, most of those facilities have AD systems installed that are capturing biogas to produce electricity on-site, rather than for pipeline injection. The database of RNG producing facilities maintained by the Coalition for Renewable Natural Gas indicates that there are 12 operation WRRFs using AD systems to capture and subsequently inject RNG into the pipeline, 5 WRRFs with AD systems under substantial development, and another 5 WRRFs with AD systems under construction. ICF developed resource potentials for RNG production at WRRFs in a low and high scenario.

15 Based on data from CNWS 2015. 16 Based on data from the Water Environment Federation. 24

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§ In the low scenario, ICF assumed that AD systems would be deployed at the facilities with larger flow rates (greater than 7.25 MGD), and that presumably some of the systems with AD systems in place would be converted to pipeline injection projects. The underlying assumption is that the economics of RNG production would favor these larger facilities. ICF assumed that RNG could be produced at 30% of the facilities with a capacity greater than 7.25 MGD—this amounts to AD systems with corresponding conditioning and upgrading systems in place to inject RNG into the pipeline at about 200 of the larger sized facilities. § In the high scenario, ICF assumed that RNG could be produced at 50% of the facilities with a capacity greater than 3.3 MGD. This amounts to AD systems with corresponding conditioning and upgrading systems in place to inject RNG into the pipeline at about 450 of the larger sized facilities, and another 1,000 of the medium-sized facilities. In other words, this is a project deployment trajectory consistent with the current level of deployment of AD systems in place, but with an emphasis on RNG production rather than electricity generation. To estimate the amount of RNG produced from wastewater at WRRFs, ICF used data reported by the US EPA,17 a study of WRRFs in New York State,18 and previous work published by AGF.19 ICF used an average energy yield of 7.0 MMBtu/MG of wastewater. For the technical resource potential, ICF used all of the wastewater flow reported at the more than 14,500 facilities in the database. The figures below show the low and high resource potential for RNG production from WRRFs between 2025 and 2040. The table that follows includes the total annual RNG production potential (in units of tBtu/y) for 2040 in the low, high, and technical resource potential scenarios.

17 US EPA, Opportunities for Combined Heat and Power at Wastewater Treatment Facilities, October 2011. Available online here. 18 Wightman, J and Woodbury, P., Current and Potential Methane Production for Electricity and Heat from New York State Wastewater Treatment Plants, New York State Water Resources Institute at Cornell University. Available online here. 19 AGF, The Potential for Renewable Gas: Biogas Derived from Biomass Feedstocks and Upgraded to Pipeline Quality, September 2011. 25

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Figure 12. RNG Production Potential from WRRFs, Low Resource Potential Scenario, in tBtu/y

6.0 New England

5.0 Mid-Atlantic East North Central 4.0 West North Central 3.0 South Atlantic East South Central 2.0 West South Central 1.0 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0.0 Pacific 2025 2030 2035 2040

Figure 13. RNG Production Potential from WRRFs, High Resource Potential Scenario, in tBtu/y

7 New England 6 Mid-Atlantic

5 East North Central West North Central 4 South Atlantic 3 East South Central 2 West South Central 1 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

Table 17. Annual RNG Production Potential from WRRFs in 2040, tBtu/y RNG Potential from WRRFs, tBtu/y RNG Potential East West East West New Mid- South Scenario North North South South Mountain Pacific England Atlantic Atlantic Central Central Central Central Low Resource 1.1 4.5 5.5 1.3 3.4 1.0 2.0 1.2 4.0 High Resource 1.6 6.3 7.6 2.0 5.1 1.6 3.1 1.7 5.5 Technical Resource 4.0 14.4 18.1 5.6 12.3 4.7 7.6 4.5 12.2

ICF estimates that between 24 and 34 tBtu/y of RNG could be produced in the low and high scenarios, respectively from WRRFs. To achieve this level of RNG production from WRRFs, ICF

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estimates that 360 and 1,450 facilities would need to install AD systems in the low and high scenarios, respectively. Food Waste Food waste is a major component of municipal solid waste (MSW)—accounting for about 15% of MSW streams. More than 75% of food waste is landfilled. Food waste can be diverted from landfills to a composting or processing facility where it can be treated in an anaerobic digester. ICF limited our consideration to the potential for utilizing the food waste that is currently landfilled as a feedstock for RNG production via AD, thereby excluding the 25% of food waste that is recycled or directed to waste-to-energy facilities.20 ICF extracted information from the U.S. Department of Energy’s (DOE) Bioenergy Knowledge Discovery Framework (KDF), which includes information collected as part of U.S. DOE’s Billion-Ton Report (updated in 2016).21 The Bioenergy KDF includes food waste at price points ranging from $70/ton and $100/ton. ICF assumed a high heating value of 12.04 MMBtu/ton (dry). Note that the values from the Bioenergy KDF are reported in dry tons, so the moisture content of the food waste has already been accounted for in the DOE’s resource assessment. ICF developed the RNG production potential from food waste in a low and high scenario. § In the low scenario, ICF assumed that 40% of the food waste available at $70/dry ton would be diverted to AD systems. § In the high scenario, ICF assumed that 70% of the food waste available at $100/dry ton would be diverted to AD systems. ICF calculated the technical resource potential for RNG production from food waste in an AD system assuming 100% of the food waste that is currently landfilled is diverted to a processing facility with a digester. The figures below show the low and high RNG resource potential from the anaerobic digestion of food waste between 2025 and 2040. The table that follows includes the total annual RNG production potential (in units of tBtu/y) for 2040 in the low, high, and technical resource potential scenarios.

20 ICF notes that the diversion of food waste from landfills may limit the long-term potential (post-2040) of landfill gas as a viable resource for RNG production. However, for the purposes of this report, and the associated timeframe of the analysis to 2040, ICF used estimates based on existing waste-in-place at landfills, and the corresponding methane production at those landfills. The resource estimates between RNG from landfill gas and food waste do not conflict or overlap; however, ICF notes that successful waste diversion policies would only increase the RNG resource potential and improve the appetite for RNG production from dedicated AD systems processing diverted food waste. 21 The Billion-Ton Report is a critical national assessment performed by the Department of Energy to calculate the potential supply of biomass in the U.S.. The report finds that the U.S. has the future potential to produce at least one billion dry tons of biomass resources (composed of agricultural, forestry, waste, and algal materials) on an annual basis without adversely affecting the environment. 27

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Figure 14. RNG Production Potential from Food Waste, Low Resource Potential Scenario, in tBtu/y

7.0 New England 6.0 Mid-Atlantic

5.0 East North Central West North Central 4.0 South Atlantic 3.0 East South Central 2.0 West South Central 1.0 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0.0 Pacific 2025 2030 2035 2040

Figure 15. RNG Production Potential from Food Waste, High Resource Potential Scenario, in tBtu/y

14 New England 12 Mid-Atlantic

10 East North Central West North Central 8 South Atlantic 6 East South Central 4 West South Central 2 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

Table 18. Annual RNG Production Potential from Food Waste in 2040, tBtu/y RNG Potential from Food Waste, tBtu/y RNG Potential East West East West New Mid- South Scenario North North South South Mountain Pacific England Atlantic Atlantic Central Central Central Central Low Resource 1.8 5.0 5.7 1.9 6.0 0.8 1.4 0.9 5.6 High Resource 3.1 8.8 9.9 4.1 13.1 4.2 8.0 2.9 9.8 Technical Resource 17.7 50.1 56.6 23.5 74.5 23.6 45.5 16.5 56.0

ICF estimates that between 29 and 64 tBtu/y of RNG could be produced by 2040 at the national level in the low and high scenarios, respectively from food waste diverted to anaerobic digesters.

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RNG: Thermal Gasification of Biogenic or Renewable Resources Biomass like agricultural residues, forestry and forest produce residues, and energy crops have high energy content and are ideal candidates for thermal gasification. The thermal gasification of biomass to produce RNG occurs over a series of steps. Thermal gasification typically requires some pre-processing of the feedstock. The gasification process first generates synthesis gas (or syngas), consisting of hydrogen and carbon monoxide. Biomass gasification technology has been commercialized for nearly a decade; however, the gasification process typically yields a residual tar, which can foul downstream equipment. Furthermore, the presence of tar effectively precludes the use of a commercialized methanation unit. The high cost of conditioning the syngas in the presence of these tars has limited the potential for thermal gasification of biomass. For instance, in 1998, Tom Reed22 concluded that after “two decades” of experience in biomass gasification, “’tars’ can be considered the Achilles heel of biomass gasification.” Over the last several years, however, several commercialized technologies have been deployed to increase syngas quantity and prevent the fouling of other equipment by removing the residual tar before methanation. There are a handful of technology providers in this space including Haldor Topsoe’s tar reforming catalyst. Frontline Bioenergy takes a slightly different approach and has patented a process producing tar free syngas (referred to as TarFreeGasÔ). The syngas is further upgraded via filtration (to remove remaining excess dust generated during gasification), and other purification processes to remove potential contaminants like hydrogen sulfide, and carbon dioxide. The upgraded syngas is then methanated and dried prior to pipeline injection. ICF notes that biomass, particularly agricultural residues, are often added to anaerobic digesters to increase gas production (by improving carbon-to-nitrogen ratios, especially in animal manure digesters). It is conceivable that some of the feedstocks considered here could be used in anaerobic digesters. For the sake of simplicity, ICF did not consider any multi-feedstock applications in our assessment; however, it is important to recognize that the RNG production market will continue to include mixed feedstock processing in a manner that is cost-effective. Agricultural Residues Agricultural residues include the material left in the field, orchard, vineyard, or other agricultural setting after a crop has been harvested. More specifically, this resource is inclusive of the unusable portion of crop, stalks, stems, leaves, branches, and seed pods. Agricultural residues (and sometimes crops) are often added to anaerobic digesters ICF extracted information from the U.S. DOE Bioenergy KDF including the following agricultural residues: wheat straw, corn stover, sorghum stubble, oats straw, barley straw, citrus residues, noncitrus residues, tree nut residues, sugarcane trash, cotton gin trash, cotton residue, rice hulls, sugarcane bagasse, and rice straw. ICF extracted data from the Bioenergy KDF at three price points: $30/ton, $50/ton and $100/ton. The table below lists the energy content on a high heating value (HHV) basis for the various agricultural residues included in the analysis—these are based on values reported by the California Biomass Collaborative. To estimate the RNG production potential, ICF assumed a 65% efficiency for thermal gasification systems.23

22 NREL, Biomass Gasifier “Tars”: Their Nature, Formation, and Conversion, November 1998, NREL/TP-570-25357. Available online at https://www.nrel.gov/docs/fy99osti/25357.pdf. 23 The 2011 AGF Report on RNG report indicated a range of thermal gasification efficiencies in the range of 60% to 70%, depending upon the configuration and process conditions. And the report authors also used a conversion 29

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Table 19. Heating Values for Agricultural Residues MSW Component Btu/lb, dry MMBtu/ton, dry Wheat straw 7,527 15.054 Corn stover 7,587 15.174 Sorghum stubble 6,620 13.24 Oats straw 7,308 14.616 Barley straw 7,441 14.882 Citrus residues 8,597 17.194 Noncitrus residues 7,738 15.476 Tree nut residues 8,597 17.194 Sugarcane trash 7,738 15.476 Cotton gin trash 7,058 14.116 Cotton residue 7,849 15.698 Rice hulls 6,998 13.996 Sugarcane bagasse 7,738 15.476 Rice straw 6,998 13.996

ICF developed the RNG production potential from agricultural residues in a low and high scenario. § In the low scenario, ICF assumed that 20% of the agricultural residues available at $50/dry ton would be diverted to thermal gasification systems. § In the high scenario, ICF assumed that 50% of the agricultural residues available at $50/dry ton would be diverted to thermal gasification systems. ICF calculated the technical resource potential for RNG production from agricultural residues assuming that all of the material available at $100/ton could be gasified at 100% efficiency. The figures below show the low and high RNG resource potential from the thermal gasification of agricultural residues between 2025 and 2040. The table that follows includes the total annual RNG production potential (in units of tBtu/y) for 2040 in the low, high, and technical resource potential scenarios.

efficiency of 65%. More recently, GTI estimated the potential for RNG from the thermal gasification of wood waste in California (GTI, Low-Carbon Renewable Natural Gas from Wood Wastes, February 2019, available online at https://www.gti.energy/wp-content/uploads/2019/02/Low-Carbon-Renewable-Natural-Gas-RNG-from-Wood- Wastes-Final-Report-Feb2019.pdf), and assumed a conversion efficiency of 60%. 30

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Figure 16. RNG Production Potential from Agricultural Residue, Low Resource Potential Scenario, in tBtu/y

160 New England 140 Mid-Atlantic 120 East North Central 100 West North Central 80 South Atlantic 60 East South Central 40 West South Central 20 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

Figure 17. RNG Production Potential from Agricultural Residue, High Resource Potential Scenario, in tBtu/y

400 New England 350 Mid-Atlantic 300 East North Central 250 West North Central 200 South Atlantic 150 East South Central 100 West South Central 50 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

Table 20. Annual RNG Production Potential from Agricultural Residues in 2040, tBtu/y RNG Potential from Agricultural Residue, tBtu/y RNG Potential East West East West New Mid- South Scenario North North South South Mountain Pacific England Atlantic Atlantic Central Central Central Central Low Resource 0.1 0.5 0.3 19.5 3.2 0.1 1.0 1.8 12.0 High Resource 0.1 9.2 142.6 361.0 26.9 7.3 28.8 27.3 37.3 Technical Resource 0.3 42.1 623.8 1,405.1 93.8 38.7 123.3 115.1 126.3

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ICF estimates that between 255 and 641 tBtu/y of RNG could be produced by 2040 at the national level in the low and high scenarios, respectively from the thermal gasification of agricultural residues. Forestry and Forest Product Residues Biomass generated from logging, forest and fire management activities, and milling. Inclusive of logging residues (e.g., bark, stems, leaves, branches), forest thinnings (e.g., removal of small trees to reduce fire danger), and mill residues (e.g., slabs, edgings, trimmings, sawdust) are considered in the analysis. This includes materials from public forestlands (e.g., state, federal), but not specially designated forests (e.g., roadless areas, national parks, wilderness areas) and includes sustainable harvesting criteria as described in the U.S. DOE Billion-Ton Update. The updated DOE Billion-Ton study was altered to include additional sustainability criteria. Some of the changes included: 24 § Alterations to the biomass retention levels by slope class (e.g., slopes with between 40% and 80% grade included 40% biomass left on-site, compared to the standard 30%). § Removal of reserved (e.g., wild and scenic rivers, wilderness areas, USFS special interest areas, national parks) and roadless designated forestlands, forests on steep slopes and in wet land areas (e.g., stream management zones), and sites requiring cable systems. § The assumptions only include thinnings for over-stocked stands and didn’t include removals greater than the anticipated forest growth in a state. § No road building greater than 0.5 miles. These additional sustainability criteria provide a more realistic assessment of available forestland than other studies. ICF extracted information from the U.S. DOE Bioenergy KDF, which includes information on forest residues such as thinnings, mill residues, and different residues from woods (e.g., mixedwood, hardwood, and softwood). ICF extracted data from the Bioenergy KDF at three price points: $30/ton, $60/ton, and $100/ton. The table below lists the energy content on a HHV basis for the various forest and forest product residue elements considered in the analysis. To estimate the RNG production potential, ICF assumed a 65% efficiency for thermal gasification systems. Table 21. Heating Values for Forestry and Forest Product Residues Forestry and Forest Product Btu/lb, dry MMBtu/ton, dry Other forest residue 8,597 17.19 Other forest thinnings 9,027 18.05 Primary mill residue 8,597 17.19 Secondary mill residue 8,597 17.19 Mixed wood, residue Hardwood, lowland, residue Hardwood, upland, residue 6,500 13.00 Softwood, natural, residue Softwood, planted, residue

24 Bryce Stokes, Department of Energy, “2011 Billion-Ton Update – Assumptions and Implications Involving Forest Resources,” September 29, 2011, http://web.ornl.gov/sci/ees/cbes/workshops/Stokes_B.pdf. 32

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ICF developed the RNG production potential from forest residues in a low and high scenario. § In the low scenario, ICF assumed that 30% of the forest and forestry product residues available up to $30/dry ton would be diverted to thermal gasification systems. § In the high scenario, ICF assumed that 60% of the forest and forestry product residues available up to $60/dry ton would be diverted to thermal gasification systems. ICF calculated the technical resource potential for RNG production from forest and forestry product residues assuming that all of the material available at $100/ton could be gasified at 100% efficiency. The figures below show the low and high RNG resource potential from the thermal gasification of forestry and forest product residues between 2025 and 2040. The table that follows includes the total annual RNG production potential (in units of tBtu/y) for 2040 in the low, high, and technical resource potential scenarios. Figure 18. RNG Production Potential from Forestry and Forest Product Residues, Low Resource Potential Scenario, in tBtu/y

40 New England 35 Mid-Atlantic 30 East North Central 25 West North Central 20 South Atlantic 15 East South Central 10 West South Central 5 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

Figure 19. RNG Production Potential from Forestry and Forest Product Residues, High Resource Potential Scenario, in tBtu/y

400 New England 350 Mid-Atlantic 300 East North Central 250 West North Central 200 South Atlantic 150 East South Central 100 West South Central 50 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

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Table 22. Annual RNG Production Potential from Forestry and Forest Product Residues, tBtu/y RNG Potential from Forestry and Forest Product Residues, tBtu/y RNG Potential East West East West New Mid- South Scenario North North South South Mountain Pacific England Atlantic Atlantic Central Central Central Central Low Resource 3.6 4.8 9.7 6.5 37.6 20.6 16.3 2.7 6.8 High Resource 7.3 9.7 19.3 13.0 75.2 41.3 37.1 19.3 13.6 Technical Resource 18.6 24.9 49.5 33.4 192.9 105.8 106.7 85.5 34.7

ICF estimates that between 109 and 236 tBtu/y of RNG could be produced by 2040 at the national level in the low and high scenarios, respectively from the thermal gasification of forest and forestry product residues. Energy Crops Energy crops are inclusive of perennial grasses, trees, and some annual crops that can be grown specifically to supply large volumes of uniform, consistent quality feedstocks for energy production. ICF extracted data from the Bioenergy KDF at three price points: $50/ton, $70/ton and $100/ton. The table below lists the energy content on a HHV basis for the various energy crops included in the analysis. To estimate the RNG production potential, ICF assumed a 65% efficiency for thermal gasification systems. Table 23. Heating Values for Energy Crops Energy Crop Btu/lb, dry MMBtu/ton, dry Willow 8,550 17.10 Poplar 7,775 15.55 Switchgrass 7,929 15.86 Miscanthus 7,900 15.80 Biomass sorghum 7,240 14.48 Pine 6,210 12.42 Eucalyptus 6,185 12.37 Energy cane 7,900 15.80

ICF developed the RNG production potential from energy crops in a low and high scenario. § In the low scenario, ICF assumed that 50% of the energy crops available at $50/dry ton would be diverted to thermal gasification systems. § In the high scenario, ICF assumed that 50% of the energy crops available at $70/dry ton would be diverted to thermal gasification systems. ICF calculated the technical resource potential for RNG production from energy crops assuming that all of the material available at $100/ton could be gasified at 100% efficiency. The figures below show the low and high RNG resource potential from the thermal gasification of energy crops between 2025 and 2040. The table that follows includes the total annual RNG production potential (in units of tBtu/y) for 2040 in the low, high, and technical resource potential scenarios.

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Figure 20. RNG Production Potential from Energy Crops, Low Resource Potential Scenario, in tBtu/y

60 New England

50 Mid-Atlantic East North Central 40 West North Central 30 South Atlantic East South Central 20 West South Central 10 Mountain Annual(tBtu/y) RNG Production 0 Pacific 2025 2030 2035 2040

Figure 21. RNG Production Potential from Energy Crops, High Resource Potential Scenario, in tBtu/y

350 New England 300 Mid-Atlantic

250 East North Central West North Central 200 South Atlantic 150 East South Central 100 West South Central 50 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

Table 24. Annual RNG Production Potential from Energy Crops, tBtu/y RNG Potential from Energy Crops, tBtu/y RNG Potential East West East West New Mid- South Scenario North North South South Mountain Pacific England Atlantic Atlantic Central Central Central Central Low Resource 0.2 2.2 1.5 35.4 18.1 9.3 56.5 0.2 0.0 High Resource 0.5 9.4 64.4 260.0 77.3 91.6 330.5 3.9 0.0 Technical Resource 3.0 84.3 872.5 1,508.1 357.1 460.8 1,266.4 48.7 0.0

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ICF estimates that between 123 and 838 tBtu/y of RNG could be produced by 2040 at the national level in the low and high scenarios, respectively from the thermal gasification of forest and forestry product residues. Renewable gas from MSW Municipal solid waste (MSW) represents the trash and various items that household, commercial, and industrial consumers throw away—including materials such as glass, construction and demolition (C&D) debris, food waste, paper and paperboard, plastics, rubber and leather, textiles, wood, and yard trimmings. About 25% of MSW is currently recycled, 9% is composted, and 13% is combusted for energy recovery. And the roughly 50% balance of MSW is landfilled. ICF limited our consideration to the potential for utilizing MSW that would otherwise be landfilled as a feedstock for thermal gasification; this excludes MSW that is recycled or directed to waste-to- energy facilities. ICF also excluded food waste from consideration in this sub-section, and opted to consider that feedstock as a separate resource for AD systems.25 ICF extracted information from the U.S. DOE Bioenergy KDF, which includes information collected as part of U.S. DOE’s Billion-Ton Report (updated in 2016). The Bioenergy KDF includes the following waste residues: C&D debris, paper and paperboard, plastics, rubber and leather, textiles, wood, yard trimmings, and other. ICF extracted data from the Bioenergy KDF at two price points: $30/ton and $100/ton. The table below lists the energy content on a HHV basis for the various components of MSW. To estimate the RNG production potential, ICF assumed a 65% efficiency for thermal gasification systems. Table 25. Heating Values for MSW Components MSW Component Btu/lb, dry MMBtu/ton, dry C&D waste 6,788 13.58 Other 5,600 11.20 Paper and paperboard 7,642 15.28 Plastics 19,200 38.40 Rubber and leather 11,300 22.60 Textiles 8,000 16.00 MSW wood 8,304 16.61 Yard trimmings 6,448 12.90

ICF developed the RNG production potential from MSW in a low and high scenario. § In the low scenario, ICF assumed that 30% of the non-biogenic fraction of MSW available at $30/dry ton from the Bioenergy KDF for relevant waste residues in MSW. ICF notes that at the price of $30/ton, the DOE reports no MSW wood or yard trimmings. § In the high scenario, ICF assumed that 60% of the non-biogenic fraction of MSW available at $100/dry ton from the Bioenergy KDF for the CD waste, other, paper and paperboard, plastics, rubber and leather, and textiles waste could be gasified; and that 75% of the MSW wood and yard trimmings could be gasified.

25 ICF notes that because the assessment of thermal gasification is limited to the non-biogenic fraction of MSW, the consideration of this material being diverted from landfills has no material impact on estimated RNG production potential from landfills. 36

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ICF calculated the technical resource potential from RNG production from MSW assuming that all of the material that is currently landfilled for each MSW component could be gasified at 100% efficiency. The figures below show the low and high RNG resource potential from the thermal gasification of the non-biogenic fraction of MSW between 2025 and 2040. The table that follows includes the total annual RNG production potential (in units of tBtu/y) for 2040 in the low, high, and technical resource potential scenarios. Figure 22. RNG Production Potential from Non-Biogenic MSW, Low Resource Potential Scenario, in tBtu/y

60 New England

50 Mid-Atlantic East North Central 40 West North Central 30 South Atlantic East South Central 20 West South Central 10 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

Figure 23. RNG Production Potential from Non-Biogenic MSW, High Resource Potential Scenario, in tBtu/y

140 New England 120 Mid-Atlantic

100 East North Central West North Central 80 South Atlantic 60 East South Central 40 West South Central 20 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

Table 26. Annual RNG Production Potential from MSW, tBtu/y RNG Potential from MSW, tBtu/y RNG Potential East West East West New Mid- South Scenario North North South South Mountain Pacific England Atlantic Atlantic Central Central Central Central

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Low Resource 14.4 40.6 45.9 17.7 56.9 11.2 15.3 8.8 45.4 High Resource 32.4 91.6 103.4 46.1 136.3 43.2 83.2 50.1 108.5 Technical Resource 81.1 229.6 259.2 115.5 341.6 108.4 208.5 125.6 271.9

ICF estimates that between 256 and 695 tBtu/y of RNG could be produced by 2040 at the national level in the low and high scenarios, respectively from the non-biogenic fraction of MSW via thermal gasification. RNG from P2G/Methanation Power-to-gas (P2G) is a form of energy technology that converts electricity to a gaseous fuel. Electricity is used to split water into hydrogen and oxygen, and the hydrogen can be further processed to produce methane when combined with a source of carbon dioxide. If the electricity is sourced from renewable resources, such as wind and solar, then the resulting fuels are carbon neutral. The key process in P2G is the production of hydrogen from renewably generated electricity by means of electrolysis. This hydrogen conversion method is not new, and there are three electrolysis technologies with different efficiencies and in different stages of development and implementation: § Alkaline electrolysis; § Proton exchange membrane electrolysis; and § Solid oxide electrolysis. The hydrogen produced from P2G is a highly flexible energy product that can be used in multiple ways. It can be: § Stored as hydrogen and used to generate electricity at a later time using fuel cells or conventional generating technologies. § Injected as hydrogen into the natural gas system, where it augments the natural gas supply. § Converted to methane and injected into the natural gas system. The last option, methanation, involves the combination of hydrogen with carbon dioxide (CO2), and converting the two gases into methane. The methane produced is RNG, and is a clean alternative to conventional fossil natural gas, as it can displace fossil natural gas for combustion in buildings, residences, vehicles and electricity generation. Methanation avoids the cost and inefficiency associated with hydrogen storage and creates more flexibility in the end use through the natural gas system. The P2G RNG conversion process can also be coordinated with conventional biomass-based RNG production by using the surplus CO2 in biogas to produce the methane, creating a productive use for the CO2. A critical advantage of P2G is that the RNG produced is a highly flexible and interchangeable carbon neutral fuel. With a storage and infrastructure system already established, RNG from P2G can be produced and stored over the long term, allowing for deployment during peak demand periods in the energy system. RNG from P2G also utilizes existing natural gas transmission and distribution infrastructure, which is highly reliable and efficient, and in many cases already paid for. The flexibility of hydrogen provides advantages beyond as an input to methanation for RNG. Hydrogen can be used in place of natural gas in many applications, and hydrogen can be mixed directly with natural gas in pipeline systems, although there are physical limits to the level of

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hydrogen blending in natural gas pipeline systems.26 In addition, currently most commercially produced hydrogen is derived from conventional natural gas and does not have the environmental benefits of carbon neutral hydrogen produced from P2G. Whether hydrogen or methane is the final product, P2G offers the potential to produce carbon neutral fuels from sustainable resources and leverage existing natural gas infrastructure for long- term and large-scale storage. Competing electric energy storage options, including batteries and pumped hydro storage, are expensive as a long-term energy storage option, and can be more expensive than P2G storage. P2G also offers other benefits, such as a fully dispatchable load capable of supplying grid balancing or ancillary services. ICF estimated the potential for P2G to contribute towards RNG production over a series of steps. P2G and Curtailment Firstly, ICF utilized our Integrated Planning Model P2G discussions often focus on the role and (IPM®), which provides true integration of scale of excess (curtailed) renewable electricity as the source for hydrogen and wholesale power, system reliability, environmental RNG production. constraints, fuel choice, transmission, capacity Renewable electricity generation is generally expansion, and all key operational elements of curtailed as a result of system-wide generators on the power grid in a linear optimization oversupply and local transmission framework. The model utilizes a Windows™-based constraints. database platform and interface that captures a The concept is simple: P2G systems could detailed representation of every electric boiler and use curtailed renewable electricity generator in the power market being modeled. The generation, and reduce the costs of fundamental logic behind the model determines the operating the electrolyzer. This would help least-cost means of meeting electric generation to maximize renewable electricity generation, simply by using hydrogen or energy and capacity requirements while complying methane as the renewable energy carrier with specified constraints, including air pollution instead of electrons. regulations, transmission constraints, and plant- The issue of curtailed renewable electricity, specific operational constraints. however, is a complicated one. A detailed ICF used the IPM platform to develop a supply-cost analysis of expected curtailment rates under increasingly stringent RPS programs was curve for renewable electricity, starting in 2025 and beyond the scope of this report. Instead, we going out to 2040. We did this over a series of acknowledge the importance of developing steps. Firstly, the model was constrained by all and deploying P2G systems to use curtailed finalized and on-the-books state-level RPS and electricity in the near term as a transitional Clean Energy Standard (CES) policies and regional carbonapproach markets. to achieve The model P2G cost does reductions. not explicitly capture renewable targets announced by municipalities and corporate actors. The RPS demand modeled represents a floor on incremental renewable demand, since the model conducts capacity expansion based on relative economics–to the extent that renewable energy is cost competitive relative to other technology types, the model will choose to build renewable energy even in excess of modeled targets. The table below shows the share of generation represented by renewable resource for each region (note that the regions in IPM are distinguished by independent system operator (ISO), regional transmission organization (RTO), reliability council, etc. and are not consistent with the US Census Regions that have been employed elsewhere in the study). The table also includes the share of electricity generation that is attributable to solar and wind.

26 For the purposes of this report, ICF did not assume any hydrogen blending into natural gas pipeline systems. 39

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Table 27. Renewable Share of Electricity Generation in RPS-Compliant Run using IPM Renewable Share: Renewable Share: Region Electricity Generation Solar and Wind 2030 2035 2040 2030 2035 2040 US 27% 28% 29% 20% 20% 21% Non CA- WECC 45% 45% 47% 19% 20% 22% CAISO 70% 69% 73% 49% 49% 56% SPP 46% 45% 44% 42% 41% 40% MISO 28% 29% 31% 24% 25% 25% SERC 8% 8% 10% 4% 4% 4% ERCOT 30% 27% 25% 29% 27% 25% ISONE 44% 47% 49% 30% 34% 36% NYISO 50% 51% 60% 29% 31% 39% PJM 13% 14% 14% 11% 12% 12% FRCC 12% 12% 12% 11% 11% 11%

In the last step of the analysis using the IPM platform, ICF made a simple calculation: We developed a supply-cost curve for renewable electricity generation by extracting the total consumption of renewable electricity (in GWh) by region in 2025, 2030, 2035, and 2040, assuming all RPS and CES policies are achieved on time. ICF then determined what the corresponding levelized cost of energy (LCOE) in $10/MWh increments up to $110/MWh would be to deploy the same number of generating assets to produce the same amount of renewable electricity. ICF used those estimates, as shown in the figure below, to develop an outlook for P2G using dedicated renewable electricity generation. Figure 24. Supply-Cost Curve for Dedicated Renewable Electricity for P2G Systems, 2025-2040 450,000 $110-$120/MWh 400,000 $100-$110/MWh 350,000 $90-$100/MWh 300,000 $80-$90/MWh 250,000 $70-$80/MWh $60-$70/MWh

(GWh) 200,000 150,000 $50-$60/MWh $40-$50/MWh 100,000 $30-$40/MWh 50,000

Dedicated Renewable Electricity Renewable Dedicated $20-$30/MWh 0 $10-$20/MWh 2025 2030 2035 2040

ICF determined how much hydrogen and methane could be produced using P2G / methanation systems based on the supply-cost curve constructed for dedicated renewable electricity generation. We assumed a capacity factor ranging from 50% to 80% for dedicated renewable

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electricity generation. The energy price in each scenario was based on the LCOE supply curve for renewable electricity generation. ICF limited our considerations for the low resource potential for RNG derived from P2G and methanation to the curtailed renewable electricity generation available and dedicated renewable electricity generation that is estimated to be available at a LCOE less than $50/MWh. In the high resource potential scenario, we included curtailed renewable electricity generation and dedicated renewable electricity generation that is estimated to be available at a LCOE less than $60/MWh. ICF assumed that all of the renewable electricity would be available to an electrolyzer to produce hydrogen. Furthermore, ICF assumed the co-location of a methanation unit. The figure below includes the assumed conversion efficiencies for hydrogen production from an electrolyzer (blue) and for the methanation reaction to produce RNG for injection (orange). Figure 25. Assumed Efficiency for Electrolysis and Methanation, 2020-2040

85%

80%

75%

70%

65% Efficiency, Electrolyzer Efficiency, Methanator

System System Efficiencies 60%

55%

50% 2020 2025 2030 2035 2040

These assumptions yield the resource potential listed in Table 28 below; which also includes the hydrogen produced in the first step using P2G. The low and the high resource potential estimates are presented assuming capacity factors of 5% and 10% for systems using curtailed electricity and capacity factors of 50% and 80% for systems using dedicated renewable electricity generation.

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Table 28. Annual H2 and RNG Production (in tBtu /y) from P2G using Dedicated Renewable Electricity Generation, 2025-2040

Resource: Capacity 2025 2030 2035 2040 Dedicated RE Factor 50% 11.5 297.1 372.2 447.1 Low 80% 18.4 475.3 595.6 715.4 50% 11.5 364.6 448.7 530.2 High 80% 18.4 583.4 718.0 848.3 Max 95% 93.2 935.7 1,064.0 1,210.5 50% 8.6 230.2 297.8 357.7 Low 80% 13.8 368.4 476.5 572.3 50% 8.6 282.5 359.0 424.1 High 80% 13.8 452.1 574.4 678.7 Max 95% 74.5 748.5 851.2 968.4

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Greenhouse Gas Emissions of RNG GHG Accounting Framework and Methodology GHG emission accounting for a given source of emissions relies on the application of an emission factor to activity data. In the example below, we use the emission factor for fossil or geological natural gas to determine the annual GHG emissions associated with an average household’s natural gas consumption (the activity data) using data from the Environmental Protection Agency (EPA)27 and the American Gas Association (AGA):28 12 34 6 7789: 12 34 6 !"#$$#%&'()*%+_-. 0 5 ; × =)*#>#*?@(*( 0 ; = .E._!"#$$#%&$ 0 5 ;, calculated as: 7789: AB:C6 AB:C6 JK LM O PPQ*R JK LM O 53.11 N × 63.5 = 3,372 N PPQ*R ℎ%R$O ℎ%R$O RNG represents a valuable renewable energy source with a low or net negative emissions factor depending on the feedstock and the accounting framework. The GHG emission accounting method and scope employed can have a significant impact on how GHG emission factors for RNG are reported and estimated. GHG emissions accounting becomes complex when an assessment scope includes a diverse set of sources. This is most often seen in GHG emission inventories for agencies, corporations, and jurisdictions (e.g., community, city, county, state, country) where entities must account for a wide range of sectors (e.g., transportation, energy, agriculture). Each sector has an array of emissions sources with unique variations in emission factors, activity data, and other aspects to consider. GHG emission profiles can be complex for specific products or resources, when a scope may consider elements outside of product use, such as emissions from supply chains, co-products, and disposal. For example, California’s Low Carbon Fuel Standard (LCFS) relies on a life-cycle assessment approach for estimating carbon intensities of transportation fuels. As a result, LCFS emissions for a specific transportation fuel pathway includes all emission sources in the fuel lifecycle from resource extraction to final consumption in a vehicle. IPCC Guidelines for Biogenic Fuel Sources GHG emission accounting for inventories typically relies on guidance from the Intergovernmental Panel on Climate Change (IPCC) developed in 2006.29 The IPCC provides guidance for different levels of detail depending on the availability of data and capacity of the inventory team for all sectors typically considered in a GHG inventory. GHG emission reporting programs that address a specific sector or subsector, like the LCFS, may have unique guidelines that diverge from IPCC and typical inventories in accounting methods. IPCC guidelines state that CO2 emissions from biogenic fuel sources (e.g., biogas or biomass based RNG) should not be included when accounting for emissions in combustion – only CH4 and N2O are included. This is to avoid any upstream “double counting” of CO2 emissions that occur in the agricultural or land use sectors per IPCC guidance.

27 US EPA. 2018. Emission Factors for Greenhouse Gas Inventories, Available online at https://www.epa.gov/sites/production/files/2018-03/documents/emission-factors_mar_2018_0.pdf. 28 Personal communication with AGA. 29 IPCC. 2006. 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Available at: https://www.ipcc- nggip.iges.or.jp/public/2006gl/. 44

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Other approaches exclude biogenic CO2 in combustion as it is assumed that the CO2 sequestered by the biomass during its lifetime offsets combustion CO2 emissions. This method of excluding biogenic CO2 is still commonly practiced for RNG users and producers. Greenhouse Gas Protocol The Greenhouse Gas Protocol is a commonly used set of reporting standards developed by the World Resources Institute and the World Business Council for Sustainable Development. A GHG Protocol-based approach is most common with corporations, but still incorporates many of the same sources and emission factors used by jurisdictions and public agencies. The GHG Protocol uses “Scope” levels to define the different sources and activity data included within an assessment. Instead of thinking in terms of geographic or sector-based boundaries, the Protocol groups emissions in direct and indirect categories through these Scopes. Figure 26 shows how the Protocol groups these emission sources by Scopes, and how they relate to an organization’s operations. Figure 26. Scopes for categorizing emissions under the GHG Protocol (GHG Protocol 2019).

Organizations most often may limit their assessment to Scope 1 and 2 emissions, which includes directly controlled assets. Scope 3 emissions reflect a life cycle assessment approach that includes supply chain activities and associated, but not directly controlled, organizations. There is often confusion about who can claim and monetize the environmental benefits of RNG production and consumption across various stakeholders and GHG reporting structures. For example, a corporation based in California buys RNG from a fuel distributor to fuel their fleet of shuttle buses. The RNG was produced out of state and transported and sold in California to take advantage of the LCFS credit program. The value of the LCFS credits are owned and monetized by the various actors within the fuel production supply chain. However, the corporation purchasing the RNG as an end-user can still factor in the fuel’s low carbon intensity into their corporate emissions accounting by including the volumes purchased in their Scope 1 emissions.

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RNG and GHG Accounting There are two broad methodologies to account for the GHG emissions from RNG: a combustion accounting framework or a lifecycle accounting framework. § A combustion GHG accounting framework is the standard approach for most volumetric GHG targets, inventories and mitigation measures (e.g., RPS programs, carbon taxes, cap- and-trade programs, etc.) as they are more closely tied to a particular jurisdiction – where the emissions physically occur. Using the combustion framework, the CO2 emissions from the combustion of biogenic renewable fuels are considered zero, or carbon neutral. In other words, RNG has a carbon intensity of zero. This includes RNG from any biogenic feedstock, including landfill gas, animal manure and food waste. Upstream emissions, whether positive (electricity emissions associated with biogas processing) or negative (avoided methane emissions), are not included. § When using a lifecycle accounting methodology RNG’s carbon intensity (i.e., GHG emissions per unit of energy) varies substantially between feedstocks and production methods. Carbon intensities can also vary by location of production and how the fuel is transported and distributed. The GHG accounting methods and scopes previously discussed dictate which of RNG’s life-cycle elements are included as a carbon intensity in emissions reporting. Figure 27 below shows the various steps in RNG production—including the collection and processing of raw biogas, injection into the pipeline, transmission and distribution to end users, and then finally use as a fuel in various applications. The combustion approach (in green) focuses on the end use and recognizes RNG as a biogenic source. The lifecycle approach (in blue) accounts for all the emissions associated with each step in the supply chain associated with RNG production. Figure 27. Overview of GHG Accounting Frameworks for RNG

GHG Emissions from RNG Resource Assessment ICF reports the GHG emission reductions for RNG consistent with the combustion approach outlined pre IPCC guidelines stating that emissions from biogenic fuel sources should not be included when accounting for emissions in combustion. This accounting approach is employed to avoid any upstream “double counting” of emissions that occur in the agricultural or land use sectors per IPCC guidance. ICF did account for N2O and CH4 emissions during combustion of RNG. 46

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ICF used an emissions factor of 53.06 kg/MMBtu for fossil natural gas. ICF also developed an estimated emissions factor of 15 kg/MMBtu for renewable gas from thermal gasification of MSW and incorporated that into the analysis. The tables below show the range of GHG emission reductions in units of million metric tons (MMT) for the low and high resource potential scenarios. ICF estimates that in the low resource potential scenario, about 101 MMT of GHG emissions would be reduced through the deployment of RNG; and in the high resource potential scenario, 235 MMT of GHG emissions could be reduced. The GHG emission reduction potential in the low and high resource potential scenarios is equivalent to displacing 59-95% of the average GHG emissions attributable to natural gas consumption in the residential energy sector nationwide over the ten-year period 2009-2018 (see Figure 28 below). Average CO2 Emissions (MMT) from Figure 28. Average Annual CarbonNatural Dioxide Emissions Gas Consumption, (in MMT) from Natural 2009 Gas- Consumption2018 in the U.S. 2009-2018 Residential

Electric Gen 248 466

Commercial 170

Industrial

392

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Table 29. GHG Emission Reductions (in MMT) for RNG in the Low Resource Potential Case Low RNG Resource Case | GHG Emission Reduction Potential, MMT Feedstock East North West North South East South West South New England Mid-Atlantic Mountain Pacific Total Central Central Atlantic Central Central RNG from biogenic or renewable resources Landfill Gas 0.7 3.1 5.6 1.5 4.7 1.9 3.5 2.0 5.1 28.0 Animal Manure 0.4 0.6 1.6 2.4 1.7 1.0 1.9 1.5 1.1 12.3 WRRF 0.1 0.2 0.2 0.1 0.2 0.1 0.1 0.1 0.2 1.2

Food Waste 0.1 0.3 0.3 0.1 0.3 0.0 0.1 0.0 0.3 1.5 Ag Residue 0.0 0.2 3.0 7.7 0.5 0.2 0.6 0.6 0.8 13.5 Forestry and Forest 0.2 0.3 0.5 0.3 2.0 1.1 0.9 0.1 0.4 5.8 Residue Energy Crops 0.0 0.1 0.1 1.9 1.0 0.5 3.0 0.0 0.0 6.5 Sub-Total 1.5 4.8 11.4 13.9 10.4 4.7 10.0 4.4 7.8 68.9 Renewable gas from MSW MSW 0.5 1.5 1.7 0.7 2.2 0.4 0.6 0.3 1.7 9.8 RNG from P2G / Methanation P2G / Methanation 22.3 Totals 2.0 6.3 13.2 14.6 12.5 5.2 10.6 4.7 9.6 100.9

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Table 30. GHG Emission Reductions (in MMT) for RNG in the High Resource Potential Case High RNG Resource Case | GHG Emission Reduction Potential, MMT Feedstock East North West North South East South West South New England Mid-Atlantic Mountain Pacific Total Central Central Atlantic Central Central RNG from biogenic or renewable resources Landfill Gas 1.2 5.0 9.2 2.5 7.7 3.1 5.6 3.3 8.2 45.9 Animal Manure 0.8 1.3 3.2 4.7 3.4 2.0 3.8 3.1 2.2 24.5 WRRF 0.1 0.3 0.4 0.1 0.3 0.1 0.2 0.1 0.3 1.8 Food Waste 0.2 0.5 0.5 0.2 0.7 0.2 0.4 0.2 0.5 3.4

Ag Residue 0.0 0.5 7.6 19.2 1.4 0.4 1.5 1.4 2.0 34.0 Forestry and Forest 0.4 0.5 1.0 0.7 4.0 2.2 2.0 1.0 0.7 12.5 Residue Energy Crops 0.0 0.5 3.4 13.8 4.1 4.9 17.5 0.2 0.0 44.4 Sub-Total 2.7 8.6 25.3 41.2 21.5 12.9 31.1 9.3 14.0 166.6 Renewable gas from MSW MSW 1.2 3.5 3.9 1.8 5.2 1.6 3.2 1.9 4.1 26.4 RNG from P2G / Methanation P2G / Methanation 42.3 Totals 3.9 12.1 29.3 42.9 26.7 14.5 34.2 11.2 18.1 235.3

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RNG Cost Assessment ICF developed assumptions for the capital expenditures and operational costs for RNG production from the various feedstock and technology pairings outlined previously—and developed supply- cost estimates for RNG with an outlook to 2040. ICF characterizes costs based on a series of assumptions regarding the production facility sizes (as measured by gas throughput in units of standard cubic feet per minute [SCFM]), gas upgrading and conditioning and upgrading costs (depending on the type of technology used, the contaminant loadings, etc.), compression, and interconnect for pipeline injection. We also include operational costs for each technology type. The table below outlines some ICF’s baseline assumptions that we employ in our RNG costing model for anaerobic digestion systems and thermal gasification systems. Table 31. Illustrative Cost Assumptions Developed to Estimate RNG Production Costs in 2040 Cost Parameter ICF Cost Assumptions

• Differentiate by feedstock and technology type: AD and TG Facility Sizing • Prioritize larger facilities to the extent feasible, but driven by resource estimate Gas Conditioning • These costs depend on the feedstock and the technology required. and Upgrade

Compression • Capital costs for compressing the conditioned/upgraded gas for pipeline injection.

• Costs for each equipment type–digesters, conditioning equipment, collection Operational Costs equipment, and compressors–as well as utility charges for estimated electricity consumption.

Feedstock • Feedstock costs (for thermal gasification), ranging from $30 to $100 per dry ton.

• Financing costs, including carrying costs of capital (assuming a 60/40 debt/equity ratio Financing and an interest rate of 7%), an expected rate of return on investment (set at 10%), and a 15 year repayment period.

• Costs of interconnection—representing the point of receipt and any pipeline extension. This cost is in line with financing, constructing, and maintaining a pipeline of about 1- Interconnection mile in length. The costs of delivering the same volumes of RNG that require pipeline construction greater than 1-mile will increase, depending on feedstock/technology type, with a typical range of $1-5/MMBtu.

• 20 years. The levelized cost of gas was calculated based on the initial capital costs in Project lifetimes Year 1, annual operational costs discounted at an annual rate of 5% over 20 years, and biogas production discounted at an annual rate of 5% for 20 years.

ICF notes that our cost estimates are not intended to replicate a developer’s estimate when deploying a project. For instance, ICF recognizes that the cost category “conditioning and upgrading” actually represents an array of decisions that a project developer would have to make with respect to CO2 removal, H2S removal, siloxane removal, N2/O2 rejection, deployment of a thermal oxidizer, etc. Furthermore, we understand that project developers have reported a wide range of interconnection costs, with numbers as low as $200,000 reported in some states, and as high as $9 million in other states. We appreciate the variance between projects, including those that use anaerobic digestion, thermal gasification, or power-to-gas technologies; and our supply- 50

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cost curves are meant to be illustrative, rather than deterministic. This is especially true of our outlook to 2040—we have not included significant cost reductions that might occur as a result of a rapidly growing RNG market, or sought to capture some technological breakthrough or breakthroughs. We have made some assumptions in line with those in the publicly available literature regarding potential decreases in the costs of P2G systems; however, for anaerobic digestion and thermal gasification systems we have focused on projects that have reasonable scale, representative capital expenditures, and reasonable operations and maintenance estimates. ICF’s cost estimates in the following sections are shown for 2040 (reported in 2019 dollars); and we have made only modest assumptions with respect to the potential for RNG cost reductions. The most significant assumption in our outlook to 2040 is the presumption that the underlying structure of the market will change. Today in the U.S., there is no standard market price for RNG— rather, the market is largely driven by the value of environmental commodities such as those derived from participating in the federal Renewable Fuel Standard and/or California’s LCFS program. For instance, many landfill gas projects are estimated to produce RNG at a cost of $10- 20/MMBtu, and dairy manure projects may produce RNG at a cost of closer to $40/MMBtu. ICF reports substantial RNG production volumes at prices lower than $20/MMBtu (see below); so how can we reconcile today’s estimated production costs of $10-$40/MMBtu with only 40 tBtu/y of RNG production from AD systems with cost estimates for a market producing up to 4,500 tBtu/y using a combination of AD systems, TG systems, and P2G systems? Clearly, this is a non-trivial exercise. And ultimately, ICF’s cost estimates focus on a more mature market with some economies of scale achieved as a result of hundreds of projects being developed to achieve the volumes presented. Further, we assume that contractual arrangements will be considerably different and local/regional barriers with respect to RNG pipeline injection have been overcome. Together, these assumptions help us to develop a reasonable outlook on RNG production costs to 2040.

Achieving Significant RNG Production Cost Reductions Advanced manufacturing (or the lack thereof) will play an important role in making RNG more cost-competitive with geological natural gas and other fossil-based resource. To help achieve more significant reductions, the various aspects of RNG production (e.g., gas receipt skids, gas separation and upgrading equipment, conversion processes, etc.) need to be modular, autonomous, process intensive and manufactured in large numbers. Consider, for instance, that the DOE’s Office of Energy Efficiency and Renewable Energy announced in 2016 that the American Institute of Chemical Engineers was selected to lead a new Manufacturing USA Institute, referred to as the Rapid Advancement in Process Intensification Deployment (RAPID) Institute. The RAPID Institute is focused on developing breakthrough technologies to boost the energy productivity and energy efficiency through manufacturing processes in industries such oil and gas, pulp and paper and various domestic chemical manufacturers. A similar effort dedicated towards RNG and other biomass conversion technologies could help reduce costs substantially.

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RNG from Anaerobic Digestion Landfill Gas ICF developed assumptions for each region by distinguishing between four types of landfills: candidate landfills30 without collection systems in place, candidate landfills with collection systems in place, landfills31 without collection systems in place, and landfills with collections systems in place.32 For each region, ICF further characterized the number of landfills across these four types of landfills, distinguishing facilities by estimated biogas throughput (reported in units of standard cubic feet per minute of biogas). For utility costs, ICF assumed 25 kWh per MMBtu of RNG injected and 6% of geological or fossil natural gas used in processing. Electricity costs and delivered natural gas costs were reflective of industrial rates reported at the state level by the EIA. The table below summarizes the key parameters that ICF employed in our cost analysis of LFG. Table 32. Cost Consideration in Levelized Cost of Gas Analysis for RNG from Landfill Gas Factor Cost Elements Considered Costs

Performance • Capacity factor • 95%

• Construction / Engineering • 25% of uninstalled costs of equipment Installation Costs • Owner’s Cost • 10% of uninstalled costs of equipment • CO2 separation • $2.3 to $7.0 million depending on facility Gas Upgrading • H2S removal • $0.3 to $1.0 million depending on facility • N2/O2 removal • $1.0 to $2.5 million depending on facility • Electricity: 25 kWh/MMBtu • 4.6—13.7 ¢/kWh Utility Costs • Natural Gas: 6% of product • $3.00-$8.25/MMBtu Operations & • 1 FTE for maintenance • 10% of installed capital costs Maintenance • Miscellany • Interconnect • $2 million For Injection • Pipeline • $1.5 million • Compressor • $0.2-0.5 million • Rate of Return • 10% Financial Parameters • Discount Rate • 7%

The figure below includes ICF’s estimates for the RNG from landfill gas supply curve.

30 The EPA characterizes candidate landfills as one that is accepting waste or has been closed for five years or less, has at least one million tons of WIP, and does not have an operational, under-construction, or planned project. Candidate landfills can also be designated based on actual interest by the site. 31 Excluding those that are designated as candidate landfills. 32 Landfills that are currently producing RNG for pipeline injection are included here. 52

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Figure 29. Supply-Cost Curve for RNG from Landfill Gas ($/MMBtu vs tBtu)

$20 $18 $16 $14 $12 $10 $8 $6 RNG Cost Cost RNG ($/MMBtu) $4 $2 $0 0 100 200 300 400 500 600 700 800 RNG from Landfill Gas (trillion Btu)

Animal Manure ICF developed assumptions for each region by distinguishing between animal manure projects, based on a combination of the size of the farms and assumptions that certain areas would need to aggregate or cluster resources to achieve the economies of scale necessary to warrant an RNG project. There is some uncertainty associated with this approach because an explicit geospatial analysis was not conducted; however, ICF did account for considerable costs in the operational budget for each facility assuming that aggregating animal manure would potentially be expensive. The table below includes the main assumptions used across regions—including national average estimates for the cost per MMBtu across the various buckets. We have included the number of dairy cows by way of reference to help contextualize the results for the reader; note, however, that the final analysis will manure from dairy cows, beef cows, chickens (layers and boilers), turkey, and swine.

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Table 33. Cost Consideration in Levelized Cost of Gas Analysis for RNG from Animal Manure Factor Cost Elements Considered Costs

Performance • Capacity factor • 95%

• Construction / Engineering • 25% of uninstalled costs of equipment Installation Costs • Owner’s Cost • 10% of uninstalled costs of equipment • CO2 separation • $2.3 to $7.0 million depending on facility Gas Upgrading • H2S removal • $0.3 to $1.0 million depending on facility • N2/O2 removal • $1.0 to $2.5 million depending on facility • Electricity: 30 kWh/MMBtu • 4.6—13.7 ¢/kWh Utility Costs • Natural Gas: 6% of product • $3.00-$8.25/MMBtu Operations & • 1 FTE for maintenance • 15% of installed capital costs Maintenance • Miscellany • Interconnect • $2.0 million For Injection • Pipeline • $1.5 million • Compressor • $0.2-0.5 million • Value of digestate • Valued for dairy at about $100/cow/y Other • Tipping fee • Excluded from analysis • Rate of Return • 10% Financial Parameters • Discount Rate • 7%

ICF reports a range of costs for RNG from animal manure at $18.4/MMBtu to $32.6/MMBtu. Water Resource Recovery Facilities ICF developed assumptions for each region by distinguishing between water resource recovery facilities based on the throughput of the facilities. The table below includes the main assumptions used across regions—including national average estimates for the cost per MMBtu across the various facility sizes. Table 34. Cost Consideration in Levelized Cost of Gas Analysis for RNG from WRRFs Factor Cost Elements Considered Costs

Performance • Capacity factor • 95%

• Construction / Engineering • 25% of uninstalled costs of equipment Installation Costs • Owner’s Cost • 10% of uninstalled costs of equipment • CO2 separation • $2.3 to $7.0 million depending on facility Gas Upgrading • H2S removal • $0.3 to $1.0 million depending on facility • N2/O2 removal • $1.0 to $2.5 million depending on facility • Electricity: 26 kWh/MMBtu • 4.6—13.7 ¢/kWh Utility Costs • Natural Gas: 6% of product • $3.00-$8.25/MMBtu Operations & • 1 FTE for maintenance • 10% of installed capital costs Maintenance • Miscellany • Interconnect • $2.0 million For Injection • Pipeline • $1.5 million • Compressor • $0.2-0.5 million • Rate of Return • 10% Financial Parameters • Discount Rate • 7% 54

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ICF reports a range of costs for RNG from WRRFs at $7.4/MMBtu to $26.1/MMBtu. Food Waste ICF made the simplifying assumption that food waste processing facilities would be purpose built, and be capable of processing 60,000 tons of waste per year—ICF estimates that these facilities would produce about 500 standard cubic feet per minute (SCFM) of biogas for conditioning and upgrading before pipeline injection. In addition to the other costs included in other AD systems, we also included assumptions about the cost of collecting food waste and processing it accordingly. Table 35. Cost Consideration in Levelized Cost of Gas Analysis for RNG from Food Waste Factor Cost Elements Considered Costs • Capacity factor • 95% Performance • Processing Capability • 60,000 tons per year • Organics Processing • $10.0 million Dedicated Equipment • Digester • $12.0 million • Construction / Engineering • 25% of uninstalled costs of equipment Installation Costs • Owner’s Cost • 10% of uninstalled costs of equipment • CO2 separation • $2.3 to $7.0 million depending on facility Gas Upgrading • H2S removal • $0.3 million • N2/O2 removal • $1.0 million • Electricity: 28 kWh/MMBtu • 4.6—13.7 ¢/kWh Utility Costs • Natural Gas: 5% of product • $3.00-$8.25/MMBtu • 1.5 FTE for maintenance Operations & Maintenance • 15% of installed capital costs • Miscellany

Other • Tipping fees • Varied by region;

• Interconnect • $2.0 million For Injection • Pipeline • $1.5 million • Compressor • $0.2-0.5 million • Rate of Return • 10% Financial Parameters • Discount Rate • 7%

ICF assumed that food waste facilities would be able to offset costs with tipping fees. ICF used values presented by an analysis of municipal solid waste landfills by Environmental Research & Education Foundation (EREF). The tipping fees reported by EREF for 2018 are shown in the table below.

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Table 36. Average Tipping Fee by Region33 Region Tipping Fee, 2018 Pacific: AK, AZ, CA, HI, ID, NV, OR, WA $68.46 Northeast: CT, DE, ME, MD, MA, NH, NJ, NY, PA, RI, VA, WV $67.39 Midwest: IL, IN, IA, KS, : MI, MN, MO, NE, OH, OH, WI $46.89 Mountains / Plains: CO, MT, ND, SD, UT, WY $43.57 Southeast: AL, FL, GA, KY, MS, NC, SC, TN $43.32 South Central: AR, LA, NM, OK, TX $34.80 National Average $55.11

ICF assumed that anaerobic digesters discounted the tipping fee compared to MSW landfills, and used a 20% discount to those values listed in the table.34 ICF reports an estimated cost of RNG from food waste of $19.4/MMBtu to $28.3/MMBtu. RNG from Thermal Gasification ICF used similar assumptions across the thermal gasification of feedstocks, including agricultural residue, forestry residue, energy crops, and municipal solid waste (MSW).35 There is considerable uncertainty around the costs for thermal gasification of feedstocks, as the technology has only been deployed at pilot scale to date or in the advanced stages of demonstration at pilot scale. This is in stark contrast to the anaerobic digestion technologies considered previously. ICF reports here on the three illustrative facilities that we employed for conducting the cost analysis—distinguished by the amount of feedstock processed daily (in units of tons per day).

33 As reported by EREF; available online at https://www.waste360.com/landfill-operations/eref-study-shows- continued-increase-average-msw-landfill-tip-fees. 34 A report entitled Business Analysis of Anaerobic Digestion in the USA by Renewable Waste Intelligence notes that “a lower tipping fee (approximately by $10) than landfill is required in order to incentivize waste management companies to separate” waste from trash and deliver it to an AD facility. ICF assumed a 20% discount from the tipping fees reported would be a sufficient incentive to deliver the feedstock to an AD facility. 35 Note that MSW here refers to the non-organic, non-biogenic fraction of the MSW stream, which is assumed to be a mix of, including, but not limited to construction and demolition debris, plastics, rubber and leather, etc.. 56

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Table 37. Cost Consideration in Levelized Cost of Gas Analysis for RNG from Thermal Gasification Factor Cost Elements Considered Costs • Capacity factor • 90% Performance • Processing Capability • 1,000-2,000 tpd • $20-22 million • Feedstock Handling (drying, storage) • $60 million • Gasifier • $25 million • CO2 removal • $10 million Dedicated Equipment • Syngas Reformer • $20 million & Installation Costs • Methanation • $10 million • Other (cooling tower, water treatment) • • Miscellany (site work, etc.) • • Construction/ engineering • All-in: $335 million for 1,000 tpd • Electricity: 30 kWh/MMBtu • 4.6—13.7 ¢/kWh Utility Costs • Natural Gas: 6% of product • $3.00-$8.25/MMBtu • Feedstock Operations & • 3 FTE for maintenance • $30-$100/dry ton Maintenance • Miscellany: water sourcing, • 12% of installed capital costs treatment/disposal • Interconnect • $2.0 million For Injection • Pipeline • $1.5 million • Compressor • $0.2-0.5 million • Rate of Return • 10% Financial Parameters • Discount Rate • 7%

ICF applied these estimates across each of the four feedstocks, their corresponding feedstock cost estimates, and assumed that the smaller facilities processing 1,000 tons per day would represent 50% of the processing capacity, and that the larger facilities processing 2,000 tons per day would represent the other 50% of the processing capacity. The number of facilities built in each region was constrained by the resource assessment. ICF reports an estimated levelized costs of RNG from thermal gasification as follows: § Agricultural residues: $18.3/MMBtu to $27.4/MMBtu § Forestry and forest residues: $17.3/MMBtu to $29.2/MMBtu § Energy crops: $18.3/MMBtu to $31.2/MMBtu § MSW: $17.3/MMBtu to $44.2/MMBtu RNG from Power-to-Gas / Methanation ICF developed the levelized cost of energy for P2G systems using a combination of an electrolyzer and a methanator to produce RNG for pipeline injection. The main cost considerations include: installed cost of electrolyzers on a dollar per kW basis ($/kW), the installed cost of a methanation system on a $/kW basis, the cost of RNG compression and interconnect for pipeline injection, and the cost of electricity used to run the P2G system. ICF also estimated the operations and maintenance (O&M) costs of both the electrolyzer and the methanator. ICF notes that we assume that the renewable electricity is dedicated to the P2G system and co-located, thereby reducing other electricity costs (e.g., transmission and distribution) considerably. ICF did not quantify:

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§ The costs of CO2 that would be required for the methanation reaction; the underlying assumption is that the cost of CO2 would be a marginal contributor to the overall cost of the system, and that it would be available at a low cost (e.g., less than $30 per ton). § The costs of a heat sink for the waste heat generated from the methanation reaction, or the corresponding benefits of repurposing this heat. The graph below illustrates ICF’s assumptions regarding the installed costs of electrolyzers—we assumed that the resource base for electrolyzers would be some blend of proton exchange membrane (PEM), alkaline systems, and solid oxide systems. Rather than be deterministic about which technology will be the preferred technology, we present the cost as a blended average of the $/kW installed. This is based on ICF’s review of literature and review of assumptions developed by UC Irvine. 36 Figure 30. Installed Capacity Cost of Electrolyzers, $/kW, 2020-2040

1,200

1,000

800

600

400 Electrolyzer Costs ($/kW) 200

0 2020 2025 2030 2035 2040

ICF assumed a decreasing cost of methanation technology consistent with the figure below, presented in units of $/kW.

36 Draft Results: Future of Natural Gas Distribution in California, CEC Staff Workshop for CEC PIER-16-011, June 6, 2019, available online at https://ww2.energy.ca.gov/research/notices/2019-06-06_workshop/2019-06- 06_Future_of_Gas_Distribution.pdf. 58

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Figure 31. Installed Capacity Cost of Methanator, $/kW, 2020-2040

1,200

1,000

800

600

400 Electrolyzer Costs ($/kW) 200

0 2020 2025 2030 2035 2040

The figure below includes the assumed conversion efficiencies for hydrogen production from electrolyzers (blue) and for the methanation reaction to produce RNG for injection (orange). Figure 32. Assumed Efficiency for Electrolysis and Methanation, 2020-2040

85%

80%

75%

70%

65% Efficiency, Electrolyzer Efficiency, Methanator

System System Efficiencies 60%

55%

50% 2020 2025 2030 2035 2040

ICF developed our cost estimates assuming a 50 MW system for P2G co-located with methanation capabilities, and included the costs of compression for pipeline injection, interconnection costs, and pipeline costs. We assumed an electricity cost of $42/MWh based on the supply curve for dedicated renewables that we developed using IPM. We assumed operational costs of 10% and 7% of capex, respectively for the electrolyzer and the methanator; and we assumed operational costs of 5% of capex for pipeline and interconnect systems. The figure below shows the decreasing LCOE for RNG from P2G systems using these baseline level assumptions; the blue line shows the costs assuming a 50% capacity factor for the system and the orange line shows the costs assuming an 80% capacity factor for the system.

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Figure 33. Estimated RNG costs from P2G / Methanation ($/MMBtu) as a function of installed capacity of P2G systems $60 CF_80% $50 CF_50%

$40

$30

($/MMBtu) $20

$10 P2G / Methanation LCOE LCOE / P2GMethanation $0 0 100 200 300 400 500 Installed Capacity (GW)

Combined Supply Curves ICF estimates that more than half of the RNG production potential in the high resource potential scenario would be available at less than $20/MMBtu, as shown in the figure below. Generally speaking, ICF finds the front end of the supply curve to be landfill gas projects and WRRFs that are poised to move towards RNG production. As the estimated costs move to higher costs, the supply curve includes some of the larger animal manure projects and the well-positioned food waste projects. The tail end of the curve, showing the upward sloping to the right captures the first tranche of thermal gasification projects that we assume will just start to break that $20/MMBtu level by 2040. Figure 34. Combined RNG Supply-Cost Curve, less than $20/MMBtu in 2040

$25

$20

$15

$10

$5 Production Cost ($/MMBtu)Cost Production $0 0 500 1,000 1,500 2,000 2,500 RNG Production Potential (tBtu/y)

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GHG Cost-Effectiveness The GHG cost-effectiveness is reported on a dollar per ton basis, and is calculated as the difference between the emissions attributable to RNG and fossil natural gas. For this report, ICF followed IPCC guidelines and does not include biogenic emissions of CO2 from RNG. The cost- effectiveness calculation is simply as follows ∆(#$% , +,--./ $% ) &'() &'() = , 0.05306 78 9:;< where the RNGcost is simply the cost from the estimates reported previously. For the purposes of this report, we use a fossil natural gas price equal to the average Henry Hub spot price reported by the EIA in the 2019 Annual Energy Outlook, calculated as $3.89/MMBtu. In other words, the front end of the supply-cost curve is showing RNG is just under $7/MMBtu, which is equivalent to about $55-60/ton. As the estimated RNG cost increases to $20/MMBtu, we report an estimated cost-effectiveness of about $300/ton. The GHG cost-effectiveness of RNG as a mitigation strategy is competitive with and in many cases lower than the costs per ton that are associated with other strategies to reduce GHG emissions, such as electrification at $572-806/ton 37 and atmospheric removal of CO2 at $94-232/ton.

37 Cost estimates are from Implications of Policy-Driven Residential Electrification, AGA, 2018 study. While the cost estimates are not fully "apples-to-apples" comparison as the scope of the referenced study is different from this report, it serves as a useful point of comparison. 61

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Key Findings ICF’s assessment of RNG potential in the United States demonstrate that there is significant resource potential in both the low and the high cases considered—and in both, ICF used moderately conservative assumptions with respect to the utilization of feedstocks and technological advancements. § In the low resource potential scenario, ICF estimates that about 1,650 trillion Btu (tBtu) of RNG can be produced annually for pipeline injection by 2040. That estimate increases to 1,910 tBtu per year when including the potential for the non-biogenic fraction of MSW. § In the high resource potential scenario, ICF estimates that about 3,780 tBtu of RNG can be produced annually for pipeline injection by 2040. That estimate increases to 4,510 tBtu per year when including the potential for the non-biogenic fraction of MSW. For the sake of comparison, ICF notes that the 10-year average (2009-2018) of residential natural gas consumption is 4,846 tBtu. The reported RNG resource potential estimates reported here are 90% and 180% increases from the comparable resource potential scenarios from 2011 AGF Study. These changes are largely attributable to improved access to data regarding potential feedstocks for RNG production and are generally not attributable to more aggressive assumptions regarding feedstock utilization or conversion efficiencies. Furthermore, the analysis presented here includes estimates for RNG production from P2G systems using dedicated renewable electricity. While there are multiple studies regarding P2G technology and its uses, we believe this is the first study to quantify RNG production potential nationwide from P2G. ICF’s updated assessment also illustrates the diversity of RNG resource potential as a GHG emission reduction strategy—there is a portfolio of potential feedstocks and technologies that are or will be commercialized in the near-term future that will help realize the potential of the RNG market. On the technology side, most RNG continues to be produced using anaerobic digestion paired with conditioning and upgrading systems. The post-2025 outlook for RNG will increasingly rely on thermal gasification of sustainably harvested biomass, including agricultural residues, forestry and forest product residues, and energy crops. The long-term outlook for RNG growth will depend to some extent on technological advancements in P2G systems. ICF’s analysis of the potential for P2G systems, paired with methanation suggests that the technology could make a significant contribution to RNG production by 2040. However, ICF notes that the role of P2G systems as a contributor to RNG production requires further analysis and study. Excluding cost considerations, the deployment of P2G systems for RNG production requires assumptions across a variety of factors, including but not limited to access to renewable electricity, the corresponding capacity factor of the system given the intermittency of renewable electricity generation from some sources (e.g., solar and wind), co-location with (presumably affordable) access to carbon dioxide for methanation, and reasonable proximity to a natural gas pipeline for injection. ICF’s analysis did not seek to address all of these project development considerations; rather, we sought to understand the potential for P2G systems assuming access to dedicated renewable electricity production, meaning that these are purpose-built renewable electricity generation systems that are meant to provide dedicated power to P2G systems. Curtailment of renewable electricity generation is a complicated issue, and exploring it in detail was beyond the scope of this report. However, ICF’s initial assessment indicates that P2G systems running on curtailed renewable electricity will play an important transitional role in helping to 62

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deploy the technology and achieve the long-term price reductions that are required to improve the viability of P2G as a cost-effective pathway for RNG production. Despite the importance of curtailed renewable electricity as part of the transition towards more cost-effective P2G systems, ICF’s analysis does focus more on the opportunity for, and associated costs of RNG production using P2G systems with dedicated renewable electricity generation. It is important that this assumption by ICF is recognized as a limitation of our analysis, rather than a commentary on how the market will ultimately develop for P2G systems. In the low resource potential and high resource potential scenarios presented, RNG deployment could achieve 101 to 235 MMT of GHG emission reductions by 2040. For the sake of reference, the high end of the estimate would be the equivalent of reducing GHG emissions from the use of natural gas in the residential sector by 95% from levels observed over the last ten years (2009- 2018). ICF estimates that the majority of the RNG produced in the high resource potential scenario is available in the range of $7-$20/MMBtu, which is equivalent to $55/ton to $300/ton in 2040. ICF evaluated the potential costs associated with the deployment of each feedstock and technology pairing, and made assumptions about the sizing of systems that would need to be deployed to achieve the RNG production potential outlined in the low and high resource potential scenarios. ICF’s reported costs are dependent on a variety of assumptions, including feedstock costs, the revenue that might be generated via byproducts or other avoided costs, and the expected rate of return on capital investments. ICF finds that there is potential for cost reductions as the RNG for pipeline injection market matures, production volumes increase, and the underlying structure of the market evolves.

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Appendix A—Resource Assessment by State The tables below summarize ICF’s resource assessment for low, high, and technical resource RNG production potentials in 2040, broken down by state and by feedstock, reported in units of tBtu per year (tBtu/y). Low Resource Potential Scenario, By State Table 38. Low Resource Potential for RNG in 2040, tBtu/y, by State via Anaerobic Digestion via Thermal Gasification State Animal Food Forest Energy LFG WRRF Ag Res MSW Manure Waste Res Crops Alabama 9.561 6.536 0.177 0.121 0.186 7.000 2.508 5.563 Alaska 1.153 0.004 0.030 0.000 0.000 0.000 0.000 0.000 Arizona 10.933 1.943 0.385 0.324 0.222 0.408 0.000 2.621 Arkansas 4.156 7.260 0.077 0.024 0.629 6.219 1.256 2.904 California 76.540 15.917 3.088 4.636 9.770 2.441 0.000 37.480 Colorado 10.962 3.605 0.250 0.247 3.058 0.560 0.000 1.999 Connecticut 1.670 0.864 0.246 0.438 0.009 0.290 0.051 3.539 Delaware 1.326 3.145 0.089 0.112 0.219 0.048 0.015 0.903 D.C. 0.000 -- 0.378 0.077 0.000 0.006 0.000 0.625 Florida 23.493 3.481 1.028 2.358 5.957 3.757 3.714 19.059 Georgia 16.914 7.196 0.538 0.230 0.739 8.059 4.756 6.185 Hawaii 2.203 0.124 0.105 0.000 0.000 0.000 0.000 0.000 Idaho 1.544 5.624 0.049 0.000 2.231 0.422 0.000 0.201 Illinois 28.655 2.481 1.869 1.568 23.215 1.155 0.287 12.677 Indiana 15.835 3.027 0.652 0.796 8.288 0.952 0.428 6.438 Iowa 4.899 8.648 0.140 0.027 35.541 0.875 3.042 1.756 Kansas 5.485 5.336 0.142 0.352 6.555 0.334 27.152 2.842 Kentucky 9.435 4.348 0.228 0.534 1.691 4.450 2.004 4.316 Louisiana 8.507 3.860 0.303 0.092 4.262 4.547 3.800 0.742 Maine 1.489 5.205 0.048 0.162 0.010 1.674 0.043 1.308 Maryland 6.286 2.255 0.356 0.718 1.186 0.623 0.390 5.802 Massachusetts 5.673 0.103 0.619 0.811 0.011 0.608 0.039 6.554 Michigan 25.191 4.141 1.179 1.204 7.175 3.198 0.220 9.734 Minnesota 4.661 6.789 0.307 0.655 30.659 2.501 0.013 5.298 Mississippi 5.306 4.410 0.072 0.000 0.624 5.189 2.800 0.000 Missouri 8.499 7.869 0.576 0.734 1.266 2.225 5.058 5.933 Montana 1.430 3.901 0.034 0.000 5.127 0.462 0.000 0.000 Nebraska 3.397 6.225 0.118 0.050 38.201 0.176 0.000 0.406 Nevada 5.291 0.808 0.250 0.148 0.002 0.056 0.000 1.195 New Hampshire 2.334 0.828 0.037 0.161 0.005 0.580 0.021 1.301 New Jersey 10.625 0.917 1.033 1.081 0.088 0.360 0.157 8.740 New Mexico 3.441 8.988 0.106 0.041 0.159 0.258 0.168 1.273 New York 19.739 4.522 2.472 2.388 2.015 1.980 0.598 19.307 North Carolina 14.068 6.943 0.367 1.187 0.833 9.692 4.993 9.599

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via Anaerobic Digestion via Thermal Gasification State Animal Food Forest Energy LFG WRRF Ag Res MSW Manure Waste Res Crops North Dakota 0.783 2.573 0.021 0.000 10.871 0.110 0.000 0.691 Ohio 24.843 4.139 1.364 1.407 10.053 1.308 0.375 11.374 Oklahoma 6.667 6.570 0.186 0.099 0.883 0.829 17.454 2.418 Oregon 6.237 1.962 0.293 0.144 1.060 2.161 0.000 1.164 Pennsylvania 27.171 6.667 1.043 1.555 1.589 2.509 1.397 12.575 Rhode Island 1.447 0.008 0.103 0.128 0.001 0.126 0.007 1.037 South Carolina 7.612 2.305 0.000 0.126 0.357 6.354 2.258 4.650 South Dakota 0.874 7.026 0.012 0.102 21.324 0.281 0.104 0.822 Tennessee 11.368 3.569 0.503 0.161 0.405 3.990 1.990 1.305 Texas 45.927 18.269 1.427 1.142 4.904 4.742 34.003 9.233 Utah 4.185 1.888 0.089 0.117 0.025 0.292 0.000 0.945 Vermont 0.672 1.006 0.000 0.076 0.006 0.351 0.025 0.617 Virginia 15.569 5.430 0.599 1.016 0.691 8.031 0.912 8.213 Washington 9.052 3.034 0.472 0.840 4.100 2.173 0.000 6.791 West Virginia 3.162 0.926 0.052 0.226 0.033 1.050 1.048 1.828 Wisconsin 11.634 16.507 0.443 0.697 8.308 3.043 0.161 5.637 Wyoming 0.500 1.992 0.000 0.070 0.088 0.199 0.000 0.568

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High Resource Potential Scenario, By State Table 39. High Resource Potential for RNG in 2040, tBtu/y, by State via Anaerobic Digestion via Thermal Gasification State Animal Food Forest Energy LFG WRRF Ag Res MSW Manure Waste Res Crops Alabama 15.818 13.072 0.322 1.204 0.464 13.999 16.789 12.544 Alaska 1.869 0.008 0.038 0.000 0.000 0.000 0.000 0.000 Arizona 17.879 3.887 0.537 1.397 0.555 4.175 0.000 14.557 Arkansas 6.762 14.520 0.193 0.629 1.573 12.438 18.529 6.549 California 124.841 31.833 4.183 8.113 24.426 4.881 0.000 84.514 Colorado 17.921 7.210 0.368 0.433 7.646 3.121 1.489 11.528 Connecticut 2.756 1.728 0.418 0.766 0.023 0.579 0.052 7.981 Delaware 2.219 6.290 0.119 0.195 0.546 0.096 0.017 2.036 D.C. 0.000 0.473 0.135 0.000 0.011 0.000 1.410 Florida 38.510 6.962 1.685 4.126 14.893 7.513 16.811 42.976 Georgia 27.480 14.392 0.774 2.114 1.848 16.117 16.880 22.024 Hawaii 3.562 0.248 0.163 0.000 0.000 0.000 0.000 0.000 Idaho 2.599 11.248 0.108 0.044 5.578 0.963 0.000 3.430 Illinois 46.987 4.962 2.533 2.744 58.037 2.310 36.042 28.585 Indiana 26.341 6.055 0.962 1.394 20.719 1.904 13.002 14.516 Iowa 7.962 17.296 0.248 0.656 88.851 1.750 19.329 6.830 Kansas 8.997 10.671 0.256 0.615 16.388 0.668 128.067 6.408 Kentucky 15.679 8.697 0.372 0.934 4.228 8.899 30.320 9.733 Louisiana 13.954 7.719 0.480 0.982 10.654 9.095 13.550 10.224 Maine 2.407 10.411 0.091 0.283 0.026 3.348 0.070 2.950 Maryland 10.417 4.510 0.509 1.256 2.966 1.246 1.080 13.082 Massachusetts 9.342 0.205 0.858 1.419 0.027 1.217 0.075 14.779 Michigan 41.000 8.283 1.533 2.107 17.937 6.396 1.170 21.948 Minnesota 7.683 13.579 0.438 1.147 76.646 5.002 2.941 11.947 Mississippi 8.666 8.821 0.195 0.637 1.559 10.379 17.065 6.630 Missouri 14.105 15.739 0.807 1.284 3.165 4.450 96.367 13.379 Montana 2.320 7.801 0.059 0.000 12.817 1.042 0.552 2.232 Nebraska 5.712 12.451 0.166 0.088 95.502 0.352 1.563 4.120 Nevada 8.701 1.616 0.324 0.259 0.005 1.893 0.000 6.118 New Hampshire 3.788 1.656 0.076 0.282 0.013 1.160 0.024 2.934 New Jersey 17.254 1.835 1.414 1.892 0.221 0.720 0.727 19.708 New Mexico 5.651 17.976 0.157 0.444 0.398 2.641 1.805 4.629 New York 32.753 9.044 3.304 4.179 5.038 3.959 3.041 43.536 North Carolina 23.406 13.887 0.640 2.078 2.082 19.384 20.971 21.645 North Dakota 1.333 5.145 0.045 0.150 27.179 0.223 7.115 1.558 Ohio 40.539 8.278 1.968 2.462 25.133 2.616 3.416 25.648 Oklahoma 10.857 13.139 0.305 0.814 2.206 1.748 111.613 8.475 Oregon 10.189 3.925 0.411 0.252 2.651 4.323 0.000 8.657 Pennsylvania 44.319 13.334 1.558 2.722 3.973 5.018 5.681 28.355

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via Anaerobic Digestion via Thermal Gasification State Animal Food Forest Energy LFG WRRF Ag Res MSW Manure Waste Res Crops Rhode Island 2.357 0.016 0.150 0.224 0.003 0.251 0.007 2.337 South Carolina 12.627 4.611 0.000 1.007 0.892 12.707 11.025 10.486 South Dakota 1.470 14.052 0.015 0.178 53.311 0.563 4.632 1.853 Tennessee 18.903 7.138 0.749 1.376 1.012 7.979 27.417 14.333 Texas 74.621 36.538 2.074 5.562 12.260 13.856 186.772 57.940 Utah 7.034 3.777 0.126 0.205 0.063 4.699 0.000 6.340 Vermont 1.099 2.012 0.018 0.133 0.016 0.701 0.277 1.390 Virginia 25.316 10.861 0.834 1.778 1.729 16.062 8.696 18.519 Washington 14.745 6.069 0.694 1.470 10.251 4.347 0.000 15.313 West Virginia 5.072 1.853 0.091 0.396 0.082 2.100 1.855 4.122 Wisconsin 18.906 33.014 0.625 1.220 20.771 6.086 10.807 12.712 Wyoming 0.830 3.984 0.028 0.123 0.220 0.800 0.067 1.281

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Technical Resource Potential Scenario, By State Table 40. Technical Resource Potential for RNG in 2040, tBtu/y, by State via Anaerobic Digestion via Thermal Gasification State Animal Food Forest Energy LFG WRRF Ag Res MSW Manure Waste Res Crops Alabama 21.291 21.786 1.054 5.417 1.607 35.895 67.831 31.436 Alaska 2.732 0.013 0.097 0.814 0.000 0.000 0.000 0.000 Arizona 25.738 6.478 1.275 8.045 2.299 19.320 0.000 36.483 Arkansas 9.604 24.200 0.675 3.347 10.304 31.892 151.481 16.412 California 188.144 53.056 8.988 43.954 77.147 12.516 0.000 211.804 Colorado 26.180 12.017 0.952 6.381 34.406 13.136 22.504 28.890 Connecticut 4.085 2.879 0.992 3.945 0.071 1.485 0.249 20.001 Delaware 3.456 10.484 0.266 1.078 3.008 0.245 4.432 5.102 D.C. 0.000 0.946 0.787 0.000 0.028 0.000 3.534 Florida 55.554 11.604 3.991 23.937 45.823 19.265 57.804 107.704 Georgia 39.551 23.987 1.962 11.753 6.971 41.326 66.426 55.195 Hawaii 4.847 0.413 0.352 1.567 0.000 0.000 0.000 0.000 Idaho 4.016 18.746 0.355 1.980 23.672 2.774 0.000 8.647 Illinois 69.628 8.269 5.663 14.045 246.978 5.924 353.618 71.637 Indiana 39.815 10.091 2.458 7.430 110.916 4.881 205.848 36.379 Iowa 11.345 28.826 0.972 3.503 348.543 4.487 293.301 17.116 Kansas 13.258 17.785 0.791 3.219 82.681 1.713 464.248 16.059 Kentucky 22.443 14.495 1.080 4.959 19.345 22.819 154.183 24.392 Louisiana 19.953 12.866 1.271 5.145 38.169 23.320 76.967 25.624 Maine 3.286 17.351 0.348 1.484 0.079 8.584 0.317 7.393 Maryland 15.646 7.517 1.168 6.705 10.173 3.195 21.633 32.786 Massachusetts 14.059 0.342 1.935 7.674 0.082 3.120 0.424 37.037 Michigan 62.029 13.805 3.488 11.081 80.227 16.399 51.785 55.005 Minnesota 11.664 22.632 1.046 6.255 301.824 12.825 108.270 29.941 Mississippi 12.135 14.702 0.673 3.304 8.874 26.612 101.265 16.617 Missouri 21.131 26.231 2.066 6.799 29.302 11.410 367.684 33.528 Montana 3.287 13.002 0.205 1.188 50.944 2.976 18.432 5.593 Nebraska 8.663 20.751 0.493 2.146 352.907 0.903 53.364 10.325 Nevada 13.265 2.693 0.702 3.414 0.014 9.422 0.000 15.332 New Hampshire 5.740 2.759 0.251 1.508 0.039 2.974 0.128 7.352 New Jersey 26.340 3.058 3.099 9.867 1.164 1.847 4.193 49.391 New Mexico 8.150 29.961 0.471 2.318 2.147 12.222 7.031 11.600 New York 50.489 15.073 7.197 21.554 24.327 10.152 33.219 109.106 North Carolina 35.164 23.145 1.683 11.609 10.421 49.703 96.393 54.245 North Dakota 2.007 8.576 0.153 0.841 104.037 0.581 138.829 3.905 Ohio 59.130 13.797 4.788 12.959 103.490 6.709 130.141 64.276 Oklahoma 15.723 21.899 0.914 4.367 15.589 4.713 354.173 21.240 Oregon 15.409 6.541 1.026 4.695 12.034 11.084 0.000 21.695 Pennsylvania 66.587 22.224 4.142 14.170 16.646 12.867 46.920 71.060

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via Anaerobic Digestion via Thermal Gasification State Animal Food Forest Energy LFG WRRF Ag Res MSW Manure Waste Res Crops Rhode Island 3.629 0.026 0.338 1.169 0.008 0.644 0.034 5.857 South Carolina 18.856 7.684 0.000 5.692 4.484 32.583 37.226 26.280 South Dakota 2.257 23.420 0.048 0.987 185.826 1.442 82.444 4.644 Tennessee 28.115 11.897 1.856 7.557 8.845 20.460 137.488 35.921 Texas 108.758 60.897 4.732 32.166 52.667 46.739 683.746 145.205 Utah 10.185 6.294 0.374 3.563 0.198 22.600 0.000 15.888 Vermont 1.696 3.353 0.117 0.694 0.050 1.798 1.842 3.484 Virginia 36.882 18.101 1.891 9.479 6.735 41.186 58.678 46.411 Washington 22.019 10.115 1.692 8.478 37.107 11.145 0.035 38.375 West Virginia 6.576 3.088 0.426 1.982 0.346 5.384 14.524 10.330 Wisconsin 28.451 55.024 1.660 6.450 82.169 15.606 131.091 31.857 Wyoming 1.219 6.639 0.133 0.633 1.451 3.083 0.727 3.210

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Appendix B—GHG Emissions using Lifecycle Analysis Approach The GHG emissions factor of RNG, typically called a carbon intensity (e.g., grams of CO2 equivalents per MJ of fuel), varies primarily based on the source of the fuel (i.e., feedstock), but can be impacted by other factors such as production efficiency and location as well as transmission distances. The assessment method and scope can also have a significant impact on how RNG carbon intensities and emissions are estimated and reported. This section provides a summary of commonly used GHG emission accounting methods and how they relate to the GHG emission profiles of RNG production and consumption. California’s LCFS, consumption-based inventories, and GHG Protocol’s Scope 3 include all GHG emissions from a product or resource’s lifecycle. This relies on an approach called life-cycle assessment (LCA). LCA allows for a holistic GHG accounting approach that considers all life-cycle aspects from raw resource extraction to final disposal (i.e., “cradle to grave”). For RNG and transportation fuels, Argonne National Laboratories’ GHGs, Regulated Emissions, and Energy Use in Transportation (GREET) model is the most commonly relied on resource. RNG’s carbon intensity (i.e., GHG emissions per unit of energy) varies substantially between feedstocks and production methods. Carbon intensities can also vary by location of production and how the fuel is transported and distributed. The GHG accounting methods and scopes previously discussed dictate which of RNG’s life-cycle elements are included as a carbon intensity in emissions reporting. Variations in production Figure 35 shows how these different life-cycle elements contribute to RNG’s overall carbon intensity for a selection of RNG sources using Argonne’s GREET model: landfill gas, animal waste anaerobic digestion (AD), wastewater sludge AD, and municipal solid waste (MSW) AD. We have also included corn ethanol (E85 blend) and gasoline as reference points. Note that in the GREET model, the original sourcing of RNG is considered “fuel production” and not feedstock operations. Figure 35. Summary of carbon intensities for transportation fuels across life-cycle stages (ANL 2019).

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The biggest variations in RNG production come from the associated emissions credits from the different RNG sources. For landfill gas, animal waste, and wastewater sources, GREET assigns a significant credit for the reduction in vented and flared methane (CH4) that would have occurred in absence of the production of RNG. Depending on the reporting standard and scope, different credits may be included or excluded. The California LCFS has a similar scope in accounting for credits as the GREET results shown above. Other programs or jurisdictional inventories may exclude these credits, or incorporate them into other emission sectors. Variations based on accounting method Figure 36 shows the same GREET results from Figure 35 grouped into the GHG Protocol Scopes. Scope 1 is limited to the tailpipe emissions and Scope 3 includes all aspects of feedstock and fuel production activities. For RNG we have grouped the compression of gas before use into Scope 2, assuming electricity is used in compression. Figure 36. Life-cycle carbon intensity for RNG grouped by different GHG Protocol scopes using GREET results.38

As noted in more detail in the previous sub-section, the GHG emissions associated with the production of RNG vary depending on a number of factors including the feedstock type, collection and processing practices, and the type and efficiency of biogas upgrading. For the purposes of this report, ICF determined the lifecycle carbon intensity (CI) of RNG up to the point of pipeline injection. This includes feedstock transport and handling, gas processing, and any credits for the reduction of flaring or venting methane that would have occurred in absence of the RNG fuel production. The table below presents ranges of lifecycle CIs for different RNG feedstocks up to the point of pipeline injection. These estimates are primarily based on a combination on Argonne National Laboratory’s Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model

38 GHG Protocol. 2019. Guidance. Available at: https://ghgprotocol.org/guidance-0 71

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(GREET) model,39 California Air Resources Board’s modified California GREET model,40 and ICF analysis. Table 41. Range of Lifecycle GHG Emission Factors for RNG from Different Feedstocks and Regions (in units of g/MJ)

ICF notes the following about these emission factors: § The lowest carbon intensities are from feedstocks that prevent the release of fugitive methane, such as the collection and processing of dairy cow manure. § RNG from WRRFs has the same CI range as landfill gas because both feedstocks start with raw biogas that is processed by the same type of gas upgrading equipment. § Agricultural residue, energy crops, forestry products and forestry residues, as well as MSW all have the same CI range based on the thermal gasification process required to create biogas from woody biomass. This is an energy intensive process, but inclusion of renewables and co-produced electricity on-site can reduce the emissions impact of gas production. After the point of injection, RNG is transported through pipelines for distribution to end-users. The CI of pipeline transmission depends on the distance between the gas upgrading facility and end- use. The GREET model applies 5.8 grams of CO2e per MMBtu-mile of gas transported as the pipeline transmissions CI factor. If the gas will be used in the transportation sector, and therefore requires compression, another 3-4 gCO2e is added onto the CI. For the sake of reference, the tailpipe emissions of use in a heavy-duty truck are around 60 gCO2e/MJ. ICF applied the GHG emission factors listed in the table above to estimate the GHG reduction potential across each of the RNG potential scenarios and each region, as reported previously in Section 2. The tables below show the range of GHG emission reductions on a lifecycle basis in units of million metric tons, MMT. ICF estimates that in the low RNG resource case, about 86 to 113 MMT of GHG emissions would be reduced through the deployment of RNG; in the high RNG resource case, 170 to 247 MMT of GHG emissions could be reduced.

39 https://greet.es.anl.gov/ 40 https://ww3.arb.ca.gov/fuels/lcfs/ca-greet/ca-greet.htm 72

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Renewable Sources of Natural Gas: Supply and Emissions Reduction Assessment

Table 42. GHG Emission Reductions (in MMT) for RNG in the Low Resource Case Low RNG Resource Case | GHG Emission Reduction Potential, MMT Feedstock East North West North South East South West South New England Mid-Atlantic Mountain Pacific Total Central Central Atlantic Central Central RNG from biogenic or renewable resources Landfill Gas 0.5 - 0.5 2.2 - 2.5 3 - 3.5 0.9 - 1 3.1 - 3.4 1.3 - 1.3 2 - 2.3 1.1 - 1.5 3 - 4.3 17 - 20.5 Animal Manure 1.6 - 1.7 3.2 - 3.3 7.2 - 7.4 6 - 6.1 2.9 - 3 0.9 - 0.9 2.6 - 2.7 4.9 - 5.1 5.4 - 5.7 34.9 - 35.7 WRRF 0 - 0 0.2 - 0.2 0.1 - 0.2 0 - 0 0.1 - 0.1 0 - 0 0.1 - 0.1 0 - 0.1 0.1 - 0.2 0.8 - 1 Food Waste 0.3 - 0.3 0.7 - 0.8 0.7 - 0.8 0.2 - 0.3 0.8 - 0.9 0.1 - 0.1 0.2 - 0.2 0.1 - 0.1 0.8 - 0.9 4 - 4.4 Ag Residue 0 - 0 0 - 0.1 0.6 - 2.2 1.4 - 5.6 0.1 - 0.4 0 - 0.1 0.1 - 0.4 0.1 - 0.4 0.1 - 0.6 2.5 - 9.8 Forestry and Forest 0 - 0.1 0 - 0.2 0.1 - 0.4 0.1 - 0.3 0.4 - 1.4 0.2 - 0.8 0.2 - 0.6 0 - 0.1 0.1 - 0.3 1.1 - 4.2 Residue Energy Crops 0 - 0 0 - 0.1 0 - 0.1 0.4 - 1.4 0.2 - 0.7 0.1 - 0.4 0.6 - 2.2 0 - 0 0 - 0 1.2 - 4.8 Sub-Total 2.4 - 2.7 6.4 - 7.2 11.7 - 14.5 9 - 14.6 7.7 - 10 2.6 - 3.7 5.7 - 8.4 6.3 - 7.3 9.4 - 12 61.4 - 80.3 Renewable gas from MSW MSW 0.1 - 0.6 0.4 - 1.6 0.5 - 1.8 0.2 - 0.7 0.6 - 2.2 0.1 - 0.4 0.2 - 0.6 0.1 - 0.3 0.5 - 1.7 2.5 - 9.9 RNG from P2G / Methanation P2G / Methanation 22.3 Totals 2.6 - 3.2 6.9 - 8.8 12.2 - 16.2 9.2 - 15.2 8.3 - 12.2 2.8 - 4.1 5.9 - 9 6.4 - 7.7 9.9 - 13.7 86.3 - 112.5

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Renewable Sources of Natural Gas: Supply and Emissions Reduction Assessment

Table 43. GHG Emission Reductions (in MMT) for RNG in the High Resource Case High RNG Resource Case | GHG Emission Reduction Potential, MMT Feedstock East North West North South East South West South New England Mid-Atlantic Mountain Pacific Total Central Central Atlantic Central Central RNG from biogenic or renewable resources Landfill Gas 0.8 - 0.9 3.8 - 4.3 5.1 - 6 1.5 - 1.7 5.3 - 5.8 2.2 - 2.3 3.4 - 3.9 1.9 - 2.6 5 - 7.4 28.9 - 35 Animal Manure 3.2 - 3.3 6.4 - 6.6 14.5 - 14.8 12.1 - 12.2 5.9 - 5.9 1.8 - 1.8 5.3 - 5.3 9.8 - 10.2 10.8 - 11.4 69.7 - 71.5 WRRF 0.1 - 0.1 0.3 - 0.3 0.2 - 0.2 0.1 - 0.1 0.2 - 0.2 0.1 - 0.1 0.1 - 0.1 0.1 - 0.1 0.2 - 0.3 1.2 - 1.4 Food Waste 0.3 - 0.3 0.7 - 0.8 0.7 - 0.8 0.2 - 0.3 0.8 - 0.9 0.1 - 0.1 0.2 - 0.2 0.1 - 0.1 0.8 - 0.9 4 - 4.4 Ag Residue 0 - 0 0.1 - 0.4 1.4 - 5.5 3.6 - 13.9 0.3 - 1 0.1 - 0.3 0.3 - 1.1 0.3 - 1.1 0.4 - 1.4 6.4 - 24.7 Forestry and Forest 0.1 - 0.3 0.1 - 0.4 0.2 - 0.7 0.1 - 0.5 0.7 - 2.9 0.4 - 1.6 0.4 - 1.4 0.2 - 0.7 0.1 - 0.5 2.3 - 9.1 Residue Energy Crops 0 - 0 0.1 - 0.4 0.6 - 2.5 2.6 - 10 0.8 - 3 0.9 - 3.5 3.3 - 12.7 0 - 0.2 0 - 0 8.3 - 32.3 Sub-Total 4.4 - 4.9 11.5 - 13.1 22.7 - 30.5 20.1 - 38.6 14 - 19.8 5.5 - 9.7 12.8 - 24.8 12.4 - 14.9 17.3 - 21.9 120.8-178.2 Renewable gas from MSW MSW 0.3 - 1.2 0.9 - 3.5 1 - 4 0.5 - 1.8 1.4 - 5.2 0.4 - 1.7 0.8 - 3.2 0.5 - 1.9 1.1 - 4.2 6.9 - 26.8 RNG from P2G / Methanation P2G / Methanation 42.3 Totals 4.7 - 6.2 12.4 - 16.6 23.7 - 34.5 20.6 - 40.4 15.4 - 25 6 - 11.3 13.7 - 28 12.9 - 16.9 18.3 - 26.1 170.0-247.3

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Exhibit EG – 3

Exhibit EG-3

Date of Request: October 1, 2020 Request No. SC-010 Due Date: October 12, 2020 NMPC Req. No. NM-998

NIAGARA MOHAWK POWER CORPORATION d/b/a NATIONAL GRID Case Nos. 20-E-0380 and 20-G-0381 Electric and Gas Rates

Request for Information

FROM: Sierra Club, Joshua Berman

TO: National Grid, Future of Heat Panel

SUBJECT: Future of Heat

Request:

Note: The following information request pertains to the gas filings for 20-G-0381.

10. Referring to the Future of Heat Panel testimony’s discussion of renewable natural gas (RNG) at 44-45, has the Company evaluated how much locally sourced RNG is presently available in its service territory? If so, please provide this analysis. Has the Company evaluated how much locally sourced RNG is likely to become available in specific future years? If so, please provide all such analyses.

Response:

The potential for RNG derived from biomethane has been analyzed on a state basis. The low and high potentials for anaerobic digestion and thermal gasification from various feedstocks by 2040 can be found below. The potential for locally-sourced RNG derived from biomethane in specific future years has not been evaluated. tBTU/yr = trillion BTU/yr

Form 103 Exhibit EG-3

Resource Potential for RNG in 2040 Resource Potential tBtu/y

Anerobic Digestion Thermal Gasification State Landfill Animal WRRF Food Agricul Forest Energy MSW TOTAL NY Low 19.739 4.522 2.472 2.388 2.015 1.98 0.598 19.307 53.021 High 32.753 9.044 3.304 4.179 5.038 3.959 3.041 43.536 104.854

Name of Respondent: Date of Reply: Melissa Mauro October 8, 2020

Form 103

Exhibit EG – 4

Exhibit EG-4

Date of Request: November 13, 2020 Request No. PACE_AGREE-178 Due Date: November 23, 2020 NMPC Req. No. NM-1642

NIAGARA MOHAWK POWER CORPORATION d/b/a NATIONAL GRID Case Nos. 20-E-0380 and 20-G-0381 Electric and Gas Rates

Request for Information

FROM: Pace Energy and Climate Center; Alliance for a Green Economy

TO: National Grid, Future of Heat Panel

SUBJECT: Future of Heat

Request:

The following information request pertains to the gas filings for 20-G-0381:

178. Will all of the RNG incorporated into the Company's gas network through the Centralized Interconnection Program be purchased through the RNG Procurement Program?

Response:

178. Yes. The Company expects all RNG incorporated into the Company's gas network under the Centralized Interconnection Program will be purchased through the proposed RNG Procurement Program.

Name of Respondent: Date of Reply: Melissa Mauro November 20, 2020

Form 103

Exhibit EG – 5

Exhibit EG-5

Date of Request: November 13, 2020 Request No. PACE_AGREE-177 Due Date: November 23, 2020 NMPC Req. No. NM-1641

NIAGARA MOHAWK POWER CORPORATION d/b/a NATIONAL GRID Case Nos. 20-E-0380 and 20-G-0381 Electric and Gas Rates

Request for Information

FROM: Pace Energy and Climate Center; Alliance for a Green Economy

TO: National Grid, Future of Heat Panel

SUBJECT: Future of Heat

Request:

The following information request pertains to the gas filings for 20-G-0381:

177. Will all of the RNG incorporated into the Company's gas network through the Direct Interconnection Program be purchased through the RNG Procurement Program?

Response:

177. Yes. The Company expects all RNG incorporated into the Company's gas network under the Direct Interconnection Program will be purchased through the proposed RNG Procurement Program.

Name of Respondent: Date of Reply: Melissa Mauro November 20, 2020

Form 103

Exhibit EG – 6

Exhibit EG-6

Date of Request: September 21, 2020 Request No. PACE_AGREE-015 Due Date: October 1, 2020 NMPC Req. No. NM-858

NIAGARA MOHAWK POWER CORPORATION d/b/a NATIONAL GRID Case Nos. 20-E-0380 and 20-G-0381 Electric and Gas Rates

Request for Information

FROM: Pace Energy and Climate Center; Alliance for a Green Economy, Priya Pookkulam

TO: National Grid, Future of Heat

SUBJECT: Future of Heat - CCUS

Request:

Note: The following information request pertain to the gas filings for 20-G-0381.

15. Please provide the Company’s estimates, projections, and analyses of expected emissions generated by:

a. The production of RNG incorporated into the gas network.

b. The trucking and transportation of RNG into the gas network.

c. Methane leaks associated with the production and transport of RNG into the gas network.

Response:

An emissions analysis has not been conducted, but the gas industry is looking to develop a methodology to quantify emissions reductions from RNG projects.

Name of Respondent: Date of Reply: Melissa Mauro September 29, 2020

Form 103

Exhibit EG – 7

Exhibit EG-7

Date of Request: September 21, 2020 Request No. PACE_AGREE-012 Due Date: October 1, 2020 NMPC Req. No. NM-855

NIAGARA MOHAWK POWER CORPORATION d/b/a NATIONAL GRID Case Nos. 20-E-0380 and 20-G-0381 Electric and Gas Rates

Request for Information

FROM: Pace Energy and Climate Center; Alliance for a Green Economy, Priya Pookkulam

TO: National Grid, Future of Heat

SUBJECT: Future of Heat - CCUS

Request:

Note: The following information request pertain to the gas filings for 20-G-0381.

12. Please provide documents disaggregating the types of feedstock sources that the Company expects to incorporate into the gas network via the Centralized RNG Interconnection Program (e.g. feedstock derived from wastewater vs feedstock derived from dairies). Please be sure to include estimates of the quantity and percentages for:

a. Feedstock that has been processed using an anaerobic digester.

b. Feedstock sourced from preventable or compostable food waste.

c. Feedstock sourced from concentrated animal feeding operations.

d. Feedstock sourced from energy crops.

e. Feedstock sourced from forest residues.

Where precise figures are impossible to provide, please provide an expected range as well as any and all documentation and correspondence related to the expected mix of feedstock to be incorporated into the gas network.

Response:

The Centralized RNG Interconnection Program seeks to obtain dairy feedstock using anaerobic digesters from farms that may not be close enough to the pipeline for a direct connection but are capable of providing RNG to the gas system.

Form 103 Exhibit EG-7

The Company has received requests but, at this time, does not have enough information to estimate the amount of RNG capable of being provided. At this time, the Company anticipates the participation of four to five farms per Centralized location.

Name of Respondent: Date of Reply: Melissa Mauro September 29, 2020

Form 103

Exhibit EG – 8

Exhibit EG-8

Date of Request: September 21, 2020 Request No. PACE_AGREE-013 Due Date: October 1, 2020 NMPC Req. No. NM-856

NIAGARA MOHAWK POWER CORPORATION d/b/a NATIONAL GRID Case Nos. 20-E-0380 and 20-G-0381 Electric and Gas Rates

Request for Information

FROM: Pace Energy and Climate Center; Alliance for a Green Economy, Priya Pookkulam

TO: National Grid, Future of Heat

SUBJECT: Future of Heat - CCUS

Request:

Note: The following information request pertain to the gas filings for 20-G-0381.

13. Please provide documents disaggregating the types of feedstock sources that the Company expects to incorporate into the gas network via the Direct RNG Interconnection Program (e.g. feedstock derived from wastewater vs feedstock derived from dairies). Please be sure to include estimates of the quantity and percentages for:

a. Feedstock that has been processed using an anaerobic digester.

b. Feedstock sourced from preventable or compostable food waste.

c. Feedstock sourced from concentrated animal feeding operations.

d. Feedstock sourced from energy crops.

e. Feedstock sourced from forest residues.

Where precise figures are impossible to provide, please provide an expected range as well as any and all documentation and correspondence related to the expected mix of feedstock to be incorporated into the gas network.

Response:

The Company will accept any of the listed feedstocks into the gas system. There are no specific prospects in mind at the time, but the premise for the program is that, with the funding proposed in the rate filing, some developers may choose to inject RNG as opposed to using biogas for generation.

Name of Respondent: Date of Reply: Melissa Mauro September 29, 2020

Form 103

Exhibit EG – 9

Exhibit EG-9

Date of Request: September 21, 2020 Request No. PACE_AGREE-022 Due Date: October 1, 2020 NMPC Req. No. NM-865

NIAGARA MOHAWK POWER CORPORATION d/b/a NATIONAL GRID Case Nos. 20-E-0380 and 20-G-0381 Electric and Gas Rates

Request for Information

FROM: Pace Energy and Climate Center; Alliance for a Green Economy, Priya Pookkulam

TO: National Grid, Future of Heat

SUBJECT: Future of Heat - Hydrogen

Request:

Note: The following information request pertain to the gas filings for 20-G-0381.

22. With regard to the Multi-use Hydrogen Production and Utilization Facility, please disaggregate the feedstock for the electricity that the Company expects to be used in the production of hydrogen for the service area that is the focus of this case. Specifically, please state:

a. The expected percentage and amount of electricity generated by feedstock from surplus renewables, broken down by type of renewable (e.g. “The Company expects 40% of the feedstock for the Multi-use Hydrogen Production and Utilization Facility to come from surplus renewables: 10% wind, 30% solar”).

b. The expected percentage and amount of electricity generated by feedstock from natural gas.

c. The expected percentage and amount of electricity generated by feedstock from coal.

d. The expected percentage and amount of electricity generated by feedstock from petroleum.

e. The expected percentage and amount of electricity generated by other types of feedstock not covered by subparts a. through d. of this interrogatory, broken down by type of feedstock (e.g. “The Company expects 10% of the feedstock for the Multi-use Hydrogen Production and Utilization Facility to come from other sources of energy: 9% nuclear, 1% propane.”).

Form 103 Exhibit EG-9

Response:

The Company’s objective is to exclusively utilize electrolyzers provided with renewable electricity for the multi-use hydrogen demonstration and future multi-use hydrogen facilities as well as future Power to Gas (“P2G”) facilities. Each facility will be connected to the electric grid and will utilize fully renewable power contracted for, and transmitted to, each site and/or generated onsite from zero-carbon sources, most likely wind or photovoltaic technologies. The Company understands that, in the early years, sufficient renewable electricity might not be available immediately at a reasonable cost at each site but is confident that such zero-carbon power will become increasingly available as required by the Climate Leadership and Community Protection Act early in the life of these facilities. In the case where such power is not yet available, some power initially will be provided by the electric grid from existing sources. The feedstocks for electricity production will be the same as for similarly situated facilities in the same zone (zone F in the case of the Capital region) managed by the New York Independent System Operator (“NYISO”). In this case, the use of feedstocks varies with energy market conditions and the time-varying use of energy sources for generation is reported by the NYISO at https://www.nyiso.com/real-time-dashboard. In addition, as noted in the Future of Heat Panel’s direct testimony, future P2G facilities may further treat the hydrogen produced to produce a zero-carbon substitute natural gas (“SNG”) through methanation. Methanation requires a source of carbon-dioxide. That carbon-dioxide will be provided from one of a few means that is expected to be available from the sequestering of waste streams, possibly, the effluent from waste-water treatment. Carbon-dioxide, however, will not be produced from any fuel only for the purpose of providing carbon-dioxide for the production of SNG, thus ensuring the entire cycle is ultimately zero-carbon.

Name of Respondent: Date of Reply: Christopher A. Cavanagh, PE September 29, 2020

Form 103

Exhibit EG – 10

Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10

RHETORIC VS. REALITY: The Myth of “Renewable Natural Gas” for Building Decarbonization

1 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10

JULY 2020

Sasan Saadat, Earthjustice’s Right to Zero campaign Matt Vespa, Earthjustice’s Right to Zero campaign Mark Kresowik, Sierra Club

2 Exhibit EG-10 EXECUTIVE SUMMARY

Policymakers seeking to cut emissions and reduce reliance on fossil fuels are increasingly examining energy use within buildings, which account for nearly 40% of carbon emissions globally. One of the largest drivers of these emissions is the burning of fossil fuels like gas for home heating, hot water, and cooking. In 2018, carbon emissions from U.S. buildings increased 10% due to growth in these uses alone.1

There is growing consensus that electrifying buildings – using electric appliances like heat pumps and induction stoves to replace the need for fuel combustion – is the clearest path to mitigating their pollution. Efficient, all-electric buildings eliminate on-site carbon emissions and methane leakage, and they can eventually achieve net-zero emissions as the grid becomes cleaner. Furthermore, building electrification eliminates the health impacts from burning gas indoors,2 and reduces the safety hazards from gas leaks and explosions, all while capitalizing on the declining costs of generating electricity from solar and wind power.

Numerous studies indicate that electrification is the lowest-risk and lowest-cost method to reduce greenhouse gas emissions (“GHGs”) from buildings, while generating additional societal benefits. And because buildings last for many decades, avoiding gas infrastructure and appliances in new construction is crucial for avoiding lock-in of fossil fuel reliance. As such, many policymakers across the U.S. and globally see electrification as the future of buildings. By early 2020, more than 30 cities and counties in the U.S. passed policies requiring or supporting all-electric new construction.

Gas utilities, which rely on maintaining and expanding fuel delivery infrastructure to buildings to generate revenue, view electrification as an existential crisis. The industry’s response has been to pitch fossil gas alternatives (“FGAs”) – often marketed as “renewable” natural gas (“RNG”) – as an alternative to building electrification.

The argument goes that existing gas infrastructure can continue to operate by replacing today’s fuel with a range of biologically and synthetically derived non-fossil gaseous fuels.

This report examines the potential for FGAs to decarbonize buildings and refutes the claim that FGAs are a viable alternative to building electrification. 1 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10 Earthjustice & Sierra Club | Rhetoric vs. Reality

Topline findings include:

• The potential supply of FGAs is a small fraction of gas demand. The gas industry’s own research found that after two decades of ramping up supply and production, FGAs could only replace 13% of the existing demand for fossil gas. Any strategy to reduce building emissions that relies on FGAs in lieu of electrification would not lead to complete decarbonization and diverts limited FGA supplies from more difficult to electrify sectors.

• Replacing fossil gas with FGAs is extremely costly. High production costs mean FGAs range from 4 to 17 times more expensive than fossil gas.

• FGAs have a mixed environmental record. Facilities where FGAs are produced can exacerbate air and water pollution impacts in nearby communities. When methane is intentionally produced, leakage throughout the distribution process can result in increased emissions.

• FGAs perpetuate the health impacts of combustion. Burning FGAs in homes, offices, and commercial spaces has the same issues inherent to any combustion-based fuels: they produce toxins that harm the health of people living, working, or learning in these buildings and also contribute to local air pollution through continued emissions of NOx and other combustion byproducts.

CLEAN ALL-ELECTRIC HOUSE GAS-BURNING HOUSE

Local clean energy jobs Clean air Powered by gas Methane leakage Health and safety benefits Renewable energy Health and safety risks Indoor and outdoor Saves money and energy Wastes energy air pollution

Through electrification, decarbonizing our buildings is also an opportunity to reduce legacy sources of indoor air pollution.

22 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10

The report finds that due to the limited An internal set of AGA meeting notes from supply and high cost of biogas and March 2018 shows the industry determined synthetic gas, and the associated pollution FGAs can be used to “mitigate the and health impacts, the small and costly opposition’s fervor” to phase out the burning amount of FGAs available should be used to of gas due to climate concerns.4 decarbonize sectors where there are few or no lower-cost mitigation solutions. Buildings Another internal document makes clear do not meet these criteria. an awareness of FGAs’ limits, coming from an industry source: “[In my opinion], RNG Nevertheless, gas system incumbents will not sustain our industry at its present are embarking on a coordinated strategy size.”5 In another instance, a board member advocating for the use of FGAs in homes for a gas industry advocacy group told and buildings, irrespective of the fact that The Guardian on the record: “Dairy biogas low-grade building heat is a poor use case is way too expensive” to use in home or for the limited supply of high-cost, low- businesses – five to 10 times more expensive carbon FGAs. than fossil gas. “It doesn’t pencil out and it doesn’t make all that much sense from an The second half of the report looks at environmental standpoint. It’s a pipe dream.”6 both gas industry incumbents’ efforts to fight electrification through a well-funded We find a pattern of talking points and campaign to sway public opinion – often lobbying efforts that leverage FGAs as a through fake grassroots organizations – means of maintaining a gas-based heating and their misleading public rhetoric on the system and stalling the transition away from potential use of FGAs as an alternative fossil fuels. building electrification. This is not unfamiliar territory: The tactics Claims from utilities like Southern California come from the same energy industry Gas Company (“SoCalGas”) that replacing playbooks that have dismissed and 20% of fossil gas with FGAs can have the obfuscated the threat of climate change. same impact as electrification, or Dominion In this case, the widespread adoption of a Energy, that replacing 4% of fossil gas can proven and cost-effective means of fighting eliminate the entire carbon footprint of its climate change is being attacked and gas operations, are flawed and misleading stalled in order to protect fossil fuel financial given the limited supply of low-carbon FGAs. interests.

These statements positioning FGAs as a Ultimately, FGAs do not provide a path to clean source of energy make more sense decarbonizing the gas grid in line with a net- when reviewing internal gas industry zero emissions energy system. Policymakers documents. The American Gas Association’s must see beyond the gas industry’s rhetoric (“AGA”) Clean Energy Task Force developed around FGAs and acknowledge the reality draft policy principles stating the AGA of their high costs, limited supply, and “supports policies that define the term environmental risk. ■ ‘renewable energy’ to include RNG on par with other energy sources, such as energy generated from wind or solar resources.”3

3 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10

PART 1: The appropriate – and limited – role for lower-carbon gas alternatives on the road to decarbonization

4 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10

Climate goals require 1. a gas phaseout

To keep global average temperature from A 2019 study expanded the analysis to rising above 1.5°C and avoid the worst include leakage in distribution and end- impacts of climate destabilization, the uses, and found observed emissions from world must achieve net-zero emissions of local gas distribution to be a factor of two greenhouse gases by mid-century.7 This to three times larger than those in the U.S. requires us to stop burning fossil fuels as EPA’s inventory.13 Researchers in California rapidly as possible.8 Thus, greenhouse found average home leakage rates to gas emissions from unabated gas use be 0.5%, representing leaks “an order of are incompatible with achieving net-zero magnitude larger” than earlier estimates.14 emissions.9 Even aiming for the far less safe 2°C warming scenario would mean keeping Importantly, methane leakage issues more than half of the world’s existing gas are not limited to fossil gas. Whether the reserves unused and unburned.10 methane is synthetic, biogenic, or fracked, if it’s pumped into homes through the existing Achieving a net-zero emissions society distribution network, it will face similar inevitably means a substantial decline in leakage rates, and ultimately have the same gas consumption. With gas overtaking coal negative climate impact from methane as the largest source of fossil fuel emissions leakage into the atmosphere. in the United States, greater focus has been given to its true climate impact.

A growing body of research has highlighted the high global warming potential of Whether the methane methane, the main constituent of gas. is synthetic, biogenic, Methane’s radiative force,11 which is 36 times or fracked, if it’s more potent than CO2, and its pervasive leakage along the gas supply chain – both pumped into homes of which are proving more severe than through the existing previously understood – increase the distribution network, urgency of its near-term mitigation. it will face similar New findings suggest methane leakage leakage rates, and throughout the nation’s gas delivery system ultimately have the is much more widespread than officials understood just a few years ago. In 2018, same negative climate research published in the journal Science impact from methane found the leakage rate in the U.S. gas supply chain equaled 2.3% of U.S. gross leakage into the gas production, 60% higher than the EPA’s atmosphere. official estimate.12

Gas flare at Permian Basin— Eddy County, NM blake.thornberry, Flickr, CC BY-NC-ND 2.0

5 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10

Different sources of fossil 2. gas alternatives

The term “RNG” is currently used as an umbrella term to describe a range of fossil gas alternatives, most of which fall into two categories: biogas and synthetic gas. Different feedstocks and production methods for either of these alternatives require trade-offs around cost, supply, and social and ecological impact.15

BIOGAS

Biogas refers to methane derived from organic sources, such as crops or animal manure. It is produced via two main pathways, anaerobic digestion and thermal gasification. When upgraded and conditioned so it is pipeline-ready, biogas is typically referred to as biomethane.

ANAEROBIC DIGESTION THERMAL GASIFICATION

Anaerobic digestion is the Thermal gasification breaks down dry biomass in decomposition of wet, organic a high-heat environment, creating methane from matter by microorganisms in an solid matter where none would ordinarily occur. oxygen-free environment. Often, The feedstocks used in this process are mostly anaerobic digestion is used to lignocellulosic plants – so named because they produce biogas from sources which contain carbon-based polymers – which include: currently emit methane, including: • agricultural residues, such as the unusable • landfill gas; portions of crop stalks, stems, and branches; • animal manure from • forestry and forest residues, such as livestock operations; sawmill residue and the extraneous wood • wastewater treatment plants generated from logging; (“WWTP”); and • energy crops, grown specifically for • organic municipal solid the purpose of becoming fuel, such as waste (“MSW”), specifically perennial grasses; and food waste. • inorganic components of MSW, such as construction debris, such as plastic, glass, and textiles.

Lignocellulosic biomass can also be used as a non-gaseous fuel, such as conversion into renewable diesel. While gasification is a well-understood process, thermal gasification of biomass has not yet been proven at scale.

6 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10 Lima Synthetic Gas Research Center Ohio Development Services Agency, Flickr, CC BY 2.0

SYNTHETIC GAS

Synthetic gas is produced by converting electricity into a gaseous fuel through a process called power-to-gas, or P2G. It begins with electrolysis – using electricity to split water into hydrogen and oxygen. Hydrogen itself is a gaseous energy carrier, but to match the chemical make-up of fossil gas, it must go through a second step called methanation where carbon dioxide is added to the hydrogen.

When powered by renewable electricity, this process allows power from sources such as wind or solar to be converted into a gaseous fuel that can be carried by traditional pipelines.

But the substantial amounts of energy and conversion loss needed to turn electricity into hydrogen, and then hydrogen into synthetic methane, wastes much of the renewable power. After electrolysis, only about 67% to 81% of the initial energy remains. Not including the energy required to capture the CO2, the methanation process leaves only about 54% to 67% of the energy.16 All else being equal, using renewable electricity to power electrolysis and create synthetic methane that is then used to generate heat is far more costly and energy-intensive than the direct use of renewable electricity through heat pumps.

7 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10

Not all fossil gas alternatives 3. are environmentally beneficial

While estimates for the maximum amount Biogas from CAFOs of technically producible FGAs vary, these estimates rarely screen for those Methane generated from the anaerobic decomposition FGAs which are actually environmentally of manure in lagoons at concentrated animal feeding beneficial to use. Higher potential volumes operations (“CAFOs”) has been advanced as a of FGAs should not be assumed to be promising source of biomethane production. While often marketed as “sustainable,” biomethane capture does more environmentally beneficial. Because not abate the significant harms CAFOs have on already of methane’s severe radiative force and overburdened local communities and ecosystems. For the high probability of leakage throughout example, dairy CAFOs in the Southern San Joaquin its lifecycle, generating new sources of Valley of California are the region’s largest source of methane where none would ordinarily occur ozone-forming volatile organic compounds (“VOC”) and can lead to an overall increase in GHGs. further damage air quality through significant emissions of ammonia and fine particulate matter.i These facilities A new analysis by the Natural Resources also contribute to nitrate pollution of drinking water and Defense Council estimates that screening contaminate waterways, with nitrogen runoff leading out ecologically problematic sources of to the eutrophication of lakes and streams.II Every FGAs would exclude roughly half the total well monitored near dairies in the Central Valley Dairy amount of FGAs technically producible.17 Representative Monitoring Program showed nitrate levels above the maximum contamination limit.iii Recent research highlights the potential In addition, while proponents assert that methane from for intentionally produced methane to CAFOs manure lagoons would otherwise be emitted into create climatically significant levels of the atmosphere, these emissions are not an inevitable leakage.18 The analysis shows that FGAs or ordinarily occurring consequence of raising livestock. “from intentionally produced methane is They are the result of industrial livestock management always GHG positive unless total system decisions (namely confinement, concentration, and liquid- based manure storage)iv and a regulatory environment leakage is 0.”19 At leakage levels observed that permits these practices to continue despite their significant air and water quality impacts. Were herd sizes maintained at more manageable levels, livestock operations could avoid producing waste in excess of agronomic rates for nearby crops, maintain pasture- based livestock operations, or more feasibly employ dry handling storage systems, thereby avoiding these methane emissions in the first instance.v Because the high capital costs of anaerobic digesters make economic sense only for the CAFOs that produce and store large quantities of wet manure, markets and subsidies for biomethane capture reward the largest and most polluting CAFOs, reinforcing and intensifying trends of industry consolidation, with corresponding increases to localized pollution.vi

Dairy cattle on a hot summer day in Bakersfield, CA David McNew/Getty Images 8 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10 in the existing biogas industry, intentionally In particular, mitigation strategies that produced methane, even from climate- address the underlying causes of waste neutral CO2 sources, has substantial climate methane are important to consider when impacts.20 Thus, the climate benefit of FGAs these practices are associated with multiple depends on whether they are derived from social and environmental harms. Markets methane that would otherwise be emitted that value pollution may become obstacles into the atmosphere. Of the total volume to policies that can reform inefficient of FGAs technically producible, only a very and polluting practices or which may small portion comes from methane already appropriately make polluters responsible being emitted to the atmosphere. The study for addressing their own emissions. In the estimates that capturable waste methane graphic below, we illustrate a framework for (e.g., from uncontrolled landfills and assessing whether FGAs are actually likely to wastewater treatment plants) is less than be environmentally beneficial. The supply of 1% of current gas demand.21 The rest must FGAs from genuine and unavoidable waste be intentionally produced and will pose the methane is far more limited than the amount risk of additional methane leakage that can that is technically producible. offset any potential emission reductions.

Even FGAs that can be produced from methane already emitted into the atmosphere should not automatically be considered environmentally beneficial. As A premium should be a general rule, proposals to commoditize placed on mitigation pollution should be treated with caution. strategies that Climate “solutions” that perpetuate or exacerbate local pollution are incompatible permanently avoid the with the principles of a just and equitable generation of methane transition. In fact, creating markets for emissions through FGAs that capture methane pollution can perversely incentivize continued reliance on more sustainable practices that lead to the methane pollution practices. in the first instance. As researchers note, “because biogas and biomethane can generate revenue, it is not only possible but expected to intervene in biological systems to increase methane production beyond what would have happened anyway when there is an incentive to do so.”22 Before considering capturing and using waste methane as an FGA, decision makers should examine whether the methane emissions could be prevented in the first place through better resource or waste management practices. A premium should be placed on mitigation strategies that permanently avoid the generation of methane emissions through more sustainable practices.

9 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10 Earthjustice & Sierra Club | Rhetoric vs. Reality What Biomethane Sources are Environmentally Suitable?

The supply of biomethane that is environmentally beneficial to produce Maximum biomethane that is is substantially smaller than the total maximum potential of biomethane. technically producible Genuine waste methane which cannot be readily avoided and has few other social or environmental harms (e.g., wastewater treatment) may be environmentally beneficial to capture and reuse as biomethane.

Does production require generating new sources of methane where none would AVOID ordinarily occur? YES Thermal Gasification of: • Energy crops • Forest product residue* • Usable agricultural residue* NO

RATIONALE Due to methane’s severe radiative WHAT’S LEFT: force, and the high probability of leakage throughout its lifecycle, it Biomethane from sources of is preferable to avoid generating fugitive methane emissions new sources of methane where none would ordinarily occur.

AVOID Can methane emissions be Anaerobic Digestion of: prevented through alternative YES • Manure from CAFOs resource and waste management? • Preventable, rescuable or compostable food waste

NO RATIONALE A premium should be placed on mitigation strategies that WHAT’S LEFT: permanently avoid the generation Biomethane where capture- of emissions in the first instance. and-use is the optimal Biomethane production from these sources can perversely perpetuate mitigation strategy poor resource management.

* While they do not ordinarily generate methane, certain types of lignocellulosic biomass from agricultural or municipal solid waste (e.g., sawmill residue) may be unpreventable and difficult to compost or divert toward other uses. If no superior waste prevention or management strategy exists, it may be environmentally advantageous to redirect these waste streams toward fuel production. Nonetheless, it may be practical to exclude these from estimates of biomethane potential since multiple end-uses beyond current gas demand will compete for the limited supply of sustainable lignocellulosic biomass. Potential renewable fuel sources are generally better devoted to liquid fuels that displace more expensive, GHG-intensive petroleum or to hydrogen production which does not pose the risks of GHG increases from methane leakage or emit pollutants when combusted.

1010 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10

Fossil gas alternatives have no 4. clear path to fully decarbonizing the gas grid

Even the gas industry’s own analysis finds there is an insufficient supply of carbon-free gas to meet anything more than a small portion of current gas demand. According to a study by the American Gas Foundation (“AGF”), even after fully ramping up the production of renewable gas, FGAs could supply between just 6% to 13% of current gas demand,23 clearly falling short of the goal of net-zero emissions and requiring fossil gas to make up the difference.

In the AGF study, a proposed high-resource scenario, which would still meet just 13% of U.S. gas demand, relies on significantly increased thermal gasification of energy crops, accelerating production from 123 to 837 tBtu/year (trillion British thermal units a year, a measure of gas production). Expanding reliance on purpose-grown energy crops would introduce serious sustainability risks by diverting arable land from food to energy production. It could drive up the cost of food and drive changes in land-use patterns that would transform forests and grasslands – natural carbon sinks – into agricultural areas for energy crops. According to the U.S. EPA’s own assessment, the Renewable Fuel Standard – an existing program that incentivizes biofuel production – has resulted in the conversion of 4 to 8 million acres of land, completely nullifying and overwhelming any climate benefit the program might have had.24 Thus, additional energy crop incentives are likely to result in a dramatic loss of stored carbon and increased emissions that can make biofuels even more GHG-intensive than fossil fuels.

1111 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10

A limited amount of biogas (363-876 tBtu/year) could come from the residual portions of agricultural and forest products that are not traditionally usable. But some of these forest and crop residues would be more ecologically advantageous to devote to other purposes besides fuel production, such as animal feed or incorporation as a soil amendment into compost. The high-resource scenario also assumes that most or all forest and crop residue would be devoted exclusively to gaseous fuel production as opposed to liquid fuels or power generation, more suitable uses explored later in this report.

Even the most aggressive scenario laid out by the AGF still reflects what would be possible by 2040, after two decades of scaling FGA potential. Mobilizing all these resources toward existing gas demand, which still would only meet 13% of the nation’s gas needs, would leave a far smaller amount of biogas and synthetic gas available for more difficult to decarbonize end uses.

FGA RESOURCE POTENTIAL AND CURRENT GAS DEMAND

30,000 31,000

25,000

20,000

15,000

10,000 TOTAL VOLUME ( tBtu/Y) VOLUME TOTAL

5,000 4512.6 1913.2 220 240 0 2018 GAS LOW (2025) HIGH (2025) LOW (2040) HIGH (2040) DEMAND*

Source: American Gas Foundation RNG Report, Dec. 2019 * U.S. Energy Information Administration 1212 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10

Low-carbon gases are 5. significantly more expensive than fossil gas

Relative to the cost of fossil gas, FGAs are produce hydrogen and avoid the additional far more expensive to produce. Between step of methanation. But hydrogen can only 2018 and 2020, fossil gas prices mostly be injected into existing gas pipelines at hovered between $2.03-$2.86/MMBtu minimal volumes before risking dangerous (one million British Thermal Units).25 By levels of corrosion. Optimistic scenarios contrast, the AGF’s estimates for landfill estimate that the pipeline system could gas, typically the cheapest way to produce handle volumes of 7% hydrogen by energy biogas, range between $10-$20/MMBtu.26 content before requiring costly upgrades.29 Dairy manure projects are projected to cost closer to $40/MMBtu. Thermal gasification Thus, each FGAs decarbonization projects, necessary to achieve higher potential for building end uses is limited technical potentials, all begin at even higher by supply, cost, or environmental integrity. production costs.27 Synthetic methane is disadvantaged by its conversion inefficiencies and high costs. The AGF concluded that by 2040, half Biogas, which is limited in supply, could of all low-carbon, non-fossil gas used only be made in more substantial amounts in their aggressive resource potential by accepting significant environmental scenario could be available at $20/MMBtu. risks and higher production costs. While While some low-cost biomethane from hydrogen production is compatible with landfills and wastewater treatment plants net-zero emissions and technically unlimited is available, the costs rapidly increase as in supply, its suitability for decarbonizing production is expanded and pushed to more the existing gas grid are constrained by its challenging projects. effects on the pipeline.30

A report for the California Energy Commission similarly finds: “[e]ven under optimistic cost assumptions, the blended costs of hydrogen and synthetic natural gas are found to be 8 to 17 times more expensive than the expected price trajectory of natural gas.”28 While substantial cost declines are likely to be a decade or more away, synthetic gas from hydrogen (whereby hydrogen is produced from electrolysis and then methanated) is estimated to remain many times more expensive than fossil fuels for decades to come, even assuming aggressive and rapid industry learning. Production costs would be lower if electrolysis is used only to

13 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10

Given their limited supply and high 6. costs, fossil gas alternatives are best-suited for use in harder-to- decarbonize segments of society

Injecting FGAs into the gas delivery system hits a dead end well short of complete decarbonization. Even outstanding HOW DO HEAT improvements to the production costs of FGAs are unlikely to alter a fundamental point: Decarbonized gas is better PUMPS WORK? suited for applications that currently lack a low-cost By transferring heat rather than creating it, heat pumps deliver hot pathway to direct electrification. water 3-5 times more efficiently than conventional water heaters. Even if renewable energy costs decrease and electrolyzer Heat pump pulls warmth technology improves, lowering the cost of renewable from the air. hydrogen and using renewable synthetic gas to decarbonize Warm air is compressed, heating will likely remain far more expensive than running increasing its temperature. heat pumps on renewable power, an existing and already Condenser coils transfer widely available technology. Changes to this dynamic are heat to the water. limited by basic physics: Using renewable electricity to power electrolysis for the production of gas will result in significant conversion losses. To produce 100% renewable Cool Air Out Hot Water Out hydrogen, an electrolyzer has to have access to 3 to 3.5 times its installed capacity of solar or wind generation.31 Because of this inherent inefficiency, P2G will always Warm be considerably more expensive than directly using Air In electricity.32 On top of that, gas-burning appliances such as boilers and furnaces are far less efficient than heat pumps. Direct electrification is therefore far more effective in decarbonizing heat wherever it is possible to use heat pumps. Even for many industrial uses, which require Pump Heat temperatures between 75 to 140°C, heat pumps are the most effective option.33

Given the limited availability of economic, sustainable FGAs, their role in a net-zero energy system will necessarily be small. Dedicating FGAs to incrementally lower the carbon Tank Storage intensity of gas heating in buildings is a poor use case, especially given their potential to advance decarbonization Cool Water In in more challenging sectors.

On a cost-effectiveness basis, policymakers should focus on socially optimal use cases for liquid/gaseous renewable fuels, such as delivering high industrial heat for steel production or powering air or marine

14 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10 transportation. Biogas and synthetic gas, as well as other renewable liquid fuels, have several advantages over electricity. Though Because heat pumps costly, limited, and inefficient to produce, and electric vehicles they are energy-dense, can be stored and transported more readily than electricity, and offer superior work with existing infrastructure that must efficiency and rely on combustion. In optimizing their use, eliminate end-use the advantages of renewable fuels (e.g., flexible, combustible, dispatchable) should air pollution, direct be weighed against their disadvantages use of electricity (e.g., cost, leakage, limited supply) and should be used to the availability of alternatives such as electrification and demand management. the maximum extent Because heat pumps and electric vehicles feasible in buildings offer superior efficiency and eliminate end- use air pollution, direct use of electricity and transport. should be used to the maximum extent feasible in buildings and transport.

SOME SUGGESTED USES FOR FGAs:

HIGH-HEAT DECARBONIZING FUEL FOR HEAVY INDUSTRIAL CHEMICAL ROAD, AIR, PRODUCTION PRODUCTION AND MARITIME TRANSPORTATION Certain carbon-intensive Hydrogen is required as industrial processes, such a feedstock for industrial Renewable liquid or as steel production, require processes, such as gaseous fuels, either sustained temperatures ammonia and iron ore from biogenic materials greater than 200°C, which production. Nearly all of the or from power-to-gas/ are currently generated by hydrogen currently used power-to-liquid pathways, combusting natural gas. While to meet these demands is may eventually enable it’s possible to use advanced developed through Steam decarbonization of the heat pumps to deliver Methane Reformation heavier categories of high process heat in some (“SMR”) of fossil gas, transportation, such as instances, changing industry an emissions-intensive international air and sea operations to employ electricity process. Renewable transport. in place of combustion may hydrogen offers a way to require expensive logistical provide cleaner feedstocks changes and facility retrofits.34 to these industries. Biogas and synthetic gas could enable decarbonization of these sectors right now, without requiring costly modifications.

1515 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10

Even with the current, low-commodity Moreover, FGAs are not an ideal fuel costs of fossil gas, electrification proves source for buildings because, just like fossil to be a cost-effective energy solution gas, their combustion harms the health of for many households. The balance would people living, working, or learning in these significantly tilt in favor of electrification if buildings. They also contribute to local air FGAs were used given their extremely high pollution through continued emissions of costs. NOx and other combustion byproducts – an avoidable outcome, given the availability of These findings are not limited to warmer electric, zero-emission solutions. In addition, climates such as California. A multifaceted even after treatment for injection into gas analysis by Evolved Energy Research on pipelines, the potential residual toxicity of pathways to reducing the state of New biomethane has yet to be fully understood. Jersey’s emissions and meeting its 2050 A recent study by the California Energy climate goals included a “least cost” option. Commission found that using biomethane That scenario, along with numerous other for home appliances causes DNA damage options discussed, required buildings to be and mutagenicity, with varying results for 90% electric by 2030.35 fossil gas.36

Nevertheless, gas system incumbents The existential financial risks large-scale are embarking on a coordinated strategy electrification present to the incumbent advocating for the use of FGAs in homes fossil fuel industry – largely responsible for and buildings, irrespective of the fact that the energy and environmental challenges low-grade building heat is a poor use case we now face – should not be a reason to for the limited supply of high cost, low- waste precious time and resources and on carbon FGAs. promoting FGAs for use in buildings. ■

A father prepares a meal with his son on an induction stove. Children who grow up in a home with a gas stove are 42% more likely to develop asthma than those who don’t.37 Tom Werner/Getty Images 1616 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10

PART 2: How the reality of fossil gas alternatives differs from gas and industry rhetoric

17 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10

Fossil gas alternatives help 1. preserve the gas utility business model in the face of electrification

Despite the inefficiency of FGAs laid out in existential threat. this report, the fossil fuel industry hopes that by capitalizing on very low public As Sempra Energy, the parent company awareness of the respective cost, supply, for California utilities SoCalGas and San and sustainability challenges that exist for Diego Gas & Electric Company (“SDG&E”) broad-scale use of FGAs, they can sell them noted in its annual 10-K Report, increased as an alternative to building electrification. use of renewable energy and electrification “could have a material adverse effect on This section lays out how building SDG&E’s, SoCalGas’ and Sempra Energy’s electrification challenges the gas industry’s cash flows, financial condition and results of business model and profits, and how FGAs operations.”42 rose to prominence within their efforts and tactics to fight electrification. Indeed, in a 2014 presentation to senior management, SoCalGas already foresaw Like electric utilities, gas utilities profit not the risks of electrification to its business, by selling the gas itself, but by maintaining fighting against higher proposed efficiency infrastructure that delivers energy to homes standards for water heating in new and businesses within an exclusive service construction to block the pathway toward territory. Their businesses are regulated by highly efficient electric heat pump water state public utility commissions, which allow heating and more widespread building them to earn a rate of return on the money electrification. they invest in their gas pipeline networks. While investors have typically prized gas On average, gas utilities generate more utilities, valuing them higher than their than 85% of their gross revenues38 from electric counterparts for many years, signs their residential and commercial customers. are emerging that investor confidence in In the last 20 years, gas utilities have added the future of gas may be in question.43 This 12.4 million new residential customers,39 has also been visible on recent gas utility and spent more than $22 billion annually40 quarterly earnings calls, where company replacing old pipes, averaging a 12% per executives are increasingly being forced to year increase in capital investment from defend the sustainability of their businesses 2010 to 2016.41 About 30% of the nation’s to the financial community.44 residential and commercial gas demand is delivered by gas-only utilities, as Gas interests are under pressure to both opposed to those who deliver both gas and demonstrate they are taking steps to reduce electricity, making these organizations that emissions while also illustrating alternative much more dependent on maintaining the pathways that allow gas infrastructure to status quo. continue being “used and useful” and also expanded. Any large-scale shift that reduces gas usage, such as electrification, poses an

18 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10 Earthjustice & Sierra Club | Rhetoric vs. Reality

In a 2014 presentation to senior management, SoCalGas already foresaw the risks of electrification to its business, fighting against higher proposed efficiency standards for water heating in new construction to block the pathway toward highly efficient electric heat pump water heating and more widespread building electrification.

1919 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10

How the gas industry seeks 2. to short-circuit building electrification

The movement towards all-electric buildings, which emerged in 2019 with a wave of measures seeking to replace gas appliances with increasingly efficient and consumer- friendly electric alternatives, poses a new long-term financial threat to the gas industry.

To date, more than 30 communities in California and Massachusetts have passed policies restricting or eliminating the installation of any new gas infrastructure in new buildings, or promoting all-electric building codes. These communities include San Jose, California, the tenth largest city in the U.S., and Brookline, Massachusetts,45 which became the first local government on the East Coast to adopt its own electrification policy. Dozens of other cities across the country are considering similar measures.

States, too, are beginning to examine how to wind down investment in existing gas distribution networks. California,46 New Jersey,47 and New York48 in particular are updating and modernizing planning processes, gearing them towards a clean Residents Line Up to Speak in Support of Berkeley’s energy future that reduces or eliminates the All-Electric Building Code need for future gas infrastructure investment.

The gas industry quickly mobilized against pro-electrification legislation,49 using front groups to wage aggressive misinformation campaigns. Prominent examples include:

• SoCalGas set up and continues to fund Californians for Balanced Energy Solutions (“C4BES”), a front group masquerading as a grassroots organization.50 A filing to the California Public Utilities Commission shows how SoCalGas hired a PR firm to set up and provide ongoing support to this organization.51 • The Seattle Times recently exposed a $1 million effort from Washington and Oregon gas companies to form a new group dubbed the Partners for Energy Progress, which launched in May 2020.52 It is intended to represent a coalition of unions, businesses, and consumer groups specifically to help “prevent or defeat” local electrification initiatives. They received advice from C4BES.

20 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10

• Hawaii Gas, facing a Honolulu City would limit or ban the inclusion of gas Council bill that would limit gas water infrastructure in new buildings. Arizona heaters in newly built homes, hired legislators, at the behest of the utility a Seattle-based political consulting Southwest Gas,56 passed the first such firm to create a new front group measure, soon followed by Tennessee,57 called Our Energy Choice and fund the second state to enact such a law. additional opposition campaigns.53 Similar bills forbidding gas bans, using near • Before the town of Brookline identical language to the Arizona bill, have passed a measure to prohibit new been introduced in Kansas,58 Minnesota,59 fossil fuel infrastructure in major Mississippi,60 Missouri,61 and Oklahoma.62 construction projects, a group called SoCalGas also advocated for a similar law the Massachusetts Coalition for in California. In an email to C4BES Board Sustainable Energy unsuccessfully Members, the Vice President for External pressed Brookline officials to reject Affairs and Environmental Strategy at the policy.54 Despite its name, SoCalGas stated “Regarding the AZ bill, however, this organization is actually maybe we at C4BES should be looking at an Astroturf front group formed to that approach here in CA.” promote gas pipeline expansion projects and funded by in-state These efforts to stymie building gas interests and utilities including electrification are effectively kneecapping Enbridge, Eversource, and National local governments that are serious about Grid.55 meeting their long-term emissions reductions goals, since this sector represents such Recently, gas interests have also turned to a significant portion of citywide carbon a preemption strategy. Industry allies have emissions. Building emissions represent 27% begun pushing bills in state legislatures of the greenhouse gas footprint in Berkeley, that would preempt or prevent cities and California,63 nearly two-thirds in Brookline,64 towns from enacting local ordinances that and as high as 73% in Washington, D.C.65

Community Demonstration at SoCalGas/C4BES Press Conference in Riverside, CA 2121 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10

Industry claims about 3. fossil gas alternatives

The gas industry’s strategy to prevent electrification by locking in FGAs is framed as a pursuit of a more sustainable future. The pitch consists of oft- repeated statements meant to confuse the public over the value and cost of electric alternatives while promoting FGAs.

At least 10 op-eds from gas industry surrogates, promoting misleading data on the costs related to electrification while pushing FGAs as a better solution, have been published in California and national media between late 2018 and 2020.

Local utilities, eager to continue supplying gas to homes and buildings and provide some justification for their role in a decarbonized future, have been particularly aggressive in pushing and inflating the potential of FGAs.

SOUTHERN CALIFORNIA GAS COMPANY

In March 2019, SoCalGas announced its intent to become the “cleanest natural gas utility in North America.” A cornerstone of that strategy is to replace 20% of its fossil gas supply with FGAs by 2030:

“Research shows that replacing about 20% of California’s traditional natural gas supply with renewable natural gas would lower emissions equal to retrofitting every building in the state to run on electric-only energy and at a fraction of the cost,” a company press release claims. “Using renewable natural gas in buildings can be two to three times less expensive than any all-electric strategy and does not require families or businesses to purchase new appliances or take on costly construction projects.”66

As illustrated in Part 1 of this report, the reality is that FGAs can take California only marginally down the path of reducing emissions, and at an extremely high cost, while building electrification can cost-effectively take it to zero. The California Energy Commission, across two reports and three years, has found building electrification is the cheapest and lowest-risk option to decarbonize the state’s buildings. SoCalGas’s claims and rhetoric run counter to all reputable analyses on the topic, and SoCalGas has been silent on how much replacing 20% of its gas with FGAs would cost its customers.

Emails show that SoCalGas’s front group, C4BES, was set up specifically to help spread this inaccurate message. In a welcome letter between Ken Chawkins, a SoCalGas employee, and Matt Rahn, who was recruited by SoCalGas as the chair of the board of C4BES, Chawkins states the purpose of C4BES: “We (C4BES) will tell the public and the media about the importance of natural and renewable natural gas.”67

2222 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10

DOMINION ENERGY

Dominion Energy, a mixed-fuel utility that supplies gas to seven states, has been actively promoting FGAs as part of its pathway to decarbonization. Dominion announced68 a goal in February 2020 to reach net-zero emissions by 2050 and plans to meet that goal with FGAs, saying in their statement that capturing the methane from farms will offset “any remaining methane and carbon dioxide emissions from the company’s natural gas operations.”

Dominion’s RNG strategy includes a recently announced $200 million investment69 with pork conglomerate Smithfield Foods to produce biomethane.

According to their website as of March 26, 2020, “Our goal is to meet 4 percent of our gas utility customers’ needs with RNG by 2040. Because RNG captures 25 times more greenhouse gas than it releases, that will offset our customers’ carbon footprint by 100 percent!”70

The current version of their website makes the following claim:

“[D]id you know renewable energy can also come from our nation’s farms? That’s right. Thanks to technological innovation, we can capture waste methane from hog and dairy farms and convert it into clean energy that can heat homes and power businesses.

It’s called renewable natural gas, or RNG, and it’s transforming the future of clean energy. When methane is converted into RNG, it captures 25 times more greenhouse gases from the atmosphere than are released when RNG is used by consumers. That makes RNG better than zero-carbon. It’s actually carbon-beneficial!”71

The claim that RNG captures 25 times more greenhouse gases is unsupported, and specious at best. As explained in Part 1, sources of FGAs vary in their carbon intensity. The vast majority of FGAs are not carbon negative, and most, like landfill gas, are not even carbon neutral. Even those FGAs which are sometimes considered “carbon negative,” like biomethane from manure, that consideration is based on the presumption these emissions are inevitable, in contradiction to alternative management systems which avoid emissions altogether.

No utility has thus far been forthcoming about the costs of FGAs as an alternative to building electrification, though regulators have been clear. The Minnesota Attorney General’s office called the cost of FGAs “unreasonably high”72 and noted that if a customer used that fuel exclusively, their gas bill would increase by thousands of dollars annually.

23 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10

Despite what it’s telling customers, 4. the gas industry knows the shortfalls of fossil gas alternatives

Despite these public statements, many in the role FGAs can play in “decarbonizing” the gas industry are all too aware of the the gas system, internal documents show problems with wide-scale promotion and there were and are concerns about the production of FGAs. Internal documents and costs and supply of these fuels. communications illustrate how and when the strategy of using FGAs as a defense against In a document obtained by the Climate building electrification emerged, as well as Investigations Center,75 Mark Krebs, an the cost and feasibility issues around these energy policy specialist at St. Louis-based fuels. Spire Energy, wrote to other gas utility employees, “If CA sees builders use more The American Gas Association’s Clean gas, they will probably clamp down on it; Energy Task Force developed draft policy unless it is RNG; hence all the hoopla over principles for FGAs in January 2018. RNG. In my opinion, RNG will not sustain our As stated in the document,73 the AGA industry at its present size.” “supports policies that define the term ‘renewable energy’ to include RNG on par Even members of the board of C4BES – the with other energy sources, such as energy pro-gas industry front group developed and generated from wind or solar resources.” funded by SoCalGas – expressed concerns The principles also discuss FGAs as a way about the misleading characterization of for gas to count towards Zero Net Energy FGAs. Michael Boccadoro, a lobbyist for standards for buildings. California’s dairy industry, which stands to benefit from incentives promoting the An internal set of AGA meeting notes from production of FGAs from large dairies, sat March 2018 shows the industry’s interest on the board of C4BES at its launch. He in using FGAs to “mitigate the opposition’s told The Guardian, “Dairy biogas is way too fervor.” After FGAs “piqued the interest expensive” to use in home or businesses – of opposition group” Mothers Out Front, five to 10 times more expensive than fossil a Boston-based nonprofit dedicated to gas. phasing out fossil fuels, the group reached out to National Grid, a gas utility that He also stated, “It doesn’t pencil out and operates in Massachusetts, to learn more it doesn’t make all that much sense from about the fuel. The meeting notes record an environmental standpoint. It’s a pipe the following action item in response: dream.”76 “Consider how technologies to decarbonize the pipeline can serve as a conduit to Boccadoro raised his concerns about supply environmental organizations, thereby and price in emails with the rest of the seeking to mitigate the opposition’s fervor C4BES board, which were played down by against infrastructure expansion.”74 the chairman, Matt Rahn. Boccadoro left the board shortly thereafter. ■ At the same time as the industry quickly began to outwardly express confidence in

24 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10

CONCLUSION: Benefits of building electrification should not be obscured by a fog of gas industry misinformation

The continued evolution of our energy systems and the push towards net-zero emissions require honest accounting of the pros and cons of different energy solutions. State agencies and independent analysis have overwhelmingly concluded that powering the grid with renewable energy and electrifying buildings is one of the quickest, most cost-effective ways to hit emission reduction goals.

Closer scrutiny of the production and distribution challenges of fossil gas alternatives (called “renewable natural gas” by the gas industry) are not, and are unlikely to ever be, a substitute for widespread electrification. Their role, if any, should be specialized and limited to specific industries that can’t easily electrify, specifically heavy industry and air or maritime transport. If focused on those specific functions, these fuels can play a potential role in complementing the society-wide energy transition.

The gas industry’s well-documented campaign of skewing facts, misleading consumers, and branding fossil gas alternatives as a renewable, sustainable energy source must be recognized for what it is: a PR campaign to protect the industry’s financial interests and preserve a business model that is incompatible with achieving a net-zero emissions society. The movement towards building electrification is gaining ground in the United States on a local level because it’s the most viable and affordable option for reducing emissions from the built environment. A straightforward reading of the facts and the adoption of existing technology can steer policymakers, consumers, and utilities alike towards a future of cleaner energy. ■

2525 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10

ENDNOTES 1. Energy & Climate Staff, Preliminary US Emissions Estimates for 2018, Rhodium Group (Jan. 8, 2019), https://rhg.com/ research/preliminary-us-emissions-estimates-for-2018. 2. UCLA Fielding School of Public Health, Effects of esidentialR Gas Appliances on Indoor and Outdoor Air Quality and Public Health in California (Apr. 2020), https://ucla.app.box.com/s/xyzt8jc1ixnetiv0269qe704wu0ihif7; Brady Seals and Andee Krasner, Gas Stoves: Health and Air Quality Impacts and Solutions, Rocky Mountain Institute (2020), https://rmi.org/insight/gas-stoves-pollution-health/. 3. AGA, CETF Meeting February 2018: RNG Draft Policy Principles, at 11–13 (Feb. 8, 2018) (“AGA CETF Meeting February 2018”), https://www.documentcloud.org/documents/6772341-CETF-Meeting-Febuary-2018.html. 4. AGA, AGA Spring 2018 SGC Meeting at 108 (Mar. 2018), https://www.documentcloud.org/documents/6772294-AGA- Spring-2018-SGC-Meeting.html#document/p108/a549422. 5. AGA, APGA Basecamp 2018, at 615 (2018), https://www.documentcloud.org/documents/6768592-APGA- Basecamp-2018.html#document/p615/a549439. 6. Susie Cagle, US gas utility funds ‘front’ consumer group to fight natural gas bans, The Guardian (July 26, 2019), https://www.theguardian.com/us-news/2019/jul/26/us-natural-gas-ban-socalgas-berkeley. 7. Intergovernmental Panel on Climate Change (“IPCC”), Summary for Policymakers (2018), https://www.ipcc.ch/site/ assets/uploads/sites/2/2019/05/SR15_SPM_version_report_LR.pdf. 8. D. Tong et al., Committed emissions from existing energy infrastructure jeopardize 1.5 °C climate target, 572 Nature 373 (2019), https://www.nature.com/articles/s41586-019-1364-3. 9. Lorne Stockman, Burning the Gas ‘Bridge Fuel’ Myth: Why Gas is Not Clean, Cheap, or Necessary, Oil Change International, at 6 (May, 2019), http://priceofoil.org/content/uploads/2019/05/gasBridgeMyth_web-FINAL.pdf. 10. Christopher McGlade and Paul Elkins, The geographical distribution of fossil fuels unused when limiting global warming to 2°C, 517 Nature 187, 187–190 (Jan. 7, 2015), https://www.nature.com/articles/nature14016. 11. The IPCC recently revised upward the radiative force of methane, counting its warming effect as 87 times that of

CO2 over 20 years, or 36 times CO2 over 100 years. 12. Ramon A. Alvarez et al., Assessment of Methane Emissions from the U.S. Oil and Gas Supply Chain, 361 Science 186, 186–188 (July 13, 2018), https://science.sciencemag.org/content/361/6398/186. 13. Genevieve Plant et al., Large Fugitive Methane Emissions From Urban Centers Along the U.S. East Coast, 46 Geophysical Research Letters 8500, 8500–8507 (July 15, 2019), https://agupubs.onlinelibrary.wiley.com/doi/ full/10.1029/2019GL082635. 14. Marc L. Fischer et al., An Estimate of Natural Gas Methane Emissions from California Homes, 52 Envtl. Sci. Tech. 10205, 10205–10213 (Aug. 2, 2018). 15. National Renewable Energy Laboratory, Energy Analysis: Biogas Potential in the United States (Oct. 2013), https:// www.nrel.gov/docs/fy14osti/60178.pdf. 16. Agora Energiewende and Agora Verkehrswende, The Future Cost of Electricity-Based Synthetic Fuels, at 14 (Sept. 19, 2018), https://www.agora-energiewende.de/fileadmin2/Projekte/2017/SynKost_2050/Agora_SynKost_Study_EN_ WEB.pdf. 17. Natural Resources Defense Council, A Pipe Dream or Climate Solution? The Opportunities and Limits of Biogas and Synthetic Gas to Replace Fossil Gas (June 2020), https://www.nrdc.org/sites/default/files/pipe-dream-climate- solution-bio-synthetic-gas-ib.pdf. 18. Emily Grubert, At Scale, Renewable Natural Gas Systems Could be Climate Intensive: The Influence of Methane Feedstock and Leakage Rates, Envtl. Research Letters (2020) (in press), https://doi.org/10.1088/1748-9326/ab9335. 19. Id. at 6. 20. Id. at 2. 21. Id. at 7. 22. Id. at 7. 23. AGF, Renewable Sources of Natural Gas: Supply and Emissions Reduction Assessment (Dec. 2019), https://www. gasfoundation.org/wp-content/uploads/2019/12/AGF-2019-RNG-Study-Executive-Summary-Final-12-18-2019-AS-1. pdf. The AGF Study estimates total resource potential in 2040 to be between 1,660 tBtu (low scenario) and 3,780 tBtu (high scenario). According to the U.S. Energy Information Administration (“U.S. EIA”), total US Gas Consumption in 2018 equals 30,075 tBtu. U.S. EIA, Natural Gas Explained, https://www.eia.gov/energyexplained/natural-gas/use- of-natural-gas.php (last visited May 29, 2020). FGA resource potential therefore ranges from 6% (1,660 tBtu / 30,075 tBtu) to 13% (3,780 tBtu / 30,075 tBtu). 24. U.S. EPA, Biofuels and the Environment: The Second Triennial Report to Congress, at 37 (June 29, 2018), https:// cfpub.epa.gov/si/si_public_record_report.cfm?Lab=IO&dirEntryId=341491 25. U.S. EIA, Henry Hub Natural Gas Spot Price, https://www.eia.gov/dnav/ng/hist/rngwhhdD.htm (last visited May 28, 2020).

2626 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10 26. AGF, Renewable Sources of Natural Gas: Supply and Emissions Reduction Assessment, at 51 (Dec. 2019), https:// gasfoundation.org/wp-content/uploads/2019/12/AGF-2019-RNG-Study-Full-Report-FINAL-12-18-19.pdf. 27. See, e.g., California Energy Commission, The Challenge of Retail Gas in California’s Low-Carbon Future (Apr. 2020), https://ww2.energy.ca.gov/2019publications/CEC-500-2019-055/CEC-500-2019-055-F.pdf. 28. Id. at 4. 29. Id. at 24. 30. Id. at 4. 31. National Renewable Energy Laboratory, California Power-to-Gas and Power-to-Hydrogen Near-Term Business Case Evaluation, at 37 (Dec. 2016), https://www.nrel.gov/docs/fy17osti/67384.pdf. 32. Agora Energiewende and Agora Verkehrswende, The Future Cost of Electricity-Based Synthetic Fuels, at 11 (Sept. 19, 2018), https://www.agora-energiewende.de/fileadmin2/Projekte/2017/SynKost_2050/Agora_SynKost_Study_EN_ WEB.pdf. 33. Id. at 14. 34. Id. 35. Evolved Energy Research, New Jersey 2019 IEP Technical Appendix (Nov. 29, 2019), https://nj.gov/emp/pdf/New_ Jersey_2019_IEP_Technical_Appendix.pdf. 36. California Energy Commission, Air Quality Implications of Using Biogas to Replace Natural Gas in California (May 2020), https://ww2.energy.ca.gov/2020publications/CEC-500-2020-034/CEC-500-2020-034.pdf. 37. UCLA Fielding School of Public Health, Effects of esidentialR Gas Appliances on Indoor and Outdoor Air Quality and Public Health in California, at 18 (Apr. 2020), https://ucla.app.box.com/s/xyzt8jc1ixnetiv0269qe704wu0ihif7. 38. AGA, Gas Industry Revenues From Sales by Class of Service 1996–2018, https://www.aga.org/ contentassets/95bfd59fd72048baa030f00d08094592/table7-1.pdf (last visited May 28, 2020). 39. AGA, Natural Gas, Our Clean Energy Future: 2020 Playbook, http://playbook.aga.org (last visited May 28, 2020). 40. AGA, Get the Facts: Pipeline Safety (2019), https://www.aga.org/ contentassets/7e9157649d70496391b38baff62506ed/pipeline-safety_final.pdf. 41. Adam Barth et al., Are US gas utilities nearing the end of their golden age?, McKinsey & Co. (Sept. 20, 2018), https:// www.mckinsey.com/industries/electric-power-and-natural-gas/our-insights/are-us-gas-utilities-nearing-the-end-of- their-golden-age. 42. Sempra Energy, SoCalGas and SDG&E, Form 10-K Annual Report at 45 (Feb. 27, 2020), https://investor.sempra.com/ static-files/68af0350-d99c-412c-af4f-aa8e6c8e2606. 43. Gerson Freitas Jr. and Vanessa Dezem, Wall Street Is Falling Out of Love With a Once-Coveted Fossil Fuel, Bloomberg (Mar. 3, 2020), https://www.bloomberg.com/news/articles/2020-03-03/wall-street-is-falling-out-of-love- with-a-once-coveted-fossil-fuel. 44. Tom DiChristopher, Utility CEOs embrace role as natural gas defenders on earnings calls, S&P Global Market Intelligence (Mar. 6, 2020), https://www.spglobal.com/marketintelligence/en/news-insights/latest-news-headlines/ utility-ceos-embrace-role-as-natural-gas-defenders-on-earnings-calls-57446738. 45. Jon Chesto, Brookline’s ban on natural gas connections spurs other municipalities to consider the idea, Boston Globe (Dec. 11, 2019), https://www.bostonglobe.com/business/2019/12/11/after-brookline-other-cities-and-towns-start- consider-their-own-natural-gas-bans/BRKynpIlfOs4miQlDKIkIK. 46. Kavya Balaraman, California launches rulemaking to manage transition away from natural gas, Utility Dive (Jan. 17, 2020), https://www.utilitydive.com/news/cpuc-launches-rulemaking-transition-natural-gas/570653/. 47. New Jersey Board of Public Utilities et al., 2019 New Jersey Energy Master Plan: Pathway to 2050, https://nj.gov/ emp/docs/pdf/2020_NJBPU_EMP.pdf (last visited May 28, 2020). 48. Tom DiChristopher, In bid to cut gas use, pipe investment, NY regulator to overhaul energy policy, S&P Global Market Intelligence (Mar. 20, 2020), https://www.spglobal.com/marketintelligence/en/news-insights/latest-news- headlines/in-bid-to-cut-gas-use-pipe-investment-ny-regulator-to-overhaul-energy-policy-57696460. 49. Tom DiChristopher, AGA takes steps to counter gas bans, state opposition to pipelines, S&P Global Market Intelligence (Jan. 17, 2020), https://www.spglobal.com/marketintelligence/en/news-insights/latest-news- headlines/56763558. 50. Michael Hiltzik, Column: SoCal Gas accused of setting up an ‘astro-turf’ group to plead its case to regulators, Los Angeles Times (Aug. 8, 2019), https://www.latimes.com/business/story/2019-08-07/socal-gas-astroturf-group- allegations; Michael Hiltzik, Column: An Alleged SoCalGas front group withdraws from a PUC proceeding — but questions remain, Los Angeles Times (Aug. 21, 2019), https://www.latimes.com/business/story/2019-08-21/ californians-for-balanced-energy-solutions-socal-gas-puc. 51. California Public Utility Commission (“CPUC”), Rulemaking (“R.”) 19-01-011, Response of the Public Advocates Office to SoCalGas’ Motion to Strike Sierra Club’s Reply to Responses to Motion to Deny Party Status to Californians for Balanced Energy Solutions or, in the Alternative to Grant Motion to Compel Discovery (July 5, 2019), https:// earthjustice.org/sites/default/files/files/PAO-Response-to-SoCalGas-Motion-to-Strike.pdf. 52. Hal Bernton and Daniel Beekman, Natural gas industry’s $1 million PR campaign sets up fight over Northwest’s energy future, Seattle Times (Dec. 22, 2019), https://www.seattletimes.com/seattle-news/natural-gas-industrys-1- million-pr-campaign-sets-up-fight-over-northwests-energy-future/. 53. Stewart Yerton, How The Gas Company Plans To Fight A Bill Banning Gas Water Heaters, Honolulu Civil Beat (Dec. 9, 2019), https://www.civilbeat.org/2019/12/how-the-gas-company-plans-to-fight-a-bill-banning-gas-water-heaters/. 54. Chris D’Angelo, The Gas Industry’s Bid To Kill A Town’s Fossil Fuel Ban, The Huffington Post (Dec. 8, 2019), https:// www.huffpost.com/entry/massachusetts-natural-gas-ban_n_5de93ae2e4b0913e6f8ce07d.

2727 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10 55. Itai Vardi, A New Massachusetts ‘Sustainable Energy’ Coalition Is Really A Front For Gas Interests, The Huffington Post (Feb. 22, 2018), https://www.huffpost.com/entry/natural-gas-coalition-massachusetts_n_5a8f2563e4b0528232 aa904e. 56. Elizabeth Whitman, Arizona Bill That Would Ban Local Gas Bans Lands on Governor Ducey’s Desk, Phoenix New Times (Feb. 19, 2020), https://www.phoenixnewtimes.com/news/arizona-natural-gas-preemption-southwest-gas- ducey-utilities-11445592. 57. Tom DiChristopher, Gas Ban Monitor: California clears coronavirus hurdles; Mass. strategy splinters, S&P Global Market Intelligence (Apr. 6, 2020), https://www.spglobal.com/marketintelligence/en/news-insights/latest-news- headlines/gas-ban-monitor-california-clears-coronavirus-hurdles-mass-strategy-splinters-57926053. 58. House Bill (“HB”) 2703 (2020), http://www.kslegislature.org/li/b2019_20/measures/hb2703. 59. HF 3303 (2020), https://www.revisor.mn.gov/bills/text.php?number=HF3033&version=0&session=ls91&session_ year=2020&session_number=0. 60. Senate Bill 2685 (2020), http://billstatus.ls.state.ms.us/2020/pdf/history/SB/SB2685.xml. 61. HB 2697 (2020), https://house.mo.gov/Bill.aspx?bill=HB2697&year=2020&code=R. 62. HB 3619 (2020), http://webserver1.lsb.state.ok.us/cf_pdf/2019-20%20COMMITTEE%20AMENDMENTS/House/ HB3619%20FULLPCS1%20TERRY%20ODONNELL-AMM.PDF. 63. Office of City Manager, Climate Action Plan Update (Dec. 6, 2018), https://www.cityofberkeley.info/Clerk/City_ Council/2018/12_Dec/Documents/2018-12-06_WS_Item_01_Climate_Action_Plan_Update_pdf.aspx. 64. Town of Brookline, Massachusetts Greenhouse Gas Inventory Overview (May 21, 2010), https://www.brooklinema. gov/ArchiveCenter/ViewFile/Item/628. 65. Department of Energy & Environment, Greenhouse Gas Inventories, https://doee.dc.gov/service/greenhouse-gas- inventories (last visited May 28, 2020). 66. SoCalGas, SoCalGas Announces Vision to be Cleanest Natural Gas Utility in North America, PR Newswire (Mar. 6, 2019), https://www.prnewswire.com/news-releases/socalgas-announces-vision-to-be-cleanest-natural-gas-utility-in- north-america-300807922.html. 67. CPUC, R.19-01-011, Sierra Club’s Mot. to Deny Party Status to [C4BES] or, in the Alternative, to Grant Mot. to Compel Disc., Attach. D (May 14, 2019), https://docs.cpuc.ca.gov/PublishedDocs/Efile/G000/M292/K932/292932611.PDF. 68. Dominion Energy, Dominion Energy Sets New Goal of Net Zero Emissions by 2050 (Feb. 11, 2020), https://news. dominionenergy.com/2020-02-11-Dominion-Energy-Sets-New-Goal-of-Net-Zero-Emissions-by-2050. 69. Catherine Morehouse, Dominion extends poop power push with $200M Vanguard Renewables partnership, Utility Dive (Dec. 13, 2019), https://www.utilitydive.com/news/dominion-extends-poop-power-200m-vanguard-renewables- RNG-farms-natural-gas/569004/. 70. Dominion Energy, Renewable Natural Gas (Mar. 26, 2020), https://web.archive.org/web/20200326001324/https:// www.dominionenergy.com/company/renewable-natural-gas. 71. Dominion Energy, Renewable Natural Gas: Turning Waste into Clean Energy, https://www.dominionenergy.com/ company/renewable-natural-gas (last visited May 28, 2020). 72. Frank Jossi, Minnesota utility wants to offer customers renewable natural gas option, Energy News Network (Jan. 30, 2019), https://energynews.us/2019/01/30/midwest/minnesota-utility-wants-to-offer-customers-renewable-natural- gas-option/. 73. AGA CETF Meeting February 2018 at 12. 74. Climate Investigations Center, Renewable Natural Gas (Feb. 9, 2020), https://climateinvestigations.org/renewable- natural-gas/. 75. Id. 76. Susie Cagle, US gas utility funds ‘front’ consumer group to fight natural gas bans, The Guardian (July 26, 2019), https://www.theguardian.com/us-news/2019/jul/26/us-natural-gas-ban-socalgas-berkeley.

i. Sheraz Gill et al., Air Pollution Control Officer’s Revision of the Dairy VOC Emission Factors, SJVAPCD, at 9 (Feb. 2012), https://www.valleyair.org/busind/pto/emission_factors/2012-Final-Dairy-EE-Report/FinalDairyEFReport(2-23-12).pdf. ii. Eli Moore et al., The Human Costs of Nitrate-contaminated Drinking Water in the San Joaquin Valley, Pacific Institute, at 7 (Mar. 2011), https://pacinst.org/wp-content/uploads/2011/03/nitrate_contamination3.pdf. iii. J.P. Cativiela et al., Summary Representative Monitoring Report (Revised*), CVDRMP, at 6 (Apr. 19, 2019), https://www. waterboards.ca.gov/centralvalley/water_issues/confined_animal_facilities/groundwater_monitoring/srmr_20190419.pdf. iv. U.S. EPA, Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2017 – Agriculture, at 5–9, (2019) https:// www.epa. v. gov/sites/production/files/2019-04/documents/us-ghg-inventory-2019-chapter-5-agriculture.pdf. California Climate and Agriculture Network, Diversified Strategies for Reducing Methane Emissions from Dairy Operations (Oct. 2015), http://calclimateag.org/wp-content/uploads/2015/11/Diversified-Strategies-for-Methane-in- vi. Dairies-Oct.-2015.pdf. Leadership Counsel for Justice and Accountability, A Working Paper on the CDFA Dairy Digester Research and Development Program (Apr. 2019), https://leadershipcounsel.org/wp-content/uploads/2019/04/A-Working-Paper-on- GGRF-Dairy-Digester-Program.pdf.

2828 Earthjustice & Sierra Club | Rhetoric vs. Reality Exhibit EG-10

29

Exhibit EG – 11

Exhibit EG-11

Date of Request: October 9, 2020 Request No. PACE_AGREE-093 Due Date: October 19, 2020 NMPC Req. No. NM-1155

NIAGARA MOHAWK POWER CORPORATION d/b/a NATIONAL GRID Case Nos. 20-E-0380 and 20-G-0381 Electric and Gas Rates

Request for Information

FROM: Pace Energy and Climate Center; Alliance for a Green Economy, Marianna Lo

TO: National Grid, Future of Heat Panel

SUBJECT: Future of Heat - Hydrogen

Request:

The following information request pertains to the gas filings for 20-G-0381.

93. In response to PACE_AGREE-022 and PACE_AGREE-023, the Company writes that the “Company’s objective is to exclusively utilize electrolyzers provided with renewable electricity for the multi-use hydrogen demonstration and future multi-use hydrogen facilities as well as future Power to Gas (“P2G”) facilities.”

a. How many megawatts from zero-carbon sources or renewable electricity (such as wind or photovoltaic technologies) must the electrolyzer capacity have access to in order to produce 100% renewable hydrogen? b. How much energy loss does the Company and Standard Hydrogen Corporation of Ithaca, NY expect or anticipate when it engages in the electrolysis process of hydrogen? c. How much conversion loss does the Company and Standard Hydrogen Corporation of Ithaca, NY expect or anticipate when it engages in the electrolysis process of hydrogen? d. How much energy loss does the Company aintrend Standard Hydrogen Corporation of Ithaca, NY expect or anticipate when it engages in the methanation process of hydrogen? e. How much conversion loss does the Company and Standard Hydrogen Corporation of Ithaca, NY expect or anticipate when it engages in the methanation process of hydrogen?

Response:

a. Niagara Mohawk’s gas delivery system has delivered 1.0 MMDTH on a peak winter day for all uses by distribution customers which is about 42,000 MDTH per hour and is typically lower. The hydrogen equivalent is 310,000 kg per hour

Form 103 Exhibit EG-11

of green hydrogen, which, using the electrolyze efficiency from the response to part b. below, would require 17,200 MW of electrolyzers. When the US Department of Energy (“DOE”) development target for electrolyzers of 43 kWh per kg1 is achieved, the total electric capacity requirement would ultimately be 13,300 MW at current natural gas usage, which is less than New York’s “Upstate Summer Installed Capacity” 2 for electric generation. One of the objectives of the Climate Leadership and Community Protection Act is a “100% Carbon-free Electricity by 2040.” When this is achieved, hydrogen can be as large a part of the portfolio of practical options for heat decarbonization for use by any of customers as needed.

b. The total conversion losses in the electrolysis process are reflected by the energy conversion efficiency: energy output (here, as hydrogen generated) divided by the energy input (here, as electricity input). Hydrogen has an energy content of 39 kWh per kilogram.

The final vendor for the electrolysis equipment to be used in the project has yet to be selected. Standard Hydrogen Corporation (“SHC”) has an internal technology roadmap that they are following, which today requires using certified and, at times, UL-listed components, and replacing them with higher performing components as they become available. Initially, SHC plans to use a polymer electrolyte membrane electrolyzer for its environmental and operational benefits. SHC has received vendor quotes for the initial electrolyzer that cite an energy requirement of between 55.6 – 59 kWh per each kilogram of hydrogen generated. Therefore, the initial energy conversion efficiency expected is between 70 percent (39/55.6) and 66 percent (39/59). SHC’s roadmap is consistent with US DOE guidelines, which reflects technology improvements that will yield electrolyzers with an energy requirement of 43 kWh/kg H2, or 91% energy conversion efficiency, before 2025.

It is also important to note that efficiency should not be compared directly with the efficiency of many incumbent energy processes, such as those using combustion. For example, in incumbent processes, the conversion efficiency reflects the maximum amount of useful energy that can be extracted from the fuel resource. In the SHC process, the conversion efficiency reflects the amount of renewable electricity harnessed and consistently converted into stored hydrogen, which otherwise may have been curtailed.

c. The total conversion losses for each process is not known in advance of the design and will be dependent on the energy losses described in the responses to

1 Please see table 1 https://www.nrel.gov/docs/fy19osti/73353.pdf. 2 Please see Figure 14: Generating Capacity in New York State by Fuel Source — Statewide, Upstate New York and Downstate New York: 2018, Power Trends 2018. NY ISO, https://www.nyiso.com/documents/20142/2223020/2018-Power-Trends.pdf/4cd3a2a6-838a-bb54-f631- 8982a7bdfa7a.

Form 103 Exhibit EG-11

part b. above and part d. below and the ultimate design of systems and materials. The development of the facility will be conducted through a process of Value Engineering, which is a systematic method to improve the “value” of goods or products and services by using an examination of function. Value, as defined, is the ratio of function to cost. Therefore, value can be increased by either improving the function or reducing the cost. In this project, environmental factor and functions will inherently have the highest value.

d. The Company has not made a decision to utilize methanation for the services provided by the Energy Transfer station that displace natural gas and will consider doing so based on a comparison of the cost and efficiencies with any gas system upgrades costs that the location chosen might require. There are multiple methods to combine hydrogen and waste CO2 to make a synthetic methane. The simplest and most common method is highly exothermic, and it will be necessary to recover and use the heat produced. A low-temperature method using a nickel catalyst appears to be highly efficient and may be the best choice.

e. Please see the response to part c. above.

Name of Respondent: Date of Reply: Christopher A. Cavanagh, PE October 19, 2020

Form 103

Exhibit EG – 12

Exhibit EG-12

Date of Request: October 9, 2020 Request No. PACE_AGREE-094 Due Date: October 19, 2020 NMPC Req. No. NM-1156

NIAGARA MOHAWK POWER CORPORATION d/b/a NATIONAL GRID Case Nos. 20-E-0380 and 20-G-0381 Electric and Gas Rates

Request for Information

FROM: Pace Energy and Climate Center; Alliance for a Green Economy, Marianna Lo

TO: National Grid

SUBJECT: Future of Heat - Hydrogen

Request:

The following information request pertains to the gas filings for 20-G-0381.

94. PACE_AGREE-020 Response supplies a general answer to the question of how much hydrogen might be able to be injected into gas networks across the United States. Please explain how much hydrogen can be injected into the Company’s gas network. Specifically, please provide a figure for the service area covered by this case.

Response:

At present, there is no specific maximum blend ratio for hydrogen that is allowed to be injected into the present or future gas distribution system. Because of this fact, the Company does not have an analysis of how much hydrogen can be injected into its gas network. The evaluation of pipeline systems to establish such a guideline is one purpose of the NYSERDA project with the Institute for Gas Innovation and Technology referenced in the response to PACE_AGREE-020.

The ultimate potential is 100 percent hydrogen injected into new pipeline systems, which is similar to the 300 miles of hydrogen pipelines and 2.5 billion cubic feet of storage operated today by Linde1 in Texas and Louisiana.

Name of Respondent: Date of Reply: Christopher A. Cavanagh, PE October 19, 2020

1 Praxair /Linde Hydrogen Pipeline Infrastructure, Linde - NREL Blending Conference April 2020

Form 103

Exhibit EG – 13

Exhibit EG-13

Date of Request: October 9, 2020 Request No. PACE_AGREE-095 Due Date: October 19, 2020 NMPC Req. No. NM-1157

NIAGARA MOHAWK POWER CORPORATION d/b/a NATIONAL GRID Case Nos. 20-E-0380 and 20-G-0381 Electric and Gas Rates

Request for Information

FROM: Pace Energy and Climate Center; Alliance for a Green Economy, Marianna Lo

TO: National Grid

SUBJECT: Future of Heat - Hydrogen

Request:

The following information request pertains to the gas filings for 20-G-0381.

95. In PACE_AGREE-021 Response, the Company states that “locations that require significant modifications to the gas system to limit corrosion or embrittlement or would incur significant upgrade costs will not be considered” for inclusion into the Multi-use Hydrogen Production and Utilization facility project. Please provide a map and/or a detailed description of the locations in the service area that would be excluded under the aforementioned criteria.

Response:

The Company has not developed an exhaustive set of criteria for project site selection and has not produced a map of areas where hydrogen blending may require additional system upgrades based on the aforementioned criteria.

The Company, however, is of the opinion that areas having higher concentration of leak-prone pipe and/or aging infrastructure are not suitable to transport hydrogen-blended natural gas. Whereas, areas with higher concentration of newer plastic pipe have a higher probability of being chosen for this project.

For example, the results of research at the Gas Technology Institute indicated that “Overall the 5% hydrogen-blended gas did not appear to have significant impact on the integrity of non- metallic materials”. In a typical year, miles of leak-prone pipe are replaced, much of that with polyethylene pipe (“PE”). These areas are geographically spread across the service area. The Company, like all gas utilities, provides annual reports to the U.S. Department of Transportation, Pipeline and Hazardous Materials Safety Administration, listing the length and type of piping in use. In the case of Niagara Mohawk’s gas service area in upstate New York, there are 4,832

Form 103 Exhibit EG-13

miles of PE pipe1 in service. If PE or new steel pipe or any other type listed is determined to be the best choice, there will be numerous areas to choose from across the service area, and these will be the first systems considered for hydrogen blending.

Name of Respondent: Date of Reply: Christopher A. Cavanagh, PE October 19, 2020

1 Please see https://www.phmsa.dot.gov/data-and-statistics/pipeline/gas-distribution-gas-gathering-gas-transmission-hazardous- liquids

Form 103

Exhibit EG – 14

Exhibit EG-14

Date of Request: September 21, 2020 Request No. PACE_AGREE-021 Due Date: October 1, 2020 NMPC Req. No. NM-864

NIAGARA MOHAWK POWER CORPORATION d/b/a NATIONAL GRID Case Nos. 20-E-0380 and 20-G-0381 Electric and Gas Rates

Request for Information

FROM: Pace Energy and Climate Center; Alliance for a Green Economy, Priya Pookkulam

TO: National Grid, Future of Heat

SUBJECT: Future of Heat - Hydrogen

Request:

Note: The following information request pertain to the gas filings for 20-G-0381.

21. Please explain whether the gas network in the service area would need to be upgraded in order to prevent corrosion and accommodate hydrogen from the Company’s Multi-use Hydrogen Production and Utilization Facility. If so, please estimate the costs of these upgrades.

Response:

The site selection criteria for the demonstration of the Multi-use Hydrogen Production and Utilization facility will include the impact of introducing hydrogen blends in the existing local gas system in accordance with all applicable industry standards and Company policies. Therefore, locations that require significant modifications to the gas system to limit corrosion or embrittlement or would incur significant upgrade costs will not be considered.

Name of Respondent: Date of Reply: Christopher A. Cavanagh, PE September 29, 2020

Form 103

Exhibit EG – 15

Exhibit EG-15

Date of Request: November 5, 2020 Request No. PACE_AGREE-171 Due Date: November 16, 2020 NMPC Req. No. NM-1602

NIAGARA MOHAWK POWER CORPORATION d/b/a NATIONAL GRID Case Nos. 20-E-0380 and 20-G-0381 Electric and Gas Rates

Request for Information

FROM: Pace Energy and Climate Center; Alliance for a Green Economy

TO: National Grid

SUBJECT: Future of Heat

Request:

The following information request pertains to the gas filings for 20-G-0381:

171. In SC-010 Response, the Company provides the low and high resource potentials for anaerobic digestion and thermal gasification from various feedstocks by 2040. Please provide:

a. The models or methodologies, as applicable, the Company used to arrive at these estimates for each of the feedstocks listed in SC-10 Response for both the low and high scenarios.

b. In the Company’s response to subpart a. above, for landfills specifically, please be sure to include the model the Company used in estimating the emission rates for landfill gas to arrive at the RNG potential listed in SC-010.

c. In the Company’s response to subpart a. above, for animals specifically, please be sure to include the animal population assessed and other relevant parameters such as the total wet manure produced per animal, assumed moisture content, and energy content of dried manure.

d. For each feedstock listed in SC-10, please include any and all assumptions, sources of data, and any other relevant information used by the Company in reaching the high and low potentials for each.

e. If the Company received this information from a third party, please provide the source of the estimates provided in SC-010.

Response: a. - e. The figures in the table in the Company’s response to SC-010 were taken from Appendix A of the American Gas Foundation December 2019 study titled Renewable Sources of

Form 103 Exhibit EG-15

Natural Gas: Supply and Emissions Reduction Assessment, a copy of which is provided as Attachment 1.

Name of Respondent: Date of Reply: Melissa Mauro November 13, 2020

Form 103 Niagara Mohawk Power Corporation d/b/a National Grid Exhibit EG-15 Cases 20-E-0380 and 20-G-0381 PACE_AGREE-171 Attachment 1 Page of 1 of 80

December 2019

RENEWABLE SOURCES OF NATURAL GAS: SUPPLY AND EMISSIONS REDUCTION ASSESSMENT

An American Gas Foundation Study Prepared by: Niagara Mohawk Power Corporation d/b/a National Grid Exhibit EG-15 Cases 20-E-0380 and 20-G-0381 PACE_AGREE-171 Attachment 1 Page of 2 of 80

Legal Notice This report was prepared for the American Gas Foundation, with the assistance of its contractors, to be a source of independent analysis. Neither the American Gas Foundation, its contractors, nor any person acting on their behalf: § Makes any warranty or representation, express or implied with respect to the accuracy, completeness, or usefulness of the information contained in this report, or that the use of any information, apparatus, method, or process disclosed in this report may not infringe privately-owned rights, § Assumes any liability, with respect to the use of, damages resulting from the use of, any information, method, or process disclosed in this report, § Recommends or endorses any of the conclusions, methods or processes analyzed herein. References to work practices, products or vendors do not imply an opinion or endorsement of the American Gas Foundation or its contractors. Use of this publication is voluntary and should be taken after an independent review of the applicable facts and circumstances. Copyright © American Gas Foundation, 2019.

American Gas Foundation (AGF) Founded in 1989, the American Gas Foundation (AGF) is a 501(c)(3) organization focused on being an independent source of information research and programs on energy and environmental issues that affect public policy, with a particular emphasis on natural gas. When it comes to issues that impact public policy on energy, the AGF is committed to making sure the right questions are being asked and answered. With oversight from its board of trustees, the foundation funds independent, critical research that can be used by policy experts, government officials, the media and others to help formulate fact-based energy policies that will serve this country well in the future.

ICF ICF (NASDAQ:ICFI) is a global consulting services company with over 7,000 full- and part-time employees, but we are not your typical consultants. At ICF, business analysts and policy specialists work together with digital strategists, data scientists and creatives. We combine unmatched industry expertise with cutting-edge engagement capabilities to help organizations solve their most complex challenges. Since 1969, public and private sector clients have worked with ICF to navigate change and shape the future. Learn more at icf.com. Niagara Mohawk Power Corporation d/b/a National Grid Exhibit EG-15 Cases 20-E-0380 and 20-G-0381 PACE_AGREE-171 Attachment 1 Page of 3 of 80 Renewable Sources of Natural Gas: Supply and Emissions Reduction Assessment

Table of Contents Executive Summary ...... 1 Introduction ...... 6 RNG Production Technologies ...... 6 RNG Feedstocks ...... 7 Resource Assessment Scenarios ...... 7 Review of Previous Work ...... 7 Regional RNG Resource Assessment ...... 9 Summary of RNG Potential ...... 10 RNG: Anaerobic Digestion of Biogenic or Renewable Resources ...... 16 RNG: Thermal Gasification of Biogenic or Renewable Resources ...... 29 Renewable gas from MSW ...... 36 RNG from P2G/Methanation ...... 38 Greenhouse Gas Emissions of RNG ...... 44 GHG Accounting Framework and Methodology ...... 44 GHG Emissions from RNG Resource Assessment ...... 46 RNG Cost Assessment ...... 50 RNG from Anaerobic Digestion ...... 52 RNG from Thermal Gasification ...... 56 RNG from Power-to-Gas / Methanation ...... 57 Combined Supply Curves ...... 60 GHG Cost-Effectiveness ...... 61 Key Findings ...... 62 Appendix A—Resource Assessment by State ...... 64 Appendix B—GHG Emissions using Lifecycle Analysis Approach ...... 70

i Niagara Mohawk Power Corporation d/b/a National Grid Exhibit EG-15 Cases 20-E-0380 and 20-G-0381 PACE_AGREE-171 Attachment 1 Page of 4 of 80 Renewable Sources of Natural Gas: Supply and Emissions Reduction Assessment

List of Tables Table 1. Summary of Feedstocks Considered for RNG Production ...... 7 Table 2. Summary of RNG Potential from 2011 AGF Study in units of tBtu/year ...... 8 Table 3. Summary of Feedstock Utilization in the Low and High Resource Potential Scenarios ...... 11 Table 4. Low Resource Potential for RNG in 2040, tBtu/y ...... 13 Table 5. High Resource Potential for RNG in 2040, tBtu/y ...... 14 Table 6. Technical Resource Potential for RNG in 2040, tBtu/y ...... 15 Table 7. Landfill Gas Constituents and Corresponding Upgrading Technologies ...... 16 Table 8. Number of Candidate Landfills by Census Region ...... 17 Table 9. Landfill to Energy Projects and Candidate Landfills by Census Region ...... 17 Table 10. Annual RNG Potential from Landfills in 2040, tBtu/y ...... 19 Table 11. Key Parameters to Determine Animal Manure Resource for RNG Production ...... 20 Table 12. Summary of AgStar Projects at Farms using AD Systems, by Census Region ...... 21 Table 13. Annual RNG Production Potential from Animal Manure in 2040, tBtu/y ...... 22 Table 14. Number of WRRFs by Census Region ...... 23 Table 15. Total Flow (in MGD) of WRRFs by Census Regions ...... 24 Table 16. WRRFs with Anaerobic Digesters, by Census Regions ...... 24 Table 17. Annual RNG Production Potential from WRRFs in 2040, tBtu/y ...... 26 Table 18. Annual RNG Production Potential from Food Waste in 2040, tBtu/y ...... 28 Table 19. Heating Values for Agricultural Residues ...... 30 Table 20. Annual RNG Production Potential from Agricultural Residues in 2040, tBtu/y ...... 31 Table 21. Heating Values for Forestry and Forest Product Residues ...... 32 Table 22. Annual RNG Production Potential from Forestry and Forest Product Residues, tBtu/y ...... 34 Table 23. Heating Values for Energy Crops ...... 34 Table 24. Annual RNG Production Potential from Energy Crops, tBtu/y ...... 35 Table 25. Heating Values for MSW Components ...... 36 Table 26. Annual RNG Production Potential from MSW, tBtu/y ...... 37 Table 27. Renewable Share of Electricity Generation in RPS-Compliant Run using IPM ...... 41 Table 28. Annual H2 and RNG Production (in tBtu /y) from P2G using Dedicated Renewable Electricity Generation, 2025-2040 ...... 43 Table 29. GHG Emission Reductions (in MMT) for RNG in the Low Resource Potential Case ...... 48 Table 30. GHG Emission Reductions (in MMT) for RNG in the High Resource Potential Case ...... 49 Table 31. Illustrative Cost Assumptions Developed to Estimate RNG Production Costs in 2040 ...... 50 Table 32. Cost Consideration in Levelized Cost of Gas Analysis for RNG from Landfill Gas ...... 52 Table 33. Cost Consideration in Levelized Cost of Gas Analysis for RNG from Animal Manure ...... 54 Table 34. Cost Consideration in Levelized Cost of Gas Analysis for RNG from WRRFs ...... 54 Table 35. Cost Consideration in Levelized Cost of Gas Analysis for RNG from Food Waste ...... 55 Table 36. Average Tipping Fee by Region ...... 56 Table 37. Cost Consideration in Levelized Cost of Gas Analysis for RNG from Thermal Gasification ...... 57 Table 38. Low Resource Potential for RNG in 2040, tBtu/y, by State ...... 64 Table 39. High Resource Potential for RNG in 2040, tBtu/y, by State ...... 66 Table 40. Technical Resource Potential for RNG in 2040, tBtu/y, by State ...... 68 Table 41. Range of Lifecycle GHG Emission Factors for RNG from Different Feedstocks and Regions (in units of g/MJ) ...... 72 Table 42. GHG Emission Reductions (in MMT) for RNG in the Low Resource Case ...... 73 Table 43. GHG Emission Reductions (in MMT) for RNG in the High Resource Case ...... 74 ii

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List of Figures Figure 1. Estimated Annual RNG Production, Low Resource Potential Scenario, tBtu/y ...... 3 Figure 2. Estimated Annual RNG Production, High Resource Potential Scenario, tBtu/y ...... 3 Figure 3. Average Annual CO2 Emissions (in MMT) from Natural Gas Consumption, 2009-2018 ...... 4 Figure 4. U.S. Census Regions ...... 9 Figure 5. Estimated Annual RNG Production, Low Resource Potential Scenario, tBtu/y ...... 10 Figure 6. Estimated Annual RNG Production, High Resource Potential Scenario, tBtu/y ...... 11 Figure 7. RNG Technical Resource Potential vs Average Domestic Natural Gas Consumption in Different End Uses, 2009-2018 (in tBtu/y) ...... 12 Figure 8. RNG Production Potential from Landfill Gas, Low Resource Potential Scenario, in tBtu/y ...... 18 Figure 9. RNG Production Potential from Landfill Gas, High Resource Potential Scenario, in tBtu/y ...... 19 Figure 10. RNG Production Potential from Animal Manure, Low Resource Potential Scenario, in tBtu/y ...... 22 Figure 11. RNG Production Potential from Animal Manure, High Resource Potential Scenario, in tBtu/y ...... 22 Figure 12. RNG Production Potential from WRRFs, Low Resource Potential Scenario, in tBtu/y ...... 26 Figure 13. RNG Production Potential from WRRFs, High Resource Potential Scenario, in tBtu/y ...... 26 Figure 14. RNG Production Potential from Food Waste, Low Resource Potential Scenario, in tBtu/y ...... 28 Figure 15. RNG Production Potential from Food Waste, High Resource Potential Scenario, in tBtu/y ...... 28 Figure 16. RNG Production Potential from Agricultural Residue, Low Resource Potential Scenario, in tBtu/y 31 Figure 17. RNG Production Potential from Agricultural Residue, High Resource Potential Scenario, in tBtu/y ...... 31 Figure 18. RNG Production Potential from Forestry and Forest Product Residues, Low Resource Potential Scenario, in tBtu/y ...... 33 Figure 19. RNG Production Potential from Forestry and Forest Product Residues, High Resource Potential Scenario, in tBtu/y ...... 33 Figure 20. RNG Production Potential from Energy Crops, Low Resource Potential Scenario, in tBtu/y ...... 35 Figure 21. RNG Production Potential from Energy Crops, High Resource Potential Scenario, in tBtu/y ...... 35 Figure 22. RNG Production Potential from Non-Biogenic MSW, Low Resource Potential Scenario, in tBtu/y . 37 Figure 23. RNG Production Potential from Non-Biogenic MSW, High Resource Potential Scenario, in tBtu/y 37 Figure 24. Supply-Cost Curve for Dedicated Renewable Electricity for P2G Systems, 2025-2040 ...... 41 Figure 25. Assumed Efficiency for Electrolysis and Methanation, 2020-2040 ...... 42 Figure 26. Scopes for categorizing emissions under the GHG Protocol (GHG Protocol 2019)...... 45 Figure 27. Overview of GHG Accounting Frameworks for RNG ...... 46 Figure 28. Average Annual Carbon Dioxide Emissions (in MMT) from Natural Gas Consumption in the U.S. 2009-2018 ...... 47 Figure 29. Supply-Cost Curve for RNG from Landfill Gas ($/MMBtu vs tBtu) ...... 53 Figure 30. Installed Capacity Cost of Electrolyzers, $/kW, 2020-2040 ...... 58 Figure 31. Installed Capacity Cost of Methanator, $/kW, 2020-2040 ...... 59 Figure 32. Assumed Efficiency for Electrolysis and Methanation, 2020-2040 ...... 59 Figure 33. Estimated RNG costs from P2G / Methanation ($/MMBtu) as a function of installed capacity of P2G systems ...... 60 Figure 34. Combined RNG Supply-Cost Curve, less than $20/MMBtu in 2040 ...... 60 Figure 35. Summary of carbon intensities for transportation fuels across life-cycle stages (ANL 2019)...... 70 Figure 36. Life-cycle carbon intensity for RNG grouped by different GHG Protocol scopes using GREET results...... 71

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Executive Summary Renewable natural gas (RNG) is derived from biomass or other renewable resources, and is a pipeline-quality gas that is fully interchangeable with conventional natural gas. The American Gas Association (AGA) uses the following definition for RNG:

Pipeline compatible gaseous fuel derived from biogenic or other renewable sources that has lower lifecycle carbon dioxide equivalent (CO2-eq) emissions than geological natural gas. ICF conducted an assessment to outline the potential for RNG to contribute meaningfully and cost- effectively to greenhouse gas (GHG) emission reduction initiatives across the country. The report serves as an update and expansion to a 2011 report published by the American Gas Foundation (AGF) entitled The Potential for Renewable Gas: Biogas Derived from Biomass Feedstocks and Upgraded to Pipeline Quality. Building upon the previous work, this report is focused on assessing a) the RNG production potential from various feedstocks, b) the corresponding GHG emission reduction potential, and c) the estimated costs of bringing RNG supply on to the system. ICF developed production potential estimates by incorporating a variety of constraints regarding accessibility to feedstocks, the time that it would take to deploy projects over the timeline of the study (out to 2040), the development of technology that would be required to achieve higher levels of RNG production, and consideration of likely project economics—with the assumption that the most economic projects will come online first. ICF developed low and high resource potential scenarios by considering RNG production from nine (9) feedstocks and three production technologies. The feedstocks include landfill gas, animal manure, water resource recovery facilities (WRRFs), food waste, agricultural residues, forestry and forest product residues, energy crops, the use of renewable electricity, and the non-biogenic fraction of municipal solid waste (MSW).1 These feedstocks were assumed to be processed using one of three technologies to produce RNG, including anaerobic digesters, thermal gasification systems, and power-to-gas (P2G) in combination with a methanation system. It is important to note that ICF’s analysis is not meant to be prescriptive, rather illustrative in terms of how the market for RNG production potential might evolve given our understanding of the feedstocks that can be used and the current state of technology development. Consider for instance that many anaerobic digester projects use a combination of animal manure and agricultural residues as feedstocks—the analysis presented here only considers the anaerobic digestion of animal manure and the thermal gasification of agricultural residues. ICF recognizes that these type of multi- feedstock considerations will continue to exist in the market; however, we needed to make simplifying distinctions for the purposes of the resource assessment. ICF estimated low and high resource potential scenarios by considering constraints unique to each potential RNG feedstock—these constraints were based on factors such as feedstock accessibility and the economics of RNG production using the feedstock. These constraints were then used to develop low and high utilization assumptions regarding each feedstock. The resource potential reported is also a function of the conversion efficiency of the production technology to which each

1 ICF notes that the non-biogenic fraction of MSW does not satisfy AGA’s definition of RNG; however, this feedstock was included in the analysis. The results associated with RNG potential from this non-biogenic fraction of MSW are called out separately throughout the report for the sake of transparency. 1

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feedstock is paired. ICF also presents a technical resource potential, which does not consider accessibility or economic constraints. The resource assessment was conducted using a combination of national-, state-, and regional-level information regarding the availability of different feedstocks; and the information is presented using the nine (9) U.S. Census Regions. In the low resource potential scenario, ICF estimates that about 1,660 trillion Btu (tBtu) of RNG can be produced annually for pipeline injection by 2040 (see Figure 1 below). That estimate increases to 1,910 tBtu per year when including the potential for the non-biogenic fraction of MSW. In the high resource potential scenario, ICF estimates that about 3,780 tBtu of RNG can be produced annually for pipeline injection by 2040 (see Figure 2 below). That estimate increases to 4,510 tBtu per year when including the potential for the non-biogenic fraction of MSW. For the sake of comparison, ICF notes that the 10-year average (2009 to 2018) for residential natural gas consumption nationwide is 4,846 tBtu; this is shown as the black-dotted line in Figure 1 and Figure 2 below. Ultimately, market conditions, technology development, and policy structures will determine the extent to which each of the feedstocks considered can be utilized. For the sake of reference, ICF also reports a technical resource potential scenario of nearly 13,960 tBtu—a production potential intended to reflect the RNG production potential without any technical or economic constraints. The reported RNG resource potential estimates reported here are 90% and 180% increases from the comparable resource potential scenarios from 2011 AGF Study. These changes are largely attributable to improved access to data regarding potential feedstocks for RNG production and are generally not attributable to more aggressive assumptions regarding feedstock utilization or conversion efficiencies. Furthermore, the analysis presented here includes estimates for RNG production from P2G systems using dedicated renewable electricity. While there are multiple studies regarding P2G technology and its uses, we believe this is the first study to quantify RNG production potential nationwide from P2G. A diverse array of resources can contribute to RNG production—there is a portfolio of potential feedstocks and technologies that are or will be commercialized in the near-term future that will help realize the potential of the RNG market. Figure 1 and Figure 2 below demonstrate the diversity of RNG resource potential as a GHG emission reduction strategy. On the technology side, most RNG continues to be produced using anaerobic digestion paired with conditioning and upgrading systems. The post-2025 outlook for RNG will increasingly rely on thermal gasification of sustainably harvested biomass, including agricultural residues, forestry and forest product residues, and energy crops. The long-term outlook for RNG growth will depend to some extent on technological advancements in power-to-gas systems.2

2 The RNG potential for P2G/methanation is shown as a pattern fill in Figure 1 and Figure 2 because of the way ICF estimates likely project economics for P2G. In reality, however, the low and high resource potential for P2G using dedicated renewable electricity will be constrained by more factors that could be considered in this report; and it is conceivable that the RNG resource potential from P2G is considerably higher than considered here. 2

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Figure 1. Estimated Annual RNG Production, Low Resource Potential Scenario, tBtu/y

5,000 P2G/Methanation

4,500 MSW

4,000 Energy Crops 3,500 Forest Residue 3,000 Ag Residue 2,500 Food Waste 2,000 WRRF 1,500 Animal Manure

Annual RNG Production(tBtu/y) 1,000 Landfill Gas 500

0 NG Residential Consumption, 2025 2030 2035 2040 10-yr avg

Figure 2. Estimated Annual RNG Production, High Resource Potential Scenario, tBtu/y

5,000 P2G/Methanation

4,500 MSW

4,000 Energy Crops 3,500 Forest Residue 3,000 Ag Residue 2,500 Food Waste 2,000 WRRF 1,500 Animal Manure

Annual RNG Production(tBtu/y) 1,000 Landfill Gas 500

0 NG Residential Consumption, 2025 2030 2035 2040 10-yr avg

The potential for power-to-gas systems as a contributor to RNG production could be significant. Power-to-gas (P2G) is a form of energy technology that converts electricity to a gaseous fuel. Electricity is used to split water into hydrogen and oxygen, and the hydrogen can be further processed to produce methane when combined with a source of carbon dioxide. If the electricity is sourced from renewable resources, such as wind and solar, then the resulting fuels are carbon neutral. In this study, ICF made the simplifying assumption that all hydrogen produced via P2G would be methanated for pipeline injection. This assumption should not be viewed as a determination of the best use of hydrogen as an energy carrier in the future; rather, it was a 3

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simplifying assumption to compare more easily P2G to other potential RNG resources evaluated in this study. ICF generally finds that the potential for RNG deployment could exceed the estimated high resource potential scenario because we opted to employ moderately conservative assumptions regarding the expected utilization of various feedstocks. These assumptions manifest themselves as constraints on the availability of supply for each feedstock, recognizing there will likely be competition for each feedstock. It is important to note that ICF did not make any assumptions regarding a specific policy or incentive framework that would favor RNG production over some other energy source (e.g., liquid biofuels). Excluding cost considerations, the deployment of P2G systems for RNG production requires assumptions across a variety of factors, including but not limited to access to renewable electricity, the corresponding capacity factor of the system given the intermittency of renewable electricity generation from some sources (e.g., solar and wind), co-location with (presumably affordable) access to carbon dioxide for methanation, and reasonable proximity to a natural gas pipeline for injection. ICF’s analysis did not seek to address all of these project development considerations; rather, we sought to understand the potential for P2G systems assuming access to dedicated renewable electricity production, meaning that these are purpose-built renewable electricity generation systems that are meant to provide dedicated power to P2G systems. ICF did not explicitly consider renewable electricity that could be curtailed from over-supply of renewable electricity as a result of compliance with Renewable Portfolio Standards (RPS). Ultimately, the issue of curtailment is a complicated one, and exploring it in detail was beyond the scope of this analysis. However, ICF’s initial assessment indicates that P2G systems running on curtailed renewable electricity will play an important transitional role in helping to deploy the technology and achieve the long-term price reductions that are required to improve the viability of P2G as a cost- effective pathway for RNG production. Despite the importance of curtailed renewable electricity as part of the transition towards more cost-effective P2G systems, ICF’s analysis does focus more on the opportunity for, and associated costs of RNG production using P2G systems with dedicated renewable electricity generation. It is important that this assumption by ICF is recognized as a limitation of our analysis, rather than a commentary on how the market will ultimately develop for P2G systems. ICF estimates that RNG deployment could achieve 101 to 235 million metric tons (MMT) of GHG emission reductions by 2040. The GHG emission reductions were calculated using IPCC guidelines stating that emissions from biogenic fuel Figure 3.Average Average CO AnnualEmissions CO2 Emissions(MMT) from (in MMT) sources should not be included when accounting from Natural Gas2 Consumption, 2009-2018 Natural Gas Consumption, 2009-2018 for emissions in combustion. This accounting Residential approach is employed to avoid any upstream Electric Gen 248 “double counting” of emissions that occur in the 466 agricultural or land-use sectors per IPCC guidance. Generally speaking, biogenic carbon in combustion is excluded from carbon accounting Commercial 170 methodologies because it is assumed that the carbon sequestered by the biomass during its

lifetime offsets emissions that occur during Industrial combustion. Figure 3 shows the 10-year average 392 (2009-2018) of carbon dioxide (CO2) emissions from natural gas consumption across multiple sectors; and most notably that the residential 4

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energy sector on average emitted about 248 MMT of CO2 emissions nationwide over the 10-years considered. GHG emission reductions attributable to RNG can be a complicated issue driven by different accounting systems. Although we focus on the GHG emission reductions potential using IPCC guidelines in this report, many stakeholders are likely familiar with the lifecycle accounting approach for GHG emissions that is used by California’s Low Carbon Fuel Standard (LCFS) program. In that accounting system, the GHG emissions from production and processing to combustion are accounted for—and fuels like RNG sourced from animal manure generally have a negative emissions factor, which reflects the upstream “crediting” of capturing methane that would have otherwise been vented to the atmosphere. ICF addresses these various accounting systems, and reviews the GHG emission reductions under a lifecycle accounting framework in an appendix. ICF estimates that the majority of the RNG produced in the high resource potential scenario is available in the range of $7-$20/MMBtu, which results in a cost of GHG emission reductions between $55/ton to $300/ton in 2040. ICF evaluated the potential costs associated with the deployment of each feedstock and technology pairing, and made assumptions about the sizing of systems that would need to be deployed to achieve the RNG production potential outlined in the low and high resource potential scenarios. ICF reports that RNG will be available from various feedstocks in the range of $7/MMBtu to $45/MMBtu. These costs are dependent on a variety of assumptions, including feedstock costs, the revenue that might be generated via byproducts or other avoided costs, and the expected rate of return on capital investments. ICF finds that there is potential for cost reductions as the RNG for pipeline injection market matures, production volumes increase, and the underlying structure of the market evolves. As noted previously, the opportunity of RNG from P2G systems (and paired with methanation units) warrants further consideration; however, ICF’s analysis demonstrates that the combination of production potential and potential cost reductions for P2G systems is promising. With respect to RNG from P2G, the three main drivers for the production costs include: a) the electrolyzer, b) the cost of renewable electricity, and c) the cost of methanation. ICF finds that there is significant cost reduction potential in the P2G market, as the installed capacity (measured in GW, for instance) for electrolyzers increases over the next 10-15 years. ICF assumed that dedicated renewable electricity systems, co-located with P2G systems, could provide electricity at a levelized cost in the range of $10 to $55 per MWh. Lastly, there is significant cost reduction potential for methanation paired with P2G systems.

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Introduction Renewable natural gas (RNG) is derived from biomass or other renewable resources, and is a pipeline-quality gas that is fully interchangeable with conventional natural gas. The American Gas Association uses the following definition for RNG: Pipeline compatible gaseous fuel derived from biogenic or other renewable sources that has lower lifecycle carbon dioxide equivalent (CO2e) emissions than geological natural gas. The primary objective of this report is to characterize the resource and economic potential for RNG as a greenhouse gas (GHG) emission reduction strategy. Further, this report seeks to improve policy makers’ understanding of the extent to which delivering RNG to all sectors of the economy can contribute to broader GHG emission reduction initiatives. The following sub-sections introduce the RNG production technologies and corresponding feedstocks. ICF assessed the production potential for renewable gas into three categories: 1) RNG from renewable feedstocks using anaerobic digestion (AD) and thermal gasification (TG), 2) RNG derived from municipal solid waste (MSW),3 and 3) RNG produced via combination power-to-gas (P2G) and methanation. For each resource and production technology pairing, ICF estimated the production cost and corresponding range of GHG emissions. RNG Production Technologies RNG is produced over a series of steps–namely collection of a feedstock, delivery to a processing facility for biomass-to-gas conversion, gas conditioning, compression, and interconnection and injection into the pipeline. § The most common way to produce RNG today is via anaerobic digestion, whereby microorganisms break down organic material in an environment without oxygen. In the context of RNG production, the process generally takes place in a controlled environment, referred to as a digester or reactor. When organic material is introduced to the digester, it is broken down over time (e.g., days) by microorganisms, and the gaseous products of that process contain a large fraction of methane and carbon dioxide, sometimes referred to as biogas. The biogas is subsequently upgraded and conditioned to yield biomethane, and injected into the common carrier pipeline. § The thermal gasification of biomass also produces RNG—this includes a broad range of processes whereby a carbon containing feedstock is converted into a mixture of gases referred to as synthetic gas or syngas, including hydrogen, carbon monoxide, steam, carbon dioxide, methane, and trace amounts of other gases. This process generally occurs at high temperatures and varying temperatures (depending on the gasification system). § Lastly, this assessment considers RNG produced using renewable electricity (as a feedstock) to generate hydrogen via electrolysis, which is methanated for subsequent injection into the pipeline—this process is referred to as power-to-gas (P2G).

3 Gas produced from the thermal gasification of MSW does not satisfy AGA’s definition of RNG because it is not from a biogenic or renewable source; however, it does have lower lifecycle CO2e emissions than geological natural gas. As a result, MSW as a resource was assessed in this study, but is presented separately from the other feedstocks considered. 6

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RNG Feedstocks RNG can be produced from a variety of renewable feedstocks, as described in Table 1 below. More information about each feedstock and its corresponding contribution to the RNG resource potential is included in Section 0. Table 1. Summary of Feedstocks Considered for RNG Production Feedstock for RNG Description The anaerobic digestion of organic waste in landfills produces a mix of Landfill gas (LFG) gases, including methane (40-60%).

Manure produced by livestock, including dairy cows, beef cattle, swine, Animal manure sheep, goats, poultry, and horses. Wastewater consists of waste liquids and solids from household, Water Resource Recovery commercial, and industrial water use; in the processing of wastewater, a Facilities (WRRF) sludge is produced, which serves as the feedstock for RNG.

Anaerobic digestion Commercial food waste, including from food processors, grocery stores, Food waste cafeterias, and restaurants, as well as residential food waste, typically collected as part of waste diversion programs. The material left in the field, orchard, vineyard, or other agricultural setting Agricultural residue after a crop has been harvested. Inclusive of unusable portion of crop, stalks, stems, leaves, branches, and seed pods.

Biomass generated from logging, forest and fire management activities, Forestry and forest and milling. Inclusive of logging residues, forest thinnings, and mill product residue residues. Also materials from public forestlands, but not specially designated forests (e.g., roadless areas, national parks, wilderness areas). Inclusive of perennial grasses, trees, and some annual crops that can be Energy crops grown specifically to supply large volumes of uniform, consistent quality feedstocks for energy production. Thermal Gasification Refers to the non-biogenic fraction of waste that would be landfilled after Municipal solid waste diversion of other waste products (e.g., food waste or other organics), (MSW) including construction and demolition debris, plastics, etc.

Renewable electricity (presumably excess generation thereof) serves as Renewable electricity feedstock for P2G technologies. P2G produces hydrogen, which can then P2G be blended directly into the pipeline or methanated.

Resource Assessment Scenarios ICF developed three scenarios for each feedstock—with variations between a low resource and high resource scenario regarding utilization of the feedstock, and a technical resource potential based on the energy content of the resource under consideration. This is substantially similar to the AGF study completed in 2011 regarding RNG, as noted below. Review of Previous Work In 2011, the American Gas Foundation (AGF) published The Potential for Renewable Gas: Biogas Derived from Biomass Feedstocks and Upgraded to Pipeline Quality, a study aimed at assessing the

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resource potential of renewable gas which included three scenarios, as described here, and the resource potential results are shown in Table 2 below.4 § Non-Aggressive Scenario: This represented a low level of feedstock utilization, with utilization levels reportedly depending on feedstock, with a range from 15%-25% for feedstocks that were converted to renewable gas using anaerobic digestion technologies. The utilization rates of feedstocks for thermal gasification in the non-aggressive scenario ranged from 5-10%. § Aggressive Scenario: This scenario represented a higher level of feedstock utilization, with utilization levels reportedly depending on feedstock, with a range from 40%-75% for feedstocks that were converted to RNG using anaerobic digestion technologies. The utilization rates of feedstocks for thermal gasification in the aggressive scenario ranged from 15-25%. § Maximum Scenario: This represents an “absolute upper bound” regarding the energy production potential and was used for illustrative purposes. Table 2. Summary of RNG Potential from 2011 AGF Study in units of tBtu/year RNG Production Potential, tBtu/y Feedstock Non-Aggressive Aggressive Landfill Gas 182 364 Animal Manure 148 493 WRRF 4 13 Food Waste N/A N/A Sub-Total, AD 335 871 Ag Residue 401 1,002 Forestry and Forest 82 206 Residue Energy Crops 80 200 MSW 69 207 Sub-Total, TG 632 1,614 Totals 967 2,485

4 Note that the 2011 RNG assessment did not consider P2G. 8

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Regional RNG Resource Assessment There are more than 85 projects producing RNG for pipeline injection today, compared to less than a half-dozen in 2010 when AGF first assessed the potential for RNG. In the following sub-sections, ICF outlines the potential for RNG for pipeline injection, broken down by the feedstocks presented previously, and considering the potential for RNG growth over time with 2040 being the final year in the analysis. ICF presents a low and a high RNG potential, varying both the assumed utilization of existing resources, as well as the rate of project development required to deploy RNG at the volumes presented. The resource potential is presented on a national-level and broken down by the nine (9) U.S. Census Regions, as shown in the figure below: New England, Middle Atlantic, East North Central, West North Central, South Atlantic, East South Central, West South Central, Mountain, and Pacific. Figure 4. U.S. Census Regions

The RNG potential is based on assessment of resource availability—in a competitive market, that resource availability will be a function of factors including, but not limited to demand, feedstock costs, technological development, and the policies in place that might support RNG project development. The intent of ICF’s estimates is to outline the RNG potential that could be realized given the right market considerations (without explicitly defining what those are), and then capture the corresponding costs and GHG emissions reductions associated with our production estimates. For the RNG market more broadly, ICF assumed that the market would continue to grow to 2025 at a compound annual growth rate slightly higher than we have seen over the last 5 years—at a rate of

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about 35%.5 This rate is reflective of existing investments in at least 40 new domestic RNG projects coming online, and other announcements that have not yet been made. Based on this assumption, we assume that the potential for RNG injected into the pipeline will be on the order of 220 to 240 tBtu in 2025. For RNG production potential post-2025, ICF used a logistic function to approximate the growth trajectory, whereby the initial stage of growth is approximated as an exponential, and thereafter growth slows to a linear rate, and then approaches a plateau (or limited to no growth) at maturity. Summary of RNG Potential The figures below illustrate ICF’s estimates for the low and high potential scenario across each feedstock, reported in units of trillion Btu per year (tBtu/y). Figure 5. Estimated Annual RNG Production, Low Resource Potential Scenario, tBtu/y

5,000 P2G/Methanation

4,500 MSW

4,000 Energy Crops 3,500 Forest Residue 3,000 Ag Residue 2,500 Food Waste 2,000 WRRF 1,500 Animal Manure

Annual RNG Production(tBtu/y) 1,000 Landfill Gas 500

0 NG Residential Consumption, 2025 2030 2035 2040 10-yr avg

5 ICF estimates that there were about 17.5 tBtu of RNG produced for pipeline injection in 2016 and that there will be about 50 tBtu of RNG produced for pipeline injection in 2020—this yields a compound annual growth rate of about 30%. 10

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Figure 6. Estimated Annual RNG Production, High Resource Potential Scenario, tBtu/y

5,000 P2G/Methanation

4,500 MSW

4,000 Energy Crops 3,500 Forest Residue 3,000 Ag Residue 2,500 Food Waste 2,000 WRRF 1,500 Animal Manure

Annual RNG Production(tBtu/y) 1,000 Landfill Gas 500

0 NG Residential Consumption, 2025 2030 2035 2040 10-yr avg

ICF estimates that the low and high resource potential scenarios will yield about 1,910 tBtu/y and 4,510 tBtu/y of RNG production by 2040. For the sake of comparison, the United States has consumed on average 15,850 tBtu of natural gas over the last ten years (2009-2018) in the residential (4,846 tBtu), commercial (3,318 tBtu), transportation (36 tBtu), and industrial sectors (7,652 tBtu).6 ICF sought to utilize reasonable, and in most cases, conservative assumptions regarding the utilization of different feedstocks. Table 3 below summarizes the utilization of the different feedstocks that ICF used in the analysis. Table 3. Summary of Feedstock Utilization in the Low and High Resource Potential Scenarios RNG Feedstock Low Resource High Resource LFG • 40% of the LFG facilities that have • 65% of the LFG facilities that have collection systems in place collection systems in place • 30% of the LFG facilities that do not have • 60% of the LFG facilities that do not have collections systems in place collections systems in place • 50% of EPA’s candidate landfills • 80% of EPA’s candidate landfills Animal manure • 30% of technically available animal • 60% of technically available animal manure manure WRRF • 30% of WRRFs with a capacity greater • 50% of WRRFs with a capacity greater than than 7.25 million gallons per day 3.3 million gallons per day Food waste • 40% of the food waste available at • 70% of the food waste available at $70/dry ton $100/dry ton Agricultural residue • 20% of the agricultural residues available • 50% of the agricultural residues available at at $50/dry ton $50/dry ton

6 Based on data reported by the Energy Information Administration, available online at https://www.eia.gov/dnav/ng/ng_cons_sum_dcu_nus_a.htm. 11

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RNG Feedstock Low Resource High Resource Forestry and forest • 30% of the forest and forestry product • 60% of the forest and forestry product product residue residues available at $30/dry ton residues available at $60/dry ton Energy crops • 50% of the energy crops available at • 50% of the energy crops available at $50/dry ton $70/dry ton Municipal solid • 30% of the non-biogenic fraction of MSW • 60% of the non-biogenic fraction of MSW waste (MSW) available at $30/dry ton available at $100/dry ton P2G • 50% capacity factor for dedicated • 80% capacity for dedicated renewables renewables

Ultimately, market conditions, technology development, and policy structures will determine the extent to which each of the feedstocks considered can be utilized. For the sake of reference, ICF also reports a technical resource potential scenario of nearly 13,960 tBtu—an estimate intended to reflect the RNG production potential without any technical or economic constraints. Figure 7 below shows how the RNG technical resource potential compares to the domestic consumption of natural gas in different end uses.7 Figure 7. RNG Technical Resource Potential vs Average Domestic Natural Gas Consumption in Different End Uses, 2009-2018 (in tBtu/y)

RNG Technical Resource

Vehicle 2018

- Industrial

Commercial

Residential Average U.S. Natural Gas Natural U.S. Average Consumption, 2009 Consumption, Trillion Btu per year

The tables below summarize ICF’s resource assessment for low, high, and technical resource RNG production potential in 2040, broken down by Census Region and by feedstock, reported in units of tBtu per year (tBtu/y). The last row in each table also includes the amount of natural gas consumed in the residential, commercial, transportation, and industrial sectors broken down by Census Region in 2018 for the sake of reference.

7 The technically achievable RNG production potential excludes P2G as a source. 12

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Low Resource Potential Scenario Table 4. Low Resource Potential for RNG in 2040, tBtu/y RNG Potential: Low Scenario (in tBtu/y) East West East West Feedstock New Mid- South North North South South Mountain Pacific Total England Atlantic Atlantic Central Central Central Central RNG from biogenic or renewable resources Landfill Gas 13.3 57.5 106.2 28.6 88.4 35.7 65.3 38.3 95.2 528.4

Animal Manure 8.0 12.1 30.3 44.5 31.7 18.9 36.0 28.7 21.0 231.2

WRRF 1.1 4.5 5.5 1.3 3.4 1.0 2.0 1.2 4.0 24.0

Food Waste 1.8 5.0 5.7 1.9 6.0 0.8 1.4 0.9 5.6 29.2

Sub-Total, AD 24.2 79.1 147.8 76.3 129.5 56.4 104.7 69.1 125.8 812.8

Ag Residue 0.0 3.7 57.0 144.4 10.0 2.9 10.7 10.9 14.9 254.6 Forestry and 3.6 4.8 9.7 6.5 37.6 20.6 16.3 2.7 6.8 108.6 Forest Residue Energy Crops 0.2 2.2 1.5 35.4 18.1 9.3 56.5 0.2 0.0 123.4

Sub-Total, TG 3.8 10.7 68.2 186.3 65.7 32.8 83.5 13.8 21.7 486.6 Renewable gas from MSW MSW 14.4 40.6 45.9 17.7 56.9 11.2 15.3 8.8 45.4 256.2 RNG from P2G / Methanation P2G / 357.7 Methanation Totals 42.3 130.5 261.8 280.4 252.1 100.3 203.4 91.7 192.9 1,913.2

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High Resource Potential Scenario Table 5. High Resource Potential for RNG in 2040, tBtu/y RNG Potential: High Scenario (in tBtu/y) East West East West Feedstock New Mid- South North North South South Mountain Pacific Total England Atlantic Atlantic Central Central Central Central RNG from biogenic or renewable resources Landfill Gas 21.7 94.3 173.8 47.3 145.0 59.1 106.2 32.9 155.2 865.6

Animal Manure 16.0 24.2 60.6 88.9 63.4 37.7 71.9 57.5 42.1 462.3

WRRF 1.6 6.3 6.6 2.0 5.1 1.6 3.1 1.7 5.5 33.5

Food Waste 3.1 8.8 9.9 4.1 13.1 4.2 8.0 2.9 9.8 63.9

Sub-Total, AD 42.4 133.6 250.9 142.3 226.6 102.6 189.2 125.0 212.6 1,425.3

Ag Residue 0.1 9.2 142.6 361.0 26.9 7.3 28.8 27.3 37.3 640.5 Forestry and 7.3 9.7 19.3 13.0 75.2 41.3 37.1 19.3 13.6 235.8 Forest Residue Energy Crops 0.5 9.4 64.4 260.0 77.3 91.6 330.5 3.9 0.0 837.6

Sub-Total, TG 7.9 28.3 226.3 634.0 179.4 140.2 396.4 50.5 50.9 1,713.9 Renewable gas from MSW MSW 32.4 91.6 103.4 46.1 136.3 43.2 83.2 50.1 108.5 694.8 RNG from P2G / Methanation P2G / 678.7 Methanation Totals 80.5 245.2 569.4 819.4 532.0 283.5 658.1 222.5 359.4 4,512.6

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Technical Resource Potential Table 6. Technical Resource Potential for RNG in 2040, tBtu/y RNG Potential: Technical Potential (in tBtu/y) East West East West Feedstock New Mid- South North North South South Mountain Pacific Total England Atlantic Atlantic Central Central Central Central RNG from biogenic or renewable resources Landfill Gas 32.5 143.4 259.1 70.3 211.7 84.0 154.0 92.0 233.2 1,280.2

Animal Manure 88.9 99.3 285.2 602.7 316.5 207.7 453.5 340.5 178.1 2,572.4

WRRF 4.0 14.4 18.1 5.6 12.3 4.7 7.6 4.5 12.2 83.2

Food Waste 17.7 50.1 56.6 23.5 74.5 23.6 45.5 16.5 56.0 364.1

Sub-Total, AD 143.1 307.2 619.0 702.1 615.0 320.0 660.6 453.5 479.5 4,300.0

Ag Residue 0.3 42.1 623.8 1,405.1 93.8 38.7 123.3 115.1 126.3 2,568.5 Forestry and 18.6 24.9 49.5 33.4 192.9 105.8 106.7 85.5 34.7 652.0 Forest Residue Energy Crops 3.0 84.3 872.5 1,508.1 357.1 460.8 1,266.4 48.7 0.0 4,600.9

Sub-Total, TG 21.9 151.3 1,545.8 2,946.6 643.8 605.3 1,496.4 249.3 161.0 7,821.4 Renewable gas from MSW MSW 85.8 242.7 274.0 122.2 361.2 114.6 220.5 133.1 287.5 1,841.6 RNG from P2G / Methanation P2G / N/A; dependent on market developments beyond scope of study Methanation Totals 250.8 701.2 2,438.8 3,770.9 1,620.0 1,039.9 2,377.5 835.9 928.0 13,963.1

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RNG: Anaerobic Digestion of Biogenic or Renewable Resources Landfill Gas The Resource Conservation and Recovery Act of 1976 (RCRA, 1976) sets criteria under which landfills can accept municipal solid waste and nonhazardous industrial solid waste. Furthermore, the RCRA prohibits open dumping of waste and hazardous waste is managed from the time of its creation to the time of its disposal. Landfill gas (LFG) is captured from the anaerobic digestion of biogenic waste disposed of in landfills and produces a mix of gases, including methane, typically with a methane content ranging from 45-60%. The landfill itself acts as the digester tank—a closed volume that becomes devoid of oxygen over time, leading to favorable conditions for certain micro- organisms to break down biogenic materials. The composition of the LFG is dependent on the materials in the landfill, and other factors, but is typically made up of methane, carbon dioxide (CO2), nitrogen (N2), hydrogen, carbon monoxide (CO), oxygen (O2), sulfides (e.g., hydrogen sulfide or H2S), ammonia, and trace elements like amines, sulfurous compounds, and siloxanes. RNG production from LFG requires advanced treatment and upgrading the biogas via removal of CO2, H2S, siloxanes, N2, and O2 to achieve a high Btu content gas for pipeline injection. Table 7 below summarizes landfill gas constituents, the typical concentration ranges in LFG, and commonly deployed upgrading technologies in use today. Table 7. Landfill Gas Constituents and Corresponding Upgrading Technologies LFG Constituent Typical Concentration Range Upgrading Technology for Removal • High-selectivity membrane separation • Pressure swing adsorption (PSA) Carbon dioxide, CO2 40-60% systems • Water scrubbing systems • Amine scrubbing systems • Solid chemical scavenging Hydrogen sulfide, • Liquid chemical scavenging 0-1% H2S • Solvent adsorption • Chemical oxidation-reduction • Non-regenerative adsorption Siloxanes <0.1% • Regenerative adsorption Nitrogen, N2 2-5% • PSA systems Oxygen, O2 0.1-1% • Catalytic removal (O2 only)

To develop the RNG potential from LFG, ICF extracted data from the Landfill Methane Outreach Program (LMOP) administered by the U.S. Environmental Protection Agency (EPA)—which included more than 2,000 landfills. ICF considered only landfills that are either open or were closed post- 2000. This constraint was imposed to account for the fact that the phase during which the decomposition of waste in a landfill produces sufficient methane concentrations lasts about 20-25 years, and this is the period during which waste-to-energy projects are most viable.8 While landfills continue to emit methane for 50 years or more, this constraint limits the potential for the assessment to over-estimate the production from older landfills with a decrease methane

8 US EPA Landfill Methane Outreach Program, LFG Energy Project Development Handbook, Chapter 1, Available online at https://www.epa.gov/sites/production/files/2016-07/documents/pdh_chapter1.pdf 16

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emissions concentration. This constraint reduces the number of candidate landfills to just over 1,500 landfills. The table below includes the number of candidate landfills considered in each Census region. Table 8. Number of Candidate Landfills by Census Region9 East West East West Landfill New Mid- South North North South South Mountain Pacific England Atlantic Atlantic Status Central Central Central Central Closed 33 16 51 21 54 19 25 24 58 (post-2000) Open 25 79 173 121 221 107 160 162 166

The US EPA’s LMOP database shows that there are about 620 operational LFG to energy projects nationwide, however, only 60 (10%) of them produce RNG, and only 52 of those actually inject RNG into the pipeline. Most of the projects capture LFG and combust it in reciprocating engines to make electricity (72%) or have a direct use (18%) for the energy (e.g., thermal use on-site). Moreover, the EPA currently estimates that there are 480 candidate landfills that could capture LFG for use as energy—the EPA characterizes candidate landfills as one that is accepting waste or has been closed for five years or less, has at least one million tons of waste-in-place (WIP), and does not have an operational, under-construction, or planned project. Candidate landfills can also be designated based on actual interest by the site. The table below includes LFG to Energy projects and candidate landfills broken down by Census Region. Table 9. Landfill to Energy Projects and Candidate Landfills by Census Region10

LFG to East West East West New Mid- South North North South South Mountain Pacific Energy England Atlantic Atlantic Project Type Central Central Central Central Electricity 28 64 105 23 101 20 19 18 71

Direct 1 12 26 17 31 6 10 1 5

RNG 1 9 13 5 4 4 19 1 4 Candidate 8 14 62 46 88 60 95 57 43 Landfills

ICF developed resource potentials for RNG production at landfills in a low and high scenario, considering the potential at LFG facilities with collection systems in place, without collection systems in place, and at candidate landfills identified by the US EPA. § In the low scenario, ICF assumed that RNG could be produced at 40% of the LFG facilities that have collection systems in place, 30% of the LFG facilities that do not have collections systems in place, and at 50% of the candidate landfills. Combined, ICF’s estimates in the low resource potential scenario represent about 425 of the more than 2,000 landfills included in the US EPA LMOP database.

9 Based on data from the Landfill Methane Outreach Program at the US EPA (updated February 2019). 10 Ibid. 17

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§ In the high scenario, ICF assumed that RNG could be produced at 65% of the LFG facilities that have collection systems in place, 80% of the LFG facilities that do not have collections systems in place, and at 80% of the candidate landfills. Combined, ICF’s estimates in the low resource potential scenario represent about 750 of the more than 2,000 landfills included in the US EPA LMOP database. To estimate the amount of RNG that could be injected from LFG projects, ICF used outputs from the LandGEM model—which is an automated tool with an MS Excel interface developed by the US EPA to estimate the emissions rates for landfill gas and methane based on user inputs like waste- in-place, facility location (and climate conditions), waste received per year, etc.. The estimated LFG output was estimated on a facility-by-facility basis. About 1,150 facilities report methane content; for the facilities for which no data were reported, ICF assumed the median methane content of 49.6%. The figures below show the low and high RNG resource potential from landfill gas between 2025 and 2040. The table that follows includes the total annual RNG production potential (in units of tBtu/y) for 2040 in the low, high, and technical resource potential scenarios. Figure 8. RNG Production Potential from Landfill Gas, Low Resource Potential Scenario, in tBtu/y

120 New England

100 Mid-Atlantic East North Central 80 West North Central 60 South Atlantic East South Central 40 West South Central 20 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

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Figure 9. RNG Production Potential from Landfill Gas, High Resource Potential Scenario, in tBtu/y

175 New England 150 Mid-Atlantic

125 East North Central West North Central 100 South Atlantic 75 East South Central 50 West South Central 25 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

Table 10. Annual RNG Potential from Landfills in 2040, tBtu/y RNG Potential from Landfills, tBtu/y RNG Potential East West East West New Mid- South Scenario North North South South Mountain Pacific England Atlantic Atlantic Central Central Central Central Low Resource 12.2 52.2 97.6 27.0 83.4 35.2 60.6 36.2 86.0 High Resource 20.9 89.8 166.8 46.5 141.8 60.0 102.1 61.8 146.8 Technical Resource 32.5 143.4 259.1 70.3 211.7 84.0 154.0 92.0 233.2

ICF estimates that between 528 and 866 tBtu/y of RNG could be produced at the national level by 2040 in the low and high scenarios, respectively from LFG facilities. Animal Manure The US EPA lists a variety of benefits associated with the anaerobic digestion of animal manure at farms as an alternative to traditional manure management systems, including but not limited to:11 § Diversifying farm revenue: The biogas produced from the digesters has the highest potential value. But digesters can also provide revenue streams via “tipping fees” from non- farm organic waste streams that are diverted to the digesters; organic nutrients from the digestion of animal manure; and displacement of animal bedding or peat moss by using digested solids. § Conservation of agricultural land: Digesters can help to improve soil health by converting the nutrients in manure to a more accessible form for plants to use and help protect the local water resources by reducing nutrient run-off and destroying pathogens. § Promoting energy independence: The RNG produced can reduce on-farm energy needs or provide energy via pipeline injection for use in other applications, thereby displacing fossil or geological natural gas.

11 More information available online at https://www.epa.gov/agstar/benefits-anaerobic-digestion. . 19

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§ Bolstering farm-community relationships: Digesters help to reduce odors form livestock manure, improve growth prospects by minimizing potential negative impacts of farm operations on local communities, and help forge connections between farmers and the local community through environmental and energy stewardship. The main components of anaerobic digestion of manure include manure collection, the digester, effluent storage (e.g., a tank or lagoon), and gas handling equipment. There are a variety of livestock manure processing systems that are employed at farms today, including plug-flow or mixed plug-flow digesters, complete-mixed digesters, covered lagoons, fixed-film digesters, sequencing-batch reactors, and induced-blanked digesters. Most dairy manure projects today use the plug-flow or mixed plug-flow digesters. ICF considered animal manure from a variety of animal populations, including beef and dairy cows, broiler chickens, layer chickens, turkeys, and swine. Animal populations were derived from the United States Department of Agriculture’s (USDA) National Agricultural Statistics Service. ICF used information provided from the most recent census year (2017) and extracted total animal populations on a state-by-state basis. ICF estimated the total amount of animal manure produced based on the animal population, the total wet manure produced per animal, an assumed moisture content, and the energy content of the dried manure. The values in the table below are taken from a California Energy Commission report prepared by the California Biomass Collaborative.12 Table 11. Key Parameters to Determine Animal Manure Resource for RNG Production Technical Total Wet Manure Moisture Content HHV Animal Type Availability (lb/animal/day) (% wet basis) (Btu/lb, dry basis) Factors Dairy Cow 140 87 7,308 0.50 Beef Cow 125 88 7,414 0.20 Swine 50 88 7,161 0.20 Poultry, Layer Chickens 10 91 6,839 0.50 Poultry, Broiler Chickens 0.2 75 6,663 0.50 Poultry, Turkeys 0.22 74 6,839 0.50

For the technical resource potential for RNG production, ICF did not account for the technical availability factors included in the table above. The US EPA AgStar database indicates that there are nearly 250 operational digesters at farms— more than 90% of which produce electricity or use the biogas for cogeneration. Only 5 of the projects (2%) currently inject gas into the pipeline.

12 Williams, R. B., B. M. Jenkins and S. Kaffka (California Biomass Collaborative). 2015. An Assessment of Biomass Resources in California, 2013 – DRAFT. Contractor Report to the California Energy Commission. PIER Contract 500-11-020. Available online here. 20

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Table 12. Summary of AgStar Projects at Farms using AD Systems, by Census Region East West East West New Mid- South North North South South Mountain Pacific AgStar Projects England Atlantic Atlantic Central Central Central Central Project Status Operational 22 62 69 16 20 5 4 16 34 Construction 2 3 3 7 2 -- -- 3 14 Project Type Electricity / Cogen 22 57 64 10 19 5 3 15 34 Flared -- 8 10 6 -- -- 2 2 Pipeline ------3 1 ------1 Animal Type Dairy 22 55 61 8 6 1 -- 11 34 Swine -- 4 2 7 12 1 4 5 -- Poultry -- 1 1 -- 2 3 ------Multiple -- 2 5 1 ------

ICF developed resource potentials for RNG production from the anaerobic digestion of animal manure in a low and high scenario. § In the low scenario, ICF assumed that RNG could be produced from 30% of the animal manure, after accounting for the technical availability factor. Generally speaking, this represents the share of animal manure that would be recoverable from the larger farms (e.g., dairy farms with more than 1,000 head of cattle and hog farms with more than 5,000 hogs). § In the high scenario, ICF assumed that RNG could be produced from 60% of the animal manure, after accounting for the technical availability factor. Generally speaking, this share of the animal manure represents the resources that could be recoverable from the medium to large farms (e.g., dairy farms with more than 500 head of cattle and hog farms with more than 5,000 hogs). In many cases, anaerobic digesters at dairy farms co-process other substrates (or feedstocks) to boost gas production—the co-digestion of substrates is used to help balance the carbon-to- nitrogen ratio for more favorable anaerobic digestion conditions.13 The figures below show the low and high RNG resource potential from animal manure between 2025 and 2040. The table that follows includes the total annual RNG production potential (in units of tBtu/y) for 2040 in the low, high, and technical resource potential scenarios.

13 US EPA, Increasing Anaerobic Digester Performance with Codigestion, September 2012. Available online: https://www.epa.gov/sites/production/files/2014-12/documents/codigestion.pdf. 21

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Figure 10. RNG Production Potential from Animal Manure, Low Resource Potential Scenario, in tBtu/y

45 New England 40 Mid-Atlantic 35 East North Central 30 West North Central 25 South Atlantic 20 East South Central 15 West South Central 10 5 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

Figure 11. RNG Production Potential from Animal Manure, High Resource Potential Scenario, in tBtu/y

90 New England 80 Mid-Atlantic 70 East North Central 60 West North Central 50 South Atlantic 40 East South Central 30 West South Central 20 10 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

Table 13. Annual RNG Production Potential from Animal Manure in 2040, tBtu/y RNG Potential from Animal Manure, tBtu/y RNG Potential East West East West New Mid- South Scenario North North South South Mountain Pacific England Atlantic Atlantic Central Central Central Central Low Resource 8.0 12.1 30.3 44.5 31.7 18.9 36.0 28.7 21.0 High Resource 16.0 24.2 60.6 88.9 63.4 37.7 71.9 57.5 42.1 Technical Resource 88.9 99.3 285.2 602.7 316.5 207.7 453.5 340.5 178.1

ICF estimates that between 231 and 462 tBtu/y of RNG could be produced in the low and high scenarios, respectively from animal manure by 2040.

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Water Resource Recovery Facilities Wastewater is created from residences and commercial or industrial facilities, and it consists primarily of waste liquids and solids from household water usage, from commercial water usage, or from industrial processes. Depending on the architecture of the sewer system and local regulation, it may also contain storm water from roofs, streets, or other runoff areas. The contents of the wastewater may include anything which is expelled (legally or not) from a household and enters the drains. If storm water is included in the wastewater sewer flow, it may also contain components collected during runoff: soil, metals, organic compounds, animal waste, oils, solid debris such as leaves and branches, etc. Processing of the influent to a large water resource recovery facility (WRRF) is comprised typically of four stages: pre-treatment, primary, secondary, and tertiary treatments. These stages consist of mechanical, biological, and sometimes chemical processing. § Pre-treatment removes all the materials that can be easily collected from the raw wastewater that may otherwise damage or clog pumps or piping using in treatment processes. § In the primary treatment stage, the wastewater flows into large tanks or settling bins, thereby allowing sludge to settle while fats, oils, or greases rise to the surface. § The secondary treatment stage is designed to degrade the biological content of the wastewater and sludge, and is typically done using water-borne micro-organisms in a managed system. § The tertiary treatment stage prepares the treated effluent for discharge into another ecosystem, and often uses chemical or physical processes to disinfect the water. The treated sludge from the WRRF can be landfilled, and during processing it can be treated via anaerobic digestion, thereby producing methane which can be used for beneficial use with the appropriate capture and conditioning systems put in place. ICF reviewed more than 14,500 wastewater treatment facilities surveyed as part of the Clean Watersheds Needs Survey (CWNS) conducted in 2012 by the US EPA, an assessment of capital investment needed for wastewater collection and treatment facilities to meet the water quality goals of the Clean Water Act. ICF further distinguished between facilities based on location, and facility size as a measure of average flow (in units of million gallons per day, MGD). ICF also reviewed more than 1,200 facilities that are reported to have anaerobic digesters in place, as reported by the Water Environment Federation. The tables below summarize the key data points from the survey of WRRFs in the United States, broken down by Census Region. Table 14. Number of WRRFs by Census Region14 East West East West Facility New Mid- South North North South South Mountain Pacific Size (MGD) England Atlantic Atlantic Central Central Central Central <0.02 33 70 169 581 94 46 127 107 32 0.02-0.07 58 255 495 1,125 222 191 362 263 137 0.07-0.18 83 289 607 602 291 224 380 217 145 0.18-1.00 176 555 838 552 569 391 459 308 293 1.01-3.30 109 234 324 160 267 177 178 126 162

14 Based on data from CNWS 2015. 23

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East West East West Facility New Mid- South North North South South Mountain Pacific Size (MGD) England Atlantic Atlantic Central Central Central Central 3.31-7.25 46 91 122 53 137 68 88 39 78 7.26-34.05 35 67 116 36 112 30 58 36 88 34.05+ 5 30 24 9 21 8 15 7 24

Table 15. Total Flow (in MGD) of WRRFs by Census Regions15 East West East West Facility New Mid- South North North South South Mountain Pacific Size (MGD) England Atlantic Atlantic Central Central Central Central <0.02 0 1 2 6 1 0 1 1 0 0.02-0.07 2 10 20 40 9 8 14 10 5 0.07-0.18 9 33 68 66 33 26 42 24 16 0.18-1.00 84 255 380 228 261 170 201 139 135 1.01-3.30 201 440 632 292 511 338 323 238 304 3.31-7.25 231 461 576 259 678 323 439 198 394 7.26-34.05 535 1,009 1,734 569 1,645 424 863 552 1,320 34.05+ 494 3,438 3,651 717 1,686 536 1,086 586 2,580

In other words, these tables tell us that despite the more than 14,500 WRRFs nationwide, nearly 45% of the wastewater is being processed at 142 of the facilities, or just 1% of the total WRRFs for which ICF was able to identify data. Furthermore, more than 70% of the wastewater is being processed at just 5% of the facilities. The table below shows the distribution of the more than 1,250 WRRFs with installed AD systems. Table 16. WRRFs with Anaerobic Digesters, by Census Regions16 West West New Mid- East North South East South North South Mountain Pacific England Atlantic Central Atlantic Central Central Central AD Facilities 34 231 309 125 133 47 74 82 233

The three tables above illustrate the challenges and opportunities associated with deploying AD systems at WRRFs: Most of the wastewater in the U.S. is treated at a small number of facilities. And of the facilities that already have an AD system installed, they tend to be the larger facilities. However, most of those facilities have AD systems installed that are capturing biogas to produce electricity on-site, rather than for pipeline injection. The database of RNG producing facilities maintained by the Coalition for Renewable Natural Gas indicates that there are 12 operation WRRFs using AD systems to capture and subsequently inject RNG into the pipeline, 5 WRRFs with AD systems under substantial development, and another 5 WRRFs with AD systems under construction. ICF developed resource potentials for RNG production at WRRFs in a low and high scenario.

15 Based on data from CNWS 2015. 16 Based on data from the Water Environment Federation. 24

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§ In the low scenario, ICF assumed that AD systems would be deployed at the facilities with larger flow rates (greater than 7.25 MGD), and that presumably some of the systems with AD systems in place would be converted to pipeline injection projects. The underlying assumption is that the economics of RNG production would favor these larger facilities. ICF assumed that RNG could be produced at 30% of the facilities with a capacity greater than 7.25 MGD—this amounts to AD systems with corresponding conditioning and upgrading systems in place to inject RNG into the pipeline at about 200 of the larger sized facilities. § In the high scenario, ICF assumed that RNG could be produced at 50% of the facilities with a capacity greater than 3.3 MGD. This amounts to AD systems with corresponding conditioning and upgrading systems in place to inject RNG into the pipeline at about 450 of the larger sized facilities, and another 1,000 of the medium-sized facilities. In other words, this is a project deployment trajectory consistent with the current level of deployment of AD systems in place, but with an emphasis on RNG production rather than electricity generation. To estimate the amount of RNG produced from wastewater at WRRFs, ICF used data reported by the US EPA,17 a study of WRRFs in New York State,18 and previous work published by AGF.19 ICF used an average energy yield of 7.0 MMBtu/MG of wastewater. For the technical resource potential, ICF used all of the wastewater flow reported at the more than 14,500 facilities in the database. The figures below show the low and high resource potential for RNG production from WRRFs between 2025 and 2040. The table that follows includes the total annual RNG production potential (in units of tBtu/y) for 2040 in the low, high, and technical resource potential scenarios.

17 US EPA, Opportunities for Combined Heat and Power at Wastewater Treatment Facilities, October 2011. Available online here. 18 Wightman, J and Woodbury, P., Current and Potential Methane Production for Electricity and Heat from New York State Wastewater Treatment Plants, New York State Water Resources Institute at Cornell University. Available online here. 19 AGF, The Potential for Renewable Gas: Biogas Derived from Biomass Feedstocks and Upgraded to Pipeline Quality, September 2011. 25

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Figure 12. RNG Production Potential from WRRFs, Low Resource Potential Scenario, in tBtu/y

6.0 New England

5.0 Mid-Atlantic East North Central 4.0 West North Central 3.0 South Atlantic East South Central 2.0 West South Central 1.0 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0.0 Pacific 2025 2030 2035 2040

Figure 13. RNG Production Potential from WRRFs, High Resource Potential Scenario, in tBtu/y

7 New England 6 Mid-Atlantic

5 East North Central West North Central 4 South Atlantic 3 East South Central 2 West South Central 1 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

Table 17. Annual RNG Production Potential from WRRFs in 2040, tBtu/y RNG Potential from WRRFs, tBtu/y RNG Potential East West East West New Mid- South Scenario North North South South Mountain Pacific England Atlantic Atlantic Central Central Central Central Low Resource 1.1 4.5 5.5 1.3 3.4 1.0 2.0 1.2 4.0 High Resource 1.6 6.3 7.6 2.0 5.1 1.6 3.1 1.7 5.5 Technical Resource 4.0 14.4 18.1 5.6 12.3 4.7 7.6 4.5 12.2

ICF estimates that between 24 and 34 tBtu/y of RNG could be produced in the low and high scenarios, respectively from WRRFs. To achieve this level of RNG production from WRRFs, ICF

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estimates that 360 and 1,450 facilities would need to install AD systems in the low and high scenarios, respectively. Food Waste Food waste is a major component of municipal solid waste (MSW)—accounting for about 15% of MSW streams. More than 75% of food waste is landfilled. Food waste can be diverted from landfills to a composting or processing facility where it can be treated in an anaerobic digester. ICF limited our consideration to the potential for utilizing the food waste that is currently landfilled as a feedstock for RNG production via AD, thereby excluding the 25% of food waste that is recycled or directed to waste-to-energy facilities.20 ICF extracted information from the U.S. Department of Energy’s (DOE) Bioenergy Knowledge Discovery Framework (KDF), which includes information collected as part of U.S. DOE’s Billion-Ton Report (updated in 2016).21 The Bioenergy KDF includes food waste at price points ranging from $70/ton and $100/ton. ICF assumed a high heating value of 12.04 MMBtu/ton (dry). Note that the values from the Bioenergy KDF are reported in dry tons, so the moisture content of the food waste has already been accounted for in the DOE’s resource assessment. ICF developed the RNG production potential from food waste in a low and high scenario. § In the low scenario, ICF assumed that 40% of the food waste available at $70/dry ton would be diverted to AD systems. § In the high scenario, ICF assumed that 70% of the food waste available at $100/dry ton would be diverted to AD systems. ICF calculated the technical resource potential for RNG production from food waste in an AD system assuming 100% of the food waste that is currently landfilled is diverted to a processing facility with a digester. The figures below show the low and high RNG resource potential from the anaerobic digestion of food waste between 2025 and 2040. The table that follows includes the total annual RNG production potential (in units of tBtu/y) for 2040 in the low, high, and technical resource potential scenarios.

20 ICF notes that the diversion of food waste from landfills may limit the long-term potential (post-2040) of landfill gas as a viable resource for RNG production. However, for the purposes of this report, and the associated timeframe of the analysis to 2040, ICF used estimates based on existing waste-in-place at landfills, and the corresponding methane production at those landfills. The resource estimates between RNG from landfill gas and food waste do not conflict or overlap; however, ICF notes that successful waste diversion policies would only increase the RNG resource potential and improve the appetite for RNG production from dedicated AD systems processing diverted food waste. 21 The Billion-Ton Report is a critical national assessment performed by the Department of Energy to calculate the potential supply of biomass in the U.S.. The report finds that the U.S. has the future potential to produce at least one billion dry tons of biomass resources (composed of agricultural, forestry, waste, and algal materials) on an annual basis without adversely affecting the environment. 27

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Figure 14. RNG Production Potential from Food Waste, Low Resource Potential Scenario, in tBtu/y

7.0 New England 6.0 Mid-Atlantic

5.0 East North Central West North Central 4.0 South Atlantic 3.0 East South Central 2.0 West South Central 1.0 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0.0 Pacific 2025 2030 2035 2040

Figure 15. RNG Production Potential from Food Waste, High Resource Potential Scenario, in tBtu/y

14 New England 12 Mid-Atlantic

10 East North Central West North Central 8 South Atlantic 6 East South Central 4 West South Central 2 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

Table 18. Annual RNG Production Potential from Food Waste in 2040, tBtu/y RNG Potential from Food Waste, tBtu/y RNG Potential East West East West New Mid- South Scenario North North South South Mountain Pacific England Atlantic Atlantic Central Central Central Central Low Resource 1.8 5.0 5.7 1.9 6.0 0.8 1.4 0.9 5.6 High Resource 3.1 8.8 9.9 4.1 13.1 4.2 8.0 2.9 9.8 Technical Resource 17.7 50.1 56.6 23.5 74.5 23.6 45.5 16.5 56.0

ICF estimates that between 29 and 64 tBtu/y of RNG could be produced by 2040 at the national level in the low and high scenarios, respectively from food waste diverted to anaerobic digesters.

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RNG: Thermal Gasification of Biogenic or Renewable Resources Biomass like agricultural residues, forestry and forest produce residues, and energy crops have high energy content and are ideal candidates for thermal gasification. The thermal gasification of biomass to produce RNG occurs over a series of steps. Thermal gasification typically requires some pre-processing of the feedstock. The gasification process first generates synthesis gas (or syngas), consisting of hydrogen and carbon monoxide. Biomass gasification technology has been commercialized for nearly a decade; however, the gasification process typically yields a residual tar, which can foul downstream equipment. Furthermore, the presence of tar effectively precludes the use of a commercialized methanation unit. The high cost of conditioning the syngas in the presence of these tars has limited the potential for thermal gasification of biomass. For instance, in 1998, Tom Reed22 concluded that after “two decades” of experience in biomass gasification, “’tars’ can be considered the Achilles heel of biomass gasification.” Over the last several years, however, several commercialized technologies have been deployed to increase syngas quantity and prevent the fouling of other equipment by removing the residual tar before methanation. There are a handful of technology providers in this space including Haldor Topsoe’s tar reforming catalyst. Frontline Bioenergy takes a slightly different approach and has patented a process producing tar free syngas (referred to as TarFreeGasÔ). The syngas is further upgraded via filtration (to remove remaining excess dust generated during gasification), and other purification processes to remove potential contaminants like hydrogen sulfide, and carbon dioxide. The upgraded syngas is then methanated and dried prior to pipeline injection. ICF notes that biomass, particularly agricultural residues, are often added to anaerobic digesters to increase gas production (by improving carbon-to-nitrogen ratios, especially in animal manure digesters). It is conceivable that some of the feedstocks considered here could be used in anaerobic digesters. For the sake of simplicity, ICF did not consider any multi-feedstock applications in our assessment; however, it is important to recognize that the RNG production market will continue to include mixed feedstock processing in a manner that is cost-effective. Agricultural Residues Agricultural residues include the material left in the field, orchard, vineyard, or other agricultural setting after a crop has been harvested. More specifically, this resource is inclusive of the unusable portion of crop, stalks, stems, leaves, branches, and seed pods. Agricultural residues (and sometimes crops) are often added to anaerobic digesters ICF extracted information from the U.S. DOE Bioenergy KDF including the following agricultural residues: wheat straw, corn stover, sorghum stubble, oats straw, barley straw, citrus residues, noncitrus residues, tree nut residues, sugarcane trash, cotton gin trash, cotton residue, rice hulls, sugarcane bagasse, and rice straw. ICF extracted data from the Bioenergy KDF at three price points: $30/ton, $50/ton and $100/ton. The table below lists the energy content on a high heating value (HHV) basis for the various agricultural residues included in the analysis—these are based on values reported by the California Biomass Collaborative. To estimate the RNG production potential, ICF assumed a 65% efficiency for thermal gasification systems.23

22 NREL, Biomass Gasifier “Tars”: Their Nature, Formation, and Conversion, November 1998, NREL/TP-570-25357. Available online at https://www.nrel.gov/docs/fy99osti/25357.pdf. 23 The 2011 AGF Report on RNG report indicated a range of thermal gasification efficiencies in the range of 60% to 70%, depending upon the configuration and process conditions. And the report authors also used a conversion 29

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Table 19. Heating Values for Agricultural Residues MSW Component Btu/lb, dry MMBtu/ton, dry Wheat straw 7,527 15.054 Corn stover 7,587 15.174 Sorghum stubble 6,620 13.24 Oats straw 7,308 14.616 Barley straw 7,441 14.882 Citrus residues 8,597 17.194 Noncitrus residues 7,738 15.476 Tree nut residues 8,597 17.194 Sugarcane trash 7,738 15.476 Cotton gin trash 7,058 14.116 Cotton residue 7,849 15.698 Rice hulls 6,998 13.996 Sugarcane bagasse 7,738 15.476 Rice straw 6,998 13.996

ICF developed the RNG production potential from agricultural residues in a low and high scenario. § In the low scenario, ICF assumed that 20% of the agricultural residues available at $50/dry ton would be diverted to thermal gasification systems. § In the high scenario, ICF assumed that 50% of the agricultural residues available at $50/dry ton would be diverted to thermal gasification systems. ICF calculated the technical resource potential for RNG production from agricultural residues assuming that all of the material available at $100/ton could be gasified at 100% efficiency. The figures below show the low and high RNG resource potential from the thermal gasification of agricultural residues between 2025 and 2040. The table that follows includes the total annual RNG production potential (in units of tBtu/y) for 2040 in the low, high, and technical resource potential scenarios.

efficiency of 65%. More recently, GTI estimated the potential for RNG from the thermal gasification of wood waste in California (GTI, Low-Carbon Renewable Natural Gas from Wood Wastes, February 2019, available online at https://www.gti.energy/wp-content/uploads/2019/02/Low-Carbon-Renewable-Natural-Gas-RNG-from-Wood- Wastes-Final-Report-Feb2019.pdf), and assumed a conversion efficiency of 60%. 30

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Figure 16. RNG Production Potential from Agricultural Residue, Low Resource Potential Scenario, in tBtu/y

160 New England 140 Mid-Atlantic 120 East North Central 100 West North Central 80 South Atlantic 60 East South Central 40 West South Central 20 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

Figure 17. RNG Production Potential from Agricultural Residue, High Resource Potential Scenario, in tBtu/y

400 New England 350 Mid-Atlantic 300 East North Central 250 West North Central 200 South Atlantic 150 East South Central 100 West South Central 50 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

Table 20. Annual RNG Production Potential from Agricultural Residues in 2040, tBtu/y RNG Potential from Agricultural Residue, tBtu/y RNG Potential East West East West New Mid- South Scenario North North South South Mountain Pacific England Atlantic Atlantic Central Central Central Central Low Resource 0.1 0.5 0.3 19.5 3.2 0.1 1.0 1.8 12.0 High Resource 0.1 9.2 142.6 361.0 26.9 7.3 28.8 27.3 37.3 Technical Resource 0.3 42.1 623.8 1,405.1 93.8 38.7 123.3 115.1 126.3

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ICF estimates that between 255 and 641 tBtu/y of RNG could be produced by 2040 at the national level in the low and high scenarios, respectively from the thermal gasification of agricultural residues. Forestry and Forest Product Residues Biomass generated from logging, forest and fire management activities, and milling. Inclusive of logging residues (e.g., bark, stems, leaves, branches), forest thinnings (e.g., removal of small trees to reduce fire danger), and mill residues (e.g., slabs, edgings, trimmings, sawdust) are considered in the analysis. This includes materials from public forestlands (e.g., state, federal), but not specially designated forests (e.g., roadless areas, national parks, wilderness areas) and includes sustainable harvesting criteria as described in the U.S. DOE Billion-Ton Update. The updated DOE Billion-Ton study was altered to include additional sustainability criteria. Some of the changes included: 24 § Alterations to the biomass retention levels by slope class (e.g., slopes with between 40% and 80% grade included 40% biomass left on-site, compared to the standard 30%). § Removal of reserved (e.g., wild and scenic rivers, wilderness areas, USFS special interest areas, national parks) and roadless designated forestlands, forests on steep slopes and in wet land areas (e.g., stream management zones), and sites requiring cable systems. § The assumptions only include thinnings for over-stocked stands and didn’t include removals greater than the anticipated forest growth in a state. § No road building greater than 0.5 miles. These additional sustainability criteria provide a more realistic assessment of available forestland than other studies. ICF extracted information from the U.S. DOE Bioenergy KDF, which includes information on forest residues such as thinnings, mill residues, and different residues from woods (e.g., mixedwood, hardwood, and softwood). ICF extracted data from the Bioenergy KDF at three price points: $30/ton, $60/ton, and $100/ton. The table below lists the energy content on a HHV basis for the various forest and forest product residue elements considered in the analysis. To estimate the RNG production potential, ICF assumed a 65% efficiency for thermal gasification systems. Table 21. Heating Values for Forestry and Forest Product Residues Forestry and Forest Product Btu/lb, dry MMBtu/ton, dry Other forest residue 8,597 17.19 Other forest thinnings 9,027 18.05 Primary mill residue 8,597 17.19 Secondary mill residue 8,597 17.19 Mixed wood, residue Hardwood, lowland, residue Hardwood, upland, residue 6,500 13.00 Softwood, natural, residue Softwood, planted, residue

24 Bryce Stokes, Department of Energy, “2011 Billion-Ton Update – Assumptions and Implications Involving Forest Resources,” September 29, 2011, http://web.ornl.gov/sci/ees/cbes/workshops/Stokes_B.pdf. 32

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ICF developed the RNG production potential from forest residues in a low and high scenario. § In the low scenario, ICF assumed that 30% of the forest and forestry product residues available up to $30/dry ton would be diverted to thermal gasification systems. § In the high scenario, ICF assumed that 60% of the forest and forestry product residues available up to $60/dry ton would be diverted to thermal gasification systems. ICF calculated the technical resource potential for RNG production from forest and forestry product residues assuming that all of the material available at $100/ton could be gasified at 100% efficiency. The figures below show the low and high RNG resource potential from the thermal gasification of forestry and forest product residues between 2025 and 2040. The table that follows includes the total annual RNG production potential (in units of tBtu/y) for 2040 in the low, high, and technical resource potential scenarios. Figure 18. RNG Production Potential from Forestry and Forest Product Residues, Low Resource Potential Scenario, in tBtu/y

40 New England 35 Mid-Atlantic 30 East North Central 25 West North Central 20 South Atlantic 15 East South Central 10 West South Central 5 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

Figure 19. RNG Production Potential from Forestry and Forest Product Residues, High Resource Potential Scenario, in tBtu/y

400 New England 350 Mid-Atlantic 300 East North Central 250 West North Central 200 South Atlantic 150 East South Central 100 West South Central 50 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

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Table 22. Annual RNG Production Potential from Forestry and Forest Product Residues, tBtu/y RNG Potential from Forestry and Forest Product Residues, tBtu/y RNG Potential East West East West New Mid- South Scenario North North South South Mountain Pacific England Atlantic Atlantic Central Central Central Central Low Resource 3.6 4.8 9.7 6.5 37.6 20.6 16.3 2.7 6.8 High Resource 7.3 9.7 19.3 13.0 75.2 41.3 37.1 19.3 13.6 Technical Resource 18.6 24.9 49.5 33.4 192.9 105.8 106.7 85.5 34.7

ICF estimates that between 109 and 236 tBtu/y of RNG could be produced by 2040 at the national level in the low and high scenarios, respectively from the thermal gasification of forest and forestry product residues. Energy Crops Energy crops are inclusive of perennial grasses, trees, and some annual crops that can be grown specifically to supply large volumes of uniform, consistent quality feedstocks for energy production. ICF extracted data from the Bioenergy KDF at three price points: $50/ton, $70/ton and $100/ton. The table below lists the energy content on a HHV basis for the various energy crops included in the analysis. To estimate the RNG production potential, ICF assumed a 65% efficiency for thermal gasification systems. Table 23. Heating Values for Energy Crops Energy Crop Btu/lb, dry MMBtu/ton, dry Willow 8,550 17.10 Poplar 7,775 15.55 Switchgrass 7,929 15.86 Miscanthus 7,900 15.80 Biomass sorghum 7,240 14.48 Pine 6,210 12.42 Eucalyptus 6,185 12.37 Energy cane 7,900 15.80

ICF developed the RNG production potential from energy crops in a low and high scenario. § In the low scenario, ICF assumed that 50% of the energy crops available at $50/dry ton would be diverted to thermal gasification systems. § In the high scenario, ICF assumed that 50% of the energy crops available at $70/dry ton would be diverted to thermal gasification systems. ICF calculated the technical resource potential for RNG production from energy crops assuming that all of the material available at $100/ton could be gasified at 100% efficiency. The figures below show the low and high RNG resource potential from the thermal gasification of energy crops between 2025 and 2040. The table that follows includes the total annual RNG production potential (in units of tBtu/y) for 2040 in the low, high, and technical resource potential scenarios.

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Figure 20. RNG Production Potential from Energy Crops, Low Resource Potential Scenario, in tBtu/y

60 New England

50 Mid-Atlantic East North Central 40 West North Central 30 South Atlantic East South Central 20 West South Central 10 Mountain Annual(tBtu/y) RNG Production 0 Pacific 2025 2030 2035 2040

Figure 21. RNG Production Potential from Energy Crops, High Resource Potential Scenario, in tBtu/y

350 New England 300 Mid-Atlantic

250 East North Central West North Central 200 South Atlantic 150 East South Central 100 West South Central 50 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

Table 24. Annual RNG Production Potential from Energy Crops, tBtu/y RNG Potential from Energy Crops, tBtu/y RNG Potential East West East West New Mid- South Scenario North North South South Mountain Pacific England Atlantic Atlantic Central Central Central Central Low Resource 0.2 2.2 1.5 35.4 18.1 9.3 56.5 0.2 0.0 High Resource 0.5 9.4 64.4 260.0 77.3 91.6 330.5 3.9 0.0 Technical Resource 3.0 84.3 872.5 1,508.1 357.1 460.8 1,266.4 48.7 0.0

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ICF estimates that between 123 and 838 tBtu/y of RNG could be produced by 2040 at the national level in the low and high scenarios, respectively from the thermal gasification of forest and forestry product residues. Renewable gas from MSW Municipal solid waste (MSW) represents the trash and various items that household, commercial, and industrial consumers throw away—including materials such as glass, construction and demolition (C&D) debris, food waste, paper and paperboard, plastics, rubber and leather, textiles, wood, and yard trimmings. About 25% of MSW is currently recycled, 9% is composted, and 13% is combusted for energy recovery. And the roughly 50% balance of MSW is landfilled. ICF limited our consideration to the potential for utilizing MSW that would otherwise be landfilled as a feedstock for thermal gasification; this excludes MSW that is recycled or directed to waste-to- energy facilities. ICF also excluded food waste from consideration in this sub-section, and opted to consider that feedstock as a separate resource for AD systems.25 ICF extracted information from the U.S. DOE Bioenergy KDF, which includes information collected as part of U.S. DOE’s Billion-Ton Report (updated in 2016). The Bioenergy KDF includes the following waste residues: C&D debris, paper and paperboard, plastics, rubber and leather, textiles, wood, yard trimmings, and other. ICF extracted data from the Bioenergy KDF at two price points: $30/ton and $100/ton. The table below lists the energy content on a HHV basis for the various components of MSW. To estimate the RNG production potential, ICF assumed a 65% efficiency for thermal gasification systems. Table 25. Heating Values for MSW Components MSW Component Btu/lb, dry MMBtu/ton, dry C&D waste 6,788 13.58 Other 5,600 11.20 Paper and paperboard 7,642 15.28 Plastics 19,200 38.40 Rubber and leather 11,300 22.60 Textiles 8,000 16.00 MSW wood 8,304 16.61 Yard trimmings 6,448 12.90

ICF developed the RNG production potential from MSW in a low and high scenario. § In the low scenario, ICF assumed that 30% of the non-biogenic fraction of MSW available at $30/dry ton from the Bioenergy KDF for relevant waste residues in MSW. ICF notes that at the price of $30/ton, the DOE reports no MSW wood or yard trimmings. § In the high scenario, ICF assumed that 60% of the non-biogenic fraction of MSW available at $100/dry ton from the Bioenergy KDF for the CD waste, other, paper and paperboard, plastics, rubber and leather, and textiles waste could be gasified; and that 75% of the MSW wood and yard trimmings could be gasified.

25 ICF notes that because the assessment of thermal gasification is limited to the non-biogenic fraction of MSW, the consideration of this material being diverted from landfills has no material impact on estimated RNG production potential from landfills. 36

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ICF calculated the technical resource potential from RNG production from MSW assuming that all of the material that is currently landfilled for each MSW component could be gasified at 100% efficiency. The figures below show the low and high RNG resource potential from the thermal gasification of the non-biogenic fraction of MSW between 2025 and 2040. The table that follows includes the total annual RNG production potential (in units of tBtu/y) for 2040 in the low, high, and technical resource potential scenarios. Figure 22. RNG Production Potential from Non-Biogenic MSW, Low Resource Potential Scenario, in tBtu/y

60 New England

50 Mid-Atlantic East North Central 40 West North Central 30 South Atlantic East South Central 20 West South Central 10 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

Figure 23. RNG Production Potential from Non-Biogenic MSW, High Resource Potential Scenario, in tBtu/y

140 New England 120 Mid-Atlantic

100 East North Central West North Central 80 South Atlantic 60 East South Central 40 West South Central 20 Mountain Annual RNG Production (tBtu/y) RNG AnnualProduction 0 Pacific 2025 2030 2035 2040

Table 26. Annual RNG Production Potential from MSW, tBtu/y RNG Potential from MSW, tBtu/y RNG Potential East West East West New Mid- South Scenario North North South South Mountain Pacific England Atlantic Atlantic Central Central Central Central

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Low Resource 14.4 40.6 45.9 17.7 56.9 11.2 15.3 8.8 45.4 High Resource 32.4 91.6 103.4 46.1 136.3 43.2 83.2 50.1 108.5 Technical Resource 81.1 229.6 259.2 115.5 341.6 108.4 208.5 125.6 271.9

ICF estimates that between 256 and 695 tBtu/y of RNG could be produced by 2040 at the national level in the low and high scenarios, respectively from the non-biogenic fraction of MSW via thermal gasification. RNG from P2G/Methanation Power-to-gas (P2G) is a form of energy technology that converts electricity to a gaseous fuel. Electricity is used to split water into hydrogen and oxygen, and the hydrogen can be further processed to produce methane when combined with a source of carbon dioxide. If the electricity is sourced from renewable resources, such as wind and solar, then the resulting fuels are carbon neutral. The key process in P2G is the production of hydrogen from renewably generated electricity by means of electrolysis. This hydrogen conversion method is not new, and there are three electrolysis technologies with different efficiencies and in different stages of development and implementation: § Alkaline electrolysis; § Proton exchange membrane electrolysis; and § Solid oxide electrolysis. The hydrogen produced from P2G is a highly flexible energy product that can be used in multiple ways. It can be: § Stored as hydrogen and used to generate electricity at a later time using fuel cells or conventional generating technologies. § Injected as hydrogen into the natural gas system, where it augments the natural gas supply. § Converted to methane and injected into the natural gas system. The last option, methanation, involves the combination of hydrogen with carbon dioxide (CO2), and converting the two gases into methane. The methane produced is RNG, and is a clean alternative to conventional fossil natural gas, as it can displace fossil natural gas for combustion in buildings, residences, vehicles and electricity generation. Methanation avoids the cost and inefficiency associated with hydrogen storage and creates more flexibility in the end use through the natural gas system. The P2G RNG conversion process can also be coordinated with conventional biomass-based RNG production by using the surplus CO2 in biogas to produce the methane, creating a productive use for the CO2. A critical advantage of P2G is that the RNG produced is a highly flexible and interchangeable carbon neutral fuel. With a storage and infrastructure system already established, RNG from P2G can be produced and stored over the long term, allowing for deployment during peak demand periods in the energy system. RNG from P2G also utilizes existing natural gas transmission and distribution infrastructure, which is highly reliable and efficient, and in many cases already paid for. The flexibility of hydrogen provides advantages beyond as an input to methanation for RNG. Hydrogen can be used in place of natural gas in many applications, and hydrogen can be mixed directly with natural gas in pipeline systems, although there are physical limits to the level of

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hydrogen blending in natural gas pipeline systems.26 In addition, currently most commercially produced hydrogen is derived from conventional natural gas and does not have the environmental benefits of carbon neutral hydrogen produced from P2G. Whether hydrogen or methane is the final product, P2G offers the potential to produce carbon neutral fuels from sustainable resources and leverage existing natural gas infrastructure for long- term and large-scale storage. Competing electric energy storage options, including batteries and pumped hydro storage, are expensive as a long-term energy storage option, and can be more expensive than P2G storage. P2G also offers other benefits, such as a fully dispatchable load capable of supplying grid balancing or ancillary services. ICF estimated the potential for P2G to contribute towards RNG production over a series of steps. P2G and Curtailment Firstly, ICF utilized our Integrated Planning Model P2G discussions often focus on the role and (IPM®), which provides true integration of scale of excess (curtailed) renewable electricity as the source for hydrogen and wholesale power, system reliability, environmental RNG production. constraints, fuel choice, transmission, capacity Renewable electricity generation is generally expansion, and all key operational elements of curtailed as a result of system-wide generators on the power grid in a linear optimization oversupply and local transmission framework. The model utilizes a Windows™-based constraints. database platform and interface that captures a The concept is simple: P2G systems could detailed representation of every electric boiler and use curtailed renewable electricity generator in the power market being modeled. The generation, and reduce the costs of fundamental logic behind the model determines the operating the electrolyzer. This would help least-cost means of meeting electric generation to maximize renewable electricity generation, simply by using hydrogen or energy and capacity requirements while complying methane as the renewable energy carrier with specified constraints, including air pollution instead of electrons. regulations, transmission constraints, and plant- The issue of curtailed renewable electricity, specific operational constraints. however, is a complicated one. A detailed ICF used the IPM platform to develop a supply-cost analysis of expected curtailment rates under increasingly stringent RPS programs was curve for renewable electricity, starting in 2025 and beyond the scope of this report. Instead, we going out to 2040. We did this over a series of acknowledge the importance of developing steps. Firstly, the model was constrained by all and deploying P2G systems to use curtailed finalized and on-the-books state-level RPS and electricity in the near term as a transitional Clean Energy Standard (CES) policies and regional carbonapproach markets. to achieve The model P2G cost does reductions. not explicitly capture renewable targets announced by municipalities and corporate actors. The RPS demand modeled represents a floor on incremental renewable demand, since the model conducts capacity expansion based on relative economics–to the extent that renewable energy is cost competitive relative to other technology types, the model will choose to build renewable energy even in excess of modeled targets. The table below shows the share of generation represented by renewable resource for each region (note that the regions in IPM are distinguished by independent system operator (ISO), regional transmission organization (RTO), reliability council, etc. and are not consistent with the US Census Regions that have been employed elsewhere in the study). The table also includes the share of electricity generation that is attributable to solar and wind.

26 For the purposes of this report, ICF did not assume any hydrogen blending into natural gas pipeline systems. 39

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Table 27. Renewable Share of Electricity Generation in RPS-Compliant Run using IPM Renewable Share: Renewable Share: Region Electricity Generation Solar and Wind 2030 2035 2040 2030 2035 2040 US 27% 28% 29% 20% 20% 21% Non CA- WECC 45% 45% 47% 19% 20% 22% CAISO 70% 69% 73% 49% 49% 56% SPP 46% 45% 44% 42% 41% 40% MISO 28% 29% 31% 24% 25% 25% SERC 8% 8% 10% 4% 4% 4% ERCOT 30% 27% 25% 29% 27% 25% ISONE 44% 47% 49% 30% 34% 36% NYISO 50% 51% 60% 29% 31% 39% PJM 13% 14% 14% 11% 12% 12% FRCC 12% 12% 12% 11% 11% 11%

In the last step of the analysis using the IPM platform, ICF made a simple calculation: We developed a supply-cost curve for renewable electricity generation by extracting the total consumption of renewable electricity (in GWh) by region in 2025, 2030, 2035, and 2040, assuming all RPS and CES policies are achieved on time. ICF then determined what the corresponding levelized cost of energy (LCOE) in $10/MWh increments up to $110/MWh would be to deploy the same number of generating assets to produce the same amount of renewable electricity. ICF used those estimates, as shown in the figure below, to develop an outlook for P2G using dedicated renewable electricity generation. Figure 24. Supply-Cost Curve for Dedicated Renewable Electricity for P2G Systems, 2025-2040 450,000 $110-$120/MWh 400,000 $100-$110/MWh 350,000 $90-$100/MWh 300,000 $80-$90/MWh 250,000 $70-$80/MWh $60-$70/MWh

(GWh) 200,000 150,000 $50-$60/MWh $40-$50/MWh 100,000 $30-$40/MWh 50,000

Dedicated Renewable Electricity Renewable Dedicated $20-$30/MWh 0 $10-$20/MWh 2025 2030 2035 2040

ICF determined how much hydrogen and methane could be produced using P2G / methanation systems based on the supply-cost curve constructed for dedicated renewable electricity generation. We assumed a capacity factor ranging from 50% to 80% for dedicated renewable

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electricity generation. The energy price in each scenario was based on the LCOE supply curve for renewable electricity generation. ICF limited our considerations for the low resource potential for RNG derived from P2G and methanation to the curtailed renewable electricity generation available and dedicated renewable electricity generation that is estimated to be available at a LCOE less than $50/MWh. In the high resource potential scenario, we included curtailed renewable electricity generation and dedicated renewable electricity generation that is estimated to be available at a LCOE less than $60/MWh. ICF assumed that all of the renewable electricity would be available to an electrolyzer to produce hydrogen. Furthermore, ICF assumed the co-location of a methanation unit. The figure below includes the assumed conversion efficiencies for hydrogen production from an electrolyzer (blue) and for the methanation reaction to produce RNG for injection (orange). Figure 25. Assumed Efficiency for Electrolysis and Methanation, 2020-2040

85%

80%

75%

70%

65% Efficiency, Electrolyzer Efficiency, Methanator

System System Efficiencies 60%

55%

50% 2020 2025 2030 2035 2040

These assumptions yield the resource potential listed in Table 28 below; which also includes the hydrogen produced in the first step using P2G. The low and the high resource potential estimates are presented assuming capacity factors of 5% and 10% for systems using curtailed electricity and capacity factors of 50% and 80% for systems using dedicated renewable electricity generation.

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Table 28. Annual H2 and RNG Production (in tBtu /y) from P2G using Dedicated Renewable Electricity Generation, 2025-2040

Resource: Capacity 2025 2030 2035 2040 Dedicated RE Factor 50% 11.5 297.1 372.2 447.1 Low 80% 18.4 475.3 595.6 715.4 50% 11.5 364.6 448.7 530.2 High 80% 18.4 583.4 718.0 848.3 Max 95% 93.2 935.7 1,064.0 1,210.5 50% 8.6 230.2 297.8 357.7 Low 80% 13.8 368.4 476.5 572.3 50% 8.6 282.5 359.0 424.1 High 80% 13.8 452.1 574.4 678.7 Max 95% 74.5 748.5 851.2 968.4

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Greenhouse Gas Emissions of RNG GHG Accounting Framework and Methodology GHG emission accounting for a given source of emissions relies on the application of an emission factor to activity data. In the example below, we use the emission factor for fossil or geological natural gas to determine the annual GHG emissions associated with an average household’s natural gas consumption (the activity data) using data from the Environmental Protection Agency (EPA)27 and the American Gas Association (AGA):28 12 34 6 7789: 12 34 6 !"#$$#%&'()*%+_-. 0 5 ; × =)*#>#*?@(*( 0 ; = .E._!"#$$#%&$ 0 5 ;, calculated as: 7789: AB:C6 AB:C6 JK LM O PPQ*R JK LM O 53.11 N × 63.5 = 3,372 N PPQ*R ℎ%R$O ℎ%R$O RNG represents a valuable renewable energy source with a low or net negative emissions factor depending on the feedstock and the accounting framework. The GHG emission accounting method and scope employed can have a significant impact on how GHG emission factors for RNG are reported and estimated. GHG emissions accounting becomes complex when an assessment scope includes a diverse set of sources. This is most often seen in GHG emission inventories for agencies, corporations, and jurisdictions (e.g., community, city, county, state, country) where entities must account for a wide range of sectors (e.g., transportation, energy, agriculture). Each sector has an array of emissions sources with unique variations in emission factors, activity data, and other aspects to consider. GHG emission profiles can be complex for specific products or resources, when a scope may consider elements outside of product use, such as emissions from supply chains, co-products, and disposal. For example, California’s Low Carbon Fuel Standard (LCFS) relies on a life-cycle assessment approach for estimating carbon intensities of transportation fuels. As a result, LCFS emissions for a specific transportation fuel pathway includes all emission sources in the fuel lifecycle from resource extraction to final consumption in a vehicle. IPCC Guidelines for Biogenic Fuel Sources GHG emission accounting for inventories typically relies on guidance from the Intergovernmental Panel on Climate Change (IPCC) developed in 2006.29 The IPCC provides guidance for different levels of detail depending on the availability of data and capacity of the inventory team for all sectors typically considered in a GHG inventory. GHG emission reporting programs that address a specific sector or subsector, like the LCFS, may have unique guidelines that diverge from IPCC and typical inventories in accounting methods. IPCC guidelines state that CO2 emissions from biogenic fuel sources (e.g., biogas or biomass based RNG) should not be included when accounting for emissions in combustion – only CH4 and N2O are included. This is to avoid any upstream “double counting” of CO2 emissions that occur in the agricultural or land use sectors per IPCC guidance.

27 US EPA. 2018. Emission Factors for Greenhouse Gas Inventories, Available online at https://www.epa.gov/sites/production/files/2018-03/documents/emission-factors_mar_2018_0.pdf. 28 Personal communication with AGA. 29 IPCC. 2006. 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Available at: https://www.ipcc- nggip.iges.or.jp/public/2006gl/. 44

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Other approaches exclude biogenic CO2 in combustion as it is assumed that the CO2 sequestered by the biomass during its lifetime offsets combustion CO2 emissions. This method of excluding biogenic CO2 is still commonly practiced for RNG users and producers. Greenhouse Gas Protocol The Greenhouse Gas Protocol is a commonly used set of reporting standards developed by the World Resources Institute and the World Business Council for Sustainable Development. A GHG Protocol-based approach is most common with corporations, but still incorporates many of the same sources and emission factors used by jurisdictions and public agencies. The GHG Protocol uses “Scope” levels to define the different sources and activity data included within an assessment. Instead of thinking in terms of geographic or sector-based boundaries, the Protocol groups emissions in direct and indirect categories through these Scopes. Figure 26 shows how the Protocol groups these emission sources by Scopes, and how they relate to an organization’s operations. Figure 26. Scopes for categorizing emissions under the GHG Protocol (GHG Protocol 2019).

Organizations most often may limit their assessment to Scope 1 and 2 emissions, which includes directly controlled assets. Scope 3 emissions reflect a life cycle assessment approach that includes supply chain activities and associated, but not directly controlled, organizations. There is often confusion about who can claim and monetize the environmental benefits of RNG production and consumption across various stakeholders and GHG reporting structures. For example, a corporation based in California buys RNG from a fuel distributor to fuel their fleet of shuttle buses. The RNG was produced out of state and transported and sold in California to take advantage of the LCFS credit program. The value of the LCFS credits are owned and monetized by the various actors within the fuel production supply chain. However, the corporation purchasing the RNG as an end-user can still factor in the fuel’s low carbon intensity into their corporate emissions accounting by including the volumes purchased in their Scope 1 emissions.

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RNG and GHG Accounting There are two broad methodologies to account for the GHG emissions from RNG: a combustion accounting framework or a lifecycle accounting framework. § A combustion GHG accounting framework is the standard approach for most volumetric GHG targets, inventories and mitigation measures (e.g., RPS programs, carbon taxes, cap- and-trade programs, etc.) as they are more closely tied to a particular jurisdiction – where the emissions physically occur. Using the combustion framework, the CO2 emissions from the combustion of biogenic renewable fuels are considered zero, or carbon neutral. In other words, RNG has a carbon intensity of zero. This includes RNG from any biogenic feedstock, including landfill gas, animal manure and food waste. Upstream emissions, whether positive (electricity emissions associated with biogas processing) or negative (avoided methane emissions), are not included. § When using a lifecycle accounting methodology RNG’s carbon intensity (i.e., GHG emissions per unit of energy) varies substantially between feedstocks and production methods. Carbon intensities can also vary by location of production and how the fuel is transported and distributed. The GHG accounting methods and scopes previously discussed dictate which of RNG’s life-cycle elements are included as a carbon intensity in emissions reporting. Figure 27 below shows the various steps in RNG production—including the collection and processing of raw biogas, injection into the pipeline, transmission and distribution to end users, and then finally use as a fuel in various applications. The combustion approach (in green) focuses on the end use and recognizes RNG as a biogenic source. The lifecycle approach (in blue) accounts for all the emissions associated with each step in the supply chain associated with RNG production. Figure 27. Overview of GHG Accounting Frameworks for RNG

GHG Emissions from RNG Resource Assessment ICF reports the GHG emission reductions for RNG consistent with the combustion approach outlined pre IPCC guidelines stating that emissions from biogenic fuel sources should not be included when accounting for emissions in combustion. This accounting approach is employed to avoid any upstream “double counting” of emissions that occur in the agricultural or land use sectors per IPCC guidance. ICF did account for N2O and CH4 emissions during combustion of RNG. 46

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ICF used an emissions factor of 53.06 kg/MMBtu for fossil natural gas. ICF also developed an estimated emissions factor of 15 kg/MMBtu for renewable gas from thermal gasification of MSW and incorporated that into the analysis. The tables below show the range of GHG emission reductions in units of million metric tons (MMT) for the low and high resource potential scenarios. ICF estimates that in the low resource potential scenario, about 101 MMT of GHG emissions would be reduced through the deployment of RNG; and in the high resource potential scenario, 235 MMT of GHG emissions could be reduced. The GHG emission reduction potential in the low and high resource potential scenarios is equivalent to displacing 59-95% of the average GHG emissions attributable to natural gas consumption in the residential energy sector nationwide over the ten-year period 2009-2018 (see Figure 28 below). Average CO2 Emissions (MMT) from Figure 28. Average Annual CarbonNatural Dioxide Emissions Gas Consumption, (in MMT) from Natural 2009 Gas- Consumption2018 in the U.S. 2009-2018 Residential

Electric Gen 248 466

Commercial 170

Industrial

392

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Table 29. GHG Emission Reductions (in MMT) for RNG in the Low Resource Potential Case Low RNG Resource Case | GHG Emission Reduction Potential, MMT Feedstock East North West North South East South West South New England Mid-Atlantic Mountain Pacific Total Central Central Atlantic Central Central RNG from biogenic or renewable resources Landfill Gas 0.7 3.1 5.6 1.5 4.7 1.9 3.5 2.0 5.1 28.0 Animal Manure 0.4 0.6 1.6 2.4 1.7 1.0 1.9 1.5 1.1 12.3 WRRF 0.1 0.2 0.2 0.1 0.2 0.1 0.1 0.1 0.2 1.2

Food Waste 0.1 0.3 0.3 0.1 0.3 0.0 0.1 0.0 0.3 1.5 Ag Residue 0.0 0.2 3.0 7.7 0.5 0.2 0.6 0.6 0.8 13.5 Forestry and Forest 0.2 0.3 0.5 0.3 2.0 1.1 0.9 0.1 0.4 5.8 Residue Energy Crops 0.0 0.1 0.1 1.9 1.0 0.5 3.0 0.0 0.0 6.5 Sub-Total 1.5 4.8 11.4 13.9 10.4 4.7 10.0 4.4 7.8 68.9 Renewable gas from MSW MSW 0.5 1.5 1.7 0.7 2.2 0.4 0.6 0.3 1.7 9.8 RNG from P2G / Methanation P2G / Methanation 22.3 Totals 2.0 6.3 13.2 14.6 12.5 5.2 10.6 4.7 9.6 100.9

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Table 30. GHG Emission Reductions (in MMT) for RNG in the High Resource Potential Case High RNG Resource Case | GHG Emission Reduction Potential, MMT Feedstock East North West North South East South West South New England Mid-Atlantic Mountain Pacific Total Central Central Atlantic Central Central RNG from biogenic or renewable resources Landfill Gas 1.2 5.0 9.2 2.5 7.7 3.1 5.6 3.3 8.2 45.9 Animal Manure 0.8 1.3 3.2 4.7 3.4 2.0 3.8 3.1 2.2 24.5 WRRF 0.1 0.3 0.4 0.1 0.3 0.1 0.2 0.1 0.3 1.8 Food Waste 0.2 0.5 0.5 0.2 0.7 0.2 0.4 0.2 0.5 3.4

Ag Residue 0.0 0.5 7.6 19.2 1.4 0.4 1.5 1.4 2.0 34.0 Forestry and Forest 0.4 0.5 1.0 0.7 4.0 2.2 2.0 1.0 0.7 12.5 Residue Energy Crops 0.0 0.5 3.4 13.8 4.1 4.9 17.5 0.2 0.0 44.4 Sub-Total 2.7 8.6 25.3 41.2 21.5 12.9 31.1 9.3 14.0 166.6 Renewable gas from MSW MSW 1.2 3.5 3.9 1.8 5.2 1.6 3.2 1.9 4.1 26.4 RNG from P2G / Methanation P2G / Methanation 42.3 Totals 3.9 12.1 29.3 42.9 26.7 14.5 34.2 11.2 18.1 235.3

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RNG Cost Assessment ICF developed assumptions for the capital expenditures and operational costs for RNG production from the various feedstock and technology pairings outlined previously—and developed supply- cost estimates for RNG with an outlook to 2040. ICF characterizes costs based on a series of assumptions regarding the production facility sizes (as measured by gas throughput in units of standard cubic feet per minute [SCFM]), gas upgrading and conditioning and upgrading costs (depending on the type of technology used, the contaminant loadings, etc.), compression, and interconnect for pipeline injection. We also include operational costs for each technology type. The table below outlines some ICF’s baseline assumptions that we employ in our RNG costing model for anaerobic digestion systems and thermal gasification systems. Table 31. Illustrative Cost Assumptions Developed to Estimate RNG Production Costs in 2040 Cost Parameter ICF Cost Assumptions

• Differentiate by feedstock and technology type: AD and TG Facility Sizing • Prioritize larger facilities to the extent feasible, but driven by resource estimate Gas Conditioning • These costs depend on the feedstock and the technology required. and Upgrade

Compression • Capital costs for compressing the conditioned/upgraded gas for pipeline injection.

• Costs for each equipment type–digesters, conditioning equipment, collection Operational Costs equipment, and compressors–as well as utility charges for estimated electricity consumption.

Feedstock • Feedstock costs (for thermal gasification), ranging from $30 to $100 per dry ton.

• Financing costs, including carrying costs of capital (assuming a 60/40 debt/equity ratio Financing and an interest rate of 7%), an expected rate of return on investment (set at 10%), and a 15 year repayment period.

• Costs of interconnection—representing the point of receipt and any pipeline extension. This cost is in line with financing, constructing, and maintaining a pipeline of about 1- Interconnection mile in length. The costs of delivering the same volumes of RNG that require pipeline construction greater than 1-mile will increase, depending on feedstock/technology type, with a typical range of $1-5/MMBtu.

• 20 years. The levelized cost of gas was calculated based on the initial capital costs in Project lifetimes Year 1, annual operational costs discounted at an annual rate of 5% over 20 years, and biogas production discounted at an annual rate of 5% for 20 years.

ICF notes that our cost estimates are not intended to replicate a developer’s estimate when deploying a project. For instance, ICF recognizes that the cost category “conditioning and upgrading” actually represents an array of decisions that a project developer would have to make with respect to CO2 removal, H2S removal, siloxane removal, N2/O2 rejection, deployment of a thermal oxidizer, etc. Furthermore, we understand that project developers have reported a wide range of interconnection costs, with numbers as low as $200,000 reported in some states, and as high as $9 million in other states. We appreciate the variance between projects, including those that use anaerobic digestion, thermal gasification, or power-to-gas technologies; and our supply- 50

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cost curves are meant to be illustrative, rather than deterministic. This is especially true of our outlook to 2040—we have not included significant cost reductions that might occur as a result of a rapidly growing RNG market, or sought to capture some technological breakthrough or breakthroughs. We have made some assumptions in line with those in the publicly available literature regarding potential decreases in the costs of P2G systems; however, for anaerobic digestion and thermal gasification systems we have focused on projects that have reasonable scale, representative capital expenditures, and reasonable operations and maintenance estimates. ICF’s cost estimates in the following sections are shown for 2040 (reported in 2019 dollars); and we have made only modest assumptions with respect to the potential for RNG cost reductions. The most significant assumption in our outlook to 2040 is the presumption that the underlying structure of the market will change. Today in the U.S., there is no standard market price for RNG— rather, the market is largely driven by the value of environmental commodities such as those derived from participating in the federal Renewable Fuel Standard and/or California’s LCFS program. For instance, many landfill gas projects are estimated to produce RNG at a cost of $10- 20/MMBtu, and dairy manure projects may produce RNG at a cost of closer to $40/MMBtu. ICF reports substantial RNG production volumes at prices lower than $20/MMBtu (see below); so how can we reconcile today’s estimated production costs of $10-$40/MMBtu with only 40 tBtu/y of RNG production from AD systems with cost estimates for a market producing up to 4,500 tBtu/y using a combination of AD systems, TG systems, and P2G systems? Clearly, this is a non-trivial exercise. And ultimately, ICF’s cost estimates focus on a more mature market with some economies of scale achieved as a result of hundreds of projects being developed to achieve the volumes presented. Further, we assume that contractual arrangements will be considerably different and local/regional barriers with respect to RNG pipeline injection have been overcome. Together, these assumptions help us to develop a reasonable outlook on RNG production costs to 2040.

Achieving Significant RNG Production Cost Reductions Advanced manufacturing (or the lack thereof) will play an important role in making RNG more cost-competitive with geological natural gas and other fossil-based resource. To help achieve more significant reductions, the various aspects of RNG production (e.g., gas receipt skids, gas separation and upgrading equipment, conversion processes, etc.) need to be modular, autonomous, process intensive and manufactured in large numbers. Consider, for instance, that the DOE’s Office of Energy Efficiency and Renewable Energy announced in 2016 that the American Institute of Chemical Engineers was selected to lead a new Manufacturing USA Institute, referred to as the Rapid Advancement in Process Intensification Deployment (RAPID) Institute. The RAPID Institute is focused on developing breakthrough technologies to boost the energy productivity and energy efficiency through manufacturing processes in industries such oil and gas, pulp and paper and various domestic chemical manufacturers. A similar effort dedicated towards RNG and other biomass conversion technologies could help reduce costs substantially.

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RNG from Anaerobic Digestion Landfill Gas ICF developed assumptions for each region by distinguishing between four types of landfills: candidate landfills30 without collection systems in place, candidate landfills with collection systems in place, landfills31 without collection systems in place, and landfills with collections systems in place.32 For each region, ICF further characterized the number of landfills across these four types of landfills, distinguishing facilities by estimated biogas throughput (reported in units of standard cubic feet per minute of biogas). For utility costs, ICF assumed 25 kWh per MMBtu of RNG injected and 6% of geological or fossil natural gas used in processing. Electricity costs and delivered natural gas costs were reflective of industrial rates reported at the state level by the EIA. The table below summarizes the key parameters that ICF employed in our cost analysis of LFG. Table 32. Cost Consideration in Levelized Cost of Gas Analysis for RNG from Landfill Gas Factor Cost Elements Considered Costs

Performance • Capacity factor • 95%

• Construction / Engineering • 25% of uninstalled costs of equipment Installation Costs • Owner’s Cost • 10% of uninstalled costs of equipment • CO2 separation • $2.3 to $7.0 million depending on facility Gas Upgrading • H2S removal • $0.3 to $1.0 million depending on facility • N2/O2 removal • $1.0 to $2.5 million depending on facility • Electricity: 25 kWh/MMBtu • 4.6—13.7 ¢/kWh Utility Costs • Natural Gas: 6% of product • $3.00-$8.25/MMBtu Operations & • 1 FTE for maintenance • 10% of installed capital costs Maintenance • Miscellany • Interconnect • $2 million For Injection • Pipeline • $1.5 million • Compressor • $0.2-0.5 million • Rate of Return • 10% Financial Parameters • Discount Rate • 7%

The figure below includes ICF’s estimates for the RNG from landfill gas supply curve.

30 The EPA characterizes candidate landfills as one that is accepting waste or has been closed for five years or less, has at least one million tons of WIP, and does not have an operational, under-construction, or planned project. Candidate landfills can also be designated based on actual interest by the site. 31 Excluding those that are designated as candidate landfills. 32 Landfills that are currently producing RNG for pipeline injection are included here. 52

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Figure 29. Supply-Cost Curve for RNG from Landfill Gas ($/MMBtu vs tBtu)

$20 $18 $16 $14 $12 $10 $8 $6 RNG Cost Cost RNG ($/MMBtu) $4 $2 $0 0 100 200 300 400 500 600 700 800 RNG from Landfill Gas (trillion Btu)

Animal Manure ICF developed assumptions for each region by distinguishing between animal manure projects, based on a combination of the size of the farms and assumptions that certain areas would need to aggregate or cluster resources to achieve the economies of scale necessary to warrant an RNG project. There is some uncertainty associated with this approach because an explicit geospatial analysis was not conducted; however, ICF did account for considerable costs in the operational budget for each facility assuming that aggregating animal manure would potentially be expensive. The table below includes the main assumptions used across regions—including national average estimates for the cost per MMBtu across the various buckets. We have included the number of dairy cows by way of reference to help contextualize the results for the reader; note, however, that the final analysis will manure from dairy cows, beef cows, chickens (layers and boilers), turkey, and swine.

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Table 33. Cost Consideration in Levelized Cost of Gas Analysis for RNG from Animal Manure Factor Cost Elements Considered Costs

Performance • Capacity factor • 95%

• Construction / Engineering • 25% of uninstalled costs of equipment Installation Costs • Owner’s Cost • 10% of uninstalled costs of equipment • CO2 separation • $2.3 to $7.0 million depending on facility Gas Upgrading • H2S removal • $0.3 to $1.0 million depending on facility • N2/O2 removal • $1.0 to $2.5 million depending on facility • Electricity: 30 kWh/MMBtu • 4.6—13.7 ¢/kWh Utility Costs • Natural Gas: 6% of product • $3.00-$8.25/MMBtu Operations & • 1 FTE for maintenance • 15% of installed capital costs Maintenance • Miscellany • Interconnect • $2.0 million For Injection • Pipeline • $1.5 million • Compressor • $0.2-0.5 million • Value of digestate • Valued for dairy at about $100/cow/y Other • Tipping fee • Excluded from analysis • Rate of Return • 10% Financial Parameters • Discount Rate • 7%

ICF reports a range of costs for RNG from animal manure at $18.4/MMBtu to $32.6/MMBtu. Water Resource Recovery Facilities ICF developed assumptions for each region by distinguishing between water resource recovery facilities based on the throughput of the facilities. The table below includes the main assumptions used across regions—including national average estimates for the cost per MMBtu across the various facility sizes. Table 34. Cost Consideration in Levelized Cost of Gas Analysis for RNG from WRRFs Factor Cost Elements Considered Costs

Performance • Capacity factor • 95%

• Construction / Engineering • 25% of uninstalled costs of equipment Installation Costs • Owner’s Cost • 10% of uninstalled costs of equipment • CO2 separation • $2.3 to $7.0 million depending on facility Gas Upgrading • H2S removal • $0.3 to $1.0 million depending on facility • N2/O2 removal • $1.0 to $2.5 million depending on facility • Electricity: 26 kWh/MMBtu • 4.6—13.7 ¢/kWh Utility Costs • Natural Gas: 6% of product • $3.00-$8.25/MMBtu Operations & • 1 FTE for maintenance • 10% of installed capital costs Maintenance • Miscellany • Interconnect • $2.0 million For Injection • Pipeline • $1.5 million • Compressor • $0.2-0.5 million • Rate of Return • 10% Financial Parameters • Discount Rate • 7% 54

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ICF reports a range of costs for RNG from WRRFs at $7.4/MMBtu to $26.1/MMBtu. Food Waste ICF made the simplifying assumption that food waste processing facilities would be purpose built, and be capable of processing 60,000 tons of waste per year—ICF estimates that these facilities would produce about 500 standard cubic feet per minute (SCFM) of biogas for conditioning and upgrading before pipeline injection. In addition to the other costs included in other AD systems, we also included assumptions about the cost of collecting food waste and processing it accordingly. Table 35. Cost Consideration in Levelized Cost of Gas Analysis for RNG from Food Waste Factor Cost Elements Considered Costs • Capacity factor • 95% Performance • Processing Capability • 60,000 tons per year • Organics Processing • $10.0 million Dedicated Equipment • Digester • $12.0 million • Construction / Engineering • 25% of uninstalled costs of equipment Installation Costs • Owner’s Cost • 10% of uninstalled costs of equipment • CO2 separation • $2.3 to $7.0 million depending on facility Gas Upgrading • H2S removal • $0.3 million • N2/O2 removal • $1.0 million • Electricity: 28 kWh/MMBtu • 4.6—13.7 ¢/kWh Utility Costs • Natural Gas: 5% of product • $3.00-$8.25/MMBtu • 1.5 FTE for maintenance Operations & Maintenance • 15% of installed capital costs • Miscellany

Other • Tipping fees • Varied by region;

• Interconnect • $2.0 million For Injection • Pipeline • $1.5 million • Compressor • $0.2-0.5 million • Rate of Return • 10% Financial Parameters • Discount Rate • 7%

ICF assumed that food waste facilities would be able to offset costs with tipping fees. ICF used values presented by an analysis of municipal solid waste landfills by Environmental Research & Education Foundation (EREF). The tipping fees reported by EREF for 2018 are shown in the table below.

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Table 36. Average Tipping Fee by Region33 Region Tipping Fee, 2018 Pacific: AK, AZ, CA, HI, ID, NV, OR, WA $68.46 Northeast: CT, DE, ME, MD, MA, NH, NJ, NY, PA, RI, VA, WV $67.39 Midwest: IL, IN, IA, KS, : MI, MN, MO, NE, OH, OH, WI $46.89 Mountains / Plains: CO, MT, ND, SD, UT, WY $43.57 Southeast: AL, FL, GA, KY, MS, NC, SC, TN $43.32 South Central: AR, LA, NM, OK, TX $34.80 National Average $55.11

ICF assumed that anaerobic digesters discounted the tipping fee compared to MSW landfills, and used a 20% discount to those values listed in the table.34 ICF reports an estimated cost of RNG from food waste of $19.4/MMBtu to $28.3/MMBtu. RNG from Thermal Gasification ICF used similar assumptions across the thermal gasification of feedstocks, including agricultural residue, forestry residue, energy crops, and municipal solid waste (MSW).35 There is considerable uncertainty around the costs for thermal gasification of feedstocks, as the technology has only been deployed at pilot scale to date or in the advanced stages of demonstration at pilot scale. This is in stark contrast to the anaerobic digestion technologies considered previously. ICF reports here on the three illustrative facilities that we employed for conducting the cost analysis—distinguished by the amount of feedstock processed daily (in units of tons per day).

33 As reported by EREF; available online at https://www.waste360.com/landfill-operations/eref-study-shows- continued-increase-average-msw-landfill-tip-fees. 34 A report entitled Business Analysis of Anaerobic Digestion in the USA by Renewable Waste Intelligence notes that “a lower tipping fee (approximately by $10) than landfill is required in order to incentivize waste management companies to separate” waste from trash and deliver it to an AD facility. ICF assumed a 20% discount from the tipping fees reported would be a sufficient incentive to deliver the feedstock to an AD facility. 35 Note that MSW here refers to the non-organic, non-biogenic fraction of the MSW stream, which is assumed to be a mix of, including, but not limited to construction and demolition debris, plastics, rubber and leather, etc.. 56

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Table 37. Cost Consideration in Levelized Cost of Gas Analysis for RNG from Thermal Gasification Factor Cost Elements Considered Costs • Capacity factor • 90% Performance • Processing Capability • 1,000-2,000 tpd • $20-22 million • Feedstock Handling (drying, storage) • $60 million • Gasifier • $25 million • CO2 removal • $10 million Dedicated Equipment • Syngas Reformer • $20 million & Installation Costs • Methanation • $10 million • Other (cooling tower, water treatment) • • Miscellany (site work, etc.) • • Construction/ engineering • All-in: $335 million for 1,000 tpd • Electricity: 30 kWh/MMBtu • 4.6—13.7 ¢/kWh Utility Costs • Natural Gas: 6% of product • $3.00-$8.25/MMBtu • Feedstock Operations & • 3 FTE for maintenance • $30-$100/dry ton Maintenance • Miscellany: water sourcing, • 12% of installed capital costs treatment/disposal • Interconnect • $2.0 million For Injection • Pipeline • $1.5 million • Compressor • $0.2-0.5 million • Rate of Return • 10% Financial Parameters • Discount Rate • 7%

ICF applied these estimates across each of the four feedstocks, their corresponding feedstock cost estimates, and assumed that the smaller facilities processing 1,000 tons per day would represent 50% of the processing capacity, and that the larger facilities processing 2,000 tons per day would represent the other 50% of the processing capacity. The number of facilities built in each region was constrained by the resource assessment. ICF reports an estimated levelized costs of RNG from thermal gasification as follows: § Agricultural residues: $18.3/MMBtu to $27.4/MMBtu § Forestry and forest residues: $17.3/MMBtu to $29.2/MMBtu § Energy crops: $18.3/MMBtu to $31.2/MMBtu § MSW: $17.3/MMBtu to $44.2/MMBtu RNG from Power-to-Gas / Methanation ICF developed the levelized cost of energy for P2G systems using a combination of an electrolyzer and a methanator to produce RNG for pipeline injection. The main cost considerations include: installed cost of electrolyzers on a dollar per kW basis ($/kW), the installed cost of a methanation system on a $/kW basis, the cost of RNG compression and interconnect for pipeline injection, and the cost of electricity used to run the P2G system. ICF also estimated the operations and maintenance (O&M) costs of both the electrolyzer and the methanator. ICF notes that we assume that the renewable electricity is dedicated to the P2G system and co-located, thereby reducing other electricity costs (e.g., transmission and distribution) considerably. ICF did not quantify:

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§ The costs of CO2 that would be required for the methanation reaction; the underlying assumption is that the cost of CO2 would be a marginal contributor to the overall cost of the system, and that it would be available at a low cost (e.g., less than $30 per ton). § The costs of a heat sink for the waste heat generated from the methanation reaction, or the corresponding benefits of repurposing this heat. The graph below illustrates ICF’s assumptions regarding the installed costs of electrolyzers—we assumed that the resource base for electrolyzers would be some blend of proton exchange membrane (PEM), alkaline systems, and solid oxide systems. Rather than be deterministic about which technology will be the preferred technology, we present the cost as a blended average of the $/kW installed. This is based on ICF’s review of literature and review of assumptions developed by UC Irvine. 36 Figure 30. Installed Capacity Cost of Electrolyzers, $/kW, 2020-2040

1,200

1,000

800

600

400 Electrolyzer Costs ($/kW) 200

0 2020 2025 2030 2035 2040

ICF assumed a decreasing cost of methanation technology consistent with the figure below, presented in units of $/kW.

36 Draft Results: Future of Natural Gas Distribution in California, CEC Staff Workshop for CEC PIER-16-011, June 6, 2019, available online at https://ww2.energy.ca.gov/research/notices/2019-06-06_workshop/2019-06- 06_Future_of_Gas_Distribution.pdf. 58

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Figure 31. Installed Capacity Cost of Methanator, $/kW, 2020-2040

1,200

1,000

800

600

400 Electrolyzer Costs ($/kW) 200

0 2020 2025 2030 2035 2040

The figure below includes the assumed conversion efficiencies for hydrogen production from electrolyzers (blue) and for the methanation reaction to produce RNG for injection (orange). Figure 32. Assumed Efficiency for Electrolysis and Methanation, 2020-2040

85%

80%

75%

70%

65% Efficiency, Electrolyzer Efficiency, Methanator

System System Efficiencies 60%

55%

50% 2020 2025 2030 2035 2040

ICF developed our cost estimates assuming a 50 MW system for P2G co-located with methanation capabilities, and included the costs of compression for pipeline injection, interconnection costs, and pipeline costs. We assumed an electricity cost of $42/MWh based on the supply curve for dedicated renewables that we developed using IPM. We assumed operational costs of 10% and 7% of capex, respectively for the electrolyzer and the methanator; and we assumed operational costs of 5% of capex for pipeline and interconnect systems. The figure below shows the decreasing LCOE for RNG from P2G systems using these baseline level assumptions; the blue line shows the costs assuming a 50% capacity factor for the system and the orange line shows the costs assuming an 80% capacity factor for the system.

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Figure 33. Estimated RNG costs from P2G / Methanation ($/MMBtu) as a function of installed capacity of P2G systems $60 CF_80% $50 CF_50%

$40

$30

($/MMBtu) $20

$10 P2G / Methanation LCOE LCOE / P2GMethanation $0 0 100 200 300 400 500 Installed Capacity (GW)

Combined Supply Curves ICF estimates that more than half of the RNG production potential in the high resource potential scenario would be available at less than $20/MMBtu, as shown in the figure below. Generally speaking, ICF finds the front end of the supply curve to be landfill gas projects and WRRFs that are poised to move towards RNG production. As the estimated costs move to higher costs, the supply curve includes some of the larger animal manure projects and the well-positioned food waste projects. The tail end of the curve, showing the upward sloping to the right captures the first tranche of thermal gasification projects that we assume will just start to break that $20/MMBtu level by 2040. Figure 34. Combined RNG Supply-Cost Curve, less than $20/MMBtu in 2040

$25

$20

$15

$10

$5 Production Cost ($/MMBtu)Cost Production $0 0 500 1,000 1,500 2,000 2,500 RNG Production Potential (tBtu/y)

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GHG Cost-Effectiveness The GHG cost-effectiveness is reported on a dollar per ton basis, and is calculated as the difference between the emissions attributable to RNG and fossil natural gas. For this report, ICF followed IPCC guidelines and does not include biogenic emissions of CO2 from RNG. The cost- effectiveness calculation is simply as follows ∆(#$% , +,--./ $% ) &'() &'() = , 0.05306 78 9:;< where the RNGcost is simply the cost from the estimates reported previously. For the purposes of this report, we use a fossil natural gas price equal to the average Henry Hub spot price reported by the EIA in the 2019 Annual Energy Outlook, calculated as $3.89/MMBtu. In other words, the front end of the supply-cost curve is showing RNG is just under $7/MMBtu, which is equivalent to about $55-60/ton. As the estimated RNG cost increases to $20/MMBtu, we report an estimated cost-effectiveness of about $300/ton. The GHG cost-effectiveness of RNG as a mitigation strategy is competitive with and in many cases lower than the costs per ton that are associated with other strategies to reduce GHG emissions, such as electrification at $572-806/ton 37 and atmospheric removal of CO2 at $94-232/ton.

37 Cost estimates are from Implications of Policy-Driven Residential Electrification, AGA, 2018 study. While the cost estimates are not fully "apples-to-apples" comparison as the scope of the referenced study is different from this report, it serves as a useful point of comparison. 61

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Key Findings ICF’s assessment of RNG potential in the United States demonstrate that there is significant resource potential in both the low and the high cases considered—and in both, ICF used moderately conservative assumptions with respect to the utilization of feedstocks and technological advancements. § In the low resource potential scenario, ICF estimates that about 1,650 trillion Btu (tBtu) of RNG can be produced annually for pipeline injection by 2040. That estimate increases to 1,910 tBtu per year when including the potential for the non-biogenic fraction of MSW. § In the high resource potential scenario, ICF estimates that about 3,780 tBtu of RNG can be produced annually for pipeline injection by 2040. That estimate increases to 4,510 tBtu per year when including the potential for the non-biogenic fraction of MSW. For the sake of comparison, ICF notes that the 10-year average (2009-2018) of residential natural gas consumption is 4,846 tBtu. The reported RNG resource potential estimates reported here are 90% and 180% increases from the comparable resource potential scenarios from 2011 AGF Study. These changes are largely attributable to improved access to data regarding potential feedstocks for RNG production and are generally not attributable to more aggressive assumptions regarding feedstock utilization or conversion efficiencies. Furthermore, the analysis presented here includes estimates for RNG production from P2G systems using dedicated renewable electricity. While there are multiple studies regarding P2G technology and its uses, we believe this is the first study to quantify RNG production potential nationwide from P2G. ICF’s updated assessment also illustrates the diversity of RNG resource potential as a GHG emission reduction strategy—there is a portfolio of potential feedstocks and technologies that are or will be commercialized in the near-term future that will help realize the potential of the RNG market. On the technology side, most RNG continues to be produced using anaerobic digestion paired with conditioning and upgrading systems. The post-2025 outlook for RNG will increasingly rely on thermal gasification of sustainably harvested biomass, including agricultural residues, forestry and forest product residues, and energy crops. The long-term outlook for RNG growth will depend to some extent on technological advancements in P2G systems. ICF’s analysis of the potential for P2G systems, paired with methanation suggests that the technology could make a significant contribution to RNG production by 2040. However, ICF notes that the role of P2G systems as a contributor to RNG production requires further analysis and study. Excluding cost considerations, the deployment of P2G systems for RNG production requires assumptions across a variety of factors, including but not limited to access to renewable electricity, the corresponding capacity factor of the system given the intermittency of renewable electricity generation from some sources (e.g., solar and wind), co-location with (presumably affordable) access to carbon dioxide for methanation, and reasonable proximity to a natural gas pipeline for injection. ICF’s analysis did not seek to address all of these project development considerations; rather, we sought to understand the potential for P2G systems assuming access to dedicated renewable electricity production, meaning that these are purpose-built renewable electricity generation systems that are meant to provide dedicated power to P2G systems. Curtailment of renewable electricity generation is a complicated issue, and exploring it in detail was beyond the scope of this report. However, ICF’s initial assessment indicates that P2G systems running on curtailed renewable electricity will play an important transitional role in helping to 62

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deploy the technology and achieve the long-term price reductions that are required to improve the viability of P2G as a cost-effective pathway for RNG production. Despite the importance of curtailed renewable electricity as part of the transition towards more cost-effective P2G systems, ICF’s analysis does focus more on the opportunity for, and associated costs of RNG production using P2G systems with dedicated renewable electricity generation. It is important that this assumption by ICF is recognized as a limitation of our analysis, rather than a commentary on how the market will ultimately develop for P2G systems. In the low resource potential and high resource potential scenarios presented, RNG deployment could achieve 101 to 235 MMT of GHG emission reductions by 2040. For the sake of reference, the high end of the estimate would be the equivalent of reducing GHG emissions from the use of natural gas in the residential sector by 95% from levels observed over the last ten years (2009- 2018). ICF estimates that the majority of the RNG produced in the high resource potential scenario is available in the range of $7-$20/MMBtu, which is equivalent to $55/ton to $300/ton in 2040. ICF evaluated the potential costs associated with the deployment of each feedstock and technology pairing, and made assumptions about the sizing of systems that would need to be deployed to achieve the RNG production potential outlined in the low and high resource potential scenarios. ICF’s reported costs are dependent on a variety of assumptions, including feedstock costs, the revenue that might be generated via byproducts or other avoided costs, and the expected rate of return on capital investments. ICF finds that there is potential for cost reductions as the RNG for pipeline injection market matures, production volumes increase, and the underlying structure of the market evolves.

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Appendix A—Resource Assessment by State The tables below summarize ICF’s resource assessment for low, high, and technical resource RNG production potentials in 2040, broken down by state and by feedstock, reported in units of tBtu per year (tBtu/y). Low Resource Potential Scenario, By State Table 38. Low Resource Potential for RNG in 2040, tBtu/y, by State via Anaerobic Digestion via Thermal Gasification State Animal Food Forest Energy LFG WRRF Ag Res MSW Manure Waste Res Crops Alabama 9.561 6.536 0.177 0.121 0.186 7.000 2.508 5.563 Alaska 1.153 0.004 0.030 0.000 0.000 0.000 0.000 0.000 Arizona 10.933 1.943 0.385 0.324 0.222 0.408 0.000 2.621 Arkansas 4.156 7.260 0.077 0.024 0.629 6.219 1.256 2.904 California 76.540 15.917 3.088 4.636 9.770 2.441 0.000 37.480 Colorado 10.962 3.605 0.250 0.247 3.058 0.560 0.000 1.999 Connecticut 1.670 0.864 0.246 0.438 0.009 0.290 0.051 3.539 Delaware 1.326 3.145 0.089 0.112 0.219 0.048 0.015 0.903 D.C. 0.000 -- 0.378 0.077 0.000 0.006 0.000 0.625 Florida 23.493 3.481 1.028 2.358 5.957 3.757 3.714 19.059 Georgia 16.914 7.196 0.538 0.230 0.739 8.059 4.756 6.185 Hawaii 2.203 0.124 0.105 0.000 0.000 0.000 0.000 0.000 Idaho 1.544 5.624 0.049 0.000 2.231 0.422 0.000 0.201 Illinois 28.655 2.481 1.869 1.568 23.215 1.155 0.287 12.677 Indiana 15.835 3.027 0.652 0.796 8.288 0.952 0.428 6.438 Iowa 4.899 8.648 0.140 0.027 35.541 0.875 3.042 1.756 Kansas 5.485 5.336 0.142 0.352 6.555 0.334 27.152 2.842 Kentucky 9.435 4.348 0.228 0.534 1.691 4.450 2.004 4.316 Louisiana 8.507 3.860 0.303 0.092 4.262 4.547 3.800 0.742 Maine 1.489 5.205 0.048 0.162 0.010 1.674 0.043 1.308 Maryland 6.286 2.255 0.356 0.718 1.186 0.623 0.390 5.802 Massachusetts 5.673 0.103 0.619 0.811 0.011 0.608 0.039 6.554 Michigan 25.191 4.141 1.179 1.204 7.175 3.198 0.220 9.734 Minnesota 4.661 6.789 0.307 0.655 30.659 2.501 0.013 5.298 Mississippi 5.306 4.410 0.072 0.000 0.624 5.189 2.800 0.000 Missouri 8.499 7.869 0.576 0.734 1.266 2.225 5.058 5.933 Montana 1.430 3.901 0.034 0.000 5.127 0.462 0.000 0.000 Nebraska 3.397 6.225 0.118 0.050 38.201 0.176 0.000 0.406 Nevada 5.291 0.808 0.250 0.148 0.002 0.056 0.000 1.195 New Hampshire 2.334 0.828 0.037 0.161 0.005 0.580 0.021 1.301 New Jersey 10.625 0.917 1.033 1.081 0.088 0.360 0.157 8.740 New Mexico 3.441 8.988 0.106 0.041 0.159 0.258 0.168 1.273 New York 19.739 4.522 2.472 2.388 2.015 1.980 0.598 19.307 North Carolina 14.068 6.943 0.367 1.187 0.833 9.692 4.993 9.599

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via Anaerobic Digestion via Thermal Gasification State Animal Food Forest Energy LFG WRRF Ag Res MSW Manure Waste Res Crops North Dakota 0.783 2.573 0.021 0.000 10.871 0.110 0.000 0.691 Ohio 24.843 4.139 1.364 1.407 10.053 1.308 0.375 11.374 Oklahoma 6.667 6.570 0.186 0.099 0.883 0.829 17.454 2.418 Oregon 6.237 1.962 0.293 0.144 1.060 2.161 0.000 1.164 Pennsylvania 27.171 6.667 1.043 1.555 1.589 2.509 1.397 12.575 Rhode Island 1.447 0.008 0.103 0.128 0.001 0.126 0.007 1.037 South Carolina 7.612 2.305 0.000 0.126 0.357 6.354 2.258 4.650 South Dakota 0.874 7.026 0.012 0.102 21.324 0.281 0.104 0.822 Tennessee 11.368 3.569 0.503 0.161 0.405 3.990 1.990 1.305 Texas 45.927 18.269 1.427 1.142 4.904 4.742 34.003 9.233 Utah 4.185 1.888 0.089 0.117 0.025 0.292 0.000 0.945 Vermont 0.672 1.006 0.000 0.076 0.006 0.351 0.025 0.617 Virginia 15.569 5.430 0.599 1.016 0.691 8.031 0.912 8.213 Washington 9.052 3.034 0.472 0.840 4.100 2.173 0.000 6.791 West Virginia 3.162 0.926 0.052 0.226 0.033 1.050 1.048 1.828 Wisconsin 11.634 16.507 0.443 0.697 8.308 3.043 0.161 5.637 Wyoming 0.500 1.992 0.000 0.070 0.088 0.199 0.000 0.568

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High Resource Potential Scenario, By State Table 39. High Resource Potential for RNG in 2040, tBtu/y, by State via Anaerobic Digestion via Thermal Gasification State Animal Food Forest Energy LFG WRRF Ag Res MSW Manure Waste Res Crops Alabama 15.818 13.072 0.322 1.204 0.464 13.999 16.789 12.544 Alaska 1.869 0.008 0.038 0.000 0.000 0.000 0.000 0.000 Arizona 17.879 3.887 0.537 1.397 0.555 4.175 0.000 14.557 Arkansas 6.762 14.520 0.193 0.629 1.573 12.438 18.529 6.549 California 124.841 31.833 4.183 8.113 24.426 4.881 0.000 84.514 Colorado 17.921 7.210 0.368 0.433 7.646 3.121 1.489 11.528 Connecticut 2.756 1.728 0.418 0.766 0.023 0.579 0.052 7.981 Delaware 2.219 6.290 0.119 0.195 0.546 0.096 0.017 2.036 D.C. 0.000 0.473 0.135 0.000 0.011 0.000 1.410 Florida 38.510 6.962 1.685 4.126 14.893 7.513 16.811 42.976 Georgia 27.480 14.392 0.774 2.114 1.848 16.117 16.880 22.024 Hawaii 3.562 0.248 0.163 0.000 0.000 0.000 0.000 0.000 Idaho 2.599 11.248 0.108 0.044 5.578 0.963 0.000 3.430 Illinois 46.987 4.962 2.533 2.744 58.037 2.310 36.042 28.585 Indiana 26.341 6.055 0.962 1.394 20.719 1.904 13.002 14.516 Iowa 7.962 17.296 0.248 0.656 88.851 1.750 19.329 6.830 Kansas 8.997 10.671 0.256 0.615 16.388 0.668 128.067 6.408 Kentucky 15.679 8.697 0.372 0.934 4.228 8.899 30.320 9.733 Louisiana 13.954 7.719 0.480 0.982 10.654 9.095 13.550 10.224 Maine 2.407 10.411 0.091 0.283 0.026 3.348 0.070 2.950 Maryland 10.417 4.510 0.509 1.256 2.966 1.246 1.080 13.082 Massachusetts 9.342 0.205 0.858 1.419 0.027 1.217 0.075 14.779 Michigan 41.000 8.283 1.533 2.107 17.937 6.396 1.170 21.948 Minnesota 7.683 13.579 0.438 1.147 76.646 5.002 2.941 11.947 Mississippi 8.666 8.821 0.195 0.637 1.559 10.379 17.065 6.630 Missouri 14.105 15.739 0.807 1.284 3.165 4.450 96.367 13.379 Montana 2.320 7.801 0.059 0.000 12.817 1.042 0.552 2.232 Nebraska 5.712 12.451 0.166 0.088 95.502 0.352 1.563 4.120 Nevada 8.701 1.616 0.324 0.259 0.005 1.893 0.000 6.118 New Hampshire 3.788 1.656 0.076 0.282 0.013 1.160 0.024 2.934 New Jersey 17.254 1.835 1.414 1.892 0.221 0.720 0.727 19.708 New Mexico 5.651 17.976 0.157 0.444 0.398 2.641 1.805 4.629 New York 32.753 9.044 3.304 4.179 5.038 3.959 3.041 43.536 North Carolina 23.406 13.887 0.640 2.078 2.082 19.384 20.971 21.645 North Dakota 1.333 5.145 0.045 0.150 27.179 0.223 7.115 1.558 Ohio 40.539 8.278 1.968 2.462 25.133 2.616 3.416 25.648 Oklahoma 10.857 13.139 0.305 0.814 2.206 1.748 111.613 8.475 Oregon 10.189 3.925 0.411 0.252 2.651 4.323 0.000 8.657 Pennsylvania 44.319 13.334 1.558 2.722 3.973 5.018 5.681 28.355

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via Anaerobic Digestion via Thermal Gasification State Animal Food Forest Energy LFG WRRF Ag Res MSW Manure Waste Res Crops Rhode Island 2.357 0.016 0.150 0.224 0.003 0.251 0.007 2.337 South Carolina 12.627 4.611 0.000 1.007 0.892 12.707 11.025 10.486 South Dakota 1.470 14.052 0.015 0.178 53.311 0.563 4.632 1.853 Tennessee 18.903 7.138 0.749 1.376 1.012 7.979 27.417 14.333 Texas 74.621 36.538 2.074 5.562 12.260 13.856 186.772 57.940 Utah 7.034 3.777 0.126 0.205 0.063 4.699 0.000 6.340 Vermont 1.099 2.012 0.018 0.133 0.016 0.701 0.277 1.390 Virginia 25.316 10.861 0.834 1.778 1.729 16.062 8.696 18.519 Washington 14.745 6.069 0.694 1.470 10.251 4.347 0.000 15.313 West Virginia 5.072 1.853 0.091 0.396 0.082 2.100 1.855 4.122 Wisconsin 18.906 33.014 0.625 1.220 20.771 6.086 10.807 12.712 Wyoming 0.830 3.984 0.028 0.123 0.220 0.800 0.067 1.281

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Technical Resource Potential Scenario, By State Table 40. Technical Resource Potential for RNG in 2040, tBtu/y, by State via Anaerobic Digestion via Thermal Gasification State Animal Food Forest Energy LFG WRRF Ag Res MSW Manure Waste Res Crops Alabama 21.291 21.786 1.054 5.417 1.607 35.895 67.831 31.436 Alaska 2.732 0.013 0.097 0.814 0.000 0.000 0.000 0.000 Arizona 25.738 6.478 1.275 8.045 2.299 19.320 0.000 36.483 Arkansas 9.604 24.200 0.675 3.347 10.304 31.892 151.481 16.412 California 188.144 53.056 8.988 43.954 77.147 12.516 0.000 211.804 Colorado 26.180 12.017 0.952 6.381 34.406 13.136 22.504 28.890 Connecticut 4.085 2.879 0.992 3.945 0.071 1.485 0.249 20.001 Delaware 3.456 10.484 0.266 1.078 3.008 0.245 4.432 5.102 D.C. 0.000 0.946 0.787 0.000 0.028 0.000 3.534 Florida 55.554 11.604 3.991 23.937 45.823 19.265 57.804 107.704 Georgia 39.551 23.987 1.962 11.753 6.971 41.326 66.426 55.195 Hawaii 4.847 0.413 0.352 1.567 0.000 0.000 0.000 0.000 Idaho 4.016 18.746 0.355 1.980 23.672 2.774 0.000 8.647 Illinois 69.628 8.269 5.663 14.045 246.978 5.924 353.618 71.637 Indiana 39.815 10.091 2.458 7.430 110.916 4.881 205.848 36.379 Iowa 11.345 28.826 0.972 3.503 348.543 4.487 293.301 17.116 Kansas 13.258 17.785 0.791 3.219 82.681 1.713 464.248 16.059 Kentucky 22.443 14.495 1.080 4.959 19.345 22.819 154.183 24.392 Louisiana 19.953 12.866 1.271 5.145 38.169 23.320 76.967 25.624 Maine 3.286 17.351 0.348 1.484 0.079 8.584 0.317 7.393 Maryland 15.646 7.517 1.168 6.705 10.173 3.195 21.633 32.786 Massachusetts 14.059 0.342 1.935 7.674 0.082 3.120 0.424 37.037 Michigan 62.029 13.805 3.488 11.081 80.227 16.399 51.785 55.005 Minnesota 11.664 22.632 1.046 6.255 301.824 12.825 108.270 29.941 Mississippi 12.135 14.702 0.673 3.304 8.874 26.612 101.265 16.617 Missouri 21.131 26.231 2.066 6.799 29.302 11.410 367.684 33.528 Montana 3.287 13.002 0.205 1.188 50.944 2.976 18.432 5.593 Nebraska 8.663 20.751 0.493 2.146 352.907 0.903 53.364 10.325 Nevada 13.265 2.693 0.702 3.414 0.014 9.422 0.000 15.332 New Hampshire 5.740 2.759 0.251 1.508 0.039 2.974 0.128 7.352 New Jersey 26.340 3.058 3.099 9.867 1.164 1.847 4.193 49.391 New Mexico 8.150 29.961 0.471 2.318 2.147 12.222 7.031 11.600 New York 50.489 15.073 7.197 21.554 24.327 10.152 33.219 109.106 North Carolina 35.164 23.145 1.683 11.609 10.421 49.703 96.393 54.245 North Dakota 2.007 8.576 0.153 0.841 104.037 0.581 138.829 3.905 Ohio 59.130 13.797 4.788 12.959 103.490 6.709 130.141 64.276 Oklahoma 15.723 21.899 0.914 4.367 15.589 4.713 354.173 21.240 Oregon 15.409 6.541 1.026 4.695 12.034 11.084 0.000 21.695 Pennsylvania 66.587 22.224 4.142 14.170 16.646 12.867 46.920 71.060

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via Anaerobic Digestion via Thermal Gasification State Animal Food Forest Energy LFG WRRF Ag Res MSW Manure Waste Res Crops Rhode Island 3.629 0.026 0.338 1.169 0.008 0.644 0.034 5.857 South Carolina 18.856 7.684 0.000 5.692 4.484 32.583 37.226 26.280 South Dakota 2.257 23.420 0.048 0.987 185.826 1.442 82.444 4.644 Tennessee 28.115 11.897 1.856 7.557 8.845 20.460 137.488 35.921 Texas 108.758 60.897 4.732 32.166 52.667 46.739 683.746 145.205 Utah 10.185 6.294 0.374 3.563 0.198 22.600 0.000 15.888 Vermont 1.696 3.353 0.117 0.694 0.050 1.798 1.842 3.484 Virginia 36.882 18.101 1.891 9.479 6.735 41.186 58.678 46.411 Washington 22.019 10.115 1.692 8.478 37.107 11.145 0.035 38.375 West Virginia 6.576 3.088 0.426 1.982 0.346 5.384 14.524 10.330 Wisconsin 28.451 55.024 1.660 6.450 82.169 15.606 131.091 31.857 Wyoming 1.219 6.639 0.133 0.633 1.451 3.083 0.727 3.210

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Appendix B—GHG Emissions using Lifecycle Analysis Approach The GHG emissions factor of RNG, typically called a carbon intensity (e.g., grams of CO2 equivalents per MJ of fuel), varies primarily based on the source of the fuel (i.e., feedstock), but can be impacted by other factors such as production efficiency and location as well as transmission distances. The assessment method and scope can also have a significant impact on how RNG carbon intensities and emissions are estimated and reported. This section provides a summary of commonly used GHG emission accounting methods and how they relate to the GHG emission profiles of RNG production and consumption. California’s LCFS, consumption-based inventories, and GHG Protocol’s Scope 3 include all GHG emissions from a product or resource’s lifecycle. This relies on an approach called life-cycle assessment (LCA). LCA allows for a holistic GHG accounting approach that considers all life-cycle aspects from raw resource extraction to final disposal (i.e., “cradle to grave”). For RNG and transportation fuels, Argonne National Laboratories’ GHGs, Regulated Emissions, and Energy Use in Transportation (GREET) model is the most commonly relied on resource. RNG’s carbon intensity (i.e., GHG emissions per unit of energy) varies substantially between feedstocks and production methods. Carbon intensities can also vary by location of production and how the fuel is transported and distributed. The GHG accounting methods and scopes previously discussed dictate which of RNG’s life-cycle elements are included as a carbon intensity in emissions reporting. Variations in production Figure 35 shows how these different life-cycle elements contribute to RNG’s overall carbon intensity for a selection of RNG sources using Argonne’s GREET model: landfill gas, animal waste anaerobic digestion (AD), wastewater sludge AD, and municipal solid waste (MSW) AD. We have also included corn ethanol (E85 blend) and gasoline as reference points. Note that in the GREET model, the original sourcing of RNG is considered “fuel production” and not feedstock operations. Figure 35. Summary of carbon intensities for transportation fuels across life-cycle stages (ANL 2019).

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The biggest variations in RNG production come from the associated emissions credits from the different RNG sources. For landfill gas, animal waste, and wastewater sources, GREET assigns a significant credit for the reduction in vented and flared methane (CH4) that would have occurred in absence of the production of RNG. Depending on the reporting standard and scope, different credits may be included or excluded. The California LCFS has a similar scope in accounting for credits as the GREET results shown above. Other programs or jurisdictional inventories may exclude these credits, or incorporate them into other emission sectors. Variations based on accounting method Figure 36 shows the same GREET results from Figure 35 grouped into the GHG Protocol Scopes. Scope 1 is limited to the tailpipe emissions and Scope 3 includes all aspects of feedstock and fuel production activities. For RNG we have grouped the compression of gas before use into Scope 2, assuming electricity is used in compression. Figure 36. Life-cycle carbon intensity for RNG grouped by different GHG Protocol scopes using GREET results.38

As noted in more detail in the previous sub-section, the GHG emissions associated with the production of RNG vary depending on a number of factors including the feedstock type, collection and processing practices, and the type and efficiency of biogas upgrading. For the purposes of this report, ICF determined the lifecycle carbon intensity (CI) of RNG up to the point of pipeline injection. This includes feedstock transport and handling, gas processing, and any credits for the reduction of flaring or venting methane that would have occurred in absence of the RNG fuel production. The table below presents ranges of lifecycle CIs for different RNG feedstocks up to the point of pipeline injection. These estimates are primarily based on a combination on Argonne National Laboratory’s Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model

38 GHG Protocol. 2019. Guidance. Available at: https://ghgprotocol.org/guidance-0 71

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(GREET) model,39 California Air Resources Board’s modified California GREET model,40 and ICF analysis. Table 41. Range of Lifecycle GHG Emission Factors for RNG from Different Feedstocks and Regions (in units of g/MJ)

ICF notes the following about these emission factors: § The lowest carbon intensities are from feedstocks that prevent the release of fugitive methane, such as the collection and processing of dairy cow manure. § RNG from WRRFs has the same CI range as landfill gas because both feedstocks start with raw biogas that is processed by the same type of gas upgrading equipment. § Agricultural residue, energy crops, forestry products and forestry residues, as well as MSW all have the same CI range based on the thermal gasification process required to create biogas from woody biomass. This is an energy intensive process, but inclusion of renewables and co-produced electricity on-site can reduce the emissions impact of gas production. After the point of injection, RNG is transported through pipelines for distribution to end-users. The CI of pipeline transmission depends on the distance between the gas upgrading facility and end- use. The GREET model applies 5.8 grams of CO2e per MMBtu-mile of gas transported as the pipeline transmissions CI factor. If the gas will be used in the transportation sector, and therefore requires compression, another 3-4 gCO2e is added onto the CI. For the sake of reference, the tailpipe emissions of use in a heavy-duty truck are around 60 gCO2e/MJ. ICF applied the GHG emission factors listed in the table above to estimate the GHG reduction potential across each of the RNG potential scenarios and each region, as reported previously in Section 2. The tables below show the range of GHG emission reductions on a lifecycle basis in units of million metric tons, MMT. ICF estimates that in the low RNG resource case, about 86 to 113 MMT of GHG emissions would be reduced through the deployment of RNG; in the high RNG resource case, 170 to 247 MMT of GHG emissions could be reduced.

39 https://greet.es.anl.gov/ 40 https://ww3.arb.ca.gov/fuels/lcfs/ca-greet/ca-greet.htm 72

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Table 42. GHG Emission Reductions (in MMT) for RNG in the Low Resource Case Low RNG Resource Case | GHG Emission Reduction Potential, MMT Feedstock East North West North South East South West South New England Mid-Atlantic Mountain Pacific Total Central Central Atlantic Central Central RNG from biogenic or renewable resources Landfill Gas 0.5 - 0.5 2.2 - 2.5 3 - 3.5 0.9 - 1 3.1 - 3.4 1.3 - 1.3 2 - 2.3 1.1 - 1.5 3 - 4.3 17 - 20.5 Animal Manure 1.6 - 1.7 3.2 - 3.3 7.2 - 7.4 6 - 6.1 2.9 - 3 0.9 - 0.9 2.6 - 2.7 4.9 - 5.1 5.4 - 5.7 34.9 - 35.7 WRRF 0 - 0 0.2 - 0.2 0.1 - 0.2 0 - 0 0.1 - 0.1 0 - 0 0.1 - 0.1 0 - 0.1 0.1 - 0.2 0.8 - 1 Food Waste 0.3 - 0.3 0.7 - 0.8 0.7 - 0.8 0.2 - 0.3 0.8 - 0.9 0.1 - 0.1 0.2 - 0.2 0.1 - 0.1 0.8 - 0.9 4 - 4.4 Ag Residue 0 - 0 0 - 0.1 0.6 - 2.2 1.4 - 5.6 0.1 - 0.4 0 - 0.1 0.1 - 0.4 0.1 - 0.4 0.1 - 0.6 2.5 - 9.8 Forestry and Forest 0 - 0.1 0 - 0.2 0.1 - 0.4 0.1 - 0.3 0.4 - 1.4 0.2 - 0.8 0.2 - 0.6 0 - 0.1 0.1 - 0.3 1.1 - 4.2 Residue Energy Crops 0 - 0 0 - 0.1 0 - 0.1 0.4 - 1.4 0.2 - 0.7 0.1 - 0.4 0.6 - 2.2 0 - 0 0 - 0 1.2 - 4.8 Sub-Total 2.4 - 2.7 6.4 - 7.2 11.7 - 14.5 9 - 14.6 7.7 - 10 2.6 - 3.7 5.7 - 8.4 6.3 - 7.3 9.4 - 12 61.4 - 80.3 Renewable gas from MSW MSW 0.1 - 0.6 0.4 - 1.6 0.5 - 1.8 0.2 - 0.7 0.6 - 2.2 0.1 - 0.4 0.2 - 0.6 0.1 - 0.3 0.5 - 1.7 2.5 - 9.9 RNG from P2G / Methanation P2G / Methanation 22.3 Totals 2.6 - 3.2 6.9 - 8.8 12.2 - 16.2 9.2 - 15.2 8.3 - 12.2 2.8 - 4.1 5.9 - 9 6.4 - 7.7 9.9 - 13.7 86.3 - 112.5

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Table 43. GHG Emission Reductions (in MMT) for RNG in the High Resource Case High RNG Resource Case | GHG Emission Reduction Potential, MMT Feedstock East North West North South East South West South New England Mid-Atlantic Mountain Pacific Total Central Central Atlantic Central Central RNG from biogenic or renewable resources Landfill Gas 0.8 - 0.9 3.8 - 4.3 5.1 - 6 1.5 - 1.7 5.3 - 5.8 2.2 - 2.3 3.4 - 3.9 1.9 - 2.6 5 - 7.4 28.9 - 35 Animal Manure 3.2 - 3.3 6.4 - 6.6 14.5 - 14.8 12.1 - 12.2 5.9 - 5.9 1.8 - 1.8 5.3 - 5.3 9.8 - 10.2 10.8 - 11.4 69.7 - 71.5 WRRF 0.1 - 0.1 0.3 - 0.3 0.2 - 0.2 0.1 - 0.1 0.2 - 0.2 0.1 - 0.1 0.1 - 0.1 0.1 - 0.1 0.2 - 0.3 1.2 - 1.4 Food Waste 0.3 - 0.3 0.7 - 0.8 0.7 - 0.8 0.2 - 0.3 0.8 - 0.9 0.1 - 0.1 0.2 - 0.2 0.1 - 0.1 0.8 - 0.9 4 - 4.4 Ag Residue 0 - 0 0.1 - 0.4 1.4 - 5.5 3.6 - 13.9 0.3 - 1 0.1 - 0.3 0.3 - 1.1 0.3 - 1.1 0.4 - 1.4 6.4 - 24.7 Forestry and Forest 0.1 - 0.3 0.1 - 0.4 0.2 - 0.7 0.1 - 0.5 0.7 - 2.9 0.4 - 1.6 0.4 - 1.4 0.2 - 0.7 0.1 - 0.5 2.3 - 9.1 Residue Energy Crops 0 - 0 0.1 - 0.4 0.6 - 2.5 2.6 - 10 0.8 - 3 0.9 - 3.5 3.3 - 12.7 0 - 0.2 0 - 0 8.3 - 32.3 Sub-Total 4.4 - 4.9 11.5 - 13.1 22.7 - 30.5 20.1 - 38.6 14 - 19.8 5.5 - 9.7 12.8 - 24.8 12.4 - 14.9 17.3 - 21.9 120.8-178.2 Renewable gas from MSW MSW 0.3 - 1.2 0.9 - 3.5 1 - 4 0.5 - 1.8 1.4 - 5.2 0.4 - 1.7 0.8 - 3.2 0.5 - 1.9 1.1 - 4.2 6.9 - 26.8 RNG from P2G / Methanation P2G / Methanation 42.3 Totals 4.7 - 6.2 12.4 - 16.6 23.7 - 34.5 20.6 - 40.4 15.4 - 25 6 - 11.3 13.7 - 28 12.9 - 16.9 18.3 - 26.1 170.0-247.3

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