PERFORMANCE RANKING MICHIGAN AMONGST the STATES • 2019 EDITION U-20471 Official Exhibits of Soulardarity Exhibit SOU-13 Page 2 of 4

U-20471 Official Exhibits of Soulardarity Exhibit SOU-13 Page 1 of 4

ELECTRIC UTILITY PERFORMANCE RANKING MICHIGAN AMONGST THE STATES • 2019 EDITION U-20471 Official Exhibits of Soulardarity Exhibit SOU-13 Page 2 of 4

U-20471 Official Exhibits of Soulardarity Exhibit SOU-13 Page 3 of 4 The Citizens Utility Board of Michigan (CUB of MI) was formed in 2018 to represent the interests of residential energy customers across the state of Michigan. CUB of MI educates and engages Michigan consumers in support of cost-effective investment in energy efficiency and renewable energy and against unfair rate increase requests. CUB of MI gives a voice to Michigan utility customers and helps to ensure that citizens of the state pay the lowest reasonable rate for utility services and also benefit from the environmental implications of investment in clean energy. CUB of MI is a nonpartisan, nonprofit organization whose members are individual residential customers of Michigan’s energy utilities. For more information, visit www.cubofmichigan.org.

This report was prepared for Citizens Utility Board of Michigan by 5 Lakes Energy. 5 Lakes Energy is a Michigan-based policy consulting firm dedicated to advancing policies and programs that promote clean energy and sound water policy for a resilient environment. For more information, visit https://5lakesenergy.com/.

U-20471 Official Exhibits of Soulardarity Exhibit SOU-13 Page 4 of 4 Average minutes to restore power to a customer (CAIDI)

U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 1 of 20

The True Value of Solar

Measuring the Benefits of Rooftop Solar Power U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 2 of 20

The True Value of Solar Measuring the Benefits of Rooftop Solar Power

Written by: Gideon Weissman Frontier Group Emma Searson and Rob Sargent Environment America Research and Policy Center

July 2019 U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 3 of 20

Acknowledgments

Environment America Research & Policy Center sincerely thanks Karl R. Rábago of the Pace Energy and Climate Center, John Farrell of the Institute for Local Self-Reliance, Kevin Lucas and Rachel Goldstein of the Solar Energy Industries Association and Nathan Phelps of Vote Solar for their review of this document. Thanks also to Tony Dutzik, Susan Rakov and Jonathan Sundby of Frontier Group for editorial support.

The authors bear responsibility for any factual errors. The recommendations are those of Environment America Research & Policy Center. The views expressed in this report are those of the authors and do not necessarily reflect the views those who provided review.

 2019 Environment America Research & Policy Center

Environment America Research & Policy Center is a 501(c)(3) organization. We are dedicated to protecting our air, water and open spaces. We investigate problems, craft solutions, educate the public and decision-makers, and help the public make their voices heard in local, state and national debates over the quality of our environment and our lives. For more information about Environment America Research & Policy Center or for additional copies of this report, please visit www.environmentamericacenter.org.

Frontier Group provides information and ideas to help citizens build a cleaner, healthier, fairer and more democratic America. We address issues that will define our nation’s course in the 21st century – from fracking to solar energy, global warming to transportation, clean water to clean elections. Our experts and writers deliver timely research and analysis that is accessible to the public, applying insights gleaned from a variety of disciplines to arrive at new ideas for solving pressing problems. For more information about Frontier Group, please visit www.frontiergroup.org.

Layout: Alec Meltzer/meltzerdesign.net

Cover photo: National Renewable Energy Laboratory U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 4 of 20

Table of Contents

Executive Summary ...... 1

Introduction ...... 3

The Value of Solar Power Has Important Implications for Renewable Energy Adoption ...... 4

Solar Power Delivers Important Environmental and Public Health Benefits ...... 5 Grid Benefits ...... 6 Societal Benefits ...... 7

Value-of-Solar Studies Should Account for All of Solar Energy’s Societal Benefits ...... 9

Conclusion and Recommendations ...... 12

Notes ...... 13 U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 5 of 20 Executive Summary

istributed solar energy is on the rise, gen- To help develop smart public policy around solar erating enough electricity to power more energy, many public utilities commissions, utilities than 6 million homes each year, and result- and other organizations have conducted or spon- ingD in annual carbon dioxide emission reductions sored “value-of-solar” studies that attempt to quan- equivalent to taking 4.4 million passenger vehicles tify the monetary value of the benefits delivered, and off the road.1 Public policy has been a key factor in costs imposed, by the addition of solar energy to the driving the growth of solar energy – recognizing the electric grid. Studies that include a full range of solar enormous benefits that solar power can provide both energy’s benefits – including benefits to the environ- today and in the future. ment and society – reliably conclude that the value of

Figure ES-1. The Benefits of Rooftop Solar Energy2

Benefit Category Benefit

Avoided electricity generation

Energy Reduced line losses

Market price response

Avoided capacity investment

Grid Capacity and Grid Investments Avoided transmission and distribution investment

Reduced need for grid support services

Reduced exposure to price volatility Risk and Reliability Benefits Improved grid resiliency and reliability

Compliance Reduced environmental compliance costs

Avoided greenhouse gas emissions

Avoided air pollution Environment Societal Health benefits

Avoided fossil fuel lifecycle costs

Economy Local jobs and businesses

Executive Summary 1 U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 6 of 20 those benefits approximates or exceeds the compen- exceeds the retail rate of electricity. Recent studies sation solar panel owners receive through policies from states including Maine, Pennsylvania and such as net metering. Arkansas have found that solar energy brings substantial environmental benefits, and that Many value-of-solar studies, however – especially rooftop solar owners would provide a net benefit those conducted by electric utilities – have left out key to society even with net metering compensation.3 benefits of solar energy. Policymakers and members of the public who consult these studies may be left with • Studies commissioned by electric utilities gener- a false impression of solar energy’s value to the grid ally fail to account for benefits beyond the grid, and society, with damaging results for public policy. resulting in far lower values of solar. A 2016 report published by Environment America Research and To make decisions that serve the public interest, Policy Center and Frontier Group reviewed value- policymakers should account for the full value of of-solar studies and found that, of 16 studies solar energy, including societal benefits to the reviewed, only eight accounted for avoided green- environment and public health. house gas emissions, and no studies commis- Rooftop solar energy brings a wide variety of sioned by utilities accounted for the value of solar benefits to the grid and to society. energy beyond the grid. The studies that left out societal benefits valued solar, on average, at 14.3 • Rooftop solar power generally adds value to the cents per kilowatt-hour, compared to 22.9 cents electric grid. It not only reduces the need for gener- for those studies that at least accounted for green- ation from and investment in central power plants, house gas emissions. but over the long lifetime of solar energy systems it also can increase price stability and grid reliability, Value-of-solar studies should account for all of and reduce environmental compliance costs. solar energy’s benefits to the grid and society.

• As a clean, emission-free energy source often • Policymakers must account for the societal value located on private property and built with of reduced power plant emissions, in particular considerable private, non-ratepayer investment, the value of avoided greenhouse gas emissions rooftop solar brings valuable societal benefits. and pollutants that contribute to the formation of Solar energy reduces global warming pollution, smog and soot. and also reduces emissions of dangerous air • Policymakers should also seek to account for pollutants such as nitrogen oxides, mercury and broader societal impacts of solar energy, including particulate matter. “upstream” impacts of fossil fuel production and Value-of-solar studies inconsistently account for use, such as methane emissions from fracking, and solar energy’s benefits, especially beyond the local economic development impacts. electric grid, resulting in dramatically different Public policy that fails to account for the full range of conclusions. benefits may deter the addition of solar power to the • Studies that include the benefits of solar energy grid, with ramifications for the environment, public beyond the grid generally find that its value health, and the operation of the electric grid.

2 The True Value of Solar U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 7 of 20 Introduction

he electricity system that powers our homes, tion and minimize harm to our health and environ- businesses and factories imposes heavy costs ment. But while many states aspire to least-cost utility on our environment and our health. These planning, and some even incorporate the social cost costsT accrue in a variety of ways. Particulate mat- of carbon into certain planning decisions, no state ter from burning coal harms our bodies, increases fully accounts for the external costs of electricity in mortality rates and strains the health care system.4 pricing or investment decisions.9 Fracking and coal mining degrade the environment, In the 20th century, the vast majority of electricity threaten water quality, and require expensive envi- was generated from fossil fuels at large, centralized ronmental rehabilitation.5 Each new ton of global power plants. Today, the availability of clean, afford- warming pollution – whether carbon dioxide from able renewable energy, coupled with the potential to power plants, or methane leaked from natural gas generate power close to where it is used, forces a re- wells – adds to the burden we and future genera- thinking of traditional ways of setting utility rates and tions will face from extreme weather, rising seas, and comparing the value of various options for generat- economic and societal disruption.6 ing electricity. The ways in which we choose to assign Most of these costs are quantifiable, and all are vast. value to various options for generating electricity will For instance, one U.S. Environmental Protection help to shape the electricity system of the future. It is Agency study found that the impact of fossil fuel critical that we get it right. electricity generation on premature mortality, lost As the following pages show, one important step work days, and health care costs add up to hundreds policymakers can take is to begin accurately assess- of billions of dollars each year.7 Per unit of energy, ing the costs and benefits of one of our most prom- these health costs alone often exceed the price we ising clean energy resources: rooftop solar energy. pay on our electric bill.8 By doing so, they can adhere to sound policymak- Policymakers have a variety of tools at their disposal ing principles, while putting the U.S. on a path to a to minimize the societal costs of electricity genera- cleaner, healthier and more prosperous future.

Introduction 3 U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 8 of 20 The Value of Solar Power Has Important Implications for Renewable Energy Adoption

hat is the value of solar energy? The difference can be dramatic. For example, a 2013 study by the Vermont Public Service Department In recent years, as distributed solar en- found that the costs and benefits of solar energy were ergy has grown into an important piece W approximately equal when environmental benefits of the American electricity system – now generat- were ignored. When greenhouse gas emissions were ing enough electricity to power more than 6 million accounted for, however, each kilowatt-hour of solar en- homes each year –policymakers, utilities, solar energy ergy generated brought a societal benefit of 4.3 cents.11 trade organizations and other energy policy experts have grappled with the question.10 Their attempts to The value attributed to solar energy – and how that calculate the cents per kilowatt-hour value of solar value is integrated into ratemaking and investment energy have had important ramifications – “value of decisions – has important implications for renew- solar” studies have been used as evidence for energy able energy adoption. Any homeowner or business policymaking that affects the speed and quantity of owner considering installing solar panels needs to solar energy adoption, which in turn affects the envi- compare the upfront cost of the investment with the ronment, public health, and the economy. likely utility bill savings over time – including both avoided electricity purchases and any compensation Authors of value-of-solar studies typically must paid by the utility for the excess solar power sup- contend with a variety of complex questions, but plied to the grid. Differences in the valuation of those the most important question is really the simplest: extra kilowatt-hours supplied to the grid can make What is the universe of benefits that will be included or break a distributed solar power project from a fi- and quantified in the analysis? Their answer can nancial perspective. This is reflected by the success of determine whether policymakers ultimately view net metering policies, which value solar energy at the solar energy as bringing a net benefit to society, with retail rate of electricity, in driving adoption of rooftop consequences for energy rates and the compensa- solar power. Of the 10 states that generated the most tion rooftop solar owners receive for excess energy small-scale solar energy per capita in 2017, all but two they feed to the grid. had a state net metering policy.12

4 The True Value of Solar U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 9 of 20 Solar Power Delivers Important Environmental and Public Health Benefits

ot all energy is created equal. Some energy The benefits of distributed solar power can be di- – like electricity generated by burning coal vided into two categories: benefits to the grid (which – imposes enormous costs on the public benefit utility ratepayers in their capacity as consum- Nand the environment, including air pollution, envi- ers) and benefits to the environment and society ronmental degradation and adverse health impacts. (which benefit ratepayers and others in their capacity Energy sources such as wind and solar power impose as residents and taxpayers). The following describes fewer environmental costs than fossil fuel sources, many of those benefits in detail. and can even reduce the cost of operating the grid.

Figure 1. The Benefits of Rooftop Solar Energy13

Benefit Category Benefit

Avoided electricity generation

Energy Reduced line losses

Market price response

Avoided capacity investment

Grid Capacity and Grid Investments Avoided transmission and distribution investment

Reduced need for grid support services

Reduced exposure to price volatility Risk and Reliability Benefits Improved grid resiliency and reliability

Compliance Reduced environmental compliance costs

Avoided greenhouse gas emissions

Avoided air pollution Environment Societal Health benefits

Avoided fossil fuel lifecycle costs

Economy Local jobs and businesses

Solar Power Delivers Important Environmental and Public Health Benefits 5 U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 10 of 20 Grid Benefits Market price response: Distributed solar energy also reduces the price of electricity by reducing overall Energy generated using solar panels on rooftops of demand on the grid, which can suppress wholesale homes and businesses benefits the electric grid. Not electricity prices.16 In other words, ratepayers not only only do solar panels reduce the need for electricity benefit when utilities must purchase less electricity to from central power plants, but the integration of dis- satisfy demand, but they also gain because each unit tributed clean energy resources can also help create a of electricity purchased becomes cheaper.17 These more modern, resilient and efficient grid. demand reduction-induced price effects can represent an important value to ratepayers. Energy Avoided electricity costs: Solar energy sent to the grid Capacity and grid investments reduces the amount of electricity that utilities must Avoided capacity, transmission and distribution invest- generate or purchase from power plants. The value of ment: Expanding the amount of electricity we gener- this avoided electricity consumption is often greatest ate from the sun can defer or eliminate the need for in the summer months, when demand for electricity new grid capacity investments, particularly because rises due to increased air conditioning demand and demand for energy from the grid is often highest solar energy production is near its peak. Adding solar during the day when the sun is shining. By reducing energy to the system reduces the need to power up overall and peak demand, expanding solar energy expensive, often inefficient generators that run only production helps ratepayers and utilities avoid the a few times a year, or to purchase expensive peak cost of investing in new power plants, transmission power on wholesale markets, reducing the cost of and distribution lines, and other forms of electricity electricity for all ratepayers. infrastructure. Reduced line losses: Distributed solar energy also Reduced need for ancillary services: Solar energy reduces the amount of electricity lost as heat as it may also reduce certain costs of keeping the grid travels from large, centralized power plants to our running smoothly, including regulating voltage sockets. The U.S. Energy Information Administration and reducing the need to keep backup power estimated that the United States lost about $21 bil- plants running (“spinning reserves”). Solar energy lion worth of electricity in 2017, or 5 percent of the to- systems installed with “smart inverters” and other tal amount of electricity generated that year.14 These technologies that increase two-way communica- losses cause us to generate more electricity than we tion with the grid, for example, have the potential need, increasing costs for ratepayers. to improve grid operation and reduce the need for Rooftop solar PV systems drastically reduce the centralized grid support services.18 Without such amount of system losses by producing electricity on- equipment, solar energy may increase certain grid site, thereby reducing the amount of electricity trans- support costs. mitted and distributed through the grid. Solar power is particularly effective in reducing line losses because it reduces demand on grid infrastructure at times Risk and Reliability Benefits when line losses are highest. Line losses increase with Reduced exposure to price volatility: Fossil fuel price the square of the load on the distribution system, volatility has long been a concern for utilities and with losses as high as 30 percent during the high-load ratepayers alike, but the risk has become greater as hours when most solar output is delivered.15 power companies have shifted from coal to natural

6 The True Value of Solar U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 11 of 20 gas – a fuel with a history of price volatility.19 Because Societal Benefits solar panels, once installed, do not incur fuel costs, Solar panels provide valuable benefits to society integrating more solar energy capacity onto the beyond what is addressed by current electricity rates. electric grid can reduce exposure to sudden swings Namely, solar energy reduces the need for the extrac- in the price of fossil fuels or wholesale electricity. tion, transportation and combustion of fossil fuels, Research has shown that the risk of fuel price volatil- which impose heavy costs on the environment and ity is primarily borne by ratepayers, rather than utility public health. shareholders.20 Some utilities also engage in fuel price hedging strategies to ensure that a portion of electricity costs are stable. Solar energy can help en- Environment sure price stability, a contribution with financial value Avoided greenhouse gas emissions: In 2017, the elec- for utilities and grid users.21 tricity sector was responsible for 28 percent of all U.S. Improved grid resiliency and reliability: Solar panels greenhouse gas pollution.23 The generation of elec- create a more diverse and geographically dispersed tricity with both coal and natural gas has a substantial energy portfolio, and generate energy close to the climate impact. Although natural gas is less carbon point of consumption. These attributes may help intensive than coal at the point of combustion, the reduce congestion in transmission and distribution process of natural gas extraction and transportation systems, and create a more reliable grid less prone results in vast emissions of methane, a gas that traps to central disruptions, power outages or rolling approximately 86 times more heat in the atmosphere blackouts.22 than the same amount of carbon dioxide over a 20- year time frame.24

Compliance Research suggests that every metric ton of carbon dioxide released into the air causes $37 of economic Avoided environmental compliance costs: Adding and social damage.25 In 2017, the United States elec- solar energy to the grid allows local utilities and tric power sector emitted more than 1.7 billion metric municipalities to avoid some of the growing costs tons of carbon dioxide emissions, equivalent to more of compliance with environmental regulations. than $64 billion in economic and social damages.26 Increasing distributed solar energy capacity helps Solar energy, on the other hand, is renewable and utilities avoid or reduce the costs of installing emission-free, and avoids the costs of both future new technologies to curb air and water pollution damage and future environmental compliance. or installing renewable energy. Solar energy also reduces the costs of compliance with regulations Rooftop solar in particular is also fast and flexible to on criteria pollutants like sulfur dioxide and nitro- implement, making it an important tool for taking on gen oxides, as well as greenhouse gas reduction climate change. Residential rooftop projects typically programs such as the Regional Greenhouse Gas take just a few months from initial deposit to power Initiative in the northeastern U.S., California’s cap- generation.27 Distributed solar energy can also be in- and-trade program for greenhouse gas emissions, stalled in a wide variety of urban settings, including on and any future programs that may be adopted at rooftops and parking lot canopies, making it well-suit- the state or federal levels. ed for densely populated and energy-intensive regions.

Solar Power Delivers Important Environmental and Public Health Benefits 7 U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 12 of 20 Health benefits and avoided air pollution: Solar energy and risks chemical contamination of drinking water. reduces emissions of dangerous air pollutants such as Coal mining puts coal-worker health at risk, and has nitrogen oxides, mercury and particulate matter that caused environmental devastation including the harm public health.28 Solar energy production can loss of thousands of miles of streams.33 Burning coal reduce emissions beyond the level required by envi- generates millions of tons of coal ash that are often ronmental regulations, or address environmental and stored on site at power plants, threatening ground- public health threats that are inadequately regulated, water and occasionally resulting in catastrophic spills. providing value such as reduced illness and mortality. And thermoelectric power plants – coal, natural gas and nuclear – require water for cooling, and can have According to a 2018 report by the American Lung adverse effects on water resources and ecosystems.34 Association, 41 percent of Americans live in a county where air pollution often reaches dangerous levels.29 Air pollution is linked to increased incidence of asth- Economy ma and chronic bronchitis, and has also been shown Local jobs and businesses: The solar energy industry to cause hundreds of thousands of premature deaths has created thousands of new jobs and businesses per year.30 A typical coal-fired power plant without across the nation. As of November 2017, the solar en- technology to limit emissions sends 170 pounds of ergy industry employed more than 250,000 people, mercury – an extremely harmful neurological toxin – a 168 percent increase from 2010.35 The Bureau of into the air each year.31 Labor Statistics projects that solar installation jobs Expanding the nation’s ability to source clean elec- will be the nation’s fastest growing occupation in tricity from the sun reduces our dependence on fossil terms of total employment through 2026.36 There are fuels, and lessens the amount of harmful emissions more than 10,000 solar companies in the U.S., and that flow into the air we breathe. in 2017 the solar industry generated $17 billion of investment in the U.S. economy.37 Because rooftop Avoided fossil fuel lifecycle costs: Use of solar energy solar installations take place in our communities, they reduces the need for fossil fuels, which impose a generate local spending and opportunities for local steep cost on society not just at the point of com- businesses, and serve as visible reminders of the local bustion, but also during extraction and transporta- economic benefits of clean energy. tion.32 Natural gas drilling uses vast water resources,

8 The True Value of Solar U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 13 of 20 Value-of-Solar Studies Should Account for All of Solar Energy’s Societal Benefits

ood policymaking requires accurate in- ronmental benefits, should be included in valuations, formation, and accurately valuing energy as these were typically among the reasons for policy resources is a critical part of setting good enactment in the first place.”40 energyG policy. In Karl R. Rábago and Radina Valova’s Often, however, utilities present assessments of the 2018 Electricity Journal article attempting to deter- value of solar that exclude key benefits to society, the mine new principles for modern rate design, the environment, or the grid. In 2016, Environment Amer- authors contend that policymakers must work to ica and Frontier Group published Shining Rewards, “fully comprehend and reflect resource value in which assessed recent value-of-solar studies, mostly rates” through “conscious engagement with objec- either commissioned by public utility commissions tive, data-driven valuation processes.”38 For poli- or submitted as evidence in ratemaking cases. Of 16 cymakers to fully comprehend the value of solar, studies published, only eight accounted for avoided they must understand solar energy’s full range of greenhouse gas emissions, and only three accounted costs and benefits, including environmental, public for economic development benefits. No studies com- health, and other societal impacts – and incor- missioned by utilities accounted for the value of solar porate them appropriately into rate-setting and energy beyond the grid. investment decisions.

Many states already incorporate solar energy’s societal and environmental benefits in value-of-solar studies. In Maine, for example, the state Legislature The societal benefits of [distributed solar required the public utilities commission to “determine generation] policies, such as job growth, the value of distributed solar energy generation” and in doing so to account for “the societal value of the health benefits and environmental benefits, reduced environmental impacts of the energy.”39 should be included in valuations, as these were typically among the reasons for policy The Interstate Renewable Energy Council, which works to provide energy regulators with best prac- enactment in the first place.” tices and other policy resources, has written that the “societal benefits of [distributed solar generation] - Interstate Renewable Energy Council policies, such as job growth, health benefits and envi-

Value-of-Solar Studies Should Account for All of Solar Energy’s Societal Benefits 9 U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 14 of 20 Those studies that left out societal benefits valued Meanwhile, at least two recent utility value-of-solar solar power, on average, at 14.3 cents per kilowatt- studies have accounted for the societal value of solar hour, compared to 22.9 cents for those studies that energy. A value-of-solar study conducted by Austin at least included greenhouse gas emissions.41 The Energy, a publicly owned utility that compensates difference is even starker when studies include public rooftop solar owners based on its calculated value of health, economic or other societal values. solar, accounts for the avoided carbon dioxide emissions using the social cost of carbon (as estimated by More recent value-of-solar studies from 2017 and the U.S. EPA).45 And in Minnesota, Xcel Energy’s 2019 2018 have also left out the societal value of solar value-of-solar tariff calculation includes avoided en- energy. South Carolina utilities, using a state-deter- vironmental costs that are based on the social cost of mined methodology, reported that solar generation carbon, and externality costs for non-CO2 emissions had zero value for avoided CO emissions, since they 2 developed by the Minnesota Public Utility Commis- only assessed avoided compliance costs.43 Oregon sion.46 Xcel Energy’s calculation was made using a utilities, also using a state-determined methodol- required, state-commissioned methodology.47 ogy, based avoided emission values on “anticipated environmental standards” – the estimated avoided In both studies, despite only including a subset of cost of compliance with future greenhouse gas stan- societal benefits, those benefits were found to be sig- dards – and therefore did not include the full societal nificant: Environmental benefits accounted for more benefits of avoided emissions.44 than 17 percent of the value of solar energy in Austin

25 Study Includes Some Societal Bene t Economic Development and Jobs Creation 20 Avoided Greenhouse Gas Emissions Societal Bene ts Cost of Environmental Compliance 15 Grid Resiliency 10 Reduced Financial Risks Grid

Bene ts Avoided Capital and Capacity Investment 5 Avoided Energy Costs Value of Solar Energy (Cents per kWh) Value Costs of Solar Integration 0 Miscellaneous -5 (U)—Studies written by, or commissioned by, utilities E3 (O) (PUC)—Studies written by, or commissioned by, public SAIC (U) Xcel (U) Acadia (O) utilities commissions CPR (NJ) (O) CPR (PA) (O) (O)—Studies written by, or commissioned by, non-utility CPR (Utah) (O) Synapse (PUC) CPR (Austin) (U) CPR/Xcel (PUC) organizations Maine PUC (PUC) SolarCity/NRDC (O) Vermont DPS (PUC) CPR (San Antonio)Crossborder (O) (AZ Crossborder2013) (AZ 2016)

Among 16 value-of-solar studies included in Environment America Research & Policy Center and Frontier Group’s 2016 report Shining Rewards, only eight accounted for any societal benefits, none conducted by or for utilities.42

10 The True Value of Solar U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 15 of 20 Energy’s analysis, and more than 33 percent in Xcel solar energy for the excess electricity they supply to Energy’s.48 Yet these substantial benefits are typically the grid. For example, a solar cost-benefit analysis left out of utility analyses. conducted for the Louisiana Public Service Commis- sion that did not include social benefits informed Failing to account for the full value of solar energy legislation that severely restricted Louisiana’s solar may have costly ramifications. Utility regulators, tax credit.49 legislators and the public are keenly focused on ensuring that utility rate-setting and investment deci- Understanding the full value of solar installations sions do not impose undue burdens on ratepayers. can help policymakers develop and implement ap- Value-of-solar studies that fail to include key societal, propriate tools to compensate owners of distributed environmental and grid benefits of solar power have solar projects for the value they provide. The full been used to undermine support for policies such as range of benefits to society needs to be reflected in net metering that compensate owners of distributed those policies.

Value-of-Solar Studies Should Account for All of Solar Energy’s Societal Benefits 11 U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 16 of 20 Conclusion and Recommendations

s policymakers consider the future of • The societal value of other avoided pollutants, America’s energy system, they should seek including criteria pollutants such as particulate to make decisions that serve the public matter, lead, and sulfur dioxide. Ainterest. In his seminal and oft-cited work on util- Policymakers should also seek to quantify and ac- ity ratemaking, Principles of Public Utility Rates, count for a broader set of societal impacts of solar James Bonbright defined “the theory of rates” as energy, including: “the systematic development of principles of ratemaking policy, the complete or qualified observance • The local economic benefits of solar energy, of which would subserve the public interest or the including the creation of local jobs and businesses. social welfare.”50 • The societal value of avoided costs imposed by In 2019, serving the public interest means considering fossil fuels throughout their life cycle, including: the broad impacts of electricity generation, which is closely tied to many of America’s most pressing ºº Impacts from resource extraction, such as 52 environmental and public health challenges. In 2017, methane emissions associated with fracking. electricity generation accounted for 28 percent ºº Health care and mortality costs associated with of U.S. global warming emissions, and as America pollution from the entire fossil fuel lifecycle. moves toward the electrification of transportation and heating, the importance of clean electricity will ºº Potential impacts of accidents and spills associ- only increase.51 ated with fossil fuels, including coal ash, fracking and pipeline spills. When it comes to solar energy, that means basing policy decisions on studies that accurately and fully After accounting for the full value of solar, policymakers assess the impact of solar energy on the grid and so- should seek to ensure that electricity rates, investment ciety. Failing to account for solar energy’s full range of decisions, and other energy policies fully reflect their benefits is not only unsound policymaking, but also findings. There is precedent for ensuring that electricity risks putting America on a path to a less healthy, less rates incorporate societal costs and benefits beyond sustainable, and less prosperous future. energy costs, and doing so is both justifiable and necessary.53 In some cases, legislators may need to ensure that To craft energy policy that accurately reflects the state utility commissions have the authority to account value of solar energy resources, policymakers should for external costs and benefits in ratemaking decisions. account for the societal as well as the grid benefits of solar energy, specifically including: The decisions we make about our use of power not only impact the grid, but also our health, our quality of • The societal value of avoided greenhouse gas life, and our future. Energy policy should reflect that – emissions. after all, ratepayers are taxpayers and citizens too.

12 The True Value of Solar U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 17 of 20 Notes

1 Based on 2018 “small-scale solar photovoltaic” 5 Union of Concerned Scientists, The Hidden Costs generation and 2017 household electricity use, and of Fossil Fuels, archived on 11 May 2019 at http://web.ar- EPA emissions calculator https://www.eia.gov/electric- chive.org/web/20190511145203/https://www.ucsusa.org/ ity/data/browser/; https://www.eia.gov/tools/faqs/faq. clean-energy/coal-and-other-fossil-fuels/hidden-cost-of- php?id=97&t=3; https://www.epa.gov/energy/green- fossils. house-gas-equivalencies-calculator. 6 U.S. Environmental Protection Agency, The 2 Based on a number of studies, including ICF, Social Cost of Carbon, archived on 26 March 2019 Review of Recent Cost-Benefit Studies Related to Net Me- at http://web.archive.org/web/20190326203039/ tering and Distributed Solar, https://www.icf.com/blog/ https://19january2017snapshot.epa.gov/climatechange/ energy/value-solar-studies; and Rocky Mountain Institute, social-cost-carbon_.html. A Review of Solar PV Benefit and Cost Studies nd2 Edition, 7 See note 4. September 2013, archived at https://web.archive.org/ web/20190614151829/https://rmi.org/wp-content/up- 8 Ibid. loads/2017/05/RMI_Document_Repository_Public-Reprts_ eLab-DER-Benefit-Cost-Deck_2nd_Edition131015.pdf. 9 Ibid.

3 Maine and Pennsylvania: Gideon Weissman, 10 Solar Energy Industries Association, U.S. Solar Frontier Group and Bret Fanshaw, Environment America Market Insight, 13 December 2018, archived on 5 March Research & Policy Center, Shining Rewards 2016 Edition, 2019 at http://web.archive.org/web/20190305024257/ October 2016; Arkansas: Arkansas Public Service Com- https://www.seia.org/us-solar-market-insight. mission Net-Metering Working Group, Joint Report and 11 Vermont Public Service Department, Evaluation Recommendations of The Net-Metering Working Group, of Net Metering in Vermont Conducted Pursuant to Act 125 15 September 2017, archived at https://web.archive.org/ of 2012, 15 January 2013, available at http://www.leg.state. web/20190201025654/http://www.apscservices.info/ vt.us/reports/2013ExternalReports/285580.pdf; see also: pdf/16/16-027-R_228_1.pdf Damian Pitt and Gilbert Michaud, “Assessing the Value of 4 Ben Machol and Sarah Rizk, “Economic Value of Distributed Solar Energy Generation”, Curr Sustainable Re- U.S. Fossil Fuel Electricity Health Impacts,” Environment newable Energy Rep, 2015, DOI:10.1007/s40518-015-0030-0. International, February 2013, https://doi.org/10.1016/j. envint.2012.03.003.

Notes 13 U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 18 of 20 12 Small-scale solar generation: U.S. Energy Infor- 18 Daymark Energy Advisors prepared for Mary- mation Administration, Electricity Data Browser, accessed at land Public Service Commission, Benefits and Costs of https://www.eia.gov/electricity/data/browser/ on 1 Febru- Utility Scale and Behind the Meter Solar Resources In Mary- ary 2019; net metering by state: N.C. Clean Energy Tech- land, 10 April 2018, archived at http://web.archive.org/ nology Center, DSIRE Net Metering Summary Map, April web/20180514201412/http://www.psc.state.md.us/wp- 2019, available at https://s3.amazonaws.com/ncsolarcen- content/uploads/MD-Costs-and-Benefits-of-Solar-Draft- prod/wp-content/uploads/2019/05/DSIRE_Net_Metering_ for-stakeholder-review.pdf. April2019.pdf; U.S. population by state: U.S. Census Bureau, 19 Union of Concerned Scientists, The Natural Gas Table 1. Annual Estimates of the Resident Population for the Gamble: A Risky Bet on America’s Clean Energy Future, March United States, Regions, States, and Puerto Rico: April 1, 2010 to 2015. July 1, 2018 (NST-EST2018-01), December 2018, available at https://www.census.gov/newsroom/press-kits/2018/pop- 20 Mark Bolinger, Lawrence Berkeley National estimates-national-state.html. Laboratory, Using Probability of Exceedance to Compare the Resource Risk of Renewable and Gas-Fired Generation, March 13 See note 2. 2017, available at http://eta-publications.lbl.gov/sites/de- 14 Line losses: U.S. Energy Information Administra- fault/files/lbnl-1007269.pdf. tion, United States Electricity Profile 2017: Table 10. Supply 21 Thomas Jenkin et al, National Renewable Energy and disposition of electricity, 1990 through 2017, 8 January Laboratory, Ray Byrne, Sandia National Laboratories, The 2019, available at https://www.eia.gov/electricity/state/ Use of Solar and Wind as a Physical Hedge against Price Vari- unitedstates/; average 2017 retail price of electricity was ability within a Generation Portfolio, August 2013. 10.48 cents per kWh: U.S. Energy Information Administra- tion, 22 Richard Perez et al., Clean Power Research prepared for Mid‐Atlantic Solar Energy Industries Association Electric Power Annual With Data for 2017: Table 2.4. Aver- and Pennsylvania Solar Energy Industries Association, The age Price of Electricity to Ultimate Customers, 22 October Value of Distributed Solar Electric Generation to New Jersey 2018, available at https://www.eia.gov/electricity/annual/. and Pennsylvania, November 2012, archived at http://web. 15 Lazar, J. and Baldwin, X., Valuing the Contribution archive.org/web/20170829111033/http://mseia.net/site/ of Energy Efficiency to Avoided Marginal Line Losses and wp-content/uploads/2012/05/MSEIA-Final-Benefits-of- Reserve Requirements, Regulatory Assistance Project, 2011. Solar-Report-2012-11-01.pdf. Also see: Rocky Mountain Institute, A Review of Solar PV Benefit and Cost Studies nd2 16 Michael Craig et al., “A Retrospective Analysis Edition, September 2013, archived at https://web.archive. of the Market Price Response to Distributed Photovoltaic org/web/20190614151829/https://rmi.org/wp-content/ Generation in California,” Energy Policy, 14 July 2018, doi: uploads/2017/05/RMI_Document_Repository_Public- 10.1016/j.enpol.2018.05.061. Reprts_eLab-DER-Benefit-Cost-Deck_2nd_Edition131015. 17 Paul Chernick, Resource Insight, Inc., John J. Plun- pdf. kett, Green Energy Economics Group Inc., Price Effects as a 23 U.S. Environmental Protection Agency, Sources Benefit of Energy-Efficiency Programs, 2014. of Greenhouse Gas Emissions, archived on 12 June 2019 at http://web.archive.org/web/20190612083429/https:// www.epa.gov/ghgemissions/sources-greenhouse-gas- emissions.

14 The True Value of Solar U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 19 of 20 24 Elizabeth Ridlington and Gideon Weissman, Fron- 33 Ibid. tier Group, Natural Gas and Global Warming, Summer 2016, 34 Kristen Averyt et al., Union of Concerned Scien- archived at http://web.archive.org/web/20161020192209/ tists, Freshwater Use by U.S. Power Plants: Electricity’s Thirst http://frontiergroup.org:80/sites/default/files/reports/ for a Precious Resource, November 2011, available at https:// full%20report%20-%20Frontier%20Group%20-%20 www.ucsusa.org/clean_energy/our-energy-choices/en- Natural%20Gas%20and%20Global%20Warming%20-%20 ergy-and-water-use/freshwater-use-by-us-power-plants. July%202016.pdf; Gunnar Myhre et al., “Anthropogenic html. and Natural Radiative Forcing,” in T.F. Stocker et al. (eds.), Climate Change 2013: The Physical Science Basis. Contribu- 35 The Solar Foundation, National Solar Jobs Census tion of Working Group I to the Fifth Assessment Report of 2017, January 2018. the Intergovernmental Panel on Climate Change (Cam- bridge, United Kingdom and New York, NY, USA: Cam- 36 U.S. Bureau of Labor Statistics, Occupational bridge University Press, 2013), 714. Outlook Handbook – Fastest Growing Occupations, 12 April 2019, archived at http://web.archive.org/ 25 Peter Howard, Environmental Defense Fund, web/20190612165516/https://www.bls.gov/ooh/fastest- Institute for Policy Integrity and the Natural Resources growing.htm. Defense Council, Omitted Damages: What’s Missing from the Social Cost of Carbon, 13 March 2014. 37 Solar Energy Industries Association, Solar Industry Research Data, archived on 1 February 2019 at http://web. 26 Tons of carbon dioxide pollution multiplied by archive.org/web/20190201231745/https://www.seia.org/ $37. Electric power carbon dioxide emissions: U.S. Envi- solar-industry-research-data. ronmental Protection Agency, Greenhouse Gas Inventory Data Explorer, accessed at: https://cfpub.epa.gov/ghgdata/ 38 Karl R. Rábago and Radina Valova, “Revisiting inventoryexplorer/ on 13 June 2019. Bonbright’s Principles of Public Utility Rates in a DER World,” The Electricity Journal, October 2018, https://doi. 27 SEIA, Siting & Permitting, archived at web.archive. org/10.1016/j.tej.2018.09.004. org/web/20160916220218/http://www.seia.org/policy/ th power-plant-development/siting-permitting. 39 126 Maine Legislature, An Act to Support Solar Energy Development in Maine, enacted 24 April 2014. 28 U.S. Environmental Protection Agency, Air Pollut- ants, 1 June 2015, accessed at: www.epa.gov/air/airpollut- 40 Interstate Renewable Energy Council, A Regula- ants.html. tor’s Guidebook: Calculating the Benefits and Costs of Distrib- uted Solar Generation, October 2013, available at https:// 29 American Lung Association, State of the irecusa.org/2013/10/experts-propose-standard-valuation- Air 2018, 2018, archived at http://web.archive.org/ method-to-determine-benefits-and-costs-of-distributed- web/20190214160111/https://www.lung.org/our-initia- solar-generation/. tives/healthy-air/sota/key-findings/. 41 Gideon Weissman, Frontier Group and Bret 30 Ibid. Fanshaw, Environment America Research & Policy Cen- ter, Shining Rewards: The Value of Rooftop Solar Power for 31 Union of Concerned Scientists, Environmental Im- Consumers and Society - 2016 Edition, 18 October 2016, pacts of Coal Power: Air Pollution, accessed at www.ucsusa. available at https://frontiergroup.org/reports/fg/shining- org/clean_energy/coalvswind/c02c.html#.VW5vus9Viko, 2 rewards-0. June 2015. 42 Ibid. 32 See note 5.

Notes 15 U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 20 of 20 43 South Carolina Office of Regulatory Staff,Status 49 Energy and Policy Institute, Louisiana Solar Energy Report on Distributed Energy Resource and Net Energy Meter- Attacked, date not given, archived at https://web.archive. ing Implementation, July 2017, available at https://www. org/web/20190614182149/https://www.energyandpolicy. scstatehouse.gov/reports/ORS/FINAL%20DER%20and%20 org/renewable-energy-state-policy-attacks-report-2015/ NEM%20Report%202017.pdf; further methodological louisiana-net-metering-attacked/; Brian Slodysko, “Law- details: Public Service Commission of South Carolina, IN RE: makers Curtail Louisiana’s Generous Solar Tax Break, Petition of the Office of Regulatory Staff to Establish Generic Cause Industry to Cry Foul,” Associated Press, 24 June 2015, Proceeding Pursuant to the Distributed Energy Resource available at https://www.theadvocate.com/baton_rouge/ Program Act, Act No. 236 of 2014, Ratification No. 241, Senate news/politics/legislature/article_fc19cfdd-24d4-5f56- Bill No. 1189 - DOCKET NO. 2014-246-E - ORDER NO. 2015- a557-7a1e104188a5.html; Acadian Consulting Group on 194, available at https://dms.psc.sc.gov/Attachments/ behalf of Louisiana Public Service Commission, Estimating Order/29cf4369-155d-141f-23b1536c046aebc5. the Impact of Net Metering on LPSC Jurisdictional Ratepay- ers, 27 February 2015, archived at http://web.archive. 44 Jacob Goodspeed, Portland General Electric org/web/20171230032152/http://lpscstar.louisiana.gov/ Company, RE: UM 1912 - Portland General Electric Resource star/ViewFile.aspx?Id=f2b9ba59-eaca-4d6f-ac0b-a22b- Value of Solar Filing, 4 December 2017, archived at https:// 4b0600d5. web.archive.org/web/20190131205939/https://edocs.puc. state.or.us/efdocs/HAA/haa163313.pdf. 50 James C. Bonbright, Principles of Public Utility Rates, (New York: Columbia University Press, 1961), 27, 45 Austin Energy, 2018 Value of Solar (VOS) Up- available at https://www.raponline.org/wp-content/ date, May 2017, archived at https://web.archive.org/ uploads/2016/05/powellgoldstein-bonbright-principlesof- web/20190206034952/http://www.austintexas.gov/edims/ publicutilityrates-1960-10-10.pdf. document.cfm?id=277018. 51 U.S. Environmental Protection Agency, Sources 46 Xcel Energy 2019 Value of Solar calculation: of Greenhouse Gas Emissions, archived on 18 May 2019 at See Minnesota Public Utilities Commission docket no. http://web.archive.org/web/20190518043422/https:// E002/M-13-867, available at https://www.edockets.state. www.epa.gov/ghgemissions/sources-greenhouse-gas- mn.us/EFiling/edockets/searchDocuments.do?method=sh emissions, owPoup&documentId={F06EBB69-0000-C012-9D35-422A1 9F427EA}&documentTitle=20193-151380-01; state meth- 52 See note 24. odology: Minnesota Department of Commerce, Division 53 For example, the New Jersey Societal Benefit of Energy Resources, Minnesota Value of Solar: Method- Charge: New Jersey’s Clean Energy Program, Societal ology, 9 April 2014, archived at http://web.archive.org/ Benefits Charge (SBC), archived on 28 September 2018 at web/20170521032153/http://mn.gov/commerce-stat/pdfs/ http://web.archive.org/web/20180928201733/http://www. vos-methodology.pdf. njcleanenergy.com:80/societal-benefits-charge. 47 Ibid.

48 See note 45 and note 46.

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Disparities in Distribution of Particulate Matter Emission Sources by Race and Poverty Status

Ihab Mikati, BS, Adam F. Benson, MSPH, Thomas J. Luben, PhD, MSPH, Jason D. Sacks, MPH, and Jennifer Richmond-Bryant, PhD

Objectives. To quantify nationwide disparities in the location of particulate matter cardiovascular diseases as well as premature 6–8 (PM)-emitting facilities by the characteristics of the surrounding residential population mortality. Although proximity to facilities and to illustrate various spatial scales at which to consider such disparities. emitting PM is not a direct measure of ex- Methods. We assigned facilities emitting PM in the 2011 National Emissions Inventory posure, it is a valuable metric. Unlike natural to nearby block groups across the 2009 to 2013 American Community Survey population. events that contribute to ambient PM, such as wildfires, the siting of a facility is the result of We calculated the burden from these emissions for racial/ethnic groups and by poverty a decision-making process. Disparities in siting status. We quantified disparities nationally and for each state and county in the country. may indicate underlying disparities in the Results. For PM of 2.5 micrometers in diameter or less, those in poverty had 1.35 times power to influence that process. For example, higher burden than did the overall population, and non-Whites had 1.28 times higher an Environmental Protection Agency (EPA) burden. Blacks, specifically, had 1.54 times higher burden than did the overall population. investigation in Flint, Michigan, found a direct These patterns were relatively unaffected by sensitivity analyses, and disparities held not link between racial discrimination and the only nationally but within most states and counties as well. permitting of a power station there, stating, Conclusions. Disparities in burden from PM-emitting facilities exist at multiple geo- “The preponderance of evidence supports a graphic scales. Disparities for Blacks are more pronounced than are disparities on the finding of discriminatory treatment of African basis of poverty status. Strictly socioeconomic considerations may be insufficient to Americans by [the Department of Environ- reduce PM burdens equitably across populations. (Am J Public Health. 2018;108:480– mental Quality] in the public participation process.”9 485. doi:10.2105/AJPH.2017.304297) We aimed to quantify nationwide disparities in the distribution of PM-emitting facilities by See also Houston, p. 441. the characteristics of the surrounding residential populations and to illustrate various spatial scales at he inequitable distribution of hazardous those in poverty than for those above the whichtoconsidersuchdisparities.Previouslit- T fi sites such as land lls and industrial fa- poverty line, whereas the disparity for non- erature has shown that non-Whites and below- cilities is one of the longest-standing concerns Whites (37% higher concentrations than for poverty individuals are more likely to reside near in the field of environmental justice. More 3 10 Whites) was substantially greater. stationary sites of PM2.5 emissions ; we sought to than 3 decades ago in one of the earliest There is considerable evidence concerning updateandexpandonthesefindings. environmental justice studies, the US gov- human health impacts of residential proximity ernment reported a disproportionately high to facilities emitting air pollutants.4 One such representation of socially disadvantaged pollutant is particulate matter (PM), a mixture populations residing in communities near of solid and liquid particles suspended in the landfills.1 Disparities in residential proximity METHODS air.5 Exposure to PM (PM £ 10 mmindi- to pollution sources have been evaluated in 10 We combined facility emissions data with ameter) and especially to PM (PM £ 2.5 mm terms of income level and poverty as well as 2.5 demographic data to investigate racial/ethnic race/ethnicity. A nationally representative in diameter) has been associated with a number and economic disparities in residential 1986 sample found that Blacks were 1.54 of health effects, including respiratory and proximity to sources of air pollution. times more likely than were Whites to live within 1 mile of a facility listed in the Toxics ABOUT THE AUTHORS Release Inventory—a gap that remained Ihab Mikati and Adam F. Benson are participants in the Oak Ridge Institute for Science and Education research training program fi stationed with the National Center for Environmental Assessment, Office of Research and Development, US Environmental statistically signi cant even after accounting Protection Agency, Research Triangle Park, NC. Thomas J. Luben, Jason D. Sacks, and Jennifer Richmond-Bryant are staff for income and education level.2 The dis- members with the National Center for Environmental Assessment, Office of Research and Development, US Environmental tributions of specific air pollutants, and not Protection Agency, Research Triangle Park, NC. Correspondence should be sent to Ihab Mikati, ORISE Program participant at the National Center for Environmental Assessment, just the facilities emitting them, also reflect Office of Research and Development, US Environmental Protection Agency—109 T.W. Alexander Drive, Research Triangle Park, racial disparities. For example, mean resi- NC 27709 (e-mail: [email protected]; please cc: [email protected] to ensure receipt). Reprints can be ordered at http:// www.ajph.org by clicking the “Reprints” link. dential ambient nitrogen dioxide concen- This article was accepted December 16, 2017. trations in 2010 were about 7% higher for doi: 10.2105/AJPH.2017.304297

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Data Sources hazards relative to those in large rural tracts.15 Sensitivity Analyses We accessed population data via the US To address this, we used a distance-based We conducted several sensitivity analyses Census Bureau’s 2009 to 2013 American “centroid-containment” assignment in- to address the potential for small methodo- 15 Community Survey (ACS).11 The ACS stead. We assigned each facility and its logical changes to bias our results. To examine provides self-reported data on racial/ethnic corresponding emissions (in tons per year) to whether disparities were consistent at various identification and poverty status at the census all census block groups containing a centroid distances from emissions sources, we used block group level for all 50 states and within a set radius of the facility’s geographic assignment radii at 0.50, 1.25, and 5.00 miles Washington, DC. The block group is a single coordinates. We analyzed radii ranging from as alternatives to the 2.50-mile centroid- level of resolution finer than the census tract 0.5 to 5.0 miles; in our main analysis, we used containment radius in the main analysis. To and commonly contains 600 to 3000 a 2.5-mile radius, following the NEI facility address whether the reported disparities were 10 residents. assignment of Boyce and Pastor. We assigned driven by assignments in extremely sparse or For our analyses, “White” refers to only facilities and emissions meeting the centroid- dense areas, we repeated the main analysis non-Hispanic Whites; “non-White” refers to containment criteria for a block group to the after eliminating the largest and smallest decile all others. Included in the latter group are Black population residing within that block group. of block groups (by area). An additional (non-Hispanic) and Hispanic (any race). The We measured the between-group differ- analysis ensured that facilities were always Census Bureau determines poverty status by ences in residential proximity to facilities and assigned to their host block group by com- comparing household income to a threshold facility emissions by using 2 metrics: the ab- bining the centroid-containment assignment that varies by household size and composition.12 solute burden (i.e., the average number of with the traditional unit–hazard coinci- Because there are differences between facilities or average amount of PM, in tons/ dence; this helped us address concerns that rural and urban areas both in industrialization year, emitted within a set distance from an centroid-containment assignment could un- and in demographic composition, we also individual’s block group centroid) and the derestimate the burden in rural areas, where noted rural–urban status for all block groups. proportional burden (i.e., the ratio between facilities may be far from their host block We made rural–urban status determinations a demographic subgroup’s average burden group’s centroid. from the US Department of Agriculture’s and that of the overall population). We repeated the main analysis using racial/ rural–urban commuting area (RUCA) codes To determine average absolute burden ethnic population data from the 2010 De- for 2010.13 These codes are determined on (Equation 1) for demographic subgroups, we cennial Census (poverty data unavailable for the basis of census tract–level population multiplied the emissions (or total number of this data set) to show that disparities were not density, urbanization, and daily commuting facilities) assigned to each block group by specific to the census methodology of the levels; they can be used to distinguish be- the subgroup’s population size. We divided ACS. We considered recent shifts in pollution tween metropolitan and micropolitan urban the sum of this value across block groups data by substituting the 2008 or 2014 NEI in centers, commuting (suburban) areas, small by the total subgroup population, similar to place of the 2011 data set. To gauge general towns, and rural areas.13 previous studies.10,16,17 applicability to other emissions, we also an- We collected emissions data on stationary ð1Þ Absolute Burden alyzed other criteria air pollutants available human-made point sources from the US P in the NEI: carbon monoxide (CO), lead ðPopulation · Emissions Þ P BlockGroup BlockGroup EPA National Emissions Inventory (NEI) ¼ (Pb), oxides of nitrogen (NOX), and sulfur PopulationBlockGroup “Facility-level by Pollutant” files for 2011, dioxide (SO2). the year most closely aligned to the census We calculated proportional burdens data we used for our analysis.14 This data (Equation 2) by dividing the absolute burden source allowed us to consider not just the in a subgroup of the population by the ab- presence or absence of a facility but also the solute burden in the overall population. amount of the pollutant emitted. We con- RESULTS Scores above 1.0 indicate that the subgroup sidered annual NEI totals, in tons per year, for On average, there are 5.7 NEI facilities experienced higher burden than would be primary PM and primary PM . within 2.5 miles of an individual’s census 2.5 10 expected in a perfectly equitable scenario. block group centroid (i.e., a facility burden ð Þ 2 Proportional BurdenSubgroup of 5.7). For an individual in the overall Data Analysis US population, the mean absolute burden ¼ Absolute BurdenSubgroup The spatial size (i.e., land area) of block of PM2.5 and PM10 emitted from nearby Absolute BurdenOverall groups can vary substantially between urban facilities is 22.4 and 29.2 tons per year, re- and rural areas because of the block group’s We carried out all data management and spectively. As reported in Table 1, non- restricted population range. As population analysis by using R software version 3.1.2 Whites and those living in poverty face densities increase and block groups shrink in (R Foundation for Statistical Computing, a disproportionate burden from PM-emitting urban areas, assignment via “unit–hazard Vienna, Austria; packages used: dplyr, tidyr, facilities. Blacks in particular are likely to live coincidence” (the matching of a site to its host bit64, data.table for data management; tigris in high-emission areas; the average PM2.5 unit and no others, regardless of proximity) for block group coordinates; Hmisc for cal- burden in this group is 1.54 times that of the may underestimate the number of nearby culation of correlations). population overall. It is notable that this racial

April 2018, Vol 108, No. 4 AJPH Mikati et al. Peer Reviewed Research 481 U-20471 Official Exhibits of Soulardarity Exhibit SOU-15 Page 3 of 6 AJPH ENVIRONMENTAL JUSTICE

TABLE 1—Mean Absolute and Proportional Burdens From Facilities Emitting PM in the 2011 National Emissions Inventory, Selected Subgroups: American Community Survey, United States, 2009–2013

PM2.5 Burden, PM10 Burden, Facility Burden, Variable Proportion of Population, % Absolute (Proportional) Absolute (Proportional) Absolute (Proportional) Overall population 1.00 22.4 (. . .) 29.2 (. . .) 5.7 (. . .) Race/ethnicitya White 0.63 18.8 (0.84) 24.7 (0.85) 4.1 (0.72) Non-White 0.37 28.6 (1.28) 37.0 (1.27) 8.5 (1.49) Black 0.12 34.5 (1.54) 43.6 (1.49) 6.2 (1.09) Hispanic 0.17 26.9 (1.20) 35.9 (1.23) 9.8 (1.70) Poverty level Above poverty 0.85 20.9 (0.93) 27.2 (0.93) 5.5 (0.95) Below poverty 0.15 30.3 (1.35) 39.3 (1.35) 7.2 (1.26)

Note. PM = particulate matter; PM2.5 = PM of £ 2.5 mm in diameter; PM10 = PM of £ 10 mm in diameter. Poverty level determined by the US Census Bureau in 2013. Burdens represent the PM emissions or the number of facilities in the 2011 National Emissions Inventory that are near the block group of residenceforan average individual in the 2009–2013 American Community Survey population. Absolute burden units for PM emissions are tons/year; for facilities, they are the total number. Proportional burden is the ratio of subgroup burden to overall population burden. a“White” refers to only non-Hispanic Whites; “non-White” refers to all others. Included in the latter group are Black (non-Hispanic) and Hispanic (any race).

disparity is larger than is the poverty-based subgroups. Because of a highly nonnormal Whites (8.7 tons/year) is less than is half the

PM2.5 disparity (1.35 times the overall pop- distribution, individuals residing in block absolute burden for equivalent non-Whites ulation average). Proportional burdens for groups with emissions above the overall mean (20.1 tons/year).

PM2.5 are highly similar to those for PM10, are among the top 15% most burdened. The proportional PM2.5 burden for non- but this is not true for proportional burdens in Across the distribution, the gap in burden Whites at the national level is 1.28 (Table 1). the total number of facilities. This difference between those above and those below the This indicates that high non-White pop- suggests that the magnitude of emissions from poverty line is smaller than is the gap between ulations coincide with high emissions na- a facility, and not simply its presence or ab- Whites and non-Whites. At the 50th per- tionally. Burdens can also be considered sence, is valuable information when charac- centile, Whites have an absolute PM2.5 within finer spatial scales—for example, the terizing burden. burden below 0.1 tons per year—more than ratio of burdens between non-Whites and the Figure 1 illustrates the population-wide an order of magnitude below the burden of overall population in a particular state or distribution of absolute PM2.5 burden for the any of their non-White counterparts. At the county. Disparities operate in different ways overall population as well as for several 80th percentile, the absolute burden for at each scale, yet overall higher burdens for non-Whites are a consistent outcome at both state (Figure A, part a [available as a supple- 10 000 Overall Hispanic ment to the online version of this article at 1000 White Above poverty http://www.ajph.org]) and county (Figure Black Below poverty A, part b) levels. All but 4 states (Maryland, 100 New Mexico, North Dakota, and West (Mean: 22.4) Virginia) and Washington, DC, have an 10 elevated mean PM2.5 burden for the non- 1.0 White population (i.e., proportional burdens > 1.0). Comparing the White and non-White 0.1 burdens across all states confirms a statistically significant overall difference in absolute Absolute Burden, Tons/Year 0.0 PM burdens (paired t test mean of 0 20 40 60 80 100 2.5 differences = –11.04 (–15.30, –6.79); – Percentile in Total Population t(50) = –5.22; P < 10 5). Likewise, the ma-

Note. PM2.5 = particulate matter of 2.5 micrometers in diameter or less. Burden scale (y-axis) is displayed jority of counties have higher absolute PM2.5 logarithmically. Poverty level determined by the US Census Bureau in 2013. burdens for their non-White residents (paired t test mean of differences = –3.43 (–4.37, –2.48); — – FIGURE 1 Distribution of Absolute Burdens of PM2.5 Emissions From Nearby Facilities in the t(3140) = –7.12; P < 10 11). ﬁ 2011 National Emissions Inventory, Strati ed by Race/Ethnicity and Poverty Status: We recognized rural–urban status as American Community Survey, United States, 2009–2013 a potential modiﬁer because of the

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industrialization of cities combined with 2014 NEI by a mean of 11.7 tons per year in including all facilities hosted in a block group, the high representation of non-Whites in the overall population (i.e., a 38% drop over regardless of distance to centroid; and using population-dense centers. For this reason, we the 6-year interval). This drop was slightly 2010 Decennial Census data instead of the used the RUCA codes to characterize and smaller (33%) for Blacks and slightly greater 2009 to 2013 ACS. The results of these an- stratify block groups by rural–urban status (41%) for Hispanics. Despite large drops in alyses were largely consistent with the original (Table A [available as a supplement to the absolute burden for all groups, proportional analysis, suggesting robustness in results de- online version of this article at http://www. burdens appear stagnant. The proportional spite alterations in methodology (Table C ajph.org]). As shown in Figure 2, the overall PM2.5 burden of 1.61 for Blacks in the 2014 [available as a supplement to the online national burdens are largely driven by high NEI is higher than are the proportional version of this article at http://www.ajph. emissions in the metropolitan and micro- burdens in the 2011 NEI (1.54; Table 1) and org]). Extending the analysis to other criteria politan cores (those with populations of at the 2008 NEI (1.50; Table B). Data are also pollutants tracked by the NEI (CO, Pb, least 50 000 and those with populations of at provided using the 2012 to 2016 ACS and NOX, and SO2) also remained largely con- least 10 000 but less than 50 000, respectively). 2014 NEI (Table B). However, because sistent with PM results with few exceptions Although those living above the poverty comparison of overlapping ACS data sets is (Table D [available as a supplement to the line do experience a lower burden than do advised against,18 this analysis is limited in that online version of this article at http://www. those below it within these urban areas, the it considers only changes in PM2.5 emissions ajph.org]). The block group Spearman cor- disparities in emissions are especially pro- and not changes in demographics during this relation of CO, Pb, NOX, and SO2 to PM2.5 nounced for Blacks—reinforcing the overall time span. It is not possible to determine assignments were 0.92, 0.77, 0.94, and 0.93, ﬁnding that racial disparities appear to be a causal relationship for changes over time respectively (Table E [available as a supple- markedly higher than are poverty-based from this analysis. Although there is evidence ment to the online version of this article at disparities. that lower property values attract minority http://www.ajph.org]); the amount of PM2.5 We also explored recent changes in populations after siting, high representation of emitted near a block group is likely a general emission distributions by considering avail- those groups generally also exists before the indicator of the overall emissions in that area. able NEI year data for a 6-year range (Table B siting of a facility in an area.19 [available as a supplement to the online We performed sensitivity analyses by re- version of this article at http://www.ajph. peating the main analysis after adjusting the org]). Absolute PM2.5 burden dropped for all centroid-containment radius; removing the DISCUSSION examined subgroups between the 2008 and smallest and largest decile of block groups; We characterized the populations residing near NEI facilities to determine whether individuals from certain subgroups face dis- Overall population Hispanic proportionately high burden from nearby PM 50 White Above poverty RUCA Description emissions. We observed disproportionately Black Below poverty 1 Metropolitan core 2 Metropolitan high-commuting high burdens for non-Whites and those living 3 Metropolitan low-commuting 40 in poverty (Table 1; Figure 1). Disparities 4 Micropolitan core 5 Micropolitan high-commuting for non-Whites persist at multiple scales: 6 Micropolitan low-commuting nationally, in the vast majority of states 7 Small town core 30 8 Small town high-commuting (Figure A, part a) and in the majority of in- 9 Small town low-commuting dividual counties (Figure A, part b). The lack 10 Rural of individual-level data on the intersection of 20 racial/ethnic identiﬁcation and poverty status limited our ability to make direct comparisons; however, overall, racial disparities for 10

Absolute Burden, Tons/Year both PM2.5 and PM10—specifically between Blacks and Whites—are stronger than are 0 poverty-based disparities (Table 1). This is Overall 1 2 3 4 5 6 7 8 9 10 a consistent observation even when consid- RUCA Code ering urban Whites and Blacks alone (Figure 2). PM2.5 and PM10 disparities for Hispanics Note. PM2.5 = particulate matter of 2.5 micrometers in diameter or less; RUCA = rural–urban commuting area. are less pronounced or consistent but still Dashed line indicates mean overall burden for all groups in the United States (22.4 tons/year). The US Department of Agriculture defines and assigns RUCA codes. Poverty level determined by the US Census Bureau present. The diversity within the Hispanic in 2013. population, which includes both native-born persons and recent immigrants from a variety — fi FIGURE 2 RUCA-Strati ed Absolute Burdens of PM2.5 Emissions From Nearby Facilities in of countries, has made the catchall “Hispanic” fi the 2011 National Emissions Inventory, Further Strati ed by Race/Ethnicity and Poverty designation vexing for public health Status: American Community Survey, United States, 2009–2013 research.20,21

April 2018, Vol 108, No. 4 AJPH Mikati et al. Peer Reviewed Research 483 U-20471 Official Exhibits of Soulardarity Exhibit SOU-15 Page 5 of 6 AJPH ENVIRONMENTAL JUSTICE

Our main ﬁnding of national disparities et al.2 found a disproportionately high areas. Because of the higher representation of

in PM2.5 burdens by race is consistent with number of Black residences near polluting the non-White population in urban areas, that of Boyce and Pastor,10 who carried out facilities in Midwestern metropolitan areas— centroid containment offers a more appro-

a similar analysis on PM2.5 using the 2008 NEI much more so than in Southern cities and in priate characterization of Black burdens na- and reported results equivalent to a pro- rural areas. No single scale can be considered tionally. We took several sensitivity measures portional burden of 1.25 for non-Whites best for grouping populations. In this case, to address the potential resulting un- (compared with our ﬁnding of 1.28). Such results at national, state, and county scales all derestimates of burdens in rural areas. In one disparities in residential proximity to sites of indicate that non-Whites tend to be burdened analysis, we combined unit–hazard co- pollution potentially correspond to disparities disproportionately to Whites. incidence with centroid containment to – in a range of health outcomes.22 24 calculate burdens; in others, we varied the

Exposure to PM2.5 has been linked to containment radius between 0.5 and 5.0 – increased morbidity and mortality.6 8 Al- Strengths and Limitations miles. Neither of these alterations to the though our study focused on point source Our methodology has advantages as well as methodology substantially changed the values

emissions and not on ambient PM2.5, the limitations. We relied on proximity to sta- reported in the main analysis, suggesting racial disparity in burdens from nearby facil- tionary, human-made point sources of pri- a robust result (Table C). Furthermore, ities parallels the disparities seen in both mary PM emissions rather than ambient even limiting analysis only to urban areas, modeled16 (Table F [available as a supplement concentrations. Because there is a collection a Black individual living in a metropolitan or to the online version of this article at http:// of other factors that may affect ambient PM micropolitan core has a higher burden than www.ajph.org]) and monitored17 ambient concentrations—including natural events, does her urban White counterpart (Figure 2).

PM2.5 concentration data. Disparities in ex- roadway activity, and the formation of sec- An additional strength of our analysis is the posure between Blacks and Whites have been ondary PM from precursor pollutants—this inclusion of the total amount of pollutants reported to be greater than are disparities on metric should not be interpreted as a direct emitted at each site, as opposed to only the the basis of poverty status,16 whether con- measure of PM exposure. Aggregation of presence or absence of a nearby facility. As sidering only urban, suburban, or rural census burdens to the census tract level allowed us seen in Table 1, the proportional burden in tracts.17 This potential increase in exposure to compare our absolute burden assignments facility number for Blacks is only 1.09; the

for the Black population coupled with higher to EPA’s Fused Air Quality Surface Using proportional burdens in total PM2.5 (1.54) 29 prevalence of conditions such as cardiovas- Downscaling model of PM2.5 daily con- and PM10 (1.49) are much higher. This is cular disease mortality25 and asthma,26 which centration averages for 2011. Despite the consistent with studies suggesting that scaling are known to be linked to PM exposure, presence of small racial disparities in resi- sites by the amount of pollution emitted 32 makes for a population of concern. Equiva- dential ambient PM2.5 for the contiguous can further reinforce findings of inequity. lent increases in PM2.5 have been linked to United States (Table F), mean ambient PM2.5 The difference between disparities in facility statistically significantly higher associations in concentration and tract PM2.5 burden from number and disparities in total PM implies Blacks than in Whites for health outcomes emissions were only weakly correlated that the few extra facilities near the average ranging from asthma attacks27 to overall (Spearman r = 0.30). However, there are Black residence tend to be among the highest mortality.28 In the US Medicare population, benefits to understanding proximity that go emitters. The distribution shown in Figure 1 Blacks who are not eligible for Medicaid (a beyond direct health impacts, including suggests that a relatively small proportion of proxy for higher economic status) have higher monetary reasons. Nearby pollution- the US population bears the vast majority of

PM2.5-related mortality risk than do Whites generating sites are a tangible and accessible burden from PM2.5 emissions. Analysis on the who are eligible.28 marker of pollution, and residents’ awareness basis of the EPA’s Toxic Release Inventory Our analysis considered disparities at var- of such sites is demonstrated by the negative shows that extremely high-polluting “toxic ious scales. Racial disparity at the national effect on housing values.30 outliers” tend to exist in places with higher scale is driven by high emissions in areas with Our method of assignment was to link non-White and low-income populations.33 high non-White populations. However, areas facilities to all block groups that had a centroid with a proportionately higher White pop- within a set radius of the coordinates given in ulation may still be internally inequitable. The the NEI. Centroid-containment and other Public Health Implications few non-Whites who do reside in such an area distance-based methods employing circular This research demonstrates an aspect of are disproportionately likely to live near buffers are better equipped than is unit– a multifaceted public health problem faced by a source of PM emissions. Figure A, part hazard coincidence (i.e., the assignment of marginalized groups. As was exempliﬁed in a highlights such areas; the largely White point sources to only their host census unit) in the EPA’s investigation of racially discrimi- Midwestern states contain some of the most assigning nearby hazards to a population.15,31 natory treatment in a public participation 9 disproportionately high internal PM2.5 bur- Unit–hazard coincidence inherently de- process, the lack of political capital is an den for non-Whites. Indiana, for instance, emphasizes the impact of facilities near bor- obstacle to obtaining more desirable living is more than 80% White, but the dis- ders, which becomes increasingly important conditions. In addition, social and economic proportionality in non-White burden is in small, dense, urban block groups. The challenges can lead marginalized people to greater there than in any other state. Mohai result is an overrepresentation of large, rural further populate an area made less desirable by

484 Research Peer Reviewed Mikati et al. AJPH April 2018, Vol 108, No. 4 U-20471 Official Exhibits of Soulardarity Exhibit SOU-15 Page 6 of 6 AJPH ENVIRONMENTAL JUSTICE

proximity to sources of pollution.19 The the Americans’ Changing Lives Study. Am J Public Health. 19. Mohai P, Saha R. Which came first, people or pol- – potential health effects of the resulting en- 2009;99(suppl 3):S649 S656. lution? Assessing the disparate siting and post-siting de- 3. Clark LP, Millet DB, Marshall JD. Changes in mographic change hypotheses of environmental injustice. vironmental burdens on these groups should Environ Res Lett. 2015;10:115008. transportation-related air pollution exposures by race- be considered in conjunction with existing ethnicity and socioeconomic status: outdoor nitrogen 20. Borrell LN. Racial identity among Hispanics: im- health disparities: access to health care has dioxide in the United States in 2000 and 2010. Environ plications for health and well-being. Am J Public Health. – well-documented disparities by race/eth- Health Perspect. 2017;125(9):097012. 2005;95(3):379 381. nicity,34 and the prevalence of certain diseases 4. Brender JD, Maantay JA, Chakraborty J. Residential 21. Palloni A, Arias E. Paradox lost: explaining the proximity to environmental hazards and adverse health Hispanic adult mortality advantage. Demography. 2004; is notably higher in non-White pop- outcomes. Am J Public Health. 2011;101(suppl 1): 41(3):385–415. 25,26 – ulations. Along with other inequitable S37 S52. 22. Maantay J. Asthma and air pollution in the Bronx: social and physical determinants of health, 5. US Environmental Protection Agency. Particulate methodological and data considerations in using GIS for these interlocking mechanisms must all be matter (PM) basics. Available at: https://www.epa.gov/ environmental justice and health research. Health Place. 2007;13(1):32–56. addressed to establish environmental and pm-pollution/particulate-matter-pm-basics. Accessed April 6, 2017. 23. Kouznetsova M, Huang X, Ma J, Lessner L, Carpenter public health justice. 6. Franklin M, Zeka A, Schwartz J. Association between DO. Increased rate of hospitalization for diabetes and We have presented a framework with PM2.5 and all-cause and specific-cause mortality in 27 US residential proximity of hazardous waste sites. Environ – which to consider the racial and economic communities. J Expo Sci Environ Epidemiol. 2006;17(3): Health Perspect. 2007;115(1):75 79. disparities in residential proximity to sources 279–287. 24. Choi HS, Shim YK, Kaye WE, Ryan PB. Potential of pollution in the United States. We have 7. Pope CA, Dockery DW. Health effects of fine par- residential exposure to toxics release inventory chemicals ticulate air pollution: lines that connect. J Air Waste Manag during pregnancy and childhood brain cancer. Environ – shown that a focus on poverty to the ex- Assoc. 2006;56(6):709–742. Health Perspect. 2006;114(7):1113 1118. clusion of race may be insufficient to meet the 8. Brook RD, Rajagopalan S, Pope CA, et al. Particulate 25. Mensah GA, Mokdad AH, Ford ES, Greenlund KJ, needs of all burdened populations. Applica- matter air pollution and cardiovascular disease: an update Croft JB. State of disparities in cardiovascular health in the – tion of this knowledge can be a valuable to the scientific statement from the American Heart United States. Circulation. 2005;111(10):1233 1241. – resource in improving equity. Disparity Association. Circulation. 2010;121(21):2331 2378. 26. Centers for Disease Control and Prevention. Trends in 9. US Environmental Protection Agency. 01R-94-R5 asthma prevalence, health care use, and mortality in the persists at multiple scales of observation, – MDEQ closure letter. 2017. Available at: https://www. United States, 2001 2010. 2012. Available at: https:// and this suggests that solutions can also be epa.gov/ocr/01r-94-r5-mdeq-closure-letter. Accessed www.cdc.gov/nchs/products/databriefs/db94.htm. Accessed April 17, 2017. approached on multiple levels. March 24, 2017. 27. Nachman KE, Parker JD. Exposures to fine particulate 10. Boyce JK, Pastor M. Clearing the air: incorporating air CONTRIBUTORS air pollution and respiratory outcomes in adults using two quality and environmental justice into climate policy. national datasets: a cross-sectional study. Environ Health. I. Mikati led project design, data analysis, and writing. Clim Change. 2013;120(4):801–814. A. F. Benson contributed to design, writing, and data 2012;11:25. 11. US Census Bureau. American Community Survey visualization. T. J. Luben, J. D. Sacks, and J. Richmond- 28. Di Q, Wang Y, Zanobetti A, et al. Air pollution and (ACS). Available at: https://www.census.gov/programs- Bryant supported project design and writing. mortality in the Medicare population. N Engl J Med. 2017; surveys/acs. Accessed April 17, 2017. 376(26):2513–2522. 12. US Census Bureau. How the census bureau measures ACKNOWLEDGMENTS 29. US Environmental Protection Agency. RSIG-related poverty. Available at: https://www.census.gov/topics/ This research was supported in part by an appointment downloadable data files. Available at: https://www.epa. income-poverty/poverty/guidance/poverty-measures. to the Research Participation Program for the US Envi- gov/hesc/rsig-related-downloadable-data-files. Accessed html. Accessed August 1, 2017. ronmental Protection Agency (EPA), Office of Research April 17, 2017. and Development, administered by the Oak Ridge In- 13. US Department of Agriculture. 2010 rural–urban 30. Davis LW. The effect of power plants on local housing stitute for Science and Education through an interagency commuting area (RUCA) codes documentation. Avail- values and rents. Rev Econ Stat. 2011;93(4):1391–1402. agreement between the US Department of Energy and the able at: https://www.ers.usda.gov/data-products/rural– EPA. urban-commuting-area-codes/documentation. Accessed 31. Chakraborty J, Maantay JA, Brender JD. Dispro- We thank Julian Marshall for his suggestions on April 17, 2017. portionate proximity to environmental health hazards: strengthening the study design and Danelle Lobdell and methods, models, and measurement. Am J Public Health. 14. US Environmental Protection Agency. 2011 Na- Jen Nichols for their helpful comments on the article. 2011;101(suppl 1):S27–S36. tional Emissions Inventory (NEI) data. Available at: Note. This document was reviewed in accordance https://www.epa.gov/air-emissions-inventories/ 32. McMaster RB, Leitner H, Sheppard E. GIS-based with EPA policy and approved for publication. Mention 2011-national-emissions-inventory-nei-data. Accessed environmental equity and risk assessment: methodolog- of trade names or commercial products does not constitute April 17, 2017. ical problems and prospects. Cartogr Geogr Inform. 1997; endorsement or recommendation for use. The views 24(3):172–189. 15. Mohai P, Saha R. Reassessing racial and socioeco- expressed in this article are those of the authors and do not “ ” necessarily reflect the views or policies of the EPA. nomic disparities in environmental justice research. De- 33. Collins MB, Munoz I, JaJa J. Linking toxic outliers mography. 2006;43(2):383–399. to environmental justice communities. Environ Res Lett. 2016;11(1):015004. HUMAN PARTICIPANT PROTECTION 16. Bell ML, Ebisu K. Environmental inequality in ex- 34. Smedley BD, Stith AY, Nelson AR, eds. Unequal No protocol approval was necessary because all data were posures to airborne particulate matter components in the Treatment: Confronting Racial and Ethnic Disparities in Health obtained from publicly available secondary sources. United States. Environ Health Perspect. 2012;120(12): Care. Washington, DC: National Academies Press; 2003. 1609–1704. REFERENCES 17. Bravo MA, Anthopolos R, Bell ML, Miranda ML. 1. US General Accounting Office. Siting of hazardous Racial isolation and exposure to airborne particulate waste landfills and their correlation with racial and eco- matter and ozone in understudied US populations: en- nomic status of surrounding communities. 1983. Avail- vironmental justice applications of downscaled numerical able at: http://www.gao.gov/products/RCED-83-168. model output. Environ Int. 2016;92–93:247–255. Accessed March 13, 2017. 18. US Census Bureau. Comparing ACS data. Available 2. Mohai P, Lantz PM, Morenoff J, House JS, Mero RP. at: https://www.census.gov/programs-surveys/acs/ Racial and socioeconomic disparities in residential guidance/comparing-acs-data.html. Accessed April 11, proximity to polluting industrial facilities: evidence from 2017.

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Page 1 of 10

Energy and Buildings 143 (2017) 25–34

Contents lists available at ScienceDirect

Energy and Buildings

j ournal homepage: www.elsevier.com/locate/enbuild

The intersection of energy and justice: Modeling the spatial,

racial/ethnic and socioeconomic patterns of urban residential heating

consumption and efﬁciency in Detroit, Michigan

∗

Dominic J. Bednar , Tony Gerard Reames, Gregory A. Keoleian

Center for Sustainable Systems, School of Natural Resources and Environment, University of Michigan, 440 Church St., Ann Arbor, MI 48109, United States

a r t i c l e i n f o a b s t r a c t

Article history: Residential energy conservation and efﬁciency programs are strategic interventions to reduce consump-

Received 18 August 2016

tion and increase affordability. However, the inability to identify and distinguish between high energy

Received in revised form 19 February 2017

consumers and highly energy inefﬁcient households has led to ineffective program targeting. Addition-

Accepted 9 March 2017

ally, little is known about the spatial, racial and socioeconomic patterns of urban residential energy

Available online 12 March 2017

consumption and efﬁciency. Publicly available data from the U.S. Energy Information Administration

and the U.S. Census Bureau are used with bottom-up modeling and small-area estimation techniques to

Keywords:

predict mean annual heating consumption and energy use intensity (EUI), an energy efﬁciency proxy, at

Fuel poverty

the census block group level in Detroit (Wayne County), Michigan. Using geographic information sys-

Energy justice

tems, results illustrate spatial disparities in energy consumption and EUI. Bivariate analysis show no

Energy consumption

Energy efﬁciency statistical relationship between race/ethnicity and energy consumption; however, EUI is correlated with

−

Spatial analysis racial/ethnic makeup; percent White ( 0.28), African American (0.24) and Hispanic (0.16). Income and

Space heating housing tenure reveal inverse relationships with consumption and efﬁciency. Though areas with higher

Residential buildings

median incomes and homeownership exhibited higher consumption (0.28 and 0.56, respectively), they

−

had lower EUIs ( 0.48 and −0.38, respectively). This study provides evidence supporting approaches for

conservation and energy efﬁciency program targeting that recognizes the signiﬁcance of race, ethnicity,

place and class.

1. Introduction low household incomes, rising energy costs and energy inefﬁcient

homes [3].

Residential utility costs place a disproportionate burden on Amid solutions to alleviate fuel poverty, energy conservation

low-income households. Following the Great Recession, nearly 14 and efﬁciency retroﬁt programs have proven successful [5–8].

million American households had utility bills in arrears and 2.2 mil- However, the inability to identify and distinguish between house-

lion households experienced utility shutoffs [1]. Residential energy holds with high energy consumption compared to those that

burdens, or the percentage of annual income spent on energy costs are highly energy inefﬁcient has halted interventions from utiliz-

are a major source of utility hardship. While the average American ing systematic approaches to appropriately and effectively target

household spends 7.2% of their annual income on residential energy energy conservation and efﬁciency programs.

costs, the average low-income household has an energy burden The need for more effective targeting is supported by previous

nearly double, spending 13.8% [2]. Energy burden disparities are studies exploring the spatial dynamics of energy consumption that

often expressed through the concept of fuel poverty, also referred ﬁnd distinguishable spatial disparities in both consumption and

to as energy insecurity [3,4]. Fuel poverty reﬂects an inability of energy use intensity (EUI). For instance, Heiple and Sailor [9] using

a household to meet basic energy needs or to adequately heat or national data, building energy simulation and geospatial modeling

cool their home [3]. Fuel poverty results from the interplay between

According to the U.S. Department of Energy, “Declines in energy intensity are

a proxy for efﬁciency improvements, provided a) energy intensity is represented

∗

Corresponding author. at an appropriate level of disaggregation to provide meaningful interpretation, and

E-mail addresses: [email protected] (D.J. Bednar), [email protected] b) other explanatory and behavioral factors are isolated and accounted for” (DOEa)

(T.G. Reames), [email protected] (G.A. Keoleian). [52].

http://dx.doi.org/10.1016/j.enbuild.2017.03.028

Page 2 of 10

26 D.J. Bednar et al. / Energy and Buildings 143 (2017) 25–34

techniques found variations in peak energy proﬁles for electricity best predictors to model energy consumption and efﬁciency, for

and natural gas across building types in Houston, Texas. Howard instance, energy characteristics of housing structure and a selection

et al. [10] built models from citywide data to estimate building sec- of householder characteristics; then, connect to matching spatial

tor EUI ﬁnding major differences in the magnitude of consumption data (i.e. census data).

and spatial variation across New York City. Santamouris et al. [11] A growing body of literature investigating geographical

conducted interviews on household and housing unit characteris- approaches to target fuel poverty in Europe have used this approach

tics ﬁnding higher costs per person and unit area for low-income [26–29]. Fahmy [26] developed regression models to predict the

residence in Athens. These studies provide rich information on incidence of fuel poverty in England using sample survey data and

the relationship between place and energy consumption; however, applied resultant weights to Census spatial data sets. Similarly,

their focus on both commercial and residential energy consump- Walker and Day [30] developed a small area fuel poverty risk index

tion makes it difﬁcult to identify residential energy disparities for using environmental and socioeconomic variables via geographi-

program targeting. Moreover, few studies investigate correlations cal methods ﬁnding signiﬁcant clusters of high and low-risk areas.

between residential energy consumption, efﬁciency, race/ethnicity “The underlying idea is that there are higher probabilities of fuel

and socioeconomic status for a more holistic understanding of poverty in particular areas and/or housing types” [31].

urban residential energy dynamics. Reames [12] developed a model In the U.S., Min et al. [32] applied this approach for spatially

estimating urban residential heating EUI and found positive rela- modeling national residential energy consumption end uses. Com-

tionships with areas with higher percentages of racial minorities bining regression models based on national data from the U.S.

and lower socioeconomics. Albeit some exploration, little remains Energy Information Administration’s (EIA) Residential Energy Con-

known about the spatial, racial and socioeconomic differences sumption Survey (RECS) with U.S. Census data, they mapped energy

between residential energy consumption and efﬁciency. consumption estimates for space heating, cooling, water heating

To this end, this paper develops models for residential heat- and all other electrical uses at the zip code level. Reames [12] used

ing consumption and efﬁciency at the census block group level both the RECS and Census data to explore racial and socioeconomic

and explores the spatial patterns alongside racial and socioeco- disparities in the spatial distribution of urban heating EUI. Both

nomic relationships in Detroit (Wayne County), Michigan. The studies found that signiﬁcant predictors of energy consumption

remainder of this paper is structured as follows. Section 2 presents and EUI included age of housing unit, type of housing unit, number

background information on modeling energy consumption, efﬁ- of rooms, type of heating fuel and household income.

ciency and disparities. Section 3 describes the study area, data

and methodological framework for ﬁrst developing two regression

3. Data and methodology

models to estimate residential heating energy consumption and

heating EUI, then secondly, using small area estimation techniques

3.1. Description of study area

to predict consumption and EUI in the study area. Section 4 presents

results of the regression models, spatial distributions of results

Detroit (Wayne County) is the largest urban area in the State

mapped using geographic information systems (GIS) and bivariate

of Michigan and represents nearly 20% of the state population.

analysis of the relationship between predicted energy consump-

According to the 2010 decennial census, the county had a total pop-

tion and efﬁciency with selected racial and socioeconomic block

ulation of 1,820,584 residents in 821,693 housing units. Michigan

group characteristics. Section 5 discusses key results, policy impli-

homes are typically older than homes in other states. Nearly three-

cations and study limitations. Lastly, concluding remarks and areas

quarters of housing stock in Detroit (Wayne County) was built

of future research are presented in Section 6.

before 1970. Fig. 1 illustrates the distribution of housing stock age,

displaying the median year built for block group housing structures.

Socioeconomic characteristics vary in the study area. Detroit

2. Background

exhibits a high and increasing level of residential segregation by

income. The Pew Research on Social and Demographic Trends found

To understand the factors that impact energy consumption,

that the Detroit metropolitan area’s RISI score increased from 43

scholars apply two general frameworks: the physical-technical- 2

in 1980–54 in 2010 [33]. Fig. 2 displays the spatial distribution

economic model (PTEM) and the lifestyle and social-behavioral

of block group median household incomes, ranging from $6833 to

tradition (LSB) [13–23]. In 1993, Lutzenhiser proposed the PTEM

$183,462 per year. Households in the Detroit metropolitan were

tradition arguing that the physical characteristics of buildings,

hit particularly hard during the economic recession and recovery.

investment in technical energy efﬁciency, energy prices and envi-

A survey of Detroit metropolitan area households found that 1 in 2

ronmental factors are integral to understanding and managing

respondents reported experiencing some type of material hardship

energy consumption. On the other hand, the LSB tradition con-

[34]. While roughly 14% of high-income households fell behind on

tends that these factors alone can only offer minimal explanation

utility payments, nearly 40% of low-income households reported

of energy consumption in the built environment and draws atten-

being behind and were seven times more likely to have a utility

tion to the importance of human occupants of the building, such

shutoff [34].

as, social (noneconomic), behavioral, cultural and lifestyle factors

Detroit has long been the most segregated metropolitan area

[13,14,17–20,24,25]. The models developed for this study include

in the nation, having a majority African American and Hispanic

variables merging the PTEM and LSB modeling traditions for a more

city population and a majority White suburban population [35].

holistic understanding of residential energy consumption and efﬁ-

This segregation is evident in Fig. 3, a dot density map illustrating

ciency.

Individual housing unit energy data is often not readily avail-

able for exploring residential energy dynamics at various spatial

scales. Thus, the absence of detailed information on residential The Pew Research Center developed a single Residential Income Segregation

energy use presents an impediment to spatially identifying fuel Index (RISI) score for the nation’s top 30 metropolitan areas. The score is cal-

culated by summing the share of lower-income households living in a majority

poor households and developing strategic conservation and efﬁ-

lower-income tract and the share of upper-income households living in a major-

ciency program targeting. As a result, scholars have employed

ity upper-income tract. The maximum possible RISI score is 200, indicating that

small area estimation statistical techniques to spatially explore

100% of lower-income and 100% of upper-income households would be situated in

residential energy patterns. This approach requires ﬁnding the a census tract where most households were in their same income bracket. U-20471 Official Exhibits of Soulardarity Exhibit SOU-16

Page 3 of 10

D.J. Bednar et al. / Energy and Buildings 143 (2017) 25–34 27

Fig. 1. Block group median structure year built.

the spatial distribution of residents by race/ethnicity. The house- households were surveyed to represent the state’s 4.5 million occu-

hold racial/ethnic composition included 52.3% White, 40.5% African pied housing units. Since the scope of this study focuses on annual

American and 5.2% Hispanic households. Historically marginalized space heating, six of the total 274 observations were removed from

communities of color in Detroit experience higher rates of arrears the sample because of missing heating data, resulting in 268 total

and shutoffs. For instance, African Americans were almost twice as observations for this study.

likely as non-African Americans to report being behind on utilities Spatial data for modeling and mapping the study area were

payments and more than three times more likely to experience a obtained from U.S. Census Bureau 2006–2010 American Commu-

utility service shutoff than non-blacks [34]. nity Survey (ACS) [37,38] 5-year estimates. This survey is issued

Michigan households experience harsher winters increasing the each year to provide current information about social and eco-

average household demand for space heating to 55% of total energy nomic needs of the community. Households are sampled randomly

consumption compared to 41% nationally [2]. Consequently, Michi- in each state, including Puerto Rico to provide a representative sam-

gan households also consume 38% more energy and spend six ple. The census block group was used as the unit of analysis, as the

percent more than the average U.S. household [2]. Thus, space most appropriate spatial resolution for household and housing unit

heating is the ideal energy end use for investigating patterns and characteristics data [12]. A GIS data layer of Wayne County cen-

disparities in consumption and efﬁciency. sus block groups was created by clipping the U.S. Census Bureau

TIGER/Line Shapeﬁle with demographic and economic data from

the 2006–2010 ACS [37,38] 5-year estimates. Block groups were

3.2. Data

only retained if both population and number of occupied housing

units were greater than zero. Subsequently, 1808 of 1822 block

In the absence of detailed individual energy data for every

groups were included in this analysis.

household in the study area, the EIA’s RECS provides household-

The RECS microdata set can be used to develop a bottom up

level data for a representative sample of occupied, primary

statistical model. These models have been used to explore rela-

residences at the state-level. First conducted in 1978, RECS

tionships between household energy consumption and various

collected data on energy consumption, annual expenditure,

exogenous variables [39,40,32,12,41]. Statistical models also allow

energy-related behavior, household demographics and housing

for capturing consumption variations due to demographic and

unit characteristics. Using a multi-stage, area probability design,

carefully controlled at speciﬁc levels of precision, the 2009 RECS

microdata set (released in 2013) has a sample size of 12,083 hous-

For a 95 percent conﬁdence interval, a sample size of 246 RECS observations are

ing units representing the U.S. Census Bureau’s statistical estimate

needed to prove statistical signiﬁcance. For geographic domain estimation purposes,

of 113.6 million occupied primary residences [36]. The RECS allows

base sampling w(YˆHeat ) or (YˆEUI ).eights were applied to each housing unit. Each

for state-level analysis with the collection of representative sam-

sampling weight value was used as a weighting factor in the weighted regression

ples in 12 states, including Michigan. A sample of 274 Michigan model. U-20471 Official Exhibits of Soulardarity Exhibit SOU-16

Page 4 of 10

28 D.J. Bednar et al. / Energy and Buildings 143 (2017) 25–34

Fig. 2. Block group median household income.

socioeconomic characteristics. Similar variables found in both the the predictor variables, housing unit characteristics (age of home,

RECS and ACS allow relationships derived from statistical models type of heating fuel, type of home and size of home) and control-

using RECS, known as direct estimates, to be applied to block group ling for household characteristics (household ownership, number

level ACS spatial data as indirect estimators for constructing small- of household members and household income). Dependent vari-

area estimates with the assumption that the small area exhibits the ables were natural log values of per-household ﬁnal consumption

same characteristics as the large area [42]. The next section clariﬁes and EUI for heating. The models are formulated as:

this methodological framework.

ln(Y ) = ˇ + ˇ ∗ ␹ + ˇ ∗ ␹ , (1) Heat 0 Housing unit Household RECS RECS

ln( ) = ˇ + ˇ ∗ + ˇ ∗ (2)

EUI 0 Housing unit RECS Household RECS

3.3. Methodological framework for estimating block group

heating consumption and efﬁciency where:

YHeat is energy consumption in MJ,

The goal of this study is to explore residential heating con- YEUI is EUI in MJ/m ,

sumption and efﬁciency at a geographic domain smaller than the 0 is the regression intercept,

RECS microdata, which is collected with adequate precision at a HousingUnit is the resultant weight for housing unit characteris-

state-level scale. Fig. 4 displays a schematic of the methodological tics,

framework for estimating heating energy consumption and EUI at Household is the resultant weight for household characteristics,

the block group level. RECS is household and housing unit RECS data.

The ﬁrst step uses household and housing unit variables RECS, The RECS notation is used to differentiate for model creation

from the RECS microdata set, specifying two robust regression mod- in this step, and estimation in the subsequent step using Census

els − one to predict residential heating energy consumption and data. Step one uses resultant weights, i, from the RECS, 2009 data

the other to predict heating EUI (Blue ovals). The second step uses to model energy consumption and EUI. Using the observed data

census data for small area estimations at the block group level from the state of Michigan, a statewide ordinary least squares (OLS)

␤

(purple rectangles). Resultant weights, i, derived from the afore- regression model is developed for each response variable, mea-

mentioned robust regression models are multiplied to matching sured in mega joules (MJ) and MJ per square meter per annum. The

household and housing unit spatial variables (e.g. housing unit goal of the OLS is to model the relationship between the response

type, housing units built in each decade, housing unit heating fuel and predictor variables; simply, how housing units and household

type, median household income), XCENSUS, from the U.S. Census characteristics inﬂuence total heating fuel consumption and EUI.

2006–2010 ACS 5-year estimates. Total heating consumption is the total annual heating energy con-

The objective of the ﬁrst step is to develop two robust statis- sumed from all fuel types (i.e. natural gas, electric, fuel oil, liquid

tical regression models that explain the relationship between the petroleum gas, and kerosene). The EUI is measured as the ratio of

two response variables, heating energy consumption and EUI, with total heating consumption to total square meters of heated space. A U-20471 Official Exhibits of Soulardarity Exhibit SOU-16

Page 5 of 10

D.J. Bednar et al. / Energy and Buildings 143 (2017) 25–34 29

Fig. 3. Block group racial/ethnic segregation dot density map.

Fig. 4. Methodological framework for modeling and mapping. U-20471 Official Exhibits of Soulardarity Exhibit SOU-16

Page 6 of 10

30 D.J. Bednar et al. / Energy and Buildings 143 (2017) 25–34

larger EUI value indicates relatively less efﬁciency when compared 18,658 MJ to a maximum 123,120 MJ. The study area mean heat-

to another housing unit. ing consumption, 85,107 MJ (SD=16,342 MJ), was lower than the

Step two applies resultant weights from the regression models, state mean heating consumption, 131,883 MJ. The 104,451 MJ vari-

␤

i as weighting factors to corresponding variables in the ACS to esti- ation in heating consumption estimates demonstrates that within

mate, then map the median annual heating energy consumption the study area some homes consume a disproportionate amount of

and EUI at the block group level in Wayne County. The correspond- energy when compared to others. Block groups exhibiting the high-

ing variables are standardized as the ratio of the number of housing est quintiles of heating consumption primarily surround Detroit on

units in a block group with a certain characteristic to the total the east, north and west sides of city.

number of housing units in the block group. This is done for each Estimated heating EUI (Fig. 6) values ranged from a minimum

2 2

corresponding variable (age of home, type of heating fuel, type of 285 MJ/m to a maximum 1108 MJ/m . The study area mean heat-

home, size of home, household ownership, number of household ing EUI, 613 MJ/m (SD = 9.8), was lower than the state mean

2 2

members and household income). These values then become com- heating EUI, 727 MJ/m . The 818 MJ/m variation in heating EUI

parable with binary variables in the RECS data set. Values are then estimates demonstrates that within the study area some homes

mapped via GIS to estimate heating consumption and EUI: are far less energy efﬁcient than others. Block groups exhibiting

the lowest quintile EUI (shown in green) are located along the west,

ˆ ˆ ˆ

Yˆ = ˇ + ˇ ∗ + ˇ ∗ ,

ln( Heat) 0 Housing unit Census Household Census southwest and east sides of the county, representing homes with

higher levels of energy efﬁciency. Moderate estimated EUIs, (shown

(3)

in yellow) are located in the north central portion of the county,

while a majority of the higher EUIs, (shown in red) are located

in the central region of Detroit, indicating lower levels of energy

ˆ ˇˆ ˇˆ

ln(Yˆ ) = ˇ + ∗ + ∗ (4)

EUI 0 Housing unit Census Household Census

efﬁciency. This matches areas where houses are older (Fig. 3) and

may suggest that older homes are less energy efﬁcient than newer

where:

homes a few miles outward.

ˆHeat is estimated energy consumption, in MJ

To understand the relationship between heating consumption

Y 2

ˆEUI is estimated EUI, in MJ/m ,

and EUI with measures of race/ethnicity and socioeconomic sta-

ˇˆ

0 is the estimated regression intercept,

tus, bivariate analysis using pairwise correlation was conducted.

ˇˆ

is the estimated sampling weight for housing unit

Housing Unit Pearson correlations, shown in Table 2, reveal statistically sig-

characteristics,

niﬁcant relationships between socioeconomics, education, and

ˇˆ

Household is the estimated sampling weight for household char-

housing tenure with estimated heating consumption (p < 0.001).

acteristics,

Heating consumption is positively correlated with block groups

Census is household and housing unit Census data.

with median household income (0.28) and percent of home-

owners (0.56). Furthermore, heating consumption is negatively

4. Results

correlated with number of households in poverty (−0.25) and the

percentage of adults without a diploma (−0.07). There are no sig-

The ﬁnal regression models for estimating annual heating

niﬁcant correlations between heating consumption or EUI with

consumption and EUI are summarized in Table 1, expressed

householders above the age of 65. Table 2 also shows statisti-

as natural logs. Model 1, heating consumption, consists of ﬁve

cally signiﬁcant relationships between socioeconomics, education,

statistically signiﬁcant variables representing housing unit type,

race/ethnicity, housing tenure and estimated heating consumption

primary heating fuel and number of household members. Model

and EUI (p < 0.001). Contrary to heating consumption, heating EUI

2, heating EUI, consists of six statistically signiﬁcant variables

is positively correlated with block groups with a higher number

representing housing unit type, primary heating fuel, number of

of adults without a high school diploma (0.32), higher number of

household members and housing unit size. Both models explained

households in poverty (0.32), percentage of African American (0.24)

a considerable proportion of the variability in heating consump-

and Hispanic householders (0.16). Heating EUI is negatively corre-

2 2

tion and EUI (R = 0.52, F(18,249) = 15.18, p < 0.001 and R = 0.52,

lated with median household income (−0.28), percentage of White

F(18,249) = 11.09, p < 0.001, respectively). Based on the F-values,

householders (−0.28) and percent of homeowners (−0.38). Thus,

the ﬁnal models’ sample sizes are large enough to make them sig-

census block groups with lower socioeconomics, lower median

niﬁcant.

household incomes, and higher percentages of African American or

Figs. 5 and 6 display the spatial distribution in quintiles of the

Hispanic households are more likely to have higher heating EUIs.

estimated mean annual block group heating energy consumption

Simply put, low-income, African American and Hispanic house-

and heating EUI, respectively. Red shading represents higher esti-

holds reside in housing areas where homes consume more and are

mates, while green shading represents lower estimates. The 14

less energy efﬁcient.

uninhabited block groups were left uncolored. It is important to

note that estimates represent the block group mean rather than

any speciﬁc house [32,43].

Among the 1808 block groups, there was a signiﬁcant range in

5. Discussion

estimated heating consumption (Fig. 5) values, from a minimum

Results mapped using GIS illustrate inverse spatial disparities in

heating consumption and EUI, with higher estimated consumption

If block group A has 100 homes, and 50 are single family attached, then the in block groups surrounding the central city, while block groups

corresponding variable for single family attached is 50/100 = 0.5 which would be

with higher estimated EUIs are concentrated within the city of

multiplied by 0.015 (from Table 1).

Detroit. The ﬁndings also demonstrated that inverse relationships

From the estimated log values ln(YˆHeat ) and ln(YˆEUI ) that we obtain from the

exist between the racial and socioeconomic correlations with block

regression models, actual estimated energy can be obtain by this equation: (YˆHeat ) =

2 2 group predicted consumption and EUI. While areas with greater

exp RMSE /2 · ln(YˆHeat ); (YÊUI (YÊUI ) = exp RMSE /2 · ln(YÊUI ). The scaling value

2 percentages of minority households and lower socioeconomic sta-

exp(RMSE /2) is needed when using a log-linear model because without it we sys-

tuses exhibited lower predicted heating consumption, those same

tematically underestimate the expected value of (YˆHeat ) or (YˆEUI ). (Wooldridge 2006:

219). RMSE means root mean square error of each model. areas exhibited higher EUI, signaling that although low-income, U-20471 Official Exhibits of Soulardarity Exhibit SOU-16

Page 7 of 10

D.J. Bednar et al. / Energy and Buildings 143 (2017) 25–34 31

Fig. 5. Estimated residential heating consumption in MJ.

Fig. 6. Estimated residential energy use intensity (Efﬁciency) in MJ/m U-20471 Official Exhibits of Soulardarity Exhibit SOU-16

Page 8 of 10

32 D.J. Bednar et al. / Energy and Buildings 143 (2017) 25–34

Table 1

OLS regression models for small-scale heating consumption and EUI estimation.

Categories Model 1: Model 2:

Heating Consumption Energy Use Intensity

(MJ) (MJ/m2)

Type of Housing ˇ Robust S.E. ˇ Robust S.E.

***

Apt 2–4 0.1431 0.1317 0.6728 0.1864

* *

Apt 5> −0.2989 0.1401 0.2987 0.1511

Mobile Home 0.5173 0.2361 0.1090 0.2271

Single Family Detached Reference Reference

Single Family Attached 0.01531 0.1402 0.0948 0.1809

Decade Constructed

Before 1950s 0.3317 0.1739 0.328 0.17

1950s 0.3223 0.1802 0.3521 0.1786

1960s 0.0681 0.1769 0.1126 0.1848

1970s −0.0026 0.1832 −0.0159 0.188

1980s 0.0383 0.1693 0.0843 0.1808

1990s −0.0124 0.216 −0.1232 0.2125

2000s Reference Reference

Primary Heat (MJ)

Natural Gas Reference Reference

Propane 0.0138 0.0855 −0.098 0.1055

− *** ***

Electricity 1.627 0.1404 −1.381 0.1677

Wood −1.170 0.6978 −1.198 0.6732

* **

Fuel Oil Heat −0.6926 0.270 −0.6823 0.2061

Control Variables

Household Income ($) 0.0228 0.026 −0.0012 0.0259

* *

−

No. Household Members 0.0506 0.0256 −0.0619 0.0266

Home Ownership (own = 1) 0.0806 0.0853 −0.01029 0.0874

***

Total No. of rooms 0.0203 0.0279 −0.1048 0.0254

Model Statistics

Intercept, ˇ0 10.87375 0.2568 4.269 0.248

N 268 – 268 –

F (18,249) – 15.18 – 11.09

Adjusted R 0.5242 – 0.5183 –

RMSE – 0.514 – 0.574

Signiﬁcance p < 0.05.

Signiﬁcance p < 0.01.

***

Signiﬁcance p < 0.001.

Table 2

Pairwise Correlation of Estimated Heating Energy Consumption and Energy Use Intensity.

Category Description Pearson’s Correlation

Heating Consumption Heating Intensity

*** ***

Socioeconomic Status Median Household income 0.28 −0.48

*** ***

Percent households below poverty level −0.25 0.32

** ***

Education Percent Population with Less Than High School Diploma −0.07 0.31

Age Percent Households with Householder aged 65+ 0.01 0.02

***

Race/Ethnicity Percent White Householders 0.23 −0.28

***

Percent African American Householders −0.01 0.24

***

Percent Hispanic Householders 0.02 0.16

*** ***

Housing Tenure Percent Owners 0.56 −0.38

Signiﬁcance p < 0.01.

***

Signiﬁcance p < 0.001.

minority households on average consume less energy, they are 5.1. Policy implications

more likely to live in less efﬁcient housing.

Studying cities like Detroit is important because they often have Energy assistance programs provide eligible householders with

older housing stock central to the city with much newer, suburban monetary or housing unit efﬁciency upgrade support. The federally

developments outside the city. As shown, householders occupying funded Low Income Heating Energy Affordability Program (LIHEAP)

much older housing stock are at a greater risk for increased demand provides energy assistance to residents whom are unable to afford

and a greater need for energy assistance programs. Although this their high utility bills. Identifying concentrated areas of high EUI

study is focused in the south-east region of Michigan within the and energy burden is still a concern given the aforementioned

United States, this study could be replicated in other urban areas, support from government. LIHEAP eligibility primarily depends

as well as other countries using a similar household energy con- on income; however, many qualiﬁed householders do not receive

sumption survey (i.e. Zheng [44]; ODYSSEE MURE Project) and that energy assistance. While attenuating exorbitant utility bills pro-

country’s census data. The signiﬁcance of the results presented call vides temporary relief for some householders, it perpetuates fuel

for an integrated approach that tackles fuel poverty from both a poverty by not combatting a root cause, energy inefﬁciency.

physical and policy standpoint − evaluating building energy efﬁ- The U.S. Department of Energy Weatherization Assistance Pro-

ciency and energy assistance programs. gram’s (WAP) purpose, as established by law, “provides low-to

no-cost energy efﬁciency improvements of dwellings owned or U-20471 Official Exhibits of Soulardarity Exhibit SOU-16

Page 9 of 10

D.J. Bednar et al. / Energy and Buildings 143 (2017) 25–34 33

occupied by low-income persons, reduces their total residential vey (RECS) and the U.S. Census Bureau’s American Community

expenditures, and improves their health and safety, especially low- Survey (ACS), bottom-up modeling, and small-area estimation

income persons who are particularly vulnerable such as the elderly, techniques to predict mean annual heating consumption and

person with disabilities, families with children, high residential energy use intensity (EUI), an energy efﬁciency proxy, for census

energy users, and households with high energy burden” [45]. WAP block groups in Detroit (Wayne County), Michigan. This study’s rel-

is monitored by the Department of Energy’s Oak Ridge National evance provides a best estimate of areas where householders may

Laboratory (ORNL). ORNL provides technical support to the pro- experience the greatest threat of fuel poverty. The key ﬁndings of

gram and conducts the evaluations. Led by ORNL, the Department of the study illustrate inverse spatial disparities in heating consump-

Energy sponsored two major national evaluations: The Retrospec- tion and EUI throughout Detroit (Wayne County), Michigan. Inverse

tive Evaluation (covering Program Year 2008, which is reﬂective relationships were also found between the racial and socioeco-

of a typical year in WAP operations) and the Recovery Act Eval- nomic correlations with block group predicted consumption and

uation (covering Program Year 2010, providing insight to the EUI.

national effort of job creation and economic recovery as a part Modeling both heating consumption and efﬁciency provides a

of the American Recovery and Reinvestment Act of 2009 [Recov- useful tool that may assist policymakers, energy conservation and

ery Act]) were multiyear, peer-reviewed and statistically robust efﬁciency program administrators and retroﬁt installers develop

efforts. The former was performed to provide a cost-beneﬁt anal- more effective targeting strategies. Combining consumption and

ysis of WAP services for varying housing unit types and locations efﬁciency information with an understanding of the racial and

across the country. Additionally, to assess program administration socioeconomic context of neighborhoods may also improve pro-

and to provide a comprehensive overview of the program, includ- gram implementation effectiveness.

ing information on its clients, housing stock and service providers Using spatial proximity as a guide to identifying fuel poor house-

ORNL, 2014. Effective and optimal funding of the system is veri- holders eliminates onerous applications to determine eligibility

ﬁed through “whole-house” weatherization approaches via energy and provides a quicker and more robust response to householders

audits and the three-pronged WAP funding allocation formula: in need. Furthermore, there is a need to understand the cul-

percent of low-income population, climatic conditions and approx- tural/racial differences within identiﬁed neighborhoods. Simply

imate residential energy burden. Challenges of WAP presented creating energy assistance programs without effective marketing,

revolve around maintaining and improving work quality, handling maintains the energy divide, leaving many in fuel poverty. To over-

health and safety issues discovered in homes and meeting a grow- come cultural and social barriers, community-based approaches

ing demand for program services. Further, the Recovery Act did not would enable more access to help that is readily available. Future

address renewable energy measures average costs per home. research should pursue a more granular level of understanding,

Though LIHEAP and WAP help mitigate energy burdens, these such as, incorporating individual parcel data. Additionally, spatially

programs do not permit the use of sustainable energy, such as modelling of energy burdens would provide a more holistic view

renewable energy for heating and cooling. Renewable energy sys- of residential energy assistance demands. With this information

tems have proven beneﬁcial for energy generation with respect to in hand, program administrators could target local churches, com-

retroﬁts [46–48]. There is an opportunity for growth that intro- munity centers and neighborhood groups to more effectively and

duces renewables as a conduit for greater efﬁciency; however, a efﬁciently assist those with the greatest need.

community based approach would be more fruitful for effective Addressing fuel poverty and energy consumption more broadly,

targeting. requires an integrated approach to identify the speciﬁc energy

Community-based energy programs have shown success for needs of communities. The modeling framework presented in

overcoming various barriers and increasing participation in this study is one approach to understand those needs both visu-

the adoption of energy technologies [43]. A community-based ally and statistically. Moreover, this research unpacks disparities

approach to energy efficiency that targets low-income and minor- in consumption and efficiency concluding that one-size-fits-all

ity communities recognizes the unique characteristics and needs of approaches to conservation and efﬁciency are not appropriate for

the community and can better foster equity and justice over typical all energy users in an urban area.

self-referral, broad- based program development and implemen-

tation which relies on a homogeneous view of energy users

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THE HOME ENERGY AFFORDABILITY GAP 2018 ICHIGAN M ND (2 SERIES) PUBLISHED APRIL 2019

Finding #1

Poverty Level Home Energy Burden

Below 50% 32% Home energy is a crippling financial burden for low- income Michigan households. Michigan households with 50 – 100% 17% incomes of below 50% of the Federal Poverty Level pay 32% of their annual income simply for their home energy bills. 100 – 125% 12% Home energy unaffordability, however, is not only the 125 – 150% 10% province of the very poor. Bills for households with incomes between 150% and 185% of Poverty take up 8% 150 – 185% 8% of income. Michigan households with incomes between 185% and 200% of the Federal Poverty Level have energy 185% - 200% 7% bills equal to 7% of income.

Finding #2

Number of Households Poverty Level Last Year This Year The number of households facing unaffordable home Below 50% 284,402 273,386 energy burdens is staggering. According to the most recent five-year American Community Survey, more than 50 – 100% 342,671 331,894 273,000 Michigan households live with income at or below 50% of the Federal Poverty Level and face a home 100 – 125% 173,784 174,052 energy burden of 32%. And nearly 332,000 additional Michigan households live with incomes between 50% and 125 – 150% 176,667 172,477 100% of the Federal Poverty Level and face a home energy burden of 17%. 150 – 185% 249,131 249,031 In 2018 the total number of Michigan households below 185% - 200% 101,860 102,453 200% of the Federal Poverty Level stayed relatively constant from the prior year. Total < 200% 1,328,515 1,303,293

Home Energy nd The Home Energy Affordability Gap Index (2 Series) Affordability Gap: $1,793,445,416 indicates the extent to which the Home Energy 2011 (base year) Affordability Gap has increased between the base year and the current year. In Michigan, this Index was 88.9 for 2018. Home Energy

Affordability Gap: $1,594,129,747 nd The Home Energy Affordability Gap Index (2 Series) 2018 (current year) uses the year 2011 as its base year. The Index for 2011 is set equal to 100. A current year Index of more than 100 thus indicates that the Home Energy Affordability Gap for Home Energy has increased since 2011. A current year Index of less than Affordability Gap 88.9 100 indicates that the Home Energy Affordability Gap has Index (2011 = 100) decreased since 2011.

Finding #4

Last Year This Year Existing sources of energy assistance do not adequately address the Home Energy Affordability Gap in Michigan. Gross LIHEAP LIHEAP is the federal fuel assistance program designed to Allocation $139,926 $140,943 help pay low-income heating and cooling bills. The gross ($000’s) LIHEAP allocation to Michigan was $140.9 million in 2018 and the number of average annual low-income Number of heating and cooling bills “covered” by LIHEAP was Households 977,524 951,809 120,567. <150% FPL

In comparison, the gross LIHEAP allocation to Michigan Heating/Cooling in 2017 reached $139.9 million and covered 122,100 Bills “Covered” 122,100 120,567 by LIHEAP average annual bills.

Primary Penetration by Tenure

Heating Fuel Owner Renter The Home Energy Affordability Gap in Michigan is not Electricity 5% 19% solely a function of household incomes and fuel prices. It is also affected by the extent to which low-income households use each fuel. All other things equal, the Natural gas 78% 73% Affordability Gap will be greater in areas where more households use more expensive fuels. Fuel Oil 1% 1% In 2018, the primary heating fuel for Michigan homeowners was Natural Gas (78% of homeowners). Propane 10% 4% The primary heating fuel for Michigan renters was also Natural Gas (73% of renters). All other 6% 3% Changes in the prices of home energy fuels over time are Total 100% 100% presented in Finding #6 below.

Finding #6

2016 2017 2018 Fuel Price Price Price In Michigan, natural gas prices fell 11.4% Natural gas heating (ccf) $0.794 $1.147 $1.016 during the 2017/2018 winter heating season. Fuel oil prices rose substantially Electric heating (kWh) $0.156 $0.111 $0.109 26.9% and propane prices fell 7.7%.

Propane heating (gallon) $1.866 $2.804 $2.587 Heating season electric prices stayed relatively constant in the same period and cooling season electric prices stayed Fuel Oil heating (gallon) $1.802 $2.154 $2.734 relatively constant.

Electric cooling (kWh) $0.167 $0.111 $0.110

Home Energy Affordability Gap Dashboard -- Michigan 2018 versus 2017

VERAGE DOLLAR AMOUNT A AVERAGE TOTAL HOME ENERGY BY WHICH ACTUAL HOME ENERGY BILLS BURDEN FOR HOUSEHOLDS BELOW EXCEEDED AFFORDABLE HOME ENERGY BILLS 50% OF POVERTY LEVEL. FOR HOUSEHOLDS BELOW 200% OF POVERTY LEVEL. 2017: 32% of household income 2017: $1,217 per household

2018: 32% OF 2018: $1,223 PER HOUSEHOLD HOUSEHOLD INCOME

PERCENT OF INDIVIDUALS BELOW NUMBER OF AVERAGE LOW-INCOME 100% OF POVERTY LEVEL. HEATING/COOLING BILLS COVERED BY FEDERAL HOME ENERGY ASSISTANCE. 2017: 16% Of all individuals 2017: 122,100 bills covered 2018: 16% OF ALL INDIVIDUALS 2018: 120,567 BILLS COVERED

PRIMARY HEATING FUEL (2018):

HOMEOWNERS - NATURAL GAS *** TENANTS - NATURAL GAS

The 2012 Home Energy Affordability Gap, published in May 2013, introduced the 2nd Series of the annual Affordability Gap analysis. The 2012 Home Energy Affordability Gap going forward cannot be directly compared to the Affordability Gap (1st Series) for 2011 and earlier years. While remaining fundamentally the same, several improvements have been introduced in both data and methodology in the Affordability Gap (2nd Series).

The most fundamental change in the Home Energy Affordability Gap (2nd Series) is the move to a use of the American Community Survey (ACS) (5-year data) as the source of foundational demographic data. The Affordability Gap (1st Series) relied on the 2000 Census as its source of demographic data. The ACS (5-year data) offers several advantages compared to the Decennial Census. While year-to-year changes are smoothed out through use of 5-year averages, the ACS nonetheless is updated on an annual basis. As a result, numerous demographic inputs into the Affordability Gap (2nd Series) will reflect year-to-year changes on a county-by-county basis, including:

Ø The distribution of heating fuels by tenure; Ø The average household size by tenure; Ø The number of rooms per housing unit by tenure; Ø The distribution of owner/renter status; Ø The distribution of household size; Ø The distribution of households by ratio of income to Poverty Level;

Data on housing unit size (both heated square feet and cooled square feet) is no longer calculated based on the number of rooms. Instead, Energy Information Administration/Department of Energy (EIA/DOE) data on square feet of heated and cooled living space per household member is used beginning with the Home Energy Affordability Gap (2nd Series). A distinction is now made between heated living space and cooled living space, rather than using total living space.

The change resulting in perhaps the greatest dollar difference in the aggregate and average Affordability Gap for each state is a change in the treatment of income for households with income at or below 50% of the Federal Poverty Level. In recent years, it has become more evident that income for households with income below 50% of Poverty Level is not normally distributed. Rather than using the mid-point of the Poverty range (i.e., 25% of Poverty Level) to determine income for these households, income is set somewhat higher (40% of Poverty). By setting income higher, both the average and aggregate Affordability Gap results not only for that Poverty range, but also for the state as a whole, will be lower. The Affordability Gap results for other Poverty ranges remain unaffected by this change.

Another change affecting both the aggregate and average Affordability Gap is a change in the definition of “low-income.” The Home Energy Affordability Gap (2nd Series) has increased the definition of “low- income” to 200% of the Federal Poverty Level (up from 185% of Poverty). While this change may increase the aggregate Affordability Gap, it is likely to decrease the average Affordability Gap. Since more households are added to the analysis, the aggregate is likely to increase, but since the contribution of each additional household is less than the contributions of households with lower incomes, the overall average will most likely decrease.

Most of the Home Energy Affordability Gap calculation remains the same. All references to “states” include the District of Columbia as a “state.” Low-income home energy bills are calculated in a two-step process: First, low-income energy consumption is calculated for the following end-uses: (1) space heating; (2) space cooling; (3) domestic hot water; and (4) electric appliances (including lighting and refrigeration). All space cooling and appliance consumption is assumed to involve only electricity. Second, usage is multiplied by a price per unit of energy by fuel type and end use by time of year. The

©2019 FISHER, SHEEHAN & COLTON | PUBLIC FINANCE AND GENERAL ECONOMICS | BELMONT, MASSACHUSETTS U-20471 Official Exhibits of Soulardarity Exhibit SOU-17 Page 6 of 28 price of electricity, for example, used for space cooling (cooling months), space heating (heating months), and appliances (total year) differs to account for the time of year in which the consumption is incurred.

Each state’s Home Energy Affordability Gap is calculated on a county-by-county basis. Once total energy bills are determined for each county, each county is weighted by the percentage of persons at or below 200% of the Federal Poverty Level to the total statewide population at or below 200% of the Federal Poverty Level to derive a statewide result. Bills are calculated by end-use and summed before county weighting.

LIHEAP comparisons use gross allotments from annual baseline LIHEAP appropriations as reported by the federal LIHEAP office. They do not reflect supplemental appropriations or the release of LIHEAP “emergency” funds. The number of average heating/cooling bills covered by each state’s LIHEAP allocation is determined by dividing the total base LIHEAP allocation for each state by the average heating/cooling bill in that state, the calculation of which is explained below. No dollars are set aside for administration; nor are Tribal set-asides considered.

State financial resources and utility-specific rate discounts are not considered in the calculation of the Affordability Gap. Rather, such funding should be considered available to fill the Affordability Gap. While the effect in any given state may perhaps seem to be the same, experience shows there to be an insufficiently authoritative source of state-by-state data, comprehensively updated on an annual basis, to be used as an input into the annual Affordability Gap calculation.

Energy bills are a function of the following primary factors:

Ø Tenure of household (owner/renter) Ø Housing unit size (by tenure) Ø Heating Degree Days (HDDs) and Cooling Degree Days (CDDs) Ø Housing size (by tenure) Ø Heating fuel mix (by tenure) Ø Energy use intensities (by fuel and end use)

Bills are estimated using the U.S. Department of Energy’s “energy intensities” published in the DOE’s Residential Energy Consumption Survey (RECS). The energy intensities used for each state are those published for the Census Division in which the state is located. Heating Degree Days (HDDs) and Cooling Degree Days (CDDs) are obtained from the National Weather Service’s Climate Prediction Center on a county-by-county basis for the entire country.

End-use consumption by fuel is multiplied by fuel-specific price data to derive annual bills. State price data for each end-use is obtained from the Energy Information Administration’s (EIA) fuel-specific price reports (e.g., Natural Gas Monthly, Electric Power Monthly). State-specific data on fuel oil and kerosene is not available for all states. For those states in which these bulk fuels have insufficient penetration for state-specific prices to be published, prices from the Petroleum Administration for Defense Districts (PADD) of which the state is a part are used.

The Home Energy Affordability Gap Index (2nd Series) uses 2011 as its base year. The base year (2011) Index has been set equal to 100. A current year Index of more than 100 thus indicates that the Home Energy Affordability Gap has increased since 2011. A current year Index of less than 100 indicates that the Affordability Gap has decreased since 2011. The Affordability Gap Index was, in other words, re-set in 2011. The Affordability Gap Index (2nd Series) for 2012 and beyond cannot be compared to the Affordability Gap Index (1st Series) for 2011 and before.

The Home Energy Affordability Gap is a function of many variables, annual changes in which are now tracked for nearly all of them. For example, all other things equal: increases in income would result in

©2019 FISHER, SHEEHAN & COLTON | PUBLIC FINANCE AND GENERAL ECONOMICS | BELMONT, MASSACHUSETTS U-20471 Official Exhibits of Soulardarity Exhibit SOU-17 Page 7 of 28 decreases in the Affordability Gap; increases in relative penetrations of high-cost fuels would result in an increase in the Gap; increases in amount of heated or cooled square feet of living space would result in an increase in the Gap. Not all variables will result in a change in the Affordability Gap in the same direction. The annual Affordability Gap Index allows the reader to determine the net cumulative impact of these variables, but not the impact of individual variables.

Since the Affordability Gap is calculated assuming normal Heating Degree Days (HDDs) and Cooling Degree Days (CDDs), annual changes in weather do not have an impact on the Affordability Gap or on the Affordability Gap Index.

Price data for the various fuels underlying the calculation of the Home Energy Affordability Gap (2nd Series) was used from the following time periods:

Heating prices Natural gas February 2018 Fuel oil *** Week of 02/05/2018 Liquefied petroleum gas (LPG) *** Week of 02/05/2018 Electricity February 2018 Cooling prices August 2018 Non-heating prices Natural gas May 2018 Fuel oil *** Week of 10/01/2018 Liquefied petroleum gas (LPG) *** Week of 10/01/2018 Electricity May 2018

***Monthly bulk fuel prices are no longer published. Weekly bulk fuel prices are published during the heating months (October through March). The prices used are taken from the weeks most reflective of the end-uses to which they are to be applied. Prices from the middle of February best reflect heating season prices. Bulk fuel prices from October best reflect non-heating season prices.

©2019 FISHER, SHEEHAN & COLTON | PUBLIC FINANCE AND GENERAL ECONOMICS | BELMONT, MASSACHUSETTS U-20471 Official Exhibits of Soulardarity Exhibit SOU-17 Page 8 of 28 Michigan 2018 Home Energy Affordability Gap (Published April 2019)

Shortfall Calculation -- Less than 50% of Federal Poverty Level County_Only Individual HH Number of Aggregate Home Energy Shortfall Households Shortfall Burden Alcona County $2,448 383 $937,457 42.6% Alger County $2,923 124 $362,406 45.0% Allegan County $2,397 1,917 $4,595,193 37.1% Alpena County $2,096 695 $1,456,714 36.2% Antrim County $2,662 476 $1,267,008 43.0% Arenac County $2,511 458 $1,149,930 41.7% Baraga County $2,539 209 $530,648 42.4% Barry County $2,455 970 $2,380,938 39.0% Bay County $1,967 3,260 $6,410,898 33.3% Benzie County $2,639 273 $720,571 41.6% Berrien County $1,865 4,935 $9,202,457 31.8% Branch County $2,294 1,055 $2,419,801 36.7% Calhoun County $1,890 3,641 $6,880,874 31.8% Cass County $2,280 1,346 $3,068,355 36.9% Charlevoix County $2,368 527 $1,248,066 39.3% Cheboygan County $2,215 823 $1,823,293 37.8% Chippewa County $2,577 1,085 $2,796,046 41.3% Clare County $2,664 1,059 $2,821,692 42.9% Clinton County $2,324 1,252 $2,909,917 36.3% Crawford County $2,874 450 $1,293,428 46.9% Delta County $2,310 810 $1,871,351 38.9% Dickinson County $2,185 771 $1,684,516 37.2% Eaton County $2,063 2,169 $4,475,241 34.3% Emmet County $2,250 711 $1,599,567 38.1% Genesee County $1,858 15,295 $28,424,368 31.4% Gladwin County $2,554 930 $2,375,417 42.1% Gogebic County $2,261 522 $1,180,144 39.4% Grand Traverse County $2,113 1,426 $3,013,519 34.9% Gratiot County $2,256 1,661 $3,746,664 36.9% Hillsdale County $2,476 1,367 $3,385,360 39.5% Houghton County $2,479 1,611 $3,994,145 38.7%

Shortfall Calculation -- Less than 50% of Federal Poverty Level County_Only Individual HH Number of Aggregate Home Energy Shortfall Households Shortfall Burden Huron County $2,193 818 $1,793,598 37.3% Ingham County $1,808 11,816 $21,368,568 30.9% Ionia County $2,498 1,161 $2,899,953 38.3% Iosco County $2,015 813 $1,638,447 35.2% Iron County $2,414 311 $750,873 42.1% Isabella County $2,234 3,911 $8,736,676 35.5% Jackson County $2,000 4,063 $8,127,997 33.3% Kalamazoo County $1,808 7,702 $13,922,957 30.6% Kalkaska County $3,001 619 $1,857,673 46.8% Kent County $1,996 13,982 $27,907,670 32.0% Keweenaw County $2,680 85 $227,785 45.8% Lake County $3,245 555 $1,800,930 49.8% Lapeer County $2,498 1,417 $3,539,375 38.8% Leelanau County $2,360 274 $646,690 38.8% Lenawee County $2,008 1,835 $3,685,007 33.3% Livingston County $2,196 1,734 $3,808,197 34.7% Luce County $2,511 128 $321,382 40.8% Mackinac County $2,335 352 $821,815 40.9% Macomb County $1,829 16,122 $29,482,170 30.6% Manistee County $2,204 550 $1,211,980 36.7% Marquette County $2,168 2,047 $4,437,574 35.9% Mason County $2,260 859 $1,941,594 37.7% Mecosta County $2,485 1,736 $4,313,341 38.8% Menominee County $2,354 442 $1,040,418 40.2% Midland County $2,051 1,528 $3,134,196 34.1% Missaukee County $3,091 346 $1,069,493 47.6% Monroe County $1,997 2,790 $5,572,927 32.6% Montcalm County $2,542 1,745 $4,435,806 39.7% Montmorency County $2,420 225 $544,485 40.6% Muskegon County $2,004 5,289 $10,601,324 32.6% Newaygo County $2,792 1,404 $3,920,146 43.4%

Shortfall Calculation -- Less than 50% of Federal Poverty Level County_Only Individual HH Number of Aggregate Home Energy Shortfall Households Shortfall Burden Oakland County $1,818 19,115 $34,751,985 30.6% Oceana County $2,766 719 $1,988,482 43.0% Ogemaw County $2,581 810 $2,090,818 43.1% Ontonagon County $2,403 222 $533,551 42.2% Osceola County $2,991 786 $2,350,603 45.9% Oscoda County $2,614 222 $580,401 43.6% Otsego County $2,551 550 $1,403,158 41.0% Ottawa County $2,069 4,548 $9,407,716 32.4% Presque Isle County $2,343 314 $735,731 40.4% Roscommon County $2,105 835 $1,757,316 36.9% Saginaw County $1,931 6,193 $11,957,588 32.6% St. Clair County $2,019 3,627 $7,324,287 33.4% St. Joseph County $2,203 1,763 $3,884,099 35.4% Sanilac County $2,410 1,199 $2,889,168 39.2% Schoolcraft County $2,680 308 $825,452 42.6% Shiawassee County $2,246 1,576 $3,539,957 36.4% Tuscola County $2,470 1,538 $3,799,571 39.8% Van Buren County $2,172 1,887 $4,098,938 35.0% Washtenaw County $1,774 11,203 $19,874,524 30.0% Wayne County $1,724 76,172 $131,296,297 28.7% Wexford County $2,622 929 $2,435,630 41.3%

Total Michigan $1,950 273,386 $533,112,300 32.23%

Shortfall Calculation -- 50% - 99% of Federal Poverty Level County_Only Individual HH Number of Aggregate Home Energy Shortfall Households Shortfall Burden Alcona County $2,097 357 $748,474 22.7% Alger County $2,529 299 $756,137 24.0% Allegan County $1,992 2,675 $5,329,796 19.8% Alpena County $1,732 1,217 $2,108,072 19.3% Antrim County $2,284 743 $1,697,286 22.9% Arenac County $2,142 769 $1,646,827 22.2% Baraga County $2,172 220 $477,941 22.6% Barry County $2,064 1,206 $2,488,648 20.8% Bay County $1,588 3,926 $6,235,328 17.8% Benzie County $2,250 424 $954,106 22.2% Berrien County $1,485 5,934 $8,809,613 16.9% Branch County $1,902 1,546 $2,940,063 19.6% Calhoun County $1,505 5,672 $8,537,275 17.0% Cass County $1,892 1,462 $2,766,423 19.7% Charlevoix County $1,995 773 $1,542,422 21.0% Cheboygan County $1,850 1,076 $1,990,389 20.2% Chippewa County $2,193 1,306 $2,864,369 22.0% Clare County $2,285 1,940 $4,433,405 22.9% Clinton County $1,921 1,689 $3,245,246 19.4% Crawford County $2,505 536 $1,342,699 25.0% Delta County $1,942 1,481 $2,876,058 20.8% Dickinson County $1,817 950 $1,726,542 19.8% Eaton County $1,680 2,667 $4,481,677 18.3% Emmet County $1,882 831 $1,564,199 20.3% Genesee County $1,474 18,153 $26,752,794 16.7% Gladwin County $2,183 1,292 $2,820,630 22.5% Gogebic County $1,905 836 $1,592,725 21.0% Grand Traverse County $1,730 2,145 $3,709,788 18.6% Gratiot County $1,873 1,352 $2,532,043 19.7% Hillsdale County $2,088 1,673 $3,493,542 21.1% Houghton County $2,081 1,204 $2,505,546 20.6%

Shortfall Calculation -- 50% - 99% of Federal Poverty Level County_Only Individual HH Number of Aggregate Home Energy Shortfall Households Shortfall Burden Huron County $1,824 1,078 $1,966,620 19.9% Ingham County $1,427 11,631 $16,602,120 16.5% Ionia County $2,092 1,811 $3,789,103 20.4% Iosco County $1,653 1,107 $1,830,226 18.8% Iron County $2,063 444 $916,096 22.5% Isabella County $1,837 2,896 $5,318,510 18.9% Jackson County $1,616 5,244 $8,473,370 17.8% Kalamazoo County $1,421 9,433 $13,406,393 16.3% Kalkaska County $2,615 676 $1,767,471 24.9% Kent County $1,592 17,756 $28,271,999 17.0% Keweenaw County $2,326 62 $144,212 24.4% Lake County $2,856 583 $1,664,880 26.5% Lapeer County $2,098 1,824 $3,826,209 20.7% Leelanau County $1,983 429 $850,608 20.7% Lenawee County $1,622 3,394 $5,504,029 17.7% Livingston County $1,794 2,440 $4,378,057 18.5% Luce County $2,132 311 $662,919 21.7% Mackinac County $1,984 448 $888,652 21.8% Macomb County $1,438 24,316 $34,958,428 16.3% Manistee County $1,827 904 $1,651,695 19.6% Marquette County $1,787 2,247 $4,014,944 19.1% Mason County $1,886 1,099 $2,072,280 20.1% Mecosta County $2,087 1,772 $3,698,648 20.7% Menominee County $1,993 983 $1,958,927 21.5% Midland County $1,667 2,315 $3,860,062 18.2% Missaukee County $2,701 598 $1,615,143 25.4% Monroe County $1,604 3,753 $6,018,773 17.4% Montcalm County $2,146 2,352 $5,046,324 21.2% Montmorency County $2,053 391 $802,528 21.6% Muskegon County $1,609 6,761 $10,877,462 17.4% Newaygo County $2,400 1,945 $4,668,388 23.1%

Shortfall Calculation -- 50% - 99% of Federal Poverty Level County_Only Individual HH Number of Aggregate Home Energy Shortfall Households Shortfall Burden Oakland County $1,431 26,036 $37,248,577 16.3% Oceana County $2,373 1,087 $2,579,219 22.9% Ogemaw County $2,216 927 $2,053,897 23.0% Ontonagon County $2,055 236 $484,980 22.5% Osceola County $2,597 1,091 $2,833,161 24.5% Oscoda County $2,250 452 $1,016,868 23.3% Otsego County $2,168 922 $1,999,210 21.9% Ottawa County $1,658 4,940 $8,188,350 17.3% Presque Isle County $1,986 574 $1,139,757 21.6% Roscommon County $1,747 1,360 $2,376,078 19.7% Saginaw County $1,550 7,657 $11,866,684 17.4% St. Clair County $1,633 4,965 $8,107,323 17.8% St. Joseph County $1,810 1,969 $3,564,450 18.9% Sanilac County $2,029 1,381 $2,801,507 20.9% Schoolcraft County $2,295 394 $904,376 22.7% Shiawassee County $1,859 2,025 $3,764,018 19.4% Tuscola County $2,087 1,895 $3,954,296 21.2% Van Buren County $1,778 2,750 $4,890,755 18.6% Washtenaw County $1,387 8,961 $12,425,723 16.0% Wayne County $1,324 83,584 $110,706,765 15.3% Wexford County $2,232 1,331 $2,970,345 22.0%

Total Michigan $1,574 331,894 $522,351,479 17.31%

Shortfall Calculation -- 100% - 124% of Federal Poverty Level County_Only Individual HH Number of Aggregate Home Energy Shortfall Households Shortfall Burden Alcona County $1,720 323 $555,684 15.1% Alger County $2,107 188 $396,120 16.0% Allegan County $1,559 1,844 $2,874,643 13.2% Alpena County $1,342 719 $965,184 12.9% Antrim County $1,880 534 $1,003,919 15.3% Arenac County $1,746 367 $640,743 14.8% Baraga County $1,780 157 $279,421 15.1% Barry County $1,645 812 $1,335,420 13.9% Bay County $1,183 2,094 $2,476,934 11.8% Benzie County $1,833 325 $595,804 14.8% Berrien County $1,077 3,675 $3,959,127 11.3% Branch County $1,482 846 $1,253,603 13.1% Calhoun County $1,093 2,906 $3,176,302 11.3% Cass County $1,477 759 $1,121,162 13.1% Charlevoix County $1,596 503 $802,718 14.0% Cheboygan County $1,458 659 $960,868 13.4% Chippewa County $1,782 827 $1,473,767 14.7% Clare County $1,879 770 $1,446,789 15.2% Clinton County $1,490 755 $1,124,810 12.9% Crawford County $2,109 371 $782,593 16.7% Delta County $1,547 922 $1,426,629 13.8% Dickinson County $1,424 596 $848,546 13.2% Eaton County $1,270 1,647 $2,092,047 12.2% Emmet County $1,489 714 $1,062,883 13.6% Genesee County $1,062 9,073 $9,631,838 11.2% Gladwin County $1,786 682 $1,217,769 15.0% Gogebic County $1,524 335 $510,584 14.0% Grand Traverse County $1,318 1,377 $1,815,342 12.4% Gratiot County $1,463 714 $1,044,304 13.1% Hillsdale County $1,672 869 $1,453,104 14.0% Houghton County $1,654 771 $1,275,459 13.8%

Shortfall Calculation -- 100% - 124% of Federal Poverty Level County_Only Individual HH Number of Aggregate Home Energy Shortfall Households Shortfall Burden Huron County $1,430 707 $1,010,779 13.2% Ingham County $1,019 5,033 $5,129,355 11.0% Ionia County $1,658 1,357 $2,249,593 13.6% Iosco County $1,265 584 $739,037 12.5% Iron County $1,687 315 $531,436 15.0% Isabella County $1,411 1,281 $1,807,168 12.6% Jackson County $1,204 2,632 $3,168,075 11.8% Kalamazoo County $1,007 5,043 $5,078,970 10.9% Kalkaska County $2,201 282 $620,545 16.6% Kent County $1,160 10,388 $12,046,885 11.4% Keweenaw County $1,947 55 $107,080 16.3% Lake County $2,439 377 $919,392 17.7% Lapeer County $1,669 1,688 $2,817,327 13.8% Leelanau County $1,578 279 $440,374 13.8% Lenawee County $1,208 1,830 $2,209,915 11.8% Livingston County $1,364 1,342 $1,830,048 12.3% Luce County $1,725 123 $212,207 14.5% Mackinac County $1,607 296 $475,795 14.5% Macomb County $1,019 14,447 $14,717,474 10.9% Manistee County $1,424 428 $609,343 13.1% Marquette County $1,379 1,063 $1,465,392 12.8% Mason County $1,484 645 $957,277 13.4% Mecosta County $1,662 867 $1,440,537 13.8% Menominee County $1,606 549 $881,656 14.3% Midland County $1,256 1,295 $1,626,830 12.1% Missaukee County $2,283 365 $833,270 16.9% Monroe County $1,182 1,989 $2,350,714 11.6% Montcalm County $1,721 1,298 $2,233,551 14.1% Montmorency County $1,659 223 $369,917 14.4% Muskegon County $1,185 3,522 $4,173,725 11.6% Newaygo County $1,980 1,027 $2,033,745 15.4%

Shortfall Calculation -- 100% - 124% of Federal Poverty Level County_Only Individual HH Number of Aggregate Home Energy Shortfall Households Shortfall Burden Oakland County $1,016 13,181 $13,386,553 10.9% Oceana County $1,952 737 $1,438,545 15.3% Ogemaw County $1,824 582 $1,061,512 15.3% Ontonagon County $1,682 252 $423,797 15.0% Osceola County $2,175 589 $1,281,064 16.3% Oscoda County $1,859 210 $390,379 15.5% Otsego County $1,758 439 $771,823 14.6% Ottawa County $1,217 3,290 $4,004,676 11.5% Presque Isle County $1,603 278 $445,538 14.4% Roscommon County $1,364 758 $1,034,011 13.1% Saginaw County $1,142 4,411 $5,035,264 11.6% St. Clair County $1,219 2,535 $3,089,670 11.9% St. Joseph County $1,389 1,115 $1,549,170 12.6% Sanilac County $1,620 903 $1,463,175 13.9% Schoolcraft County $1,883 176 $331,447 15.1% Shiawassee County $1,444 1,362 $1,966,336 13.0% Tuscola County $1,676 1,294 $2,168,130 14.1% Van Buren County $1,357 1,829 $2,481,204 12.4% Washtenaw County $972 3,925 $3,813,462 10.7% Wayne County $897 36,759 $32,965,438 10.2% Wexford County $1,814 963 $1,746,579 14.7%

Total Michigan $1,181 174,052 $205,539,302 11.67%

Shortfall Calculation -- 125% - 149% of Federal Poverty Level County_Only Individual HH Number of Aggregate Home Energy Shortfall Households Shortfall Burden Alcona County $1,470 269 $395,321 12.4% Alger County $1,826 164 $299,428 13.1% Allegan County $1,270 1,594 $2,024,216 10.8% Alpena County $1,083 689 $745,868 10.5% Antrim County $1,610 522 $840,639 12.5% Arenac County $1,482 410 $607,680 12.1% Baraga County $1,518 176 $267,159 12.3% Barry County $1,365 1,416 $1,933,273 11.3% Bay County $913 1,874 $1,710,295 9.7% Benzie County $1,555 277 $430,801 12.1% Berrien County $806 3,317 $2,672,803 9.2% Branch County $1,202 895 $1,075,658 10.7% Calhoun County $818 2,725 $2,229,735 9.2% Cass County $1,200 785 $942,352 10.7% Charlevoix County $1,330 492 $654,124 11.4% Cheboygan County $1,197 519 $621,199 11.0% Chippewa County $1,508 770 $1,161,120 12.0% Clare County $1,608 656 $1,054,894 12.5% Clinton County $1,202 735 $883,537 10.6% Crawford County $1,846 300 $553,700 13.6% Delta County $1,284 1,189 $1,526,938 11.3% Dickinson County $1,161 728 $845,414 10.8% Eaton County $997 1,707 $1,701,450 10.0% Emmet County $1,226 713 $874,266 11.1% Genesee County $787 8,140 $6,404,792 9.1% Gladwin County $1,521 794 $1,207,309 12.3% Gogebic County $1,270 453 $575,357 11.5% Grand Traverse County $1,044 1,560 $1,628,975 10.2% Gratiot County $1,189 897 $1,066,661 10.7% Hillsdale County $1,395 905 $1,262,294 11.5% Houghton County $1,370 804 $1,101,326 11.3%

Shortfall Calculation -- 125% - 149% of Federal Poverty Level County_Only Individual HH Number of Aggregate Home Energy Shortfall Households Shortfall Burden Huron County $1,167 717 $836,433 10.8% Ingham County $747 4,525 $3,380,051 9.0% Ionia County $1,368 962 $1,316,113 11.2% Iosco County $1,007 717 $721,955 10.2% Iron County $1,436 413 $593,196 12.2% Isabella County $1,127 1,068 $1,203,542 10.3% Jackson County $929 3,122 $2,900,063 9.7% Kalamazoo County $731 4,216 $3,082,202 8.9% Kalkaska County $1,924 465 $894,870 13.6% Kent County $871 10,830 $9,436,401 9.3% Keweenaw County $1,694 75 $127,063 13.3% Lake County $2,161 302 $652,532 14.5% Lapeer County $1,383 1,693 $2,341,847 11.3% Leelanau County $1,309 409 $535,307 11.3% Lenawee County $932 1,844 $1,717,767 9.7% Livingston County $1,077 2,065 $2,223,170 10.1% Luce County $1,454 131 $190,524 11.9% Mackinac County $1,357 291 $394,779 11.9% Macomb County $739 13,200 $9,760,368 8.9% Manistee County $1,155 434 $501,168 10.7% Marquette County $1,106 1,089 $1,204,839 10.4% Mason County $1,217 794 $965,913 11.0% Mecosta County $1,378 763 $1,051,172 11.3% Menominee County $1,348 603 $812,853 11.7% Midland County $982 1,304 $1,280,689 9.9% Missaukee County $2,004 366 $733,566 13.8% Monroe County $901 2,584 $2,327,185 9.5% Montcalm County $1,438 1,289 $1,853,035 11.5% Montmorency County $1,396 246 $343,507 11.8% Muskegon County $903 3,384 $3,054,073 9.5% Newaygo County $1,700 930 $1,581,306 12.6%

Shortfall Calculation -- 125% - 149% of Federal Poverty Level County_Only Individual HH Number of Aggregate Home Energy Shortfall Households Shortfall Burden Oakland County $739 14,292 $10,560,168 8.9% Oceana County $1,671 766 $1,280,213 12.5% Ogemaw County $1,563 575 $898,580 12.5% Ontonagon County $1,433 167 $239,293 12.3% Osceola County $1,894 545 $1,032,087 13.3% Oscoda County $1,598 205 $327,680 12.7% Otsego County $1,485 572 $849,232 11.9% Ottawa County $924 3,869 $3,573,682 9.4% Presque Isle County $1,347 403 $542,974 11.8% Roscommon County $1,109 549 $608,735 10.7% Saginaw County $869 4,095 $3,559,998 9.5% St. Clair County $943 2,929 $2,761,300 9.7% St. Joseph County $1,109 1,308 $1,450,303 10.3% Sanilac County $1,348 1,017 $1,371,096 11.4% Schoolcraft County $1,608 142 $228,401 12.4% Shiawassee County $1,167 1,313 $1,532,277 10.6% Tuscola County $1,401 1,044 $1,463,072 11.6% Van Buren County $1,075 1,853 $1,992,617 10.2% Washtenaw County $695 4,572 $3,176,967 8.7% Wayne County $612 34,092 $20,852,954 8.3% Wexford County $1,535 863 $1,324,734 12.0%

Total Michigan $910 172,477 $156,942,437 9.58%

Shortfall Calculation -- 150% - 184% of Federal Poverty Level County_Only Individual HH Number of Aggregate Home Energy Shortfall Households Shortfall Burden Alcona County $1,169 512 $598,348 10.2% Alger County $1,488 240 $357,188 10.7% Allegan County $923 2,962 $2,734,142 8.9% Alpena County $771 1,150 $886,311 8.7% Antrim County $1,287 831 $1,069,433 10.3% Arenac County $1,166 571 $665,586 10.0% Baraga County $1,204 265 $319,003 10.1% Barry County $1,030 1,632 $1,681,198 9.3% Bay County $588 2,783 $1,637,434 7.9% Benzie County $1,222 609 $743,975 9.9% Berrien County $480 4,340 $2,083,029 7.6% Branch County $866 1,394 $1,207,086 8.8% Calhoun County $489 3,960 $1,934,597 7.6% Cass County $868 1,657 $1,438,937 8.8% Charlevoix County $1,010 725 $732,187 9.4% Cheboygan County $884 1,126 $994,852 9.0% Chippewa County $1,179 1,183 $1,394,768 9.9% Clare County $1,283 1,303 $1,671,774 10.2% Clinton County $857 1,474 $1,262,956 8.7% Crawford County $1,529 450 $688,126 11.2% Delta County $969 950 $920,075 9.3% Dickinson County $846 781 $660,992 8.9% Eaton County $669 2,589 $1,730,972 8.2% Emmet County $911 1,073 $977,757 9.1% Genesee County $457 11,410 $5,215,656 7.5% Gladwin County $1,202 840 $1,010,090 10.1% Gogebic County $965 600 $579,162 9.4% Grand Traverse County $715 2,620 $1,874,022 8.3% Gratiot County $861 1,297 $1,116,692 8.8% Hillsdale County $1,062 1,381 $1,466,584 9.4% Houghton County $1,028 1,055 $1,084,991 9.2%

Shortfall Calculation -- 150% - 184% of Federal Poverty Level County_Only Individual HH Number of Aggregate Home Energy Shortfall Households Shortfall Burden Huron County $851 1,014 $862,765 8.9% Ingham County $420 7,374 $3,099,781 7.4% Ionia County $1,020 1,642 $1,675,660 9.2% Iosco County $697 1,035 $721,016 8.4% Iron County $1,135 438 $497,289 10.1% Isabella County $786 1,463 $1,150,370 8.5% Jackson County $599 4,043 $2,422,546 8.0% Kalamazoo County $400 6,022 $2,407,600 7.3% Kalkaska County $1,593 633 $1,008,483 11.2% Kent County $525 15,988 $8,398,082 7.6% Keweenaw County $1,391 77 $107,099 10.9% Lake County $1,827 272 $496,971 11.9% Lapeer County $1,040 2,257 $2,347,994 9.3% Leelanau County $985 567 $558,679 9.3% Lenawee County $600 2,524 $1,515,087 7.9% Livingston County $732 3,011 $2,204,367 8.3% Luce County $1,129 201 $226,995 9.7% Mackinac County $1,056 498 $525,729 9.8% Macomb County $404 19,620 $7,931,617 7.3% Manistee County $832 927 $771,308 8.8% Marquette County $780 1,707 $1,331,060 8.6% Mason County $895 922 $825,514 9.0% Mecosta County $1,037 1,275 $1,322,277 9.3% Menominee County $1,039 864 $897,277 9.6% Midland County $653 1,879 $1,227,333 8.1% Missaukee County $1,670 582 $971,880 11.4% Monroe County $563 3,283 $1,848,724 7.8% Montcalm County $1,098 2,157 $2,367,847 9.5% Montmorency County $1,081 499 $539,633 9.7% Muskegon County $563 5,330 $3,003,220 7.8% Newaygo County $1,364 1,511 $2,061,596 10.4%

Shortfall Calculation -- 150% - 184% of Federal Poverty Level County_Only Individual HH Number of Aggregate Home Energy Shortfall Households Shortfall Burden Oakland County $407 22,140 $9,007,373 7.3% Oceana County $1,335 970 $1,294,544 10.3% Ogemaw County $1,249 855 $1,068,204 10.3% Ontonagon County $1,134 261 $296,046 10.1% Osceola County $1,556 720 $1,120,496 11.0% Oscoda County $1,286 360 $462,898 10.4% Otsego County $1,157 633 $732,070 9.8% Ottawa County $571 6,011 $3,434,706 7.7% Presque Isle County $1,041 380 $395,557 9.7% Roscommon County $802 1,023 $820,873 8.8% Saginaw County $543 5,909 $3,207,086 7.8% St. Clair County $611 4,095 $2,503,982 8.0% St. Joseph County $772 1,876 $1,448,421 8.5% Sanilac County $1,022 1,466 $1,497,623 9.4% Schoolcraft County $1,279 290 $370,835 10.2% Shiawassee County $835 2,158 $1,801,833 8.7% Tuscola County $1,072 1,762 $1,889,693 9.5% Van Buren County $738 1,953 $1,441,028 8.3% Washtenaw County $363 6,542 $2,373,601 7.2% Wayne County $270 45,169 $12,173,438 6.8% Wexford County $1,201 1,080 $1,296,704 9.9%

Total Michigan $581 249,031 $144,700,735 7.88%

Shortfall Calculation -- 185% - 199% of Federal Poverty Level County_Only Individual HH Number of Aggregate Home Energy Shortfall Households Shortfall Burden Alcona County $918 161 $147,776 8.9% Alger County $1,207 115 $138,810 9.3% Allegan County $634 1,294 $820,465 7.7% Alpena County $511 432 $220,685 7.5% Antrim County $1,017 316 $321,480 8.9% Arenac County $902 196 $176,773 8.7% Baraga County $942 97 $91,372 8.8% Barry County $751 762 $572,144 8.1% Bay County $318 1,247 $396,723 6.9% Benzie County $944 139 $131,165 8.6% Berrien County $208 1,666 $347,255 6.6% Branch County $586 592 $346,893 7.6% Calhoun County $214 1,451 $310,181 6.6% Cass County $592 674 $398,800 7.7% Charlevoix County $744 299 $222,328 8.2% Cheboygan County $622 374 $232,767 7.9% Chippewa County $905 393 $355,623 8.6% Clare County $1,012 469 $474,695 8.9% Clinton County $569 653 $371,621 7.5% Crawford County $1,265 143 $180,955 9.7% Delta County $705 506 $356,933 8.1% Dickinson County $584 315 $183,925 7.7% Eaton County $395 1,318 $520,767 7.1% Emmet County $649 472 $306,226 7.9% Genesee County $182 4,439 $809,446 6.5% Gladwin County $937 353 $330,918 8.8% Gogebic County $711 189 $134,425 8.2% Grand Traverse County $441 1,280 $564,684 7.3% Gratiot County $588 372 $218,555 7.7% Hillsdale County $785 739 $579,832 8.2% Houghton County $744 402 $299,065 8.0%

Shortfall Calculation -- 185% - 199% of Federal Poverty Level County_Only Individual HH Number of Aggregate Home Energy Shortfall Households Shortfall Burden Huron County $588 444 $260,962 7.7% Ingham County $148 3,446 $510,677 6.4% Ionia County $731 895 $654,094 8.0% Iosco County $438 354 $155,077 7.3% Iron County $885 157 $138,878 8.7% Isabella County $502 645 $324,095 7.4% Jackson County $324 1,649 $534,987 6.9% Kalamazoo County $124 2,418 $299,205 6.3% Kalkaska County $1,317 233 $306,889 9.7% Kent County $237 6,811 $1,613,540 6.6% Keweenaw County $1,138 87 $99,020 9.5% Lake County $1,549 123 $190,539 10.3% Lapeer County $755 872 $657,956 8.1% Leelanau County $716 197 $141,002 8.1% Lenawee County $324 884 $286,603 6.9% Livingston County $445 1,308 $582,097 7.2% Luce County $858 70 $60,092 8.5% Mackinac County $805 149 $119,929 8.5% Macomb County $125 8,343 $1,042,557 6.3% Manistee County $563 449 $252,839 7.6% Marquette County $508 650 $329,936 7.5% Mason County $628 415 $260,502 7.8% Mecosta County $753 519 $390,934 8.1% Menominee County $781 315 $245,889 8.4% Midland County $379 930 $352,533 7.1% Missaukee County $1,391 257 $357,550 9.9% Monroe County $282 1,604 $452,130 6.8% Montcalm County $815 689 $561,233 8.2% Montmorency County $819 175 $143,321 8.4% Muskegon County $281 2,180 $612,397 6.8% Newaygo County $1,084 690 $748,266 9.0%

Shortfall Calculation -- 185% - 199% of Federal Poverty Level County_Only Individual HH Number of Aggregate Home Energy Shortfall Households Shortfall Burden Oakland County $130 9,687 $1,260,560 6.4% Oceana County $1,054 401 $422,648 8.9% Ogemaw County $988 399 $394,294 8.9% Ontonagon County $885 94 $83,231 8.8% Osceola County $1,275 256 $326,400 9.5% Oscoda County $1,025 187 $191,735 9.1% Otsego County $883 404 $356,749 8.5% Ottawa County $278 2,318 $644,050 6.7% Presque Isle County $786 210 $164,979 8.4% Roscommon County $547 345 $188,747 7.7% Saginaw County $271 2,367 $640,449 6.8% St. Clair County $335 1,504 $504,461 6.9% St. Joseph County $491 905 $444,792 7.4% Sanilac County $749 659 $493,854 8.1% Schoolcraft County $1,004 96 $96,382 8.8% Shiawassee County $558 545 $304,245 7.6% Tuscola County $798 799 $637,885 8.3% Van Buren County $457 1,099 $501,814 7.3% Washtenaw County $86 2,420 $208,403 6.2% Wayne County - 17,542 - 6.0% Wexford County $922 400 $368,800 8.6%

Total Michigan $307 102,453 $31,483,494 6.86%

Total Shortfall < 200% of FPL County_Only Number of Aggregate Households Shortfall Alcona County 2,005 $3,383,059 Alger County 1,130 $2,310,089 Allegan County 12,286 $18,378,455 Alpena County 4,902 $6,382,836 Antrim County 3,422 $6,199,765 Arenac County 2,771 $4,887,539 Baraga County 1,124 $1,965,545 Barry County 6,798 $10,391,621 Bay County 15,184 $18,867,612 Benzie County 2,047 $3,576,421 Berrien County 23,867 $27,074,285 Branch County 6,328 $9,243,104 Calhoun County 20,355 $23,068,964 Cass County 6,683 $9,736,029 Charlevoix County 3,319 $5,201,846 Cheboygan County 4,577 $6,623,368 Chippewa County 5,564 $10,045,693 Clare County 6,197 $11,903,249 Clinton County 6,558 $9,798,087 Crawford County 2,250 $4,841,501 Delta County 5,858 $8,977,984 Dickinson County 4,141 $5,949,935 Eaton County 12,097 $15,002,155 Emmet County 4,514 $6,384,897 Genesee County 66,510 $77,238,894 Gladwin County 4,891 $8,962,133 Gogebic County 2,935 $4,572,396 Grand Traverse County 10,408 $12,606,331 Gratiot County 6,293 $9,724,920 Hillsdale County 6,934 $11,640,716 Houghton County 5,847 $10,260,531

Total Shortfall < 200% of FPL County_Only Number of Aggregate Households Shortfall Huron County 4,778 $6,731,156 Ingham County 43,825 $50,090,553 Ionia County 7,828 $12,584,516 Iosco County 4,610 $5,805,759 Iron County 2,078 $3,427,768 Isabella County 11,264 $18,540,362 Jackson County 20,753 $25,627,037 Kalamazoo County 34,834 $38,197,327 Kalkaska County 2,908 $6,455,931 Kent County 75,755 $87,674,576 Keweenaw County 441 $812,259 Lake County 2,212 $5,725,244 Lapeer County 9,751 $15,530,708 Leelanau County 2,155 $3,172,659 Lenawee County 12,311 $14,918,408 Livingston County 11,900 $15,025,937 Luce County 964 $1,674,119 Mackinac County 2,034 $3,226,698 Macomb County 96,048 $97,892,615 Manistee County 3,692 $4,998,333 Marquette County 8,803 $12,783,745 Mason County 4,734 $7,023,080 Mecosta County 6,932 $12,216,908 Menominee County 3,756 $5,837,020 Midland County 9,251 $11,481,643 Missaukee County 2,514 $5,580,901 Monroe County 16,003 $18,570,453 Montcalm County 9,530 $16,497,797 Montmorency County 1,759 $2,743,391 Muskegon County 26,466 $32,322,201 Newaygo County 7,507 $15,013,447

Total Shortfall < 200% of FPL County_Only Number of Aggregate Households Shortfall Oakland County 104,451 $106,215,218 Oceana County 4,680 $9,003,651 Ogemaw County 4,148 $7,567,305 Ontonagon County 1,232 $2,060,897 Osceola County 3,987 $8,943,812 Oscoda County 1,636 $2,969,960 Otsego County 3,520 $6,112,241 Ottawa County 24,976 $29,253,180 Presque Isle County 2,159 $3,424,536 Roscommon County 4,870 $6,785,760 Saginaw County 30,632 $36,267,069 St. Clair County 19,655 $24,291,023 St. Joseph County 8,936 $12,341,236 Sanilac County 6,625 $10,516,424 Schoolcraft County 1,406 $2,756,893 Shiawassee County 8,979 $12,908,666 Tuscola County 8,332 $13,912,646 Van Buren County 11,371 $15,406,355 Washtenaw County 37,623 $41,872,680 Wayne County 293,318 $307,994,892 Wexford County 5,566 $10,142,792

Total Michigan 1,303,293 $1,594,129,747 $1,223

ENVIRONMENTAL JUSTICE WORK GROUP REPORT MICHIGAN AS A GLOBAL LEADER IN ENVIRONMENTAL JUSTICE

PREPARED FOR GOVERNOR RICK SNYDER MARCH 2018 U-20471 Official Exhibits of Soulardarity Exhibit SOU-18 Page 2 of 38

Contents Environmental Justice Work Group Members and Staff ...... 2 Executive Summary ...... 4 List of Recommendations ...... 6 Environmental Justice in Michigan ...... 8 Consensus Process ...... 9 Technical Definitions ...... 10 Recommendations ...... 11 Guidance, Training, and Curriculum Recommendations ...... 11 Vision for Environmental Justice in the State of Michigan ...... 11 Essential Guidance ...... 11 Training and Curriculum ...... 13 Policy Recommendations ...... 16 Integrate and Strengthen Environmental Justice and Public Health Considerations in Agency Decision Making ...... 16 Enhance Tracking, Monitoring, and Metrics ...... 18 Increase Funding and Align Tax Policy with Environmental Standards ...... 21 Improve Collaboration Across Levels of Government and with Tribes ...... 21 Create Tools and Resources for Residents ...... 24 Appendix A – Resources ...... 26 Appendix B -Training and Curriculum Materials ...... 27 Appendix C – Cumulative Effect Analysis ...... 35

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Environmental Justice Work Group Members and Staff Environmental Justice Work Group Members • Chris Kolb (Co-Chair), President & CEO, Michigan Environmental Council o Representing the Environmental Community • Fadi Mourad (Co-Chair), Director of Environmental Strategy, DTE o Representing the Business Community • Jeremy DeRoo, Executive Director, Linc UP o Representing the Environmental Justice Community • Vicki Dobbins, River Rouge Community Activist o Representing the Environmental Justice Community • Jane Keon, Pine River Superfund Citizen Task Force o Representing the Environmental Justice Community • Theresa Landrum, Community Activist, Southwest Detroit 48217 o Representing the Environmental Justice Community • Lawrence Reynolds, Flint Resident o Representing the Environmental Justice Community • Charlotte Jameson, Government Affairs Director, Michigan League of Conservation Voters o Representing the Environmental Community • Jerry Maynard, Executive Committee Member, Superior Watershed Partnership & Land Trust o Representing the Environmental Community • Rob Sisson, President, ConservAmerica o Representing the Environmental Community • Guy O. Williams, President & CEO, Detroiters Working for Environmental Justice o Representing the Environmental Community • Paul Mohai, Professor, University of Michigan School for Environment and Sustainability o Representing the Academic Community • Kyle Whyte, Associate Professor, Michigan State University o Representing the Academic Community • Adel Mozip, Software Developer o Representing the Commission on Middle-Eastern American Affairs • Kaushik Nag, Director, Employee Engagement, Amway o Representing the Asian Pacific American Affairs Commission • Jesse Venegas, Vice President, Ideal Group o Representing the Hispanic Latino Commission • Frank Ettawageshik, Executive Director, United Tribes of Michigan o Representing the Tribal Community • Kathy Evans, Program Manager, West Michigan Shoreline Regional Development Commission o Representing Local Government • Kathleen Lomako, Executive Director, Southeast Michigan Council of Governments (SEMCOG) o Representing Local Government • Sylvia Elliott, Managing Attorney, Michigan Department of Civil Rights o Representing State of Michigan Government • Chad Rogers, Environmental Quality Specialist, Michigan Department of Environmental Quality o Representing State of Michigan Government

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• Jegar Johansen, Branch Manager, Wilbur-Ellis o Representing the Business Community • Andy Such, Director of Regulatory and Environmental Policy, Michigan Manufacturers Association o Representing the Business Community

Environmental Justice Work Group Staff • Angela Ayers, Executive Office of the Governor • Matt Papadopoulos, Executive Office of the Governor • Jerry Jennings (Environmental Justice Work Group Facilitator), KKAM Communications

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Executive Summary In February of 2017, Governor Rick Snyder created the Environmental Justice Work Group (EJWG) following direct recommendations from the Flint Water Advisory Task Force (FWATF) and the Flint Water Interagency Coordinating Committee’s (FWICC) Policy Subcommittee. The EJWG was charged “to develop and provide recommendations to the Governor that improve environmental justice awareness and engagement in state and local agencies. The EJWG will examine policy and recommend for implementation environmental justice guidance, training, curriculum, and policy that further increases quality of life for all Michiganders.” The EJWG is composed of 23 members, representing environmental justice communities across the state, environmental organizations, businesses, state and local government bodies, academia, and federally recognized tribes. The EJWG undertook a scope of work “to examine current environmental justice guidance, policies, and activities in Michigan, best practices from around the country that address Michigan’s specific needs and engage with local communities to better understand environmental justice in the State of Michigan. Using knowledge gained during their review of current state guidance and national best practices, and through conversations with Michigan residents, the EJWG will recommend guidance, training, curriculum, and policy for state and local agencies that improve environmental justice awareness and engagement in Michigan. These recommendations will be submitted to the Governor for consideration, and will present an implementation roadmap of short, medium, and long term actionable tasks that meaningfully and effectively advance environmental justice across Michigan and its communities.” To achieve these goals the EJWG organized its processes as follows: I. Phase 1: Learning (May 2017-August 2017) The learning phase was focused on examining current activities and best practices in environmental justice in the State of Michigan, and around the country. • The EJWG heard directly from a variety of state departments regarding current environmental justice initiatives. Presentations were given from: Department of Environmental Quality, Department of Transportation, Department of Health and Human Services, Department of Natural Resources, Department of Talent and Economic Development. • The EJWG also contacted environmental justice experts from across the nation and heard directly from environmental justice leaders in California, Minnesota, and those at the United States Environmental Protection Agency. II. Phase 2: Listening (August 2017-September 2017) The listening phase was focused on interactive public engagement sessions in communities across the state of Michigan and designed to receive input on issues and specific recommendations the EJWG should be considering. • The EJWG conducted listening sessions designed to engage residents in a specific community with EJWG members directly. These sessions were held in the following communities: o Detroit o Grand Rapids o Traverse City o St. Louis* (The EJWG was unable to hold a listening session in St. Louis; however, the EJWG did receive a presentation from members of the community regarding environmental justice issues in their area) • Each of the listening sessions included a guided tour of the community from residents. III. Phase 3: Analyzing and Recommending (October 2017-January 2018)

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The analyzing and recommending phase was focused on analyzing information gained during the prior phases of work, and identifying, drafting, and finalizing recommendations for the Governor.

It is the hope of the EJWG that the following recommendations will provide a framework for Michigan to become a national and global leader in advancing environmental justice.

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List of Recommendations Guidance, Training, and Curriculum Recommendations: Vision for Environmental Justice in the State of Michigan 1. Strive for Michigan to be a national and global leader in environmental justice (strong consensus) Essential Guidance 2. Establish an environmental justice ombudsman in the Governor’s office (strong consensus) 3. Establish an interagency working group (strong consensus) 4. Establish an environmental justice advisory council (consensus) 5. Host an annual environmental justice summit (strong consensus) Training and Curriculum 6. Develop and implement environmental justice training (strong consensus) 7. Develop and implement environmental justice curriculum (strong consensus) 8. Develop a training and curriculum tool-kit for residents (strong consensus) 9. Increase environmental justice recruitment and retention (strong consensus)

Policy Recommendations: Integrate and Strengthen Environmental Justice and Public Health Considerations in Agency Decision Making 1. Adopt public petition process (consensus) 2. Develop an environmental justice screening tool in Michigan and include cumulative impacts in decision making processes (consensus) 3. Require environmental justice analysis in permitting applications (consensus) 4. Include environmental justice analysis in the Michigan public service commission’s certification of necessity application (consensus) 5. Implement health in all policies (consensus) 6. Conduct health impact assessments (consensus) 7. Develop health impact assessment criteria (consensus) 8. Reaffirm DEQ’s authority over rules and permits (consensus) Enhance Tracking, Monitoring, and Metrics 9. Require creation of annual environmental justice report (strong consensus) 10. Implement enhanced community environmental quality monitoring (strong consensus) 11. Establish measurable targets for eliminating childhood lead poisoning (strong consensus) 12. Implement lead poisoning and other chemical contaminants dashboards (strong consensus) 13. Implement environmental health dashboards (consensus) 14. Enhance water quality testing in schools and licensed child care facilities (strong consensus) Increase Funding and Align Tax Policy with Environmental Standards 15. Increase funding for compliance assistance and enforcement of environmental laws (strong consensus) 16. Create an air, water, and soil quality mitigation fund (strong consensus) 17. Consider environmental compliance violations in Michigan Economic Development Corporation tax credit eligibility decision making (consensus) Improve Collaboration Across All Levels of Government and with Tribes 18. Ensure governmental agencies have joint responsibility (strong consensus) 19. Support regional connections between local/state officials (strong consensus)

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20. Reduce limitations placed on local governments (strong consensus) 21. Coordinate with tribal governments (strong consensus) Create Tools and Resources for Residents 22. Develop a resource manual (strong consensus) 23. Create an emergency environmental alert, notification and evacuation plan (consensus) 24. Creation of an evacuation plan toolkit (strong consensus)

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Environmental Justice in Michigan Today, Michigan is the home of many different communities, groups and cultures whose well-being depends on a clean, healthy and safe environment. The Native American peoples of the State of Michigan (State)—the Odawa, Ojibwe and Potawatomi—use a verb that expresses the active sense of what it means to be living in good and respectful ways within our human communities and within our shared ecosystem of plant and animal species. That verb is bimaadizi. In a broad sense, it describes a way of living that maintains a balance between mental, physical and spiritual health among all of life. It encompasses the concept of conservation, and a sense of justice that recognizes the reciprocal responsibilities to maintain the best quality of life for humans and the ecosystem they inhabit. In other words, our health depends on the health of the natural world, and we must sustain both. Michigan has a legacy of leadership in conservation, environmental stewardship, civil rights, industrial innovation, and entrepreneurship. Yet actions across the state also have a legacy of polluting the environment in ways that affect negatively peoples’ health and damage the terrestrial and aquatic ecosystems that people rely on for maintaining their economic vitality, recreational enjoyment, and cultural heritage. Sometimes, certain groups suffer more from environmental harms than others, raising the issue of environmental justice. Studies have shown that the distribution of environmental hazards have been visited more acutely on some populations due to factors such as race and income level. Diverse Michigan residents have been recognized across the state and United States. for their dedication in bringing awareness to environmental injustices, including the advocacy people from African-American neighborhoods on air quality, rural low-income communities on brownfield cleanup, Native American tribes on water quality for treaty fishing rights, migrant agriculture workers on exposure to unsafe working conditions, among many others. The accepted history of the environmental justice movement in the U.S. often attributes a 1990 conference organized by academic and community leaders and hosted by the University of Michigan as the event that brought the issue of environmental justice to the attention of the U.S. Environmental Protection Agency, leading to the U.S. Executive Order 12898 on environmental justice. Today, environmental justice in Michigan can be defined as “the fair, non-discriminatory treatment and meaningful involvement of Michigan residents regarding the development, implementation, and enforcement of environmental laws, regulations, and policies by the State of Michigan.” Environmental justice can also be viewed as a constitutional obligation of the State. The Constitution of Michigan includes equal protection for all1 and a focus on the public health and general welfare of the people of Michigan in general and particularly in relationship to the use of natural resources2. In doing so the constitution creates an obligation for the state’s government to ensure that the state’s water, land and air do not contribute to disparate impacts on any residents based upon race, religion or other protected classes. Despite this obligation current health data suggests that environmental factors are contributing to health disparities in the state. Public health data showing health disparities therefore compels the State to take bold and immediate actions to meet its constitutional obligations. This report is intended to provide some recommendations to move the State in that direction.

1 Constitution of Michigan Of 1963, Article I, Section 2 2 Constitution of Michigan Of 1963, Article IV, Sections 51 And 52

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Consensus Process The EJWG elected to utilize a facilitated consensus process to discuss and finalize recommendations. That process is briefly outlined below: • When forming a potential final consensus on a specific item there were several situations when the facilitator checked for consensus. These checking situations helped to define the agreements that were in the process of developing. • This checking for consensus and final consensus process occurred through a technique of facilitated “Fist to Five”: o Five fingers signify that “I totally support this. I see it to be a very good way of moving forward toward fulfilling the Charge of the EJWG. Count on me to be a strong, vocal and practical supporter of this direction - if it becomes the group’s consensus.” o Four fingers signify that “I support this. I see it to be an effective way of moving forward toward fulfilling the Charge of the EJWG. I am ready to clearly back this and actively demonstrate my support for this proposal - if it becomes the group’s consensus.” o Three fingers signify that “I am OK with this. When I weigh the advantages and disadvantages of this suggestion’s appropriateness in moving forward toward fulfilling the Charge of the EJWG, I believe it matches OK.” o Two fingers signify that “this is not my first or second choice and that I am not strongly against this. If this is the strong consensus of the EJWG I will quietly show my support through not talking for or against it.” o One finger signifies that “I am opposed to this. If this is the strong consensus of the EJWG I will not talk against it.” o Fist signifies that “if I could, I would veto this. I would move on to find a different direction, we can agree on.” As a part of this process the EJWG agreed that two separate levels of consensus could be reached: • Strong Consensus - For a recommendation/decision to move forward or become final as a strong consensus of the EJWG, a minimum of 65% of the group members present, in- person or telephonically, will be Four’s or Five’s and no more than 10% will be Two’s, One’s or Fists. • Consensus - For a recommendation/decision to move forward or become final as a consensus of the EJWG, a minimum of 55% of the group members present, in-person or telephonically, will be Four’s or Five’s and no more than 20% will be Two’s, or One’s, or Fists.

Voting on individual recommendations was conducted on a rolling basis, so at each meeting different recommendations were voted on and added to the list of recommendations if they achieved either strong consensus or consensus. Depending on the number of individuals voting, the number of votes required to reach strong consensus or consensus changed from meeting to meeting. At a minimum, twelve members of the EJWG needed to be present for a vote to occur.

A high bar was set for any recommendation to reach consensus, let alone strong consensus. Due to the number of actual EJWG members voting, no recommendation could reach strong consensus with more than two members voting “two fingers, one finger or fist.” Likewise, due to the actual number of members voting, no recommendation could reach consensus with more than four members voting “two fingers, one finger or fist.”

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Technical Definitions Environmental Justice: the fair, non-discriminatory treatment and meaningful involvement of Michigan residents regarding the development, implementation, and enforcement of environmental laws, regulations, and policies by the State.

Environmental Justice Area/Community: Any census tract with a 30 percent or greater minority population, or 20 percent or greater at or below the federal poverty level. • The State should use this definition, until the State develops its own screening tool and can help further define an Environmental Justice community with more robust data (e.g., using a similar methodology to the CalEnviroScreen tool)

Area of Concern: The area located within ½ mile, or 4 miles in rural areas, of any of the following: • The boundary of a site where a regulated activity affecting human health and/or environment is/will occur • Areas where the State, or local government body, is authorized to determine impacts to human health and the environment (e.g., traffic corridors, groundwater plumes, significant air impact, etc.) • Areas impacted or reasonably expected to be impacted by drainage, watersheds, visual, noise, subsidence, vibration, or odor associated with the regulated activity affecting human health and/or environment

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Recommendations To facilitate progress on achieving the goals of the workgroup, we support implementation of these recommendations by executive action, and where appropriate, legislative action.

Guidance, Training, and Curriculum Recommendations Vision for Environmental Justice in the State of Michigan 1. Strive to be a national and global leader in environmental justice (strong consensus) • Michigan should strive to be a national and global leader in advancing and achieving environmental justice

Essential Guidance 2. Establish an environmental justice ombudsman in the Governor’s office (strong consensus) • The Governor should establish and hire an environmental justice ombudsman to serve as the statewide point of contact for accepting, investigating and resolving allegations of environmental injustice committed by the State. The ombudsman will also serve as a co-chair of the interagency working group (IWG) and serve as a non- voting ex-officio member of the environmental justice advisory council as detailed below. In their official capacity, the ombudsman will identify EJ related issues that transcend departmental jurisdictions and work with the interagency working group to seek solutions. It is envisioned that the ombudsman will be a highly regarded professional and be granted appropriate administrative power to facilitate the investigation of environmental injustices and the implementation of recommended solutions.

3. Establish an interagency working group (strong consensus) • The Governor should establish an interagency working group (IWG) comprised of all principle State departments as well as the Michigan Economic Development Corporation. The intent of the working group’s membership is to have all relevant State agencies represented and engaged with the group’s work. As such, the departmental representatives on the IWG should be the director or their designee, and the co-chairs of the IWG should be the environmental justice ombudsman and the Governor’s environmental policy advisor. • The IWG should be responsible for the review and consideration of environmental justice issues that have been brought to the attention of IWG members, the environmental justice ombudsman, or the Governor’s office. i. In considering issues to address, the IWG should place emphasis on those issues that transcend departmental jurisdictions. • In addition, other duties of the IWG should include: i. Identifying State departments that could benefit from the development of environmental justice policies and procedures; ii. Assisting those departments in the development of such policies and procedures; iii. Recommending performance goals and measures for State departments to further environmental justice policies and procedures; iv. Reviewing the progress of State departments in complying with environmental justice policies and procedures and promoting environmental justice;

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v. Interacting with tribal governments regarding environmental justice issues with tribal implications; vi. Recommending measures to further promote environmental justice in the State; vii. Ensuring meaningful involvement in State agencies’ decision making from disproportionately-burdened communities; viii. Promoting collaborative problem-solving for issues involving environmental justice; and, ix. Coordinating between departments to identify resources or strategies (including MOUs) needed to increase coordination and cooperation between and among departments to accomplish the goals of the IWG. x. Establish a systematic approach to receiving neighborhood level recommendations and other feedback as related to the State’s goals of becoming a national leader in achieving environmental justice. This might take the form of enlisting regional advisory committees, investing in a regular series of listening sessions across the state, etc. To be clear, this mechanism is envisioned to expand the ease with which communities can proactively inform the State above and beyond typical “public comment” periods for specific regulatory activities.

4. Establish an environmental justice advisory council (consensus) • The IWG will also establish an environmental justice advisory council (EJAC) to advise the IWG on the exercise and fulfillment of its responsibilities and duties described above. • The EJAC will advise the IWG on development and implementation of environmental justice related matters. This includes but is not limited to: i. Evaluating the effectiveness of the State’s implementation of environmental justice principles and determining metrics to measure success; ii. Holding a minimum of two business meetings and listening sessions per year to obtain information about environmental problems in the state from community residents and other stakeholders; iii. Providing recommendations to the IWG on improvements to policies and procedures to ensure integration of environmental justice principles into State agencies’ work; and, iv. Collaborating with the State to improve civic engagement with environmental justice communities. • The EJAC will be an advisory only body and not a decision-making body. • We envision that any discussions about specific regulatory actions, such as facility permits, will be only as examples of what has worked well or poorly in EJ communities. • The EJAC should be composed of members representing the following: 1. 3 members from affected communities concerned with EJ 2. 3 members from community-based organizations that work with EJ community members on environmental justice and/or environmental health issues 3. 3 members from industry and business 4. 3 members from nongovernmental environmental organizations: 5. 3 members from local governments;

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6. 3 members of academia with expertise in the areas of environmental justice, environmental health, or American Indian and indigenous affairs 7. 2 members from tribal/indigenous governments and organizations; 8. 2 members from labor organizations that live in or have experience working with impacted environmental justice communities and/or have experience working on bringing low-income people and people of color into union apprenticeship programs 9. 2 members at-large i. There will be two co-chairs who are members of the EJAC; the co-chairs will be selected by the EJAC once it is seated ii. The EJ ombudsman and the Governor’s environmental policy advisor will serve as non-voting ex-officio members on the EJAC and coordinate between the EJAC and the IWG. iii. The EJAC may also form subcommittees as it sees fit to address specific issues. These subcommittees may be composed of both members from the EJAC and those outside of the EJAC membership.

5. Host an annual environmental justice summit (strong consensus) • The Governor should host an annual environmental justice summit bringing together National, State, native American/tribal, local and community experts, and interested parties to identify environmental justice challenges, and implement ideas, approaches and solutions to overcome these challenges and advance environmental justice in Michigan.

Training and Curriculum 6. Develop and implement environmental justice training (strong consensus) • The Governor shall work with the Civil Service Commission to develop comprehensive environmental justice/social equity training for State and local employees. This training shall include: i. Written guidance (detailed within the curriculum recommendation below) ii. Workshops and panel discussions on EJ issues iii. Presentations by members of EJ communities iv. Tours of EJ communities • The Governor shall require new State employees to receive environmental justice/social equity training and encourage local employees and elected officials to do the same. • The State shall incorporate environmental justice into its employee training for positions in all departments, especially, DEQ, MDNR, MDHHS, MDARD, and MDOT, as well as open these trainings to local employees and elected officials where appropriate. • The Governor shall direct each department within State government to send at least one employee to the 2018 National Environmental Justice Conference and Training program. i. Funding should be made available to send a delegation of key State employees to this conference and training session on an annual basis. ii. The delegation will be responsible for disseminating what they have learned to others in State and local governments through presentations and publications.

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• The Governor shall direct a working group to produce teaching materials (such as emails, brief webinars, and previously published materials), to inform leaders of agriculture, business, and industry, the medical profession and others about environmental justice concepts and principles, and to promote environmental justice decision-making within their sectors. • The Governor shall direct a working group to establish a lecture and learning series to provided continuing education for the public that utilizes experts, knowledgeable individuals, and organizations to give presentations on environmental justice challenges, best practices, lessons learned from successes, and lessons learned from initiatives that have not been successful.

7. Develop and implement environmental justice curriculum (strong consensus) • The Governor shall direct a working group to compile an environmental justice teaching curriculum appropriate for use in training for State and local employees. • The curriculum shall include, but not be limited to, the following topics: i. Definitions of community, environmental justice, equity verses equality, area of concern, rural, urban, and other pertinent terms; ii. A history of the environmental justice movement and Michigan’s place in that history; iii. Discussions of what makes a community healthy, including lessons in cultural differences; iv. Discussions of toxic waste management; v. Discussions of environmental mapping and environmental justice screening tools; vi. Discussions of cumulative impacts; vii. Discussions of permitting, licensing, regulating, and enforcement; viii. Discussion of the 17 principles of environmental justice, the Jemez principles of democratic organizing, and other published documents3; ix. Communication and engagement skills training for working with individuals, community groups and the public; and, x. Participation in listening sessions and tours of environmental justice communities

8. Develop a training and curriculum tool-kit for residents (strong consensus) • The State should develop a toolkit for residents, local governments, businesses and community organizations built around the material the State utilizes with its employee’s environmental justice training and curriculum, including but not limited to: i. Environmental justice concepts and principles ii. Environmental justice challenges, successes, and lessons learned from unsuccessful initiatives iii. Definitions of community, environmental justice, equity vs. equality, area of concern, rural, urban, and other pertinent terms iv. A history of the environmental justice movement and Michigan’s place in that history v. Discussions of what makes a community healthy, including lessons in cultural differences vi. Discussions of toxic waste management vii. Discussions of environmental mapping and environmental justice screening tools

3 see appendix B for additional materials and information

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viii. Discussions of cumulative impacts ix. Discussions of permitting, licensing, regulating, and enforcement x. Discussion of the 17 principles of environmental justice, the Jemez principles of democratic organizing, and other published documents xi. Communication and engagement skills training for working with individuals, community groups and the public • The toolkit should utilize information and efforts the State is conducting in implementing the recommendations of the EJWG that would be appropriate to share with local communities and individuals who might utilize this information in their own communities, businesses and organizations to address environmental justice issues in their locales, such as: i. Information on how communities can participate in enhanced monitoring of environmental pollution/contamination areas of concern within their locales as noted in the recommendation titled “implement enhanced community environmental quality monitoring,” including the creation of a forum/process where local communities can apply to the State for an enhanced environmental quality monitoring network that: (a) measures pollutants or contaminants of concern; (b) identifies the monitoring period to accurately characterize potential exposures; (c) identifies the monitoring location(s); and (d) identifies potential community involvement in the expanded program and any required training. ii. Provide the information on the State’s experience including the process, successes, and lessons learned from non-successful initiatives to installing “health in all policies” approach in state laws, regulations, policies and procedures, so local communities can adopt successful approaches and learn from the State’s experiences. iii. Identify funding opportunities for local communities and organizations to help develop and implement local environmental justice programs, policies and procedures. iv. Provide information on how to access data collected by the state, when possible, to address environmental justice issues.

9. Increase environmental justice recruitment and retention (strong consensus) • The State should increase its focus, including active outreach, on recruitment and retention for State employees, commissions, workgroups and stakeholder group participants from environmental justice communities to increase diversity of representation.

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Policy Recommendations Integrate and Strengthen Environmental Justice and Public Health Considerations in Agency Decision Making 1. Adopt a public petition process (consensus) • The Governor should establish a petition process to allow citizens to draw attention to and seek mitigation from any environmental injustice as exhibited by disproportionate environmental risks, impacts and health disparities in their neighborhoods. The petition process is intended to help residents address existing conditions, and not to revisit appropriate agency decisions. It should provide action steps to help petitioners achieve resolution and be both transparent and public in its proceedings and records. • To these ends, the petition process should consider the following general guidelines: i. No specific form should be required in order to file a petition; a letter stating the community’s concerns is sufficient. Petitioners will be asked to state whether they have also issued or plan to issue a formal grievance to a State agency. ii. In urban areas and urban clusters, a submission should be accompanied by signatures of at least 50 Michigan residents, including at least 25 residents from the affected community. iii. In rural locations outside of census urban areas or urban clusters, signatures of at least 20 percent of the population living within four miles of a facility that is allegedly causing any disproportionate impacts, exposures or health disparities are required for the petition. iv. Petitions should be evaluated individually and an "action plan" should be developed featuring deliverables, timeframe and a description of relevant resources and in consultation with the affected neighborhood or community and local and federal governmental agencies as relevant community deliverables. Private actors may choose to participate in the development of an action plan, and the commitments are undertaken by State agencies. Commitments are based on the agencies' existing legal authority and legal duties. Agencies must also coordinate situations where a petitioner has also issued a formal grievance. v. The State should develop a website, open to the public, that documents and displays basic information about each petition issued and the status of the State’s response. vi. Detailed guidance on environmental justice petition processes, including comparisons across state and federal governments, is in the 2009 Michigan draft Environmental Justice Plan that was released for public comment on December 11, 2009.

2. Develop an environmental justice screening tool in Michigan and include cumulative impacts in decision making processes (consensus) • The IWG should develop a screening tool (e.g., U.S. EPA’s EJSCREEN, Cal EPA’s CalEnviroScreen, etc.) that can be adapted to Michigan to measure the cumulative impacts of environmental hazards, pollutants, and discharges. The tool should be used to prioritize environmental issues, to consider in making permitting decisions, allocate monetary resources, prioritize environmental hazards for remediation, recognize public health issues, and future planning toward an improved environment and quality of life for all residents and visitors to Michigan. In developing this tool, the IWG should:

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i. Determine the scope of work through a participatory public process ii. Utilize and adapt models and best practices from other states, e.g. California, Minnesota, Oregon, Illinois, U.S. EPA, etc.4 iii. Use publicly available data sources, such as the TRI, RSEI-GM, NATA, census data, and others. The State should create supplementary data sources (emissions data, health outcome data, demographic data, property values, public health trends e.g. Cancer, asthma, deaths, legionnaire’s disease and other diseases, etc.) Supplementary data sources could include increased density of air quality monitors in impacted communities to develop air quality estimates between monitors and a program to routinely test the water quality of all schools in Michigan once every three years. iv. Review, monitor and evaluate data sources annually. v. The IWG would identify who would adapt the screening tool, identify where the resources for development would come from and what entity would ultimately “own” the tool. • The tool is intended to be used by the IWG, State agencies, local governments, community organizations, and businesses.

3. Require environmental justice analysis in permitting applications (consensus) • The State shall require all environmental permit applicants (and transportation projects) to provide an environmental justice analysis that evaluates the impact, and any disproportionate impact, of the permitted activity on environmental justice communities, and any steps that can be taken to reduce or eliminate such impacts.

4. Include environmental justice analysis in the Michigan public service commission’s certification of necessity application (consensus) • The State shall require an application seeking a certificate of necessity to construct a new electric generation facility or to make a significant investment in an existing facility or enter into a power purchase agreement to include an environmental justice analysis that evaluates the impact, including any disproportionate impact, of the proposed facility on environmental justice communities, and any steps that can be taken to reduce or eliminate such impacts.

5. Implement health in all policies (consensus) • The Governor should establish appropriate policies and procedures to ensure that all departments and offices of State government with regulatory authority institute a health in all policies approach to implementing all current and future laws, regulations and policies and procedures. • The Governor should prioritize the wide application of health impact assessments as a primary tool in accomplishing a health in all policies approach. i. The purpose of HIAP is to: 1. Identify potential health impacts of a proposed project, policy, or plan; 2. Identify recommendations or methods to mitigate the adverse health impacts and maximize benefits; and, 3. Allow decision makers to better balance health impacts with other considerations by providing clear information and analysis. • The Governor should establish training programs for key regulatory staff that educate them on the use of health impact assessments, and other current best practices that

4 see appendix C for additional information regarding potential methodology

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support successful implementation of health in all policies approaches (e.g. Health in All Policies a Guide for State and Local Governments, APHA, CDC, the California endowment, et. Al., 2013).

6. Conduct health impact assessments (consensus) • The Governor should direct agencies to conduct health impact assessments (HIA) for any project that requires an environmental impact statement or air or water quality permit. Where applicable, all agencies involved in a joint decision should work toward creating a unified health impact assessment. The goal of the health impact assessment should be to determine the health effects on identified populations of any new or modified rule or permit regarding air or water pollution or of any major project or plan. • The Governor should also work with the legislature to ensure agencies have appropriate resources to conduct the needed HIAs. The Governor and legislature should also examine ways to support non-governmental bodies, local governments, industry, tribes, and/or communities in conducting HIAs, including but not limited to providing funding, technical assistance, or guidelines, or access to data.

7. Develop health impact assessment criteria (consensus) • The Governor should direct the Interagency Working Group to determine criteria for use in evaluation of health impacts within assessments and to create guidelines and worksheets for conducting effective HIAs for State agencies, local governments, tribes, industry, non-governmental organizations, and communities. Those guidelines should include direction on how to best determine negative health risks and how to evaluate cumulative impacts on human health and the environment and the potential high aggregation of risk from multiple sources.

8. Reaffirm DEQ’s authority over rules and permits (consensus) • The Governor should oppose attempts to give outside commissions or boards rule- making or permitting authority We support the establishment of environmental and public health advisory commissions to help inform the creation of sound public policy and to give stakeholders and communities more opportunity to meaningfully impact agency and administrative decisions. However, the Governor should maintain the ability of State agencies to promulgate rules that are stricter than federal standards. • The Governor should also reaffirm and support the ability of agencies working to protect environmental justice and vulnerable communities to promulgate rules and oversee permitting.

Enhance Tracking, Monitoring, and Metrics 9. Require creation of annual environmental justice report (strong consensus) • The State shall publish an “annual environmental justice report.” This report should develop and report metrics to evaluate the current state of environmental justice conditions and activities across the state, and monitor progress on environmental justice issues on a year-to-year basis.

10. Implement enhanced community environmental quality monitoring (strong consensus) • The Governor should enhance the quantity and quality of environmental monitoring programs in Michigan. Environmental quality monitoring is essential to the development of sound policies and regulations, essential to measuring progress toward community-based targets, and to communicate conditions and address

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concerns by Michigan residents. An effective environmental monitoring program should include the following: i. Providing for a sufficient number of monitors in areas known to be a problem due to environmental pollution/contamination (air, water, soil, noise, etc.), so that environmental quality can be accurately measured, and potential sources identified; ii. Creating a forum/process where local communities can apply to the State for an enhanced environmental quality monitoring network that: (a) measures pollutants or contaminants of concern; (b) identifies the monitoring period to accurately characterize potential exposures; (c) identifies the monitoring location(s); and (d) identifies potential community involvement in the expanded program and any required training; and, iii. Making certain that a stable source of funding for enhanced community environmental quality monitoring is provided. iv. Ensuring all data from environmental monitoring is accessible to the public.

11. Establish measurable targets for eliminating childhood lead poisoning (strong consensus) • Annually, a panel of State officials (including representatives from DEQ, MDHHS, MDE), pediatricians, public health experts, community-based organizations, and residents of impacted communities should meet to discuss the environmental justice dimensions of childhood lead exposure. This would include setting stretch targets for testing, reduction of childhood lead poisoning, lead remediation and abatement, and clearances. At the end of the year, the panel would consider the results and make recommendations for statewide improvements to achieve progress toward the goal of eliminating childhood lead poisoning in Michigan. Dissemination of results should be reported to the Governor, appropriate State departments, posted on State websites, and include direct contact to such groups as: i. Local public health departments ii. Municipal, county planning, and community development officials iii. Local great start collaboratives iv. School superintendents and publicly-elected board of education officials v. Non-governmental organizations and community-based organizations identified as working on children’s health and well-being, housing, or the environment vi. Affected communities • Such information should be presented in a way that is easily understandable by populations most impacted, including appropriate translations.

12. Implement lead poisoning and other chemical contaminants dashboards (strong consensus) • The Governor should create a dashboard that provides relevant information that assists in tracking progress toward addressing known problems. • The information reflected on the dashboard should present publicly across time and geographies (i.e., state, counties, cities over 5,000, and census tracts or zip code areas) key indicators of the fight to eliminate lead poisoning in Michigan. • The State should release an aggregated, anonymized version of its database at least quarterly to support these dashboards. • The indicators should include, at a minimum: i. Number and percentage of children tested (by ages); ii. Number and percentage of children lead-poisoned (by lead concentration level);

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iii. Number of housing units with hazards remediated or abated; iv. Number of lead clearances; v. Estimated number of remaining housing units with lead paint, leaded pipes, and lead in soil; and, vi. Available funding for mitigation, remediation, and abatement. • Where possible, the indicators should be tracked at the state level against national averages and against other states that are leaders in the reduction of childhood lead poisoning. • Similar dashboards should also be created for mercury poisoning and the impacts of other chemical contaminants, such as arsenic, nickel, and others, and tailored to fit community challenges.

13. Implement environmental health dashboards (consensus) • The IWG shall establish health-based metrics for materials of environmental concern, including but not limited to lead and mercury. These metrics will be tracked on a regular basis and published on the appropriate dashboards, available to the general public, local units of government, including affected communities, local health departments, and legislators. Where possible, the indicators would be tracked at the State level against national averages and against other states that are leaders in the reduction of materials of environmental concern.

14. Enhance water quality testing in schools and licensed child care facilities (strong consensus) • The Governor should enhance water quality testing in schools and licensed child care facilities across the state so that water quality standards provide all of Michigan’s children with the same level of protection. Ethically and administratively, school water standards should provide all of Michigan’s children the same level of protection. As lead contamination to drinking water has been shown to be an issue in Michigan and children are often exposed in schools, the Governor should develop a plan to routinely test the water quality of all schools and licensed child care facilities in Michigan. This plan should: i. Make certain that in every school and licensed child care facility, the State works with water utilities and other relevant agencies to have safe tap water available, free of contaminants that threaten the health of our children and school and child care staff. ii. Make certain that in every school and licensed child care facility, the State works with water utilities and other relevant agencies to: 1. Conduct an initial assessment to eliminate lead from plumbing or fixtures in all active buildings. 2. Develop and pilot-test monitoring processes based on environmental health and engineering best practices and evidence to ensure school water safety (including taking into account school schedules and the impact of flushing on drinking and food preparation water fixtures). 3. Communicate monitoring processes to the community to assure understanding of baseline conditions and trends. 4. Publicly post and report data with a plan for remediation (such as elimination of fixtures and other sources of lead to drinking water) with community input. iii. Make certain that a stable source of funding for school water quality monitoring is provided. The costs for these school programs will require a stable source of funding, but initially a combination of federal, state, county,

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and/or private funding will be required to avoid unnecessary delays. The state should ultimately provide for a stable source of funding so that poorer communities and school districts in Michigan are not overburdened. iv. Make certain that reports of progress be reported to the child lead exposure elimination commission annually for input and further recommendations to assure water safety and healthy quality.

Increase Funding and Align Tax Policy with Environmental Standards 15. Increase funding for compliance assistance and enforcement of environmental laws (strong consensus) • To address existing and prevent future EJ issues it is important that existing environmental laws be enforced. Funding should be increased for compliance assistance and enforcement within State and Local regulatory agencies.

16. Create an air, water, and soil quality mitigation fund (strong consensus) • The Governor should create an air, water, and soil quality mitigation fund (AWSQMF) within the State treasury and ensure that all civil and administrative fines and interest on those fines assessed by the State for violation of Michigan air, water, and soil quality regulations be deposited into the fund. The DEQ should oversee the disbursement of funds from the AWSQMF and a portion of the funding should go to support DEQ staffing and administrative needs for air or water pollution mitigation, soil remediation, air or water pollution monitoring, and improved compliance. The majority of the funds from the AWSQMF should be put towards grants to local community organizations, local nonprofits, local health departments, and local environmental departments where the violation occurred to support the development of health impact assessments, pollution mitigation and remediation programs, and education and training programs for community residents and local environmental regulators.

17. Consider environmental compliance violations in Michigan Economic Development Corporation tax credit eligibility decision making (consensus) • The Governor should work with the Michigan Economic Development Corporation (MEDC) and the Strategic Fund Board (SFB) to ensure that corporations with unresolved violations that impact human health and the environment are not eligible for tax credits and other economic development programs offered by the State through the MEDC. • The Michigan legislature should ensure that the requirement for compliance with Michigan’s environmental standards that impact human health and the environment is factored into any enabling legislation for new tax credit programs or economic development programs offered through MEDC going forward.

Improve Collaboration Across Levels of Government and with Tribes 18. Ensure governmental agencies have joint responsibility (strong consensus) • The Governor shall ensure that all relevant government agencies are jointly responsible for water quality and environmental health and work collaboratively with open channels of communication and data sharing for that purpose. • Agencies other than the DEQ have relevant public health expertise and vantage points for oversight of water systems across Michigan. We recommend that the Michigan department of environmental quality, Michigan department of health and

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human services, county and city health departments, and other relevant state agencies assume joint responsibility for oversight and accountability.

19. Support regional connections between local/state officials (strong consensus) • The Governor should: • Create a multi-jurisdictional public health emergency plan • Establish a position for a State health officer to coordinate with local health officers • Require the state health department to hire people with public health education and work experience • Internal politics and legalistic approaches on the part of the state health department have slowed responses to public health crises recently and historically. These approaches have increased human exposures to contaminants and toxins. • Michigan’s public health code requires both State and local health departments to respond to public health emergencies, regardless of what the other does. This should create a fail-safe redundancy; however, response to threats is often piecemeal and incomplete, worsening an environmental crisis or disaster.

20. Reduce limitations placed on local governments (strong consensus) • The Governor should: i. Instruct State agencies to seek ways to reduce and lift limitations on local government that interfere with the resolution of environmental justice issues; and, ii. Encourage local governing bodies to address environmental justice within their locales • State agencies should support local governing bodies in protecting human health and the environment by reducing limitations placed on municipal, township and county government, specifically limitations that affect a local government’s ability to identify or correct environmental justice problems within their locales. i. For example: at present, limitations placed on local governing bodies often undercut and eliminate meaningful public involvement in the decision-making process regarding environmental justice concerns. ii. Local governments are also well positioned to identify environmental justice areas within the community and issues and concerns associated with those areas. iii. A local governing body must exercise the legal authority to protect the public health and prevent the degradation of environmental resources held in the public trust taking place in its jurisdiction. • The present statutes, regulations, policies, and procedures of the State deprive local governments of utilizing their authority to function for the common good. By substituting its authority for local authority, the State preempts the initiative and responsibilities of local government and curtails any meaningful public involvement in government decision making.

21. Coordinate with tribal governments (strong consensus) • The Governor should initiate an official consultation pertaining to environmental justice issues with tribal leadership in the state per the provision of the 2002 Tribal- State compact. • Additionally, all environmental justice actions taken by the State should include efforts to engage Native American individuals and communities.

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i. Tribal governments are sovereigns and have a government-to-government relationship with the United States (U.S) of America. This relationship is stated in the U.S. constitution, commerce clause, where the U.S. Congress is delegated the power “to regulate commerce with foreign nations, and among the several states, and with the Indian tribes." the body of law emanating from treaties between tribes and the U.S., jurisprudence and federal statutes establishes tribes as exercising inherent sovereignty and the U.S. has a trust responsibility to support the best interests of tribes. Inherent sovereignty and the trust responsibility are cornerstones of the government-to-government relationship between tribes and the U.S. ii. As sovereigns, tribes provide protections and services to tribal members and exercise jurisdiction over certain lands, airs, waters and subterranean resources. Intertribal organizations whose members are tribal governments, such as the Chippewa Ottawa Resource Authority (CORA), have co- management responsibilities over certain lands and waters along with the State and in coordination with the U.S. federal government. Some tribal organizations in urban areas, chartered as 501c3 organizations, provide services for native persons living in these areas. iii. Many native people, due to racism, poverty and other forms of discrimination and inequality, are at greater risk for environmental risks relative to other populations in the state. Indigenous peoples across the state, especially tribes with long histories in Michigan and the great lakes region, practice cultures that pre-date the establishment of the U.S. The spiritual practices of these cultures are connected to issues of environmental quality and the integrity of lands and waters. iv. In 2002, the State and the twelve federally recognized tribes in Michigan signed the government-to-government accord between the State and the federally-recognized tribes in the State. In the accord, the State affirms the sovereignty of the tribes. The accord outlines a process for government-to- government consultation regarding issues of mutual concern between the State and the tribes. In addition to the government-to-government consultation process, the State has responsibilities to individual native persons who are also citizens of and reside in the state. In 2004, the State and tribes entered the Intergovernmental Accord between the federally recognized Indian tribes in Michigan and the Governor of the state of Michigan concerning the protection of shared water resources. In 2009, the State and tribes entered the intergovernmental accord between the tribal leaders of the federally recognized tribes in Michigan and the Governor of the state of Michigan to address the crucial issue of climate change. The 2004 and 2009 accords affirm tribal sovereignty, the State’s responsibility for government-to-government consultation on environmental matters and a commitment between the State and tribes to work jointly to address environmental issues of mutual concern. v. An environmental justice policy must meet the government-to-government protocols for the State to collaborate with tribal governments as well as fully address environmental justice issues relevant to tribal members and other individual native persons in the general population who are facing adverse impacts. An environmental justice policy should create opportunities for tribes, states, local government and relevant federal agencies to identify environmental justice issues and risks and to identify legal and other means to address them. It is important for tribes and the State to be clear on which

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issues or which dimensions of issues are best addressed through tribal-U.S. federal relationships, tribal-state relationships, tribal-local government relationships or some combination of these different relationships across sovereigns (U.S., State and tribal) and local governments. Native persons, as people who reside in and/or are citizens of the state, also have the right to be at the table in decision-making on environmental justice issues relevant to their well-being. An environmental justice policy, whether concerning tribal governments or native persons more generally, should respect and honor the indigenous cultures of the Great Lakes Region and in Michigan and work to ensure that indigenous histories, traditions and contemporary cultures are not threatened or erased. When considering indigenous environmental justice issues, the State should consider principles contained within the United Nations Declaration on the Rights of Indigenous peoples, especially the principle of free, prior, and informed consent.

Create Tools and Resources for Residents 22. Develop a resource manual (strong consensus) • The Governor should develop a resource manual for use by community organizations, general public, homeowner, renters, commercial entities, developers, landlords etc. • As an example, this resource manual should at a minimum include: i. Who do I call when lead is discovered in my home or on my property? ii. What number at the State should a landlord call to get a “Lead” certification? iii. How do I know what environmental issues to look for or what certifications are required before buying a home or sending my child to a new school? iv. Where/how do I report an oil leak in a river, lake, on land or in a stream? v. What do I do/who should I contact when my water tastes, smell or looks strange? vi. How do you find out whose jurisdiction (Hazmat, fire department, police, EPA, DEQ etc.) when an environmental incident occurs? vii. Best practices for businesses and developers; e.g. the use of a retaining pond to cool water temps before they are released into streams and waterways.

23. Create an emergency environmental alert, notification, and evacuation plan (consensus) • The Governor should create a state-wide emergency environmental alert, notification, and evacuation plan to use in instances of environmental emergency where the public health is potentially at risk, [e.g., air, soil or water contamination, explosion or fire], requiring evacuation, shelter in place or other responsive action by residents, businesses and travelers. The emergency environmental alert, notification, and evacuation plan should: i. Identify a lead person/agency (i.e., coast guard, homeland security, local government, State government, Michigan State Police) who will have cross- jurisdictional authority and responsibility for coordinating and directing area specific emergency environmental activities, including but not limited to communications, evacuations, and/or relocation of individuals across/within and outside of county, city, state, municipal structure or geography; ii. The State shall coordinate first responders (e.g. Fire, police, civil defense, homeland security), community organizations and businesses, in consultation

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with environmental experts to identify and define situations of environmental emergency necessitating an emergency response; iii. Recommend designating a new siren sound to indicate an environmental emergency distinguishable from the current EAS for tornado and weather emergencies; iv. Ensure evacuation routes are clearly marked using universal signage systems; v. Provide transportation and accommodations for individuals without access to personal transportation when an evacuation is likely (e.g. School buses and other modes of public transportation); vi. Establish a communications center to coordinate information from homeland security, businesses, State and local agencies and provide real time status reports and updates to individuals; vii. Ensure that all communications are easily understood and presented in a variety of languages (e.g. Arabic, Spanish, ASL, English) and utilize a variety of methods and sources (e.g. TV, radio, texts, phones, sirens) and be ADA compliant for individuals with disabilities; and, viii. Review current “emergency alert notification” systems for viability/feasibility in urban and rural areas and orchestrate changes such as instituting the “reverse 911” system in areas that do not have it. • The State will also require local governments provide community awareness and evacuation training (every three years) for schools, residents and businesses within a three-mile radius of potentially dangerous industries.

24. Creation of an evacuation plan toolkit (strong consensus) • The Governor should create a state-wide emergency response toolkit (ERTK) that could be used in instances where environmental air, soil and water contamination, explosions, fire requires evacuation of residents, businesses and travelers. This kit shall contain: o Simple language easily understood by all residents and community members; o Phone numbers, email addresses, and websites for people to get information about resources like environmental testing, compensation for expenses incurred, low-cost or pro bono legal aid, etc.; o Be easily printed and put into local organization’s newsletters, passed out at school for kids to take home, distributed to local business and mailed to residents in certain zip codes; and, o Provide real, live human beings to take phone calls and/or respond to emails and/or texts in “real-time” and to provide real time updates of information to the people who find themselves facing emergency environmental conditions.

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Appendix A – Resources Over the course of its work, the EJWG met with or received presentations from the following individuals or organizations: • Department of Environmental Quality • Department of Transportation • Department of Health and Human Services • Department of Natural Resources • Department of Talent and Economic Development • Shankar Prasad, Office of Environmental Health Hazard Assessment, State of California • Ned Brooks, Environmental Justice Coordinator, Minnesota Pollution Control Agency • Alan Walts, Environmental Justice Coordinator, US EPA, Region 5 • Stuart Batterman, Ph.D., Professor, Environmental Health Sciences, School of Public Health • Steve Black, Transaction Manager, RACER Trust • Grant Trigger, Cleanup Manager for former GM properties in Michigan, RACER Trust • Marcus Cheatham, Mid-Michigan District Health Department • Community Outreach and Education Core of the Michigan Environmental Exposure and Disease (MLEEAD) • Sierra Club • Seeds of Promise • Healthy Homes Coalition • Plaster Creek Stewards • LINC Up • Grand Traverse Band of Ottawa and Chippewa Indians

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Appendix B -Training and Curriculum Materials Principles of Environmental Justice Delegates to the First National People of Color Environmental Leadership Summit held on October 24-27, 1991, in Washington DC, drafted and adopted 17 principles of Environmental Justice. Since then, The Principles have served as a defining document for the growing grassroots movement for environmental justice. PREAMBLE WE, THE PEOPLE OF COLOR, gathered together at this multinational People of Color Environmental Leadership Summit, to begin to build a national and international movement of all peoples of color to fight the destruction and taking of our lands and communities, do hereby re- establish our spiritual interdependence to the sacredness of our Mother Earth; to respect and celebrate each of our cultures, languages and beliefs about the natural world and our roles in healing ourselves; to ensure environmental justice; to promote economic alternatives which would contribute to the development of environmentally safe livelihoods; and, to secure our political, economic and cultural liberation that has been denied for over 500 years of colonization and oppression, resulting in the poisoning of our communities and land and the genocide of our peoples, do affirm and adopt these Principles of Environmental Justice:

1) Environmental Justice affirms the sacredness of Mother Earth, ecological unity and the interdependence of all species, and the right to be free from ecological destruction.

2) Environmental Justice demands that public policy be based on mutual respect and justice for all peoples, free from any form of discrimination or bias.

3) Environmental Justice mandates the right to ethical, balanced and responsible uses of land and renewable resources in the interest of a sustainable planet for humans and other living things.

4) Environmental Justice calls for universal protection from nuclear testing, extraction, production and disposal of toxic/hazardous wastes and poisons and nuclear testing that threaten the fundamental right to clean air, land, water, and food.

5) Environmental Justice affirms the fundamental right to political, economic, cultural and environmental self-determination of all peoples.

6) Environmental Justice demands the cessation of the production of all toxins, hazardous wastes, and radioactive materials, and that all past and current producers be held strictly accountable to the people for detoxification and the containment at the point of production.

7) Environmental Justice demands the right to participate as equal partners at every level of decision-making, including needs assessment, planning, implementation, enforcement and evaluation.

8) Environmental Justice affirms the right of all workers to a safe and healthy work environment without being forced to choose between an unsafe livelihood and unemployment. It also affirms the right of those who work at home to be free from environmental hazards.

9) Environmental Justice protects the right of victims of environmental injustice to receive full compensation and reparations for damages as well as quality health care.

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10) Environmental Justice considers governmental acts of environmental injustice a violation of international law, the Universal Declaration on Human Rights, and the United Nations Convention on Genocide.

11) Environmental Justice must recognize a special legal and natural relationship of Native Peoples to the U.S. government through treaties, agreements, compacts, and covenants affirming sovereignty and self-determination.

12) Environmental Justice affirms the need for urban and rural ecological policies to clean up and rebuild our cities and rural areas in balance with nature, honoring the cultural integrity of all our communities, and provided fair access for all to the full range of resources.

13) Environmental Justice calls for the strict enforcement of principles of informed consent, and a halt to the testing of experimental reproductive and medical procedures and vaccinations on people of color.

14) Environmental Justice opposes the destructive operations of multi-national corporations.

15) Environmental Justice opposes military occupation, repression and exploitation of lands, peoples and cultures, and other life forms.

16) Environmental Justice calls for the education of present and future generations which emphasizes social and environmental issues, based on our experience and an appreciation of our diverse cultural perspectives.

17) Environmental Justice requires that we, as individuals, make personal and consumer choices to consume as little of Mother Earth's resources and to produce as little waste as possible; and make the conscious decision to challenge and reprioritize our lifestyles to ensure the health of the natural world for present and future generations.

The Proceedings to the First National People of Color Environmental Leadership Summit are available from the United Church of Christ Commission for Racial Justice, 475 Riverside Dr. Suite 1950, New York, NY 10115.

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Jemez Principles for Democratic Organizing Meeting hosted by Southwest Network for Environmental and Economic Justice (SNEEJ), Jemez, New Mexico, Dec. 1996

Activists meet on Globalization On December 6-8, 1996, forty people of color and European-American representatives met in Jemez, New Mexico, for the “Working Group Meeting on Globalization and Trade.” The Jemez meeting was hosted by the Southwest Network for Environmental and Economic Justice with the intention of hammering out common understandings between participants from different cultures, politics and organizations. The following “Jemez Principles” for democratic organizing were adopted by the participants.

#1 Be Inclusive If we hope to achieve just societies that include all people in decision-making and assure that all people have an equitable share of the wealth and the work of this world, then we must work to build that kind of inclusiveness into our own movement in order to develop alternative policies and institutions to the treaties policies under neoliberalism. This requires more than tokenism, it cannot be achieved without diversity at the planning table, in staffing, and in coordination. It may delay achievement of other important goals, it will require discussion, hard work, patience, and advance planning. It may involve conflict, but through this conflict, we can learn better ways of working together. It’s about building alternative institutions, movement building, and not compromising out in order to be accepted into the anti-globalization club.

#2 Emphasis on Bottom-Up Organizing To succeed, it is important to reach out into new constituencies, and to reach within all levels of leadership and membership base of the organizations that are already involved in our networks. We must be continually building and strengthening a base which provides our credibility, our strategies, mobilizations, leadership development, and the energy for the work we must do daily.

#3 Let People Speak for Themselves We must be sure that relevant voices of people directly affected are heard. Ways must be provided for spokespersons to represent and be responsible to the affected constituencies. It is important for organizations to clarify their roles, and who they represent, and to assure accountability within our structures.

#4 Work Together in Solidarity and Mutuality Groups working on similar issues with compatible visions should consciously act in solidarity, mutuality and support each other’s work. In the long run, a more significant step is to incorporate the goals and values of other groups with your own work, in order to build strong relationships. For instance, in the long run, it is more important that labor unions and community economic development projects include the issue of environmental sustainability in their own strategies, rather than just lending support to the environmental organizations. So, communications, strategies and resource sharing are critical, to help us see our connections and build on these.

#5 Build Just Relationships Among Ourselves We need to treat each other with justice and respect, both on an individual and an organizational level, in this country and across borders. Defining and developing “just relationships” will be a process that won’t happen overnight. It must include clarity about decision-making, sharing strategies, and resource distribution. There

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are clearly many skills necessary to succeed, and we need to determine the ways for those with different skills to coordinate and be accountable to one another.

#6 Commitment to Self-Transformation As we change societies, we must change from operating on the mode of individualism to community-centeredness. We must “walk our talk.” We must be the values that we say we’re struggling for and we must be justice, be peace, be community.

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National Environmental Justice Conference and Training Program

Leaders from various sectors will engage in 3 days of free exchange of ideas and approaches to achieving environmental justice. These interactive training sessions will feature voices of experience, research, discussions, and thought-provoking dialogue. The program format will feature the needs and challenges of communities, governments, municipalities, tribes, faith- based organizations, and others with an interest in environmental justice. It will highlight programs and collaborations that work, as well as initiatives that have not proven successful. Program speakers will feature representatives from Federal and state agencies, local governments, tribes, community groups, business and industry, public interest groups, academia, and other entities. This interactive forum will give conference participants the opportunity to network with a variety of interests from diverse quarters. All conference participants will realize informative and productive resources that can support their individual program goals and objectives. Conference participants will also see examples of approaches that produce positive results through innovation and collaboration. All in all, the conference will prove beneficial and informative to participants.

The 2018 National Environmental Justice Conference and Training Program will be held in Washington, D.C. April 25-27, 2018

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Inclusion of Citizen Science in Support of Environmental Health Decision-Making, U.S. Department of Health and Human Services, National Institutes of Health, Joseph Hughes, 12/05/2016

Additional Resources to Consider: Environmental Justice at the U.S. Environmental Protection Agency (USEPA) https://www.epa.gov/environmentaljustice

EJ Screen User’s Guide https://ejscreen.epa.gov/mapper/help/ejscreen_help.pdf

Launching the EJ Screening Tool https://www.epa.gov/ejscreen

CalEnviroScreen Version 3.0 https://oehha.ca.gov/calenviroscreen/report/calenviroscreen-30

Environmental Justice at Illinois Environmental Protection Agency (EPA) http://www.epa.illinois.gov/topics/environmental-justice/index

Illinois EPA EJ Start Mapping Tool

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http://illinois- epa.maps.arcgis.com/apps/webappviewer/index.html?id=f154845da68a4a3f837cd3b880b0233c

Illinois Commission on Environmental Justice http://www.epa.illinois.gov/topics/environmental-justice/commission/index

Illinois EJ Definitions http://www.epa.illinois.gov/Assets/iepa/environmental- justice/commission/resources/ejcommissionIPA2.pdf

Mohai, Paul, David Pellow, and J. Timmons Roberts. " Environmental Justice" Annual Review of Environment and Resources 34 (2009): 405-430. http://www.annualreviews.org/doi/10.1146/annurev-environ-082508-094348

Toxic Wastes and Race in the United States United Church of Christ. Commission for Racial Justice. Toxic Wastes and Race in the United States: A National Report on the Racial and Socio-Economic Characteristics of Communities with Hazardous Waste Sites. Public Data Access (1987) http://uccfiles.com/pdf/ToxicWastes&Race.pdf

Toxic Wastes and Race at Twenty Bullard, Robert D., Paul Mohai, Robin Saha, and Beverly Wright. "Toxic Wastes and Race at Twenty 1987–2007: Grassroots Struggles to Dismantle Environmental Racism in the United States." United Church of Christ Justice and Witness Ministries (2007). http://www.ucc.org/environmental-ministries_toxic-waste-20

Racial and Socioeconomic Disparities in Residential Proximity to Polluting Industrial Facilities Mohai, Paul, Paula M. Lantz, Jeffrey Morenoff, James S. House, and Richard P. Mero. "Racial and Socioeconomic Disparities in Residential Proximity to Polluting Industrial Facilities: Evidence from the Americans' Changing Lives Study." American Journal of Public Health 99, no. S3 (2009): S649-S656 http://ajph.aphapublications.org/doi/10.2105/AJPH.2007.131383

A Taxonomy of Environmental Justice Kuehn, Robert R. "A Taxonomy of Environmental Justice, 30 Envtl. L. Rep." Envtl. L. Inst 10, no. 10,684 (2000). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=628088

Universal Principles of Compensatory Mitigation, National Mitigation Banking Association http://www.agorarsc.org/wp-content/uploads/2015/08/Universal-Principles-of-Compensatory- Mitigation-by-NMBA.pdf

The Flint Water Crisis: Systemic Racism through the Lens of Flint Michigan Civil Rights Commission. "The Flint water crisis: Systemic racism through the lens of Flint." (2017). http://www.michigan.gov/documents/mdcr/VFlintCrisisRep-F-Edited3-13-17_554317_7.pdf

Flint Water Advisory Task Force Final Report Davis, Matthew M., Chris Kolb, Lawrence Reynolds, Eric Rothstein, and Ken Sikkema. "Flint Water Advisory Task Force Final Report." Office of Governor Rick Snyder (2016): 115.

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https://www.michigan.gov/documents/snyder/FWATF_FINAL_REPORT_21March2016_517805 _7.pdf

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Appendix C – Cumulative Effect Analysis The following information details methodology for adapting an environmental justice screening tool in the State. • The U.S. EPA’s EJ mapping tool, EJSCREEN, contains many data sources that mirror the indicators used by California. Combining state databases and federal databases provides the indicator set needed to implement the CalEnviroScreen standard. • Potential Methodology i. The methodology that CalEnviroScreen uses to identify census tracts as disadvantaged communities combines pollution burden and population characteristics. The overall score is calculated by combining the individual indicator scores within each of the two groups, then multiplying the Pollution Burden and Population Characteristics scores to produce a final score. Based on these final scores the census tracts across the State are ranked relative to one another. The text and models below explain how this method is used: 1. Each census tract receives scores for as many of the indicators as possible. Some census tracts will not have scores for every one of the indicators. 2. For each indicator, the scores are put in order from highest to lowest. This allows us to calculate a percentile for all areas that have a score. 3. The Population Characteristics score for a census tract is the average of the percentiles for all the Sensitive Populations indicators and Socioeconomic Factors indicators for that census tract. 4. The Pollution Burden score is the average of the percentile scores from Environmental Effects and Exposures indicators. 5. The Environmental Effects indicator percentiles are divided in half because we consider environmental effects to make a smaller contribution to pollution burden than exposures do. 6. To get the final score, multiply the Pollution Burden score by the Population Characteristics score. 7. Communities at the top 25% of final scores relative to the state’s range of scores qualify as disadvantaged. ii. For all statewide Michigan programs, the top 25% of scores should be considered Disadvantaged Communities (DACs) and targeted for resources. • Potential Approach for Defining Environmental Justice Communities i. The State should determine Environmental Justice Communities by analyzing data from Michigan Census tracts for the following environmental and demographic indicators, as described by the EJSCREEN and CalEnviroSreen Tools: Pollution Burden 1. Exposures a. Ozone Concentrations b. PM2.5 Concentrations c. Diesel PM Emissions d. Drinking Water Contaminants e. Pesticide Use f. Toxic Releases from Facilities g. Traffic Density 2. Environmental effects a. Cleanup Sites b. Groundwater Threats c. Hazardous Waste d. Impaired Water Bodies

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e. Solid Waste Sites and Facilities Population Characteristics 1. Sensitive populations a. Asthma Emergency Department Visits b. Low Birth Weight Infants c. Cardiovascular disease (emergency department visits for heart attacks) 2. Socio-economic indicators a. Educational Attainment b. Housing burdened low income households c. Linguistic Isolation d. Poverty e. Unemployment f. Minority Status Pollution Burden Indicators Readily Available from EJSCREEN a. National-Scale Air Toxics Assessment (NATA) air toxics cancer risk b. NATA respiratory hazard index c. NATA diesel PM d. Particulate matter e. Ozone f. Traffic proximity and volume g. Lead paint indicator h. Proximity to Risk Management Plan sites i. Proximity to Hazardous Waste Treatment, Storage and Disposal Facilities j. Proximity to National Priorities List sites k. Wastewater Dischargers Indicator Demographic indicators Readily Available from EJSCREEN: l. Percent Low-Income a. Percent Minority b. Less than high school education c. Linguistic isolation d. Individuals under age 5 e. Individuals over age 64 ii. The Agency should weight each factor using an approach adapted from CalEnviroScreen: Census tracts would be ranked for each environmental and demographic indicator, a resulting percentile score would be found for each tract, and the percentile scores would be averaged, resulting in an environmental and demographic score for each tract. The two averages would by multiplied together to determine a score.

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U-20471 Official Exhibits of Soulardarity Exhibit SOU-19 Page 1 of 3

Comments on MPSC Case No. U-18418 regarding Stakeholder Engagement in the Integrated Resource Planning Process Submitted Friday October 20th 2017

We, the undersigned, support the comments of the Sierra Club, Earthjustice, Union of Concerned Scientists, Natural Resources Defense Council, Ecology Center, 5Lakes Energy, Environmental Law and Policy Center, EcoWorks, National Housing Trust, Midwest Energy Efficiency Alliance, and NAACP in MPSC Case No. U-18418 regarding the proposed Integrated Resource Planning process. While we support the comment submitted thus far, we believe that more concrete recommendations regarding stakeholder engagement are required.

Soulardarity believes in energy democracy, the concept that people impacted by energy decisions should have a seat at the table in making them. Unfortunately, the history of energy decisions in Michigan epitomizes the well-known saying in our communities: if you aren’t at the table, you’re on the menu. It has been routinely proven that a combination of efficiency, energy storage, and distributed clean energy would provide more affordable and safe power, but the executives and shareholders who benefit from dirty energy continue to lobby for gas as a primary source of energy generation and to limit public input on these decisions. Meanwhile, Michigan communities struggling with energy poverty, the health impacts of pollution, and diminishing economic opportunity are kept in the dark and out of the conversation.

A dedicated transition to distributed clean energy and efficiency can improve grid reliability, community economic development, and reduce energy costs while creating sustainable employment for Michigan citizens. Without robust stakeholder engagement, we can expect an IRP process that will not take our communities into account. To reach a better future, Michigan citizens - and especially the environmental justice communities most harmed by the current energy system - need the opportunity to advocate for the energy future that we want.

Soulardarity 21 Highland St Highland Park, MI 48203 313.349.1063 ~ [email protected] U-20471 Official Exhibits of Soulardarity Exhibit SOU-19 Page 2 of 3

We believe that an Integrated Resource Planning process must involve robust stakeholder engagement, and that the comments thus far submitted do not go far enough in naming the specific ways this can be achieved. A strong stakeholder engagement process should: ❖ Have specific focus on demographics most impacted by energy decisions - particularly low-income communities, communities of color impacted by environmental racism, rural communities harmed by resource extraction and energy poverty, and other impacted communities. ❖ Provide education to stakeholders to understand how the IRP process works and how to make impactful comment by working through community organizations that work directly with impacted communities to ensure culturally appropriate and effective engagement. ❖ Provide multiple venues, times, and formats for engagement. Multiple sessions should be held directly in impacted communities and intended to reach working people, single parents, and others with high demands on their time and capacity. ❖ Be accessible. Translation services should be available based on community language needs, location should be easily accessible by public transportation, location should be vetted for disability access, and child care should be provided. ❖ Ensure that the input from these sessions is directly conveyed to the commission, rather than being synthesized by the utilities. ❖ Set goals for stakeholder engagement based upon actual participation, rather than just the opportunities provided for it. ❖ Clearly articulate how stakeholder input will impact the process and set binding requirements around that impact. ❖ Be ongoing. Communities should have multiple opportunities for input throughout the process, providing feedback and guidance as the IRP evolves.

We implore you to design an engagement process that gives Michigan people the opportunity to work together towards a better energy future.

Signed,

Jackson Koeppel, Executive Director On Behalf Of Soulardarity Soulardarity 21 Highland St Highland Park, MI 48203 313.349.1063 ~ [email protected] U-20471 Official Exhibits of Soulardarity Exhibit SOU-19 Page 3 of 3

MICHIGAN-BASED ORGANIZATIONAL SIGNERS

Michelle Martinez on behalf of Third Horizon Consulting Justin Schott on behalf of EcoWorks Gloria Lowe on behalf of We Want Green Too Kathryn Savoie on behalf of Ecology Center East Michigan Environmental Action William Copeland on behalf of Council Reverend Joan Ross on behalf of North End Woodward Community Coalition Aiko Fukuchi on behalf of Breathe Free Detroit Margaret Weber on behalf of Zero Waste Detroit

INDIVIDUAL SIGNERS

NAME ZIP CODE Shimekia Nichols 48205 Jackson Koeppel 48202 Jennifer Young 48220 Roslyn Ogburn 48228 Maria Thomas 48214 Gloria Lowe 48239 Furqan Khaldun 48188 Simone Sagovac 48209 Stephanie Edlinger 48212 Noah Purcell 48214 Robert Willis 48034

Soulardarity 21 Highland St Highland Park, MI 48203 313.349.1063 ~ [email protected] U-20471 Official Exhibits of Soulardarity Exhibit SOU-20 Page 1 of 7 STATE OF NEW YORK PUBLIC SERVICE COMMISSION

At a session of the Public Service Commission held in the City of Albany on January 8, 2015

COMMISSIONERS PRESENT:

Audrey Zibelman, Chair Patricia L. Acampora Garry A. Brown Gregg C. Sayre Diane X. Burman, dissenting in part and concurring in part

CASE 14-M-0565 – Proceeding on Motion of the Commission to Examine Programs to Address Energy Affordability for Low Income Utility Customers.

ORDER INSTITUTING PROCEEDING

(Issued and Effective January 9, 2015)

BY THE COMMISSION: INTRODUCTION AND BACKGROUND This Commission has long recognized that the "aid, care and support of the needy are public concerns…,"1 and for decades has provided low income assistance programs for the poor through local utilities.2 Because energy services are essential to the safety and well-being of all residents of the state, it is the State's and the Commission's policy that the "continued provision of gas, electric and steam service to residential customers without unreasonable qualifications or lengthy delays

1 New York State Constitution, Art. 17, Sec. 1.

2 In New York, customers who are eligible to participate in the Home Energy Assistance Program, i.e., those at or below 60% of state median income (SMI), are generally considered to be “low income.” U-20471 Official Exhibits of Soulardarity Exhibit SOU-20 Page 2 of 7 CASE 14-M-0565

is necessary for the preservation of the health and general welfare and is in the public interest."3 As a result, New York has a distinguished history of ensuring such protection for those who may face financial difficulties, and has approved low income affordability programs for every major gas and electric utility throughout New York. More than $128 million has been authorized annually for ratepayer-funded low income assistance programs, and more than one million energy consumers participate in those programs. These efforts recognize, among other things, that the utility and societal cost of leaving the economically disadvantaged without access to energy supplies can be much greater than the cost of maintaining access for these customers.4 The low income rate assistance programs typically have been developed, evaluated and modified as appropriate, in utility rate cases. As a result, there are substantial differences among these programs (See Appendix). These differences include: the amount of the discount, in dollar and percentage terms, provided to participating customers; the extent to which participation is open to customers who do not obtain HEAP benefits; and the extent of funding for arrears forgiveness or other targeted programs. Statewide, the dollar amount of energy utility customer arrears has trended up for several years. As of November 30, 2014, over 1.2 million residential electric and gas customers were more than 60 days in arrears, carrying more than

3 Public Service Law, §30, Home Energy Fair Practices Act (HEFPA).

4 The Commission is reviewing other aspects of services to low income consumers in other proceedings, including Case 14-M- 0101, Reforming the Energy Vision, and Case 12-M-0476, Retail Energy Markets. These efforts will continue.

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$756 million owed to utilities, and nearly 277,000 residential electric and gas customers statewide had service disconnected for non-payment during 2014. Energy utilities also wrote off nearly $195 million in uncollectible expense during that period. Low income customers experience a disproportionately high amount of arrears and service terminations for non-payment. Approximately 12% of utility customers participate in utility low income assistance programs, but they account for approximately 31% of the dollar value of residential arrearages, 22% of residential customers in arrears, and 21% of residential service terminations.5 This indicates that these customers are having difficulty paying their energy bills and maintaining utility service.

CONCLUSION Given the importance of ensuring that utility low income assistance programs continue to be consistent with our statutory and policy objectives, reflect best practices, and effectively improve energy affordability for low income households while efficiently using ratepayer funds, a proceeding is initiated to examine these programs, evaluate the effectiveness of current program designs, and identify improvements that are warranted. The primary purposes of this proceeding are to provide the opportunity to standardize utility low-income programs to reflect best practices where appropriate, streamline the regulatory process to conserve administrative resources, and ensure that these programs continue to be consistent with our statutory and policy objectives.

5 Percentage figures are based on data for calendar year 2014, through August.

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We expect a majority of the utilities to have rate cases pending before the Commission in 2015. While low income programs, in aggregate, account for less than 0.8% of utility revenues, a substantial amount of time is spent by the parties in rate cases litigating or negotiating settlement of low income program designs and funding levels. This proceeding is expected to assist the parties, especially low income advocates, in efficiently managing their finite resources. Accordingly, we direct Staff, in consultation with interested parties, to conduct an investigation of utility low income programs, to identify best practices, and develop a set of recommendations for how best to optimize the implementation of utility low income programs, for party comment. Such recommendations shall include a proposed process for incorporating the recommendations into ongoing rate cases before the Commission in 2015. It is our expectation that this will lead to adoption of a consistent, more uniform approach to the design and implementation of these programs; that will ultimately save parties the effort and expense devoted to litigating these issues in each utility rate case. Staff should proceed with deliberate speed in order to maximize our ability to inform pending and soon to be filed rate cases. Information and instructions related to becoming a party, subscribing to the service list, or otherwise monitoring the status of this proceeding can found on the Commission’s Web site at: http:// documents.dps.ny.gov/public/MatterManagement/RequestAPStatus. aspx.

The Commission orders: 1. A proceeding is instituted to examine programs to address energy affordability for low income residential utility customers.

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2. Staff is directed to conduct an investigation, in consultation with interested parties, as described in the body of this order, and within 90 days of the issuance of this order to file a report with the Secretary with recommendations concerning the design and implementation of energy utility low income rate affordability programs, for party comment and Commission consideration. 3. The Secretary may, in her sole discretion, extend the deadlines set forth in this Order. Any request for an extension must be in writing, must include a justification for the extension, and must be filed at least one day prior to the affected deadline. 4. This proceeding is continued. By the Commission,

(SIGNED) KATHLEEN H. BURGESS Secretary

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Central Hudson Con Edison KeySpan National Fuel Niagara Mohawk NYSEG Orange and RG&E Rockland Eligibility Utility HEAP Electric: Must reside in Utility HEAP Utility HEAP Must be HEAP Utility HEAP Must be HEAP recipients must receive 1- or 2-family recipients. recipients are eligible recipients eligible (auto- HEAP, SSI, home and auto-enrolled. (utility HEAP (auto- (utility HEAP enrolled). TANF, SNA, receive HEAP, recipients are enrolled) recipients are or SSI, TANF, auto- auto-enrolled) Food Stamps SNA, enrolled) Gas: same + Food Stamps, Medicaid Medicaid, CHP, (all auto- or Veteran’s enrolled) benefit (HEAP auto. enrolled) Bill $5.50 non-heat Electric - Non-heat $3 $12.50/mo.;bil Electric: Electric: Electric: Electric: Discount gas or $9.50/mo; discount, l discount for non-heat - non-heat - non-heat - non-heat - electric; Gas non-heat Heating $10.50 5 months. $5/mo, heat - $9.57/mo, heat $7/mo, $5/mo, heat - $11.00 single - $1.50/mo.; discount. LICAAP varies $15/mo; gas - - $18.57mo. heat - $15/mo. $24/mo. Gas: service non- Gas heat - Also, winter in amount $10.50/mo Gas: non-heat non-heat - heat gas or $0.4880/Th discount of ($170 – 40% of - $6.60/mo, Gas: $2/mo, heat - electric; 4 to 90 about 50% off total bill) heat - $13/mo $11.63/mo. $5.60/mo. $17.50 gas or block Th/mo, the second depending on electric heat; $7.25 rate block. household size $23.00 combo discount off LI: non-heat and income gas and bill per - $3.66/mo.; electric heat; month heat - $11.00 combo $11.26/mo + gas or electric $0.3622/Th(44% non-heat; ) up to 50 certain Th/mo. customers receive additional bill discount that varies ($50 - $225/mo.) depending on household size and income Arrears 1/24 of arrears None Up to $400 in 1/24 of Matching 1/24 of None 1/24 of Credits forgiven four equal arrears credit up to arrears arrears (note: all monthly payments over forgiven $30/mo forgiven forgiven are at 18 months monthly monthly (up to monthly (up to Company’s $1500) $1500) discretion) Other Energy One-time Financial and Energy Weatherization One-time One-time One-time Services conservation waiver of energy conservation deferral of 5% waiver of waiver of 50% waiver of education reconnection management education and (electric) or reconnection of reconnection fees education, referrals to 7.5% (gas or fees reconnection fees social service other income- elec. and gas) fees referrals and support case mgmt. programs

U-20471 Official Exhibits of Soulardarity Exhibit SOU-20 Page 7 of 7

CASE 14-M-0565

Commissioner Diane X. Burman, dissenting in part and concurring in part:

As reflected in my comments made at the public session on January 8, 2015, I dissent in part and concur in part.

U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 1 of 28

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Home About Us Prior Public Participation Hearings

Prior Public Participation Hearings and Certain Events

PG&E Request to Track Diablo Canyon Decommissioning Costs

We are holding public forums to provide an opportunity for residents and organizations in and near San Luis Obispo to comment on the utility's requests related to its Diablo Canyon Nuclear Power Plant.

• August 7, 2019: County Government Center, County Board of Supervisors Chamber, 1055 Monterey St., San Luis Obispo, CA 93408 ◦ 5 p.m.: Information Session ◦ 6 p.m.: Public Forum ◦ Webcast: www.adminmonitor.com/ca/cpuc; also available here: http://www.slocounty.ca.gov/Home/Meetings-Calendar.aspx?meetingType=4 U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 2 of 28

• August 8, 2019: County Government Center, County Board of Supervisors Chamber, 1055 Monterey St., San Luis Obispo, CA 93408 ◦ 10 a.m.: Information Hearing ◦ 11 a.m.: Public Forum ◦ Webcast: www.adminmonitor.com/ca/cpuc; also available here: http://www.slocounty.ca.gov/Home/Meetings-Calendar.aspx?meetingType=4

Media Advisory

CalPeco Rate Increase Requests

We are holding public forums to provide an opportunity for customers of Liberty Utilities (CalPeco Electric) to give their perspective and input to the CPUC regarding the utility's rate case request.

• July 24, 2019, 7 p.m.: North Tahoe Event Center - Timberline Suite, 8318 N. Lake Blvd., Kings Beach, CA 96143 ◦ Listen-only phone line: 877-988-5730, passcode: 8753051

• July 25, 2019, 7 p.m.: South Lake Tahoe City Hall - Council Chambers, 1901 Airport Rd., South Lake Tahoe, CA 96150 ◦ Live-stream: https://twitter.com/californiapuc

• July 26, 2019, 5 p.m.: Truckee Community Recreational Center - Meeting Room, 10981 Truckee Way, Truckee, CA 96161 ◦ Live-stream: https://twitter.com/californiapuc

Media Advisory

Ruling

Golden State Water's Bear Valley Electric Division's Requests

We are holding public forums to provide an opportunity for customers of Golden State Water Company's Bear Valley Electric Service Division to comment on the utility's requests.

• July 16, 2019, 6 p.m.: The Lodge at Big Bear Lake, 40650 Village Drive, Big Bear, CA 92315

Media Advisory

Convening: Preventing and Reducing Utility Disconnections

We are seeking ways to reduce natural gas and electric utilities from disconnecting consumers from service. Community organizations, utilities, and ratepayer advocates will present and there will be time for group discussion. Please join us. U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 3 of 28

• July 9, 2019, 9:30 a.m. - 5 p.m.: California State University, Monterey Bay @ Salinas, City Center, University Gallery 1, 1 Main St., Salinas, CA 93901; call-in number: 866-818-2671, participant code: 7031681

View our flyer

San Gabriel Valley Water Company Rate Increase Requests

We are holding public forums to provide an opportunity for customers of San Gabriel Valley Water Company to comment on the utility's request to increase rates.

• June 24, 2019, 6 p.m.: Fontana City Council Chambers, 8353 Sierra Ave., Fontana, CA 92335 • June 25, 2019, 6 p.m.: El Monte Community Center - Grace T. Black Auditorium, 3130 Tyler Ave., El Monte, CA 91731

Media Advisory

Cal-Am's Request to Purchase Bellflower Municipal Water System

We are holding a public forum to provide an opportunity for residents and organizations to provide their perspective and input to the CPUC about California-American Water Company's (Cal-Am) request for CPUC approval to purchase and operate the Bellflower Municipal Water System.

• May 29, 2019, 7 p.m.: Simms Park Auditorium, 16614 Clark Avenue, Bellflower, CA 90706

Read our Media Advisory Proceeding Documents

Customer Notice

Edison Grid Resiliency

Public Participation Hearings for consumers to give their perspective and input to the CPUC regarding Southern California Edison's request for CPUC approval to take certain actions to make its electric grid safer and more resilient.

• May 15, 2019, 7 p.m.: Rialto Community Center, Frances Brooks Conference Center, 214 N. Palm Ave., Rialto, CA 92376 • May 16, 2019, 7 p.m.: Oxnard Performing Arts Center, Ventura Room, 800 Hobson Way, Oxnard, CA 93030

Fact Sheet Media Advisory Proceeding Documents Customer Notice U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 4 of 28

CalWater's Rate Increase Request

California Water Service Company (CalWater) is seeking a rate increase of $50,673,500 (or 7.6 percent) in 2020; an additional increase on January 1, 2021 of $31,461,900 (or 4.4 percent), and an additional increase on January 1, 2022 of $33,000,700 (or 4.4 percent). The CPUC welcomes attendance and comment at these public forums (called Public Participation Hearings), as public comments will help the CPUC reach an informed decision:

• January 24, 2019, 6 p.m.: Dixon Council Chambers, 600 E. A St., Dixon • February 4, 2019, 7 p.m.: Palmdale Council Chambers, 38300 Sierra Highway, Palmdale • February 5, 2019, 6 p.m.: Bakersfield Council Chambers, 1600 Truxtun Ave., Bakersfield • February 6, 2019, 6 p.m.: Kernville Chamber of Commerce, 11447 Kernville Rd., Kernville • February 7, 2019, 6 p.m.: Selma Council Chambers, 1710 Tucker St., Selma • February 11, 2019, 6 p.m.: Alpine Senior Center, 3985 Country Club Dr., Lucerne • February 12, 2019, 6 p.m.: Butte County Association of Governments, Board Room, 326 Huss Dr., Chico • February 13, 2019, 6 p.m.: Willows Council Chambers, 201 N. Lassen St., Willows • February 14, 2019, 6 p.m.: 1200 Myers Street, Oroville, CA • February 19, 2019, 6 p.m.: Torrance Council Chambers, 3031 Torrance Blvd., Torrance • February 20, 2019, 7 p.m.: Montebello Council Chambers, 1600 W. Beverly Blvd., Montebello • February 25, 2019, 6 p.m.: Stockton State Building Auditorium, 31 E. Channel St., Stockton • March 5, 2019, 6 p.m.: San Carlos Public Library, Community Room, 610 Elm St., San Carlos

Customer Notice (Bakersfield Service Area)

Customer Notice (Chico Service Area)

Customer Notice (Dixon District)

Customer Notice (Dominguez Service Area)

Customer Notice (East Los Angeles Area)

Customer Notice (Hermosa Redondo Service Area)

Customer Notice (Kern River Valley District)

Customer Notice (Oroville Service Area)

Customer Notice (Selma Service Area)

Customer Notice (Visalia Service Area)

Customer Notice (Willow Service Area)

Customer Notice (Redwood Valley Service Area)

Customer Notice (Stockton Service Area)

Customer Notice (Bayshore Service Area)

Media Advisory U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 5 of 28

Proceeding Documents

Proposed San Jose Water Company and Connecticut Water Services Merger

We are holding a public forum for customers of San Jose Water Company (San Jose Water) to give their perspective and input to the CPUC regarding the investigation of the proposed merger by the water companies, as follows:

• January 31, 2019, 6 p.m.: San Jose City Hall - Rooms 118, 119 & 120, 200 E. Santa Clara Street, San Jose, CA 95113

Media Advisory

Customer Notice

Customer Notice (Spanish)

Ruling

Proceeding Documents

Proposed Sprint and T-Mobile Merger

We are holding three public forums for customers of Sprint and T-Mobile to give their perspective and input to the CPUC regarding the proposed merger by the telecommunications companies, as follows:

• January 15, 2019, 6 p.m.: Fresno City Hall Council Chambers, 2600 Fresno St., Fresno, CA 93721 • January 16, 2019, 7 p.m.: Junipero Serra State Building, Carmel Room (Auditorium), 320 W. 4th St., Los Angeles, CA 90013 • January 17, 2019, 6 p.m.: County Operations Center, Hearing Room, 5520 Overland Ave., San Diego, CA 92123

Media Advisory

Customer Notice

Proceeding Documents (A.18-07-011; 012)

Great Oaks Water Company's Rate Request

We are holding two public forums (called Public Participation Hearings) to receive comments about Great Oaks Water Company's request to increase rates for 2019, 2020, and 2021 (Application No. 18- 07-002): U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 6 of 28

• Thursday, November 29, 2018, 2 p.m. AND 7 p.m.: Santa Teresa Branch Library, 290 International Circle, San Jose, CA 95119

Read Great Oak's Customer Notice

Community Workshop: Reducing Utility Disconnections

We are seeking ways to reduce natural gas and electric utilities from disconnecting consumers from service. This workshop will discuss proposed policies and rules to reduce disconnections, and utilities and community organizations will make presentations. Time will be allocated to hear comment from the public from 6 p.m. - 7 p.m. Two workshops:

• Nov. 19, 2018, 3 p.m. - 7 p.m., UC Merced Center for Educational Partnerships, Inyo/Kern Room, 550 E. Shaw Ave., Fresno • Dec. 6, 2018, 9 a.m. - 4 p.m., San Joaquin Council of Governments, 555 E. Weber Ave., Stockton

We previously held a workshop in Riverside on Oct. 12, 2018. More Information

Read our Media Advisory

Workshop to Discuss the Accessibility of CPUC Proceedings

A workshop to brainstorm and discuss ideas for enhancing public participation and making CPUC proceedings more accessible.

• November 7, 2018, 1:30 p.m., Fresno County Board of Supervisors Chambers, Hall of Records, 2281 Tulare St., Third Floor, Fresno, CA 93721 ◦ Two-way call-in number 888-469-3084, passcode 93721 ◦ Webcast

More Information Read our Media Advisory

Public Forum on Increasing Access to Energy in the San Joaquin Valley

A forum (called a Public Participation Hearing) to hear from the public about the CPUC's efforts to increase access to affordable energy for disadvantaged communities in the San Joaquin Valley. The public is encouraged to attend to provide comment on proposed pilot projects in the communities of Allensworth, Alpaugh, California City, Cantua Creek, Ducor, Fairmead, Lanare, Le Grand, La Vina, Monterey Park Tract, Seville, and West Goshen. U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 7 of 28

• November 1, 2018, 6:15 p.m. - 8 p.m.: San Joaquin Valley Air Pollution Control Central Office, Governing Board Room, 1990 E. Gettysburg Ave., Fresno, with remote access at the San Joaquin Valley Air Pollution Control District Northern Office at 4800 Enterprise Way, Modesto, and the San Joaquin Valley Air Pollution Control District Southern Office at 34946 Flyover Ct., Bakersfield. Prior to the public forum, the CPUC will hold an All-Party Meeting from 4:45 p.m. - 6 p.m. for formal parties to the proceeding, and the public is welcome to join. • November 7, 2018, 6 p.m.: Tulare Council Chambers, 475 N. M St., Tulare, CA

Proceeding and Pilot Project Documents Read our Media Advisory

Public Forums on Pacific Power's Rate Increase Request

We are holding two public forums for customers of PacificCorp's Pacific Power to give their perspective and input about the utility's request to increase rates, as follows:

• October 29, 2018, 6 p.m.: City of Weed Council Chambers, 550 Main St., Weed, CA 96094 • October 30, 2018, 6 p.m.: Crescent City Cultural Center, 1001 Front St., Crescent City, CA 95531

Pacific Power's Customer Notice Read our Media Advisory Proceeding Documents

Public Forums on Apple Valley Ranchos Water and Park Water Rate Increase Requests

We are holding two public forums for customers of Liberty Utilities' Apple Valley Ranchos Water Corp. and Park Water Corp. to give their perspective and input to the CPUC regarding the requests by the utilities to increase rates, as follows:

• October 18, 2018, 1 p.m. AND 6 p.m.: Bellflower City Hall, 16600 Civic Center Dr., Bellflower, CA 90706 • October 25, 2018, 1 p.m. AND 6 p.m.: Apple Valley Conference Center, 14975 Dale Evans, Apple Valley, CA 92307

Media Advisory

Fact Sheet

Presentation Shown at Public Forum U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 8 of 28

Public Forum on Cost of Capital for Liberty Utilities, San Gabriel Valley Water, and Suburban Water

A public forum (called a Public Participation Hearing) for customers to give their perspective and input to the CPUC about requests to change the cost of capital for Liberty Utilities (Apply Valley Ranchos and Park Water), San Gabriel Valley Water (Los Angeles and Fontana service districts), and Suburban Water.

• Wednesday, October 10, 2018, 7 p.m.: Junipero Serra State Office Building, Carmel Room (Auditorium), 320 W. 4th St., Los Angeles, CA 90013

Media Advisory

Apple Valley Ranchos Customer Notice

Park Water Customer Notice

San Gabriel Valley Water Customer Notice

San Gabriel Valley Water Request to Increase Rates for its Cost of Capital Application (Los Angeles County Division)

Suburban Water Customer Notice

Proceeding Documents

Great Oaks Water Company's Cost of Capital

We are holding a public forum for customers of Great Oaks Water Company to give their perspective and input to the CPUC about the utility's request to decrease its Cost of Capital:

• Monday, August 27, 2018, 6 p.m.: San Jose State University, Dr. Martin Luther King Library, Room 225, 150 E. San Fernando Street, San Jose, CA 95112

Read our Media Advisory Read Great Oaks' Customer Notice

Cal-AM's Request to Purchase Fruitridge Vista Water

We are holding two public forums to provide an opportunity for residents and organizations to provide their perspective and input to the CPUC about California-American Water Company's (Cal-Am) request for CPUC approval to purchase and operate Fruitridge Vista Water Company:

• Monday, July 30, 2018, 6 p.m.: Fruitridge Community Center, 4000 Fruitridge Rd., Sacramento, CA, 95820 U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 9 of 28

• Tuesday, July 31, 2018, 6 p.m.: Fruitridge Community Center, 4000 Fruitridge Rd., Sacramento, CA 95820

Read our Media Advisory

View our Flyer

Read Cal-Am's Customer Notice

PG&E Rate Increase Requests

We are holding information sessions and public comment forums related to PG&E's request to increase rates and reallocate costs to its customers as part of its Gas Transmission and Storage (GT&S) Rate Case and its Gas Cost Allocation Proceeding, respectively:

• June 26, 2018: ◦ 1 p.m. AND 6 p.m. Information Sessions ◦ 2 p.m. AND 7 p.m. Public Comment Forums ◦ California Energy Commission, Hearing Room, 1516 9th St., Sacramento, CA 95814 ◦ View our flyer

• June 27, 2018: ◦ 1 p.m. AND 6 p.m. Information Sessions ◦ 2 p.m. AND 7 p.m. Public Comment Forums ◦ Fresno City Hall Council Chambers, 2600 Fresno St., Fresno, CA 93721 ◦ View our flyer

• June 28, 2018: ◦ 1 p.m. AND 5 p.m. Information Sessions ◦ 2 p.m. AND 6 p.m. Public Comment Forums ◦ Bakersfield City Hall Council Chambers, 1600 Truxtun Ave., Bakersfield, CA 93301 ◦ View our flyer

• July 10, 2018: ◦ 1 p.m. AND 6 p.m. Information Sessions ◦ 2 p.m. AND 7 p.m. Public Comment Forums ◦ Manzanita Place at Elks Lodge, Room 3, 1705 Manzanita Ave., Chico, CA 95926 ◦ View our flyer

• July 11, 2018: ◦ 1 p.m. AND 6 p.m. Information Sessions ◦ 2 p.m. AND 7 p.m. Public Comment Forums ◦ CPUC Auditorium, 505 Van Ness Ave., San Francisco, CA 94102 ◦ View our flyer U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 10 of 28

◦ View our webcasts of the 2 p.m. and 7 p.m. Public Forums

• July 16, 2018: ◦ 1 p.m. AND 6 p.m. Information Sessions ◦ 2 p.m. AND 7 p.m. Public Comment Forums ◦ Scottish Rite Center, 2455 Masonic Dr., San Jose, CA 95125 ◦ View our flyer

• July 17, 2018: ◦ 2 p.m. AND 7 p.m. Public Comment Forums ◦ Elihu M. Harris Building, Room 1, 1515 Clay St., Oakland, CA 94612 ◦ View our flyer

Information Sessions

At the information sessions prior to the public comment forums, there will be tables hosted by PG&E, the CPUC, and other groups participating in the proceeding. These groups are called "parties" to the proceeding, and they advocate for different perspectives, such as small businesses, agricultural customers, and residential customers. Attendees will be able to stop by each table and get information on the proceeding and ask questions.

Public Comment Forums

The public comment forums, called Public Participation Hearings, will begin with a brief overview of PG&E's rate increase request, and then public comments will be heard. The CPUC Administrative Law Judges assigned to these cases will preside over each public comment forum. The Administrative Law Judges are scheduled to write Proposed Decisions in these matters for CPUC Commissioners' consideration by the end of the year. The CPUC welcomes attendance and participation, as public comments help the CPUC reach an informed decision.

Read our Media Advisory

• Media Advisory in Spanish

PG&E's Customer Notice

• GT&S Fact Sheet for Sacramento ◦ GT&S Fact Sheet for Sacramento in Spanish

• GCAP Fact Sheet for Sacramento ◦ GCAP Fact Sheet for Sacramento in Spanish

• GT&S Fact Sheet for Fresno ◦ GT&S Fact Sheet for Fresno in Spanish U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 11 of 28

• GCAP Fact Sheet for Fresno ◦ GCAP Fact Sheet for Fresno in Spanish

• GT&S Fact Sheet for Bakersfield ◦ GT&S Fact Sheet for Bakersfield in Spanish

• GCAP Fact Sheet for Bakersfield ◦ GCAP Fact Sheet for Bakersfield in Spanish

• GT&S Fact Sheet for Chico ◦ GT&S Fact Sheet for Chico in Spanish

• GCAP Fact Sheet for Chico ◦ GCAP Fact Sheet for Chico in Spanish

• GT&S Fact Sheet for San Francisco ◦ GT&S Fact Sheet for San Francisco in Spanish

• GCAP Fact Sheet for San Francisco ◦ GCAP Fact Sheet for San Francisco in Spanish

• GT&S Fact Sheet for San Jose ◦ GT&S Fact Sheet for San Jose in Spanish

• GCAP Fact Sheet for San Jose ◦ GCAP Fact Sheet for San Jose in Spanish

• GT&S Fact Sheet for Oakland ◦ GT&S Fact Sheet for Oakland in Spanish

• GCAP Fact Sheet for Oakland ◦ GCAP Fact Sheet for Oakland in Spanish

• Gas Cost Allocation Fact Sheet ◦ Fact Sheet in Spanish

More information on PG&E's GT&S and GCAP proceedings

Watch our video on the public forums and information sessions on YouTube U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 12 of 28

Workshop: Consumer Protections for Rooftop Solar Customers

The CPUC is developing improved consumer protection programs for Californians who use the Net Energy Metering (NEM) program to go solar. This public forum is an opportunity to share community concerns, learn about current consumers protections, and identify ways to improve protections. We have invited other state agencies with authority over various parts of the solar industry to share their progress in protecting solar consumers and discuss solutions for customers who currently have concerns with their solar systems. Please join us! Spanish/English interpretation provided.

• July 10, 2018: ◦ 5:30 p.m. ◦ John Palacios Community Center, 16846 4th St., Huron, CA 93234

Proceeding information (R. 14-07-002) View our flyer in English and Spanish

SoCalGas and SDG&E Rate Case

We are holding several public forums and Information Sessions to provide an opportunity for customers of Southern California Gas Company (SoCalGas) and San Diego Gas & Electric (SDG&E) to give their perspective and input to the CPUC about the request of the utilities to increase rates in 2019-2022. The forums and Information Sessions will take place as follows:

SoCalGas

• May 29, 2018, 2 p.m. AND 7 p.m.: ◦ Visalia Convention Center, Charter Oak Ballroom A, 303 E. Acequia Ave., Visalia, CA 93291 • June 12, 2018, 2 p.m. AND 7 p.m.: ◦ Holiday Inn Palmdale, 38630 Fifth St. West, Palmdale, CA 93551

• June 14, 2018: ◦ 2 p.m. AND 7 p.m. Public Forums ◦ 1 p.m. AND 6 p.m. Information Sessions ◦ Oxnard Performing Arts and Convention Center Ventura Room, 800 Hobson Way, Oxnard, CA 93030

• June 19, 2018: ◦ 2 p.m. AND 7 p.m. Public Forums ◦ 1 p.m. AND 6 p.m. Information Sessions ◦ Inglewood City Hall Community Room, 1 Manchester Blvd., Inglewood, CA 90301

• June 20, 2018, 2 p.m. AND 7 p.m.: ◦ Long Beach Marriott, 4700 Airport Plaza Dr., Long Beach, CA 90815 U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 13 of 28

• June 21, 2018: ◦ 2 p.m. AND 7 p.m. Public Forums ◦ 1 p.m. AND 6 p.m. Information Sessions ◦ Board of Supervisors Board Chambers, 4080 Lemon St., Riverside, CA 92501

SDG&E • June 13, 2018: ◦ 2 p.m. AND 7 p.m. Public Forums ◦ 1 p.m. AND 6 p.m. Information Sessions ◦ El Cajon City Hall Council Chambers, 200 Civic Center Way, El Cajon, CA 92020

• June 26, 2018: ◦ 2 p.m. AND 7 p.m. Public Forums ◦ 1 p.m. AND 6 p.m. Information Sessions ◦ California Center for the Arts, Salon 3, 340 N. Escondido Blvd., Escondido, CA 92025

• June 28, 2018: ◦ 2 p.m. AND 7 p.m. Public Forums ◦ 1 p.m. AND 6 p.m. Information Sessions ◦ Chula Vista City Hall Council Chambers, 276 Fourth Ave., Chula Vista, CA 91910

Public Forums

The public forums will begin with a brief presentation on the proceeding and an overview of the rate increase request of the utility, and then public comments will be heard. The CPUC Administrative Law Judge assigned to the SoCalGas and SDG&E rate cases will preside over each public forum, called a Public Participation Hearing. The Administrative Law Judge is scheduled to write a proposed decision in the matter for CPUC Commissioner consideration by the end of the year. The CPUC welcomes attendance, as public comments help the CPUC reach an informed decision.

Information Sessions

As noted above, there will be Information Sessions in advance of certain public forums. There will be informational tables hosted by the utility, the CPUC, and other groups participating in the proceeding (these groups are called "parties" to the proceeding, and they advocate for different perspectives, such as small businesses, agricultural customers, and residential customers). Attendees will be able to stop by each table and get information on the proceeding and ask questions. The CPUC has also asked SoCalGas and SDG&E to provide customer service staff for customers to ask questions about their bills.

• Media Advisory • SoCalGas Customer Notice • Fact Sheet on SoCalGas Request ◦ Fact Sheet on SoCalGas Request in Spanish

• Fact Sheet on SDG&E Request ◦ Fact Sheet on SDG&E Request in Spanish U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 14 of 28

• SDG&E Customer Notice • Watch our Video about the Public Forums on YouTube ◦ Watch the Video in Spanish

• Watch our Video about General Rate Cases on YouTube • Proceeding Documents for SoCalGas (A.17-10-008) • Proceeding Documents for SDG&E (A.17-10-007)

Foresthill Telephone Rates

We are holding a public forum to provide an opportunity for customers of Foresthill Telephone Company (a Sebastian company) to comment on the utility's request to increase rates, among other things.

• June 14, 2018, 6 p.m.: Forest Hill Memorial Hall, 24601 Harrison St., Foresthill, CA 95631 • Read our media advisory • Read Foresthill's Customer Notice • View our flyer • Read the Ruling Setting the Public Participation Hearing • Proceeding Documents

San Joaquin Valley Community Energy Option Assessment Workshops

The CPUC will hold a series of public workshops to receive community input on energy options to improve affordable access to energy for the disadvantaged communities in the San Joaquin Valley that have limited access to natural gas, as follows:

• May 7, 2018, 6 p.m. - Le Grand ◦ Le Grand Elementary, 13071 E. Le Grand Rd., Le Grand, CA 95333 ◦ (Merced County)

• May 8, 2018, 6 p.m. - De La Vina ◦ Casas de La Vina, 23784 Ave 9, Madera, CA 93637 ◦ (Madera County)

• May 15, 2018, 6 p.m. - Allensworth ◦ Allensworth Elementary School Cafeteria, 3320 Young Rd., Earlimart, CA 93219 ◦ (Tulare County)

• May 16, 2018, 6 p.m. - Seville U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 15 of 28

◦ Stone Coral Elementary School Cafeteria, 15590 Ave 383, Visalia, CA 93292 ◦ (Tulare County)

• May 17, 2018, 6 p.m. - Lanare ◦ Lanare Community Center, 20620 S. Grantland Ave., Riverdale, CA 93656 ◦ (Fresno County)

• May 21, 2018, 6 p.m. - Fairmead ◦ Galilee Missionary Baptist Church, 22491 Fairmead Blvd, Chowchilla, CA 93610 ◦ (Madera County)

• May 22, 2018, 6 p.m. - Cantua Creek ◦ Cantua Creek Elementary Cafeteria, 29288 W. Clarkson, Cantua Creek, CA 93608 ◦ (Fresno County)

• May 23, 2018, 6 p.m. - California City ◦ Central Park, Strata Center, 10350 Heather Ave., California City, CA 93505 ◦ (Kern County)

• June 4, 2018, 6 p.m. - Alpaugh ◦ Alpaugh School Cafeteria, 5313 Road 39, Alpaugh, CA 93201 ◦ (Tulare County)

• June 5, 2018, 6 p.m. - West Goshen ◦ 4943 Ave. 309, Visalia, CA 93291 ◦ (Tulare County)

• June 6, 2018, 6 p.m. - Ducor ◦ Ducor Union Elementary School Cafeteria, 23761 Ave 56, Ducor, CA 93218 ◦ (Tulare County)

• TBD, 6 p.m. - Monterey Park Tract ◦ Monterey Park Tract Community Center, 7655 Foy Ave, Ceres, CA 95307 ◦ (Stanislaus County)

• More Information • Read our media advisory • In Spanish

Public Forum on Proposed Pacific Power (PacifiCorp) Substation

A public forum to provide an opportunity for customers of Pacific Power (PacifiCorp) to give their perspective and input to the CPUC about the utility's request to construct the Lassen Substation as a replacement to the existing Mt. Shasta Substation: U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 16 of 28

• June 8, 2018, 4:30 p.m.: Mount Shasta Resort, Siskiyou Room, 1000 Siskiyou Lake Blvd., Mount Shasta, CA 96067 • Read our Media Advisory • Pacific Power's Customer Notice • Documents related to the proceeding

Public Forum on San Jose Water Company Rate Increase Request

A Public Participation Hearing that will begin with a brief presentation on the proceeding and an overview of San Jose Water Company's rate request; then public comments will be heard. Beginning at 6 p.m., representatives from the CPUC and others will be available in the lobby to provide information about the proceeding and answer questions. The forum begins at 6:30 p.m.

• May 30, 2018, 6:30 p.m. San Jose City Council Chambers, 200 E. Santa Clara St., San Jose, CA 95113 • Read our Media Advisory ◦ Media Advisory in Spanish

• Fact Sheet ◦ Fact Sheet in Spanish

• Watch our Video about General Rate Cases on YouTube • Read San Jose Water Company's Customer Notice

Public Forum on Utility Poles

A Public Participation Hearing to bring awareness to residents and solicit their input about utility pole safety issues. Prior to the Public Participation Hearing, the public is invited to join former CPUC Commissioner Catherine J.K. Sandoval for a tour of utility poles in the San Jose area. The tour will start at noon on May 21 at the Willow Glen Community & Senior Center, 2175 Lincoln Ave., San Jose, CA 95125.

• May 21, 2018, 5 p.m. Isaac Newton Senter Auditorium, 70 W. Hedding St., San Jose, CA 95110 • Read our Media Advisory • View our flyer

Public Forum on Utility Poles:

The CPUC is holding this public forum to bring awareness to residents and solicit their input about utility pole safety issues. Poorly maintained poles and attached electric and communication wires have tragically caused substantial property damage from fires and loss of life in California. The CPUC is tasked with ensuring the safety of all poles in California and has opened an investigation to consider the creation of a pole census to better manage pole conditions (proceeding number I.17-06-027). The census would allow pole owners and companies that attach their communication and electric wires to U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 17 of 28

poles to share pole information and for the CPUC to better ensure pole safety. The CPUC welcomes attendance at this forum, as public comments help the CPUC reach an informed decision, as follows:

• May 9, 2018, 5 p.m.: San Bernardino County Board of Supervisors Building, Board Chambers, 385 N. Arrowhead Ave., San Bernardino, CA 92415 • Read our media advisory • View our flyer

San Onofre Nuclear Generating Station Public Participation Hearing:

A public forum to provide an opportunity for residents and organizations to provide their perspective and input to the CPUC about the proposed settlement agreement in the CPUC's San Onofre Nuclear Generating Station proceeding.

• May 2, 2018, 6 p.m.: Sea Country Senior and Community Center Grand Ballroom, 24602 Aliso Creek Rd., Laguna Niguel, CA 92677 • Read our media advisory • SDG&E Notice of Public Participation Hearing • Edison Notice of Public Participation Hearing

Ducor Telephone Company's Request to Increase Rates: Two public forums to provide an opportunity for residents and organizations to provide their perspective and input to the CPUC about Ducor Telephone Company's request to increase rates, as follows: • March 26, 2018, 5 p.m. ◦ Ducor Union Elementary School Cafeteria, 23761 Avenue 56, Ducor, CA 93218

• April 2, 2018, 5 p.m. ◦ Rancho Tehama Association, Recreation Hall, 17605 Park Terrace Rd., Corning, CA 96021

Read our Media Advisory

Read Ducor Telephone's Customer Notice for March 26 Forum

Read Ducor Telephone's Customer Notice for April 2 Forum

Read our Flyer

• Spanish Flyer

Documents related to the proceeding

Edison's Phase 2 General Rate Case: Public forums to provide an opportunity for customers of Southern California Edison to offer their perspective and input to the CPUC about the company's rate request, as follows:

• March 19, 2018, 2 p.m. AND 7 p.m. U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 18 of 28

◦ Port of Long Beach-Board Room, 4801 Airport Plaza Dr., Long Beach, CA 90815 ◦ View our Flyer

• March 20, 2018, 2 p.m. AND 7 p.m. ◦ Taylor Reception Hall, 1775 N. Indian Blvd., Claremont, CA 91711 ◦ View our Flyer

• March 21, 2018, 2 p.m. AND 7 p.m. ◦ 15556 Summit Ave., Fontana, CA 92336 ◦ View our Flyer

• March 26, 2018, 2 p.m. AND 6 p.m. ◦ 303 E. Acequia Ave., Visalia, CA 93291 ◦ View our Flyer

Read our media advisory

Visit our YouTube channel to watch our short video explaining this proceeding

Edison's Public Participation Hearing Notice

March 2018: Public Workshops on Implementation of the Internet for All Now Act

February 12, 2018, 6 p.m., Golden State Water's Calipatria/Region 3 Rates: An opportunity for customers of Golden State Water Company to provide their perspective and input to the CPUC about the company's rate request. Calipatria City Hall Council Chambers, 125 North Park, Calipatria, CA 92233.

• Media Advisory • Flyer • Customer Notice (includes Spanish Notice)

February 6, 2018, 6 p.m., Golden State Water's Santa Maria Rates: An opportunity for customers of Golden State Water Company to provide their perspective and input to the CPUC about the company's rate request. Santa Maria Public Library, Shepherd Hall, 421 S. McClelland St., Santa Maria, CA 93454.

• Media Advisory • Flyer • Customer Notice ◦ Spanish Notice U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 19 of 28

February 1, 2018, 7 p.m., Golden State Water's Huntington Park/Region 2 Rates: An opportunity for customers of Golden State Water Company to provide their perspective and input to the CPUC about the company's rate request. Carmel Room (Auditorium), 320 W. 4th St., Los Angeles, CA 90013.

• Media Advisory • Flyer

January 31, 2018, 1 p.m. AND 7 p.m., Golden State Water's Foothill Rates: An opportunity for customers of Golden State Water Company to provide their perspective and input to the CPUC about the company's rate request. Taylor Reception Hall, 1775 N. Indian Hill Blvd., Claremont, CA 91711.

• Media Advisory • Flyer • Customer Notice

January 29, 2018, 6 p.m., Golden State Water's Arden Cordova Rates: An opportunity for customers of Golden State Water Company to provide their perspective and input to the CPUC about the company's rate request. Rancho Cordova City Hall, Council Chambers, 2729 Prospect Park Dr., Rancho Cordova, CA 95670.

• Media Advisory • Flyer • Customer Notice

The CPUC has scheduled Public Participation Hearings for the public to provide their perspective and input to the CPUC about the rate increase requests of San Jose Water Company, Golden State Water Company, California-American Water Company, and California Water Service Company, as follows:

• Monday, Oct. 30, 2017, 6 p.m.: Junipero Serra State Office Building, Carmel Room/Auditorium, 320 W. 4th St., Los Angeles, CA 90013 • Wednesday, Nov. 1, 2017, 6 p.m.: Hilltop Park Center, Main Hall, 871 Jessie St., Monterey, CA 93940 • Monday, Nov. 6, 2017, 7:30 p.m.: City Hall of San Jose City Council Chambers, 200 E. Santa Clara St., San Jose, CA 95113 • Thursday, Dec. 7, 2017, 6 p.m.: Holiday Inn Resort, Timbers Conference Room, 40650 Village Dr., Big Bear Lake, CA 92315

More information

PG&E Request to Retire Diablo Canyon (A.16-08-006)

Public Participation Hearings to provide an opportunity for residents and organizations in the San Luis Obispo area to provide their perspective and input to the CPUC about Pacific Gas and Electric Company’s (PG&E) request to retire its Diablo Canyon Power Plant. U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 20 of 28

● September 14, 2017, 1:30 p.m. AND 7 p.m.: Ludwick Community Center, Assembly Room, 864 Santa Rosa St., San Luis Obispo, CA 93401

PG&E General Rate Case Phase II (A.16-03-013)

The CPUC will hold Public Participation Hearings to provide an opportunity for the public to comment about the second phase of PG&E's 2017 General Rate Case (GRC). The purpose of Phase II of the GRC is to determine the cost each customer class is responsible for and to determine the rate schedules for each customer class. This application proposes an increase of $0.5 million in annual revenues related to previously incurred rate development costs. The application also proposes to assign already authorized revenues to its customers and adjust rate design.

● July 27, 2017, 2 p.m. & 7 p.m.: Elihu M Harris Building, Room 1, 1515 Clay Street, Oakland, CA 94612

● August 14, 2017, 2 p.m. & 6 p.m.: Bakersfield City Council Chamber, 1600 Truxtun Avenue, Bakersfield, CA 9330

● August 15, 2017, 2 p.m. & 6 p.m.: 31 E. Channel Street, Auditorium, Stockton, CA. 95202

Read the bill notice

Read our media advisory

View our Oakland Flyer

View our Bakersfield Flyer

View our Stockton Flyer

Suburban Water Systems Public Participation Hearings

The CPUC will hold Public Participation Hearings to provide an opportunity for the public to comment on the request of Suburban Water Systems for CPUC approval to raise rates $11,020,932 (or 15.25 percent) in 2018, an additional $6,148,017 (or 7.38 percent) in 2019, and an additional $5,543,562 (or 6.20 percent) in 2020, for a total of $22,712,511 (or 31.43 percent) for all three years combined.

● June 26, 2017, 6 p.m.: Residence Inn by Marriot, Conference Center, 14419 Firestone Blvd., La Mirada, CA 90638

● June 27, 2017, 6 p.m.: Shadow Oak Community Center, Main Hall, 2121 E. Shadow Oak Dr., West Covina, CA 91790

Read the bill notice

Read our media advisory

Calaveras Telephone Company's Rate Case (A.16-10-002) U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 21 of 28

The CPUC is holding a public participation hearing (PPH) in the rate case of Calaveras Telephone Company. The date, time, and location of the PPH are listed below. Calaveras' application proposes to increase basic residential rates in both the Copperopolis and Jenny Lind exchanges to $22.50, not including any surcharges, fees, or taxes. Calaveras also proposes to increase its basic business rate to $26.00, not including any surcharges, fees, or taxes.

• May 26, 2017, 5:30 p.m. : Copperopolis Elementary Gym/Multipurpose Room - 217 School St., Copperopolis, CA 95228 • View Calaveras' Notice of the PPH • View our Flyer

Southern California Edison's Rate Case (A.16-09-001)

The CPUC is holding public participation hearings (PPHs) in the rate case of Southern California Edison. The dates, times, and locations of the PPHs are listed below. Southern California Edison's application proposes to increase rates and revenue by $222 million by January 2018, an additional increase of $533 million in 2019, and $570 million in 2020.

• May 9, 2017, 2:00 p.m. & 7:00 p.m.: Fontana Jessie Turner Health & Fitness Community Center - 15556 Summit Ave., Fontana, CA 92336 • May 10, 2017, 2:00 p.m. & 7:00 p.m.: Lancaster City Hall Council Chambers - 44933 N. Fern Avenue, Lancaster, CA 93534 • May 16, 2017, 2:00 p.m. & 7:00 p.m.: Azusa Azusa Memorial Park Recreation Center, 320 N. Orange Place, Azusa, CA 91702 • May 17, 2017, 2:00 p.m.: Long Beach Port of Long Beach - 4801 Airport Plaza Drive City of Long Beach, CA 90815 • May 17, 2017, 6:00 p.m.: South Gate City of Southgate Council Chambers - 8650 California Avenue, South Gate, CA 90280 • May 18, 2017, 2:00 p.m. & 7:00 p.m.: Santa Ana Delhi Community Center - 505 E. Central Ave, Santa Ana, CA 92707 • View Edison's Notice of the PPHs • View the media advisory

Proceeding to Consider Future of Aliso Canyon Natural Gas Storage Facility (I.17-02-002)

This Public Participation Hearing is an opportunity for local residents and organizations to provide their perspective and input to the CPUC regarding the proposed scope and schedule for this proceeding. The purpose of the proceeding is to examine the long-term viability of the Aliso Canyon gas storage facility. The scope of the proceeding does not include the immediate question of whether the facility should be reopened for injection in 2017, but rather the long-term feasibility of minimizing or eliminating the use of the facility while still maintaining energy and electric reliability for the Los Angeles region, consistent with maintaining just and reasonable rates. U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 22 of 28

● Monday, April 17, 2017, 6 p.m., Northridge Woman’s Club, 18401 Lassen St., Northridge, CA 91325 ● Read our media advisory

Cal-Ore Telephone Company's Rate Case (A.16-10-004)

Public participation hearing in the rate case of Cal-Ore Telephone. Cal-Ore proposes to set its residential basic rates at $21.63, not including the surcharges and fees that the FCC uses to set the Access Recovery Charge ("ARC") benchmark. The residential basic rates, inclusive of state and federal fees and surcharges, would be set at approximately $30.00, based on Cal-Ore's all-inclusive rate calculation at the time of the application. Cal-Ore also proposes to increase its basic business rate to $28.00, not including surcharges and fees.

• April 20, 2017, 6 p.m.: Butte Valley Community Center - 52900 US-97, Dorris, CA 96023 • View the customer notice • Read our media advisory

Ponderosa Telephone Company's Rate Case (A.16-10-001)

Public participation hearing in the rate case of Ponderosa Telephone. Ponderosa proposes to update its revenue requirement to $13,993,453. In Ponderosa’s last rate case, the CPUC approved a revenue requirement of $15,408,670. If Ponderosa’s rate request is approved by the CPUC, the residential basic rates would be set at approximately $32.37 in all exchanges, (including state and federal fees and surcharges), and the basic business rate would be set at $34.15 (not including surcharges and fees).

• March 27, 2017, 5 p.m.: North Fork Rancheria Community Center, 56901 Kunugib, North Fork, CA 93643 • View the media advisory • View the flyer

Sierra Telephone Company's Rate Case (A.16-10-003) Public Participation Hearing in the rate case of Sierra Telephone Company. Sierra proposes to update its revenue requirement to $28,937,006. In Sierra’s last rate case, the CPUC approved a revenue requirement of $29,970,934. If Sierra Telephone’s rate request is approved by the CPUC, the residential basic rates would be set at approximately $32.37 (including state and federal fees and surcharges), and the basic business rate would be set at $33 (not including surcharges and fees).

• February 17, 2017, 5:30 p.m.: Oakhurst Community Center Pavilion, 39800 Road - 425B (Fresno Flats Road), Oakhurst, CA 93644 • View the media advisory • View Sierra's Hearing Notice • View the flyer U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 23 of 28

Cal-Am Water Rate Increase Request (A.16-07-002)

We are holding a series of public meetings to hear directly from consumers about California-American Water Company’s request for CPUC approval to increase its revenues by $34,559,200 (16.29 percent) in 2018, by $8,478,500 (3.43 percent) in 2019, and by $7,742,600 (3.03 percent) in 2020.

• Sacramento District ◦ December 7, 2016, 1 p.m. AND 6 p.m.: City of Rancho Cordova Council Chambers, 2729 Prospect Park Dr., Rancho Cordova ◦ View the Notice

• Larkfield District ◦ January 10, 2017, 6 p.m.: Mark West Elementary Campus, Multi-Purpose Room, 4600 Lavell Rd., Santa Rosa

• Ventura County District ◦ January 17, 2017, 6 p.m.: Palm Garden Hotel – Palm I, 495 North Ventu Park Rd., Thousand Oaks

• Los Angeles County District ◦ January 18, 2017, 6 p.m.: Courtyard Marriott Hotel – Salon B, 700 W. Huntington Dr., Monrovia

• Monterey County District ◦ January 24, 2017, 1:30 p.m. AND 6 p.m.: Oldemeyer Center – Laguna Grande Hall, 986 Hilby Ave., Seaside ◦ January 25, 2017, 6 p.m.: Chualar Union Elementary School – Board Room, 24285 Lincoln St., Chualar ◾ View the Notice ◾ View the Spanish Notice

• San Diego County District ◦ February 9, 2017, 6 p.m.: City of Imperial Beach – Community Room, 825 Imperial Beach Blvd., Imperial Beach ◦ View the Notice

Ruling setting the Sacramento and Larkfield Districts Hearings

Ruling setting the Ventura, Los Angeles, Monterey, and San Diego Districts Hearings

SDG&E’s Wildfire Cost Recovery Request(A.15-09-010)

We are holding Public Participation Hearings to hear directly from consumers about San Diego Gas & Electric’s request to recover $379 million in costs it says are related to the Witch, Guejito, and Rice U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 24 of 28

wildfires that occurred in SDG&E’s service territory in October 2007. The CPUC’s Public Participation Hearings will allow the public to comment on whether SDG&E’s operation and management of its facilities prior to the 2007 Wildfires were reasonable. Prior CPUC decisions indicate that a reasonableness standard should entail a review on the prudency of SDG&E’s actions leading up to the fire.

• When: January 9, 2017, 2 p.m. AND 7 p.m. • Where:California Center for the Arts, Conference Center – Salon 1 Room, 340 N. Escondido Blvd., Escondido, CA 92025 • Viewthe CPUC’s Media Advisory for more information • View SDG&E’s Hearing Notice

PG&E Request to Close Diablo Canyon

• Oct. 20, 2016, 1:30 p.m. AND 7 p.m.: San Luis Obispo Botanical Garden in El Chorro Regional Park, Oak Glen Pavilion Room, 450 Dairy Creek Rd., San Luis Obispo

California Water Service Company’s Request to IncreaseRates:

• Aug. 25, 2016, 1 p.m. AND 6 p.m.: Lucerne Alpine Senior Center, Barnes Hall Room, 3985 Country Club Dr., Lucerne • Sept. 6, 2016. 6 p.m.: Quiet Cannon Conference & Event Center, Sunset Room, 901 Via San Clemente, Montebello ◦ View the Notice ◦ View the Notice in Spanish

• Sept. 7, 2016, 6 p.m.: Village Homes Clubhouse, 1040 Evenstar Ave., Westlake Village ◦ View the Notice

• Sept. 8, 2016, 6 p.m.: Visalia Convention Center, King Canyon Room, 303 East Acequia Ave., Visalia ◦ View the Notice ◦ View the Notice in Spanish ◦ View the Notice for Salinas Service Area ◦ View the Notice for Salinas Service Area in Spanish

• Sept. 14, 2016, 6 p.m.: City of King City Council Chambers, 212 South Vanderhurst Ave., King City ◦ View the Notice ◦ View the Notice in Spanish ◦ View the Notice for Selma Service Area ◦ View the Notice for Selma Service Area in Spanish

• Oct. 4, 2016, 6 p.m.: San Carlos Library, Community Room A, 610 Elm St., 2nd Floor, San Carlos ◦ View the Notice ◦ View the Flyer U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 25 of 28

California LifeLine Program Proposed Changes:

• Aug. 25, 2016, 3 p.m.: Lucerne Alpine Senior Center , Barnes Hall Room, 3985 Country Club Dr., Lucerne • Sept. 6, 2016. 3 p.m.: Quiet Cannon Conference & Event Center, Sunset Room, 901 Via San Clemente, Montebello • Sept. 14, 2016. 3 p.m.: City of King City Council Chambers, 212 South Vanderhurst Ave., King City • Sept. 20, 2016, 5 p.m.: Civic Auditorium, 307 Church St., Santa Cruz

California-American Water Company’s Proposed Monterey Peninsula Water Supply Project:

• Sept. 1, 2016, 9 a.m. - 1 p.m.: Sunset Center, Carpenter Hall, San Carlos St. at Ninth Ave., Carmel-by-the-Sea • View our Flyer

Intrastate Rural Call Completion Issues:

• Sept. 8, 2016, 2:30 p.m.: Visalia Convention Center, Kings Canyon Room,303 E. Acequia Ave., Visalia • Sept. 9, 2016, 5 p.m.: Twin Pine Casino & Hotel Event Center, 22223 Highway CA-29, Middletown • Sept. 20, 2016, 4 p.m.: Civic Auditorium, 307 Church St., Santa Cruz

San Diego Gas & Electric Company’s Request to Increase Rates:

• Sept. 14, 2016, 1 p.m. AND 6 p.m.: Scottish Rite Event Center, Square & Compass Rooms, 1895 Camino Del Rio South, San Diego • See our Flyer

PG&E Rate Increase Request

PG&E is requesting CPUC authority to increase revenue $333 million in 2017, followed by an additional increase of $469 million in 2018 and, in 2019, an additional increase of $368 million. The cumulative total increase for the 2017-2019 period would be $2.305 billion as compared to the 2016 revenue amount of $7.9 billion. The CPUC is holding Public Participation Hearings to hear directly from members of the public their thoughts on PG&E’s request. The hearings will take place as follows:

• July 11, 2016, 1 p.m. AND 6 p.m.: City of Bakersfield City Hall South Council Chambers, 1501 Truxtun Ave., Bakersfield ◦ See our flyer U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 26 of 28

• July 12, 2016, 1 p.m. AND 6 p.m.: Fresno City Council Chambers. 2600 Fresno St., Fresno ◦ See our flyer

• July 13, 2016, 7 p.m.: Stockton City Council Chambers, 425 N. El Dorado St., Stockton ◦ See our flyer

• July 14, 2016, 6 p.m.: Manzanita Place, 1705 Manzanita Ave., Chico ◦ See our flyer

• July 18, 2016, 7 p.m.: Courtyard Richmond Berkeley, 3150 Garrity Way, Richmond ◦ See our flyer

• July 19, 2016, 1 p.m. AND 6 p.m.: Elihu Harris State Building, 2nd Floor, Room 2, 1515 Clay St., Oakland ◦ See our flyer

• July 20, 2016, 1 p.m. AND 6 p.m.: CPUC Auditorium, 505 Van Ness Ave., San Francisco ◦ See our flyer

• July 25, 2016, 1 p.m. AND 6 p.m.: City of Santa Rosa, Recreation and Parks Department Steel Lane Community Center, Dohn Room, 415 Steele Ln., Santa Rosa ◦ See our flyer

• July 26, 2016, 1 p.m. AND 6 p.m.: San Bruno Library, Downstairs Room, 701 Angus Ave. W., San Bruno ◦ See our flyer ◾ In Spanish

• July 27, 2016, 1 p.m. AND 6 p.m.: San Jose Scottish Rite Center, Room 3, 2455 Masonic Dr., San Jose ◦ See our flyer ◾ In Spanish

• July 28, 2016, 1 p.m. AND 6 p.m.: San Luis Obispo City, County Library, Library Community Room, 995 Palm St., San Luis Obispo ◦ See our flyer ◾ In Spanish

• CPUC Media Advisory • PG&E’s Flyer U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 27 of 28

California Water Service’s Rate Change Request:

WHEN: March 22, 2016, 6:30 p.m. WHERE: Kern County Board of Supervisors, First Floor Board Chambers, 1115 Truxtun Ave., Bakersfield (the CPUC’s Residential Electric Rate Design Forum will also be held this day at 5 p.m. at the same location: www.cpuc.ca.gov/RateDesignForums)

WHEN: March 23, 2016, 4 p.m. WHERE: Kern River Valley Veterans, Senior Building, Veterans Room 2, 6405 Lake Isabella Blvd., Lake Isabella

WHEN: March 24, 2016, 5 p.m. WHERE: City of Palmdale Council Chambers, 38300 Sierra Hwy, Suite B, Palmdale

WHEN: April 26, 2016, 6 p.m. WHERE: Manzanita Place, 1705 Manzanita Ave., Chico (the CPUC’s Residential Electric Rate Design Forum will also be held this day at 5 p.m. at the same location)

WHEN: April 27, 2016, 6:30 p.m. WHERE: Cal-Tran District 3 Building, Sierra Nevada Room, 703 B St., Marysville

WHEN: April 28, 2016, 6 p.m. WHERE: Dixon City Council Chambers, 600 East A St., Dixon

• Read our media advisory • Read California Water Service’s PPH notice to Kern River Valley District customers • Read California Water Service’s PPH notice to Antelope Valley District - Fremont Valley Lake Hughes ◦ In Spanish

• Read California Water Service’s PPH notice to Antelope Valley District - Lancaster ◦ In Spanish

• Read California Water Service’s PPH notice to Antelope Valley District - Leona ◦ In Spanish

• Read California Water Service's PPH notice to Bakersfield District ◦ In Spanish

• California Water Service’s – Chico • California Water Service’s – Marysville • California Water Service’s – Willows • California Water Service’s – Dixon ◦ In Spanish

• California Water Service’s – Oroville U-20471 Official Exhibits of Soulardarity Exhibit SOU-21 Page 28 of 28

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Social Icons U-20471 Official Exhibits of Soulardarity Exhibit SOU-22 Page 1 of 7

ENERGY2017 WASTE REDUCTION Annual Report U-20471 Official Exhibits of Soulardarity Exhibit SOU-22 Page 2 of 7

Table of CONTENTS 1. Executive Summary

9. Legislative Requirements

11. Program Portfolio 13. Residential 50. Education & Awareness 37. Commercial & Industrial 52. Pilots 56. Program Achievements

59. Future Plans

61. Conclusion U-20471 Official Exhibits of Soulardarity Exhibit SOU-22 Page 3 of 7 PROGRAM EXECUTIVE LEGISLATIVE PROGRAM FUTURE CONCLUSION SUMMARY REQUIREMENTS PORTFOLIO ACHIEVEMENTS PLANS

EXECUTIVE SUMMARY The purpose of this annual report is to highlight the general results of DTE Energy’s (DTE) 2017 Energy Waste Reduction (EWR) program, communicate program changes, and provide policy overview and future guidance.

DTE Energy | Energy Waste Reduction 2017 Annual Report page 1 U-20471 Official Exhibits of Soulardarity Exhibit SOU-22 Page 4 of 7 PROGRAM EXECUTIVE LEGISLATIVE PROGRAM FUTURE CONCLUSION SUMMARY REQUIREMENTS PORTFOLIO ACHIEVEMENTS PLANS

launch in 2009 by continuing to grow customer acceptance and adoption of EWR measures. The 2017 goals were to:

1. Achieve legislated electric energy savings of 1 percent of 2016 planned retail sales or 485 gigawatt hours (GWh), and achieve legislated gas energy savings of 0.75 percent of 2016 planned retail sales or 1,305 million cubic feet (MMcf).

2. Ensure that EWR programs are cost effective. Cost Effectiveness Tests (CETs) are performed to ensure that the overall goal of reducing energy use in a cost-effective manner for the utility and its customers is being achieved. DTE uses the Utility System Resource Cost Test (USRCT) and the Total Resource Cost (TRC) test to measure the effectiveness of the various EWR programs. Specifically, the goal of the EWR portfolio (not including low-income) is to meet the minimum required USRCT score of 1.0. The low-income programs were excluded from the calculations because Section 71(4) (g) of PA 295, as amended, specifically excludes low-income in the requirement for DTE Energy’s EWR program was launched in June 2009 as in the approved 2017 EWR plan. The Company utilizes cost-effectiveness. a result of the Clean, Renewable and Efficient Energy Act, implementation contractors and has built strong networks to also known as Public Act 295 (PA 295), as amended by Public deliver energy efficiency programs throughout the State of Spending and Savings Act 342 of 2016 (PA 342). DTE continued to build on its Michigan. The Company has continued to provide energy Verified net energy savings are DTE’s reported savings after momentum from the 2009 launch by enhancing the scope of efficiency education and to raise awareness of EWR offerings they have been adjusted, based on the results of a review by existing programs and adding new program options to the by enhancing communications and messaging, while leveraging our independent evaluation contractor, Navigant Consulting portfolio. Since its inception in 2009, more than 2.9 million new trends in digital and social media communication Inc. (Navigant), and the application of Installation Rate electric customers and 2.1 million gas customers have directly channels. In 2017, while the Company continued to utilize Adjustment Factors (IRAF) and Net-to-Gross Ratios (NTGR). participated in DTE’s energy efficiency programs. targeted marketing to meet segment-specific needs for energy In 2017, DTE applied a 0.92 NTGR to most programs. efficiency information, traditional mass media was also Customers have upgraded equipment in their homes and their The exceptions to this include applying an 0.82 NTGR to used, focused on non-energy benefits of energy efficiency businesses, helping them to become more energy efficient, and standard compact fluorescent lighting in upstream programs improvements. The Pilot program process worked well in they have been provided with education, tips, strategies and and applying a 1.0 NTGR to behavioral, low-income, pilots, 2017, increasing the Company’s Pilot program productivity. tools to help them save money on their energy bills. As a result, education programs and Tier 1 Thermostats delivered by The Company’s ability to run the programs effectively has DTE has saved approximately 5,096 gigawatt hours (GWh) Commercial & Industrial programs, and Tier 2 and Tier 3 continued to improve through further maturity of systems and or 10.8 percent of planned retail sales for electric customers, Thermostats delivered by Residential programs. Planned back-office processes. and over 11,248 million cubic feet (MMcf) or about 6.6 percent savings refer to DTE’s approved 2017 EWR Plan projected of planned retail sales for gas customers since the program savings for 2017 as approved by the Michigan Public Service Goals and Targets started. The savings achieved so far will continue for years into Commission (MPSC) on June 3, 2015, for DTE Gas in Case the future. The main operational goal of the 2017 EWR program was to No. U-17763 and June 3, 2015, for DTE Electric in Case No. maintain the momentum that the program achieved since the U-17762. During 2017, DTE implemented its EWR program as outlined

DTE Energy | Energy Waste Reduction 2017 Annual Report page 2 U-20471 Official Exhibits of Soulardarity Exhibit SOU-22 Page 5 of 7 PROGRAM EXECUTIVE LEGISLATIVE PROGRAM FUTURE CONCLUSION SUMMARY REQUIREMENTS PORTFOLIO ACHIEVEMENTS PLANS

Chart 1 – 2017 EWR Program Spending and Verified Net Savings Spend, as used in this annual report, refers to the cash Chart 1 summarizes the overall EWR program 2017 spending expenditures or commitments made by DTE in implementing and verified net savings for DTE Electric and DTE Gas. the EWR program. Spend does not contemplate the eventual Each EWR program has its own spending and verified net 2017 DTE Electric 2017 DTE Gas treatment of such costs as operations and maintenance or Spending ($M) Spending ($M) saving requirements. For DTE Electric, collectively, the capitalization. The 2017 actual EWR program costs include: 100 100 Residential and Low-Income programs provided 375 GWh of O&M expenses, pre-tax return on capitalized costs and return 80 80 93.2 93.2 verified net energy savings, and C&I programs; including self- of capitalized costs (amortization), plus carrying charges on 60 60 direct, provided 342 GWh. DTE Electric achieved 45 GWh 40 over/(under) recovered balances. 40 savings from the Education and Pilot programs. For DTE Gas, 20 20 25.4 25.5 DTE has adopted verified net savings for reporting of energy collectively, the residential and low-income programs provided 0 0 Planned Actual Planned Actual savings in 2017, as agreed to in the EWR Collaborative. DTE’s 1,012 MMcf of verified net energy savings and C&I programs 2017 DTE Electric 2017 DTE Gas EWR program resulted in total verified net electric savings provided 612 MMcf. DTE Gas achieved 112 MMcf savings Savings (GWh) Savings (MMcf) 2017 DTE Electric Spending 2017 DTE Gas Spending 800 2000 of 762 GWh, or 1.57 percentby Program of 2016 ($93 planned.2M) retail sales, by fromProgram the ($ education25.5M) and pilot programs. 700 762 1600 600 1735 as compared to the minimum legislative requirement of 485 3% 3% 5% 500 568 Chart 2 displays program spending and verified net savings 1200 1381 485 1305 400 GWh. For DTE Gas, the total verified net gas energy savings 5% 300 800 5% for the various EWR programs in 2017. 5% 200 was 1,735 MMcf, or 1.33 percent of 2016 planned retail sales, 400 100 as compared to the minimum legislative requirement of 0 0 20177% DTE Electric Spending 2017 DTE Gas Spending Required Planned Actual Required Planned Actual Long-term EWR Impacts Minimum Minimum 1,305MMcf. by Program ($93.2M) by Program ($25.5M)47% 43% 21% 3% 3% In 2017, DTE Electric spent $93.2 million compared to the 5%Even though Michigan’s EWR programs are only eight 5% years old, they have matured quickly. Regulators and other planned $93.2 million, whereas5% DTE Gas spent $25.5 million 5% 37% participants are already looking beyond the first-year energy compared to the planned $25.4 million. 19% 7% savings goals set out in PA 295 toward longer-term goals, such Education 47% 43% 21% Chart 2 – 2017 EWR Spending and Verified Net Energy Savings by Program Pilots

37% EM&V 19% 2017 DTE Electric Spending 2017 DTE Gas Spending 2017 DTE Electric Savings 2017 DTE Gas Savings by Program ($93.2M) by Program ($25.5M) by Program (762 GWh) by Program (1,735 MMcf) EducationLow Income 3% 3% 5% 2% 1% 2% 4% 4% PilotsCommercial and Industrial 5% 4% 5% 5% EM&VResidential 13% 7% 2017 DTE Electric Savings 2017 DTE Gas Savings Self-Direct Plan 47% by Program (762 GWh) by Program (1,735 MMcf) Low Income 43% 21% 45% 2% 1% 2% 46% 44%4% 4% Commercial and Industrial 4% 35% 37% Residential 19% 13% Education Self-Direct Plan

Pilots 45% 46% 44%

EM&V 35%

2017 DTE Electric Savings 2017 DTE Gas Savings by Program (762 GWh) by Program (1,735 MMcf) Low Income

1% 4% 2% 4% 2% Commercial and Industrial DTE Energy 4%| Energy Waste Reduction 2017 Annual Report page 3 Residential 13% Self-Direct Plan

45% 46% 44% 35% U-20471 Official Exhibits of Soulardarity Exhibit SOU-22 Page 6 of 7 PROGRAM EXECUTIVE LEGISLATIVE PROGRAM FUTURE CONCLUSION SUMMARY REQUIREMENTS PORTFOLIO ACHIEVEMENTS PLANS

as overall lifecycle savings, both in dollars and energy. The average life of measures being installed; and reduction DTE 2017 EWR Programs — Lifecycle Dollar Savings (All Values in Dollars) in future peak. This section provides definitions and the 2017 Program DTE Electric DTE Gas EWR program results for a number of these measures of long- Present Value Present Value term interest. Residential Residential and Small Business ENERGY STAR® Products $181,263,584.74 $2,207,637.69 I. Lifecycle Dollar Savings: This represents the dollar Residential Appliance Recycling $16,998,674.42 - savings resulting from the current and future energy costs Residential HVAC $11,514,111.43 $14,078,886.33 avoided as a result of an energy efficiency action over the Multifamily—Standard (MFR) $2,509,216.98 $718,524.14 effective life of that action. Lifecycle dollar savings may be Residential Audit & Weatherization $1,015,153.89 $1,833,738.65 presented for an individual measure, a collection of measures, Residential HEC $9,842,593.63 $8,342,671.22 a program or a portfolio of programs. As presented for DTE Residential Schools $2,409,067.66 $1,753,095.45 Energy’s programs, the lifecycle dollar savings are based on Residential Online Energy Audit (OEA/HES) $2,887,441.55 $1,520,312.94 verified net savings, which have been adjusted for free-riders. Residential Behavior Programs (HER) $7,654,630.99 $953,624.32 Lifecycle dollar savings are presented as the present value of Residential Emerging Programs (EP) $1,678,274.22 $45,327.19 those savings. This is not net of the program expenses and Residential Subtotal $237,772,749.51 $31,453,817.94 includes line losses. C&I Table 1 displays that DTE’s 2017 EWR programs C&I Prescriptive (CIP) $131,045,180.30 $14,572,963.55 produced very significant dollar savings for its customers C&I Non-Prescriptive (C&I Custom/RFP) $113,209,654.10 $8,704,411.49 for future years. C&I Emerging (BEC/EPC/RCx) $22,445,498.09 $834,656.19 C&I ENERGY STAR Retail Lighting (ESL) $13,335,723.21 - C&I Multifamily Common Areas (MFC) $2,024,399.67 $871,947.30 C&I Self-Direct $474,122.13 - C&I Subtotal $282,534,577.49 $24,983,978.53 Low-Income—All (includes EEAP, LI Multifamily, $15,274,032.49 $7,796,536.06 LI HEC, LI HER) Pilot $27,047,776.65 $4,013,247.90 Education $16,252,824.87 $2,334,596.81 Portfolio $578,881,961.01 $70,582,177.25 Table 1- Lifecycle Dollar Savings

DTE Energy | Energy Waste Reduction 2017 Annual Report page 4 U-20471 Official Exhibits of Soulardarity Exhibit SOU-22 Page 7 of 7 PROGRAM EXECUTIVE LEGISLATIVE PROGRAM FUTURE CONCLUSION SUMMARY REQUIREMENTS PORTFOLIO ACHIEVEMENTS PLANS

II. Lifecycle Energy Savings: This represents the total cumulative program energy savings (MWh or MMcf) produced by the energy saving actions taken for all of the years in the particular actions’ effective lives. Again, as presented here, these represent net energy savings with free-riders removed. Table 2 displays the long-term energy savings associated with the cost savings in Table 1.

III. Peak Demand Reduction (MW): One particular concern for electric EWR programs is to achieve significant peak demand reductions to minimize the need for future power plants. This represents the aggregate reduction in DTE Electric’s service area load at the time of the Michigan Zone of the Midwest Independent System Operator (MISO) market’s expected peak demand that is estimated to result from the measures installed and actions taken by customers participating in the EWR program (nominally, from 3 p.m. to 7 p.m. on a weekday in July). Table 3 shows that the DTE Electric 2017 EWR programs achieved significant demand reductions, as well as energy savings. All values shown as measured at the customers’ meters. Line losses are not included.

DTE 2017 EWR Programs — Lifecycle Energy Savings DTE 2017 EWR Programs — DTE Electric Peak Demand Net Savings Program DTE Electric MWh DTE Gas MMcf Residential 2017 Verified Net Impact and Savings Impact and Savings Peak Demand Cumulative (Losses Included) Cumulative (Losses Included) Savings MW Residential Residential and Small Business ENERGY STAR® Products 3.89 Residential and Small Business ENERGY STAR® Products 2,291,850.98 527,560.65 Residential ENERGY STAR® Lighting Program 20.91 Residential Appliance Recycling 228,669.88 - Residential Appliance Recycling Program 3.22 Residential HVAC 152,124.54 3,695,496.10 Residential HVAC Program 2.57 Multifamily — Standard (MFR) 31,195.07 177,352.35 Multifamily — Standard (MFR) 0.21 Residential Audit & Weatherization 14,318.34 550,517.97 Residential Audit and Weatherization Program 0.3 Residential HEC 124,777.39 2,046,989.13 Residential HEC Program 0.78 Residential Schools 34,888.25 423,811.38 Residential School Program 0.22 Residential Online Energy Audit (OEA/HES) 40,823.48 382,919.69 Residential Online Energy Audit (OEA) 0.26 Residential Behavior Programs (HER) 75,482.41 206,183.57 Residential Behavior Programs (HER) 27 Residential Emerging Programs (EP) 22,856.93 9,800.21 Residential Emerging Programs (EP) 1.82 Residential Subtotal 3,016,987.28 8,020,631.05 Residential Subtotal 61.18 C&I C&I Prescriptive (CIP) 2,158,908.72 3,845,922.53 C&I C&I Non-Prescriptive (C&I Custom/RFP) 1,883,858.00 2,332,506.60 C&I Prescriptive 23.58 C&I Emerging (BEC/EPC/RCx) 330,003.84 201,816.74 C&I Non-Prescriptive (C&I Custom/NC/RFP) 11.78 C&I ENERGY STAR® Retail Lighting (ESL) 161,842.32 - C&I Emerging (BEC/EPC/RCx) 3.7 C&I Multifamily Common Areas (MFC) 41,263.19 241,918.68 Self-Direct 0.66 Self-Direct 6,038.58 - C&I Subtotal 39.72 C&I Subtotal 4,581,914.65 6,622,164.54 Pilot 4.34 Pilot 427,326.30 1,052,670.47 Education 2.52 Education 248,833.49 607,921.79 Low-Income—All (includes EEAP, LI Multifamily, LI HEC, LI HER) 7.77 Low-Income—All (includes EEAP, LI Multifamily, 199,282.16 1,975,014.89 Total EWR Portfolio 115.53 LI HEC, LI HER) Portfolio 8,474,343.88 18,278,402.74

Table 2 – Lifecycle Energy Savings Table 3 – DTE Electric Peak Demand Savings

DTE Energy | Energy Waste Reduction 2017 Annual Report page 5 U-20471 Official Exhibits of Soulardarity Exhibit SOU-23 Page 1 of 10 University of Michigan December 01, 2017 Social Equity in State Energy Policy: Indicators for Michigan’s Energy Efficiency Programs

Summary State policies providing residential energy efficiency programs have emerged over the past decade with the goal of producing widespread economic and environmental benefits. While these policies have largely achieved and surpassed legislated objectives, the degree to which program benefits are distributed amongst population subgroups, particularly low-income residents, remains unclear. On average in the United States, low-income households are less energy efficient contributing towards 1 in 3 of these homes struggle to afford energy, and 1 in 5 facing decisions between energy use and other necessities such as food or medicine. Energy efficiency programs however, may offer a critical avenue in alleviating energy poverty. This study focuses on measuring the social equity achieved through Michigan’s “Energy Waste Reduction” programs for the state’s two major investor-owned utilities (IOUs). The study establishes a novel, quantitatively sensitive measure, called the Energy Efficiency Equitable baseline (E3b). This measure is used to identify disparities that occur in policy decision-making and outcomes. Particularly, the study quantifies disparities in program investments and household energy savings on a per capita basis between low and high-income residential groups. E3b reveals trends in policy outcomes from a social perspective, illustrating high variability in social equity between energy type and providers. Broad patterns showed that gas program investments approached equitable levels, however, electric Low-Income program investments fall well below the E3b. Household energy savings also demonstrated substantial disparities, where per capita ratios reached up to 22:1 when comparing high to low-income program benefits. As states aim to transition towards clean and affordable energy, social equity must be quantitatively evaluated to prevent discriminatory impact on vulnerable populations.

Ben Stacey & Tony Reames Urban Energy Justice Lab School for Environment & Sustainability University of Michigan U-20471 Official Exhibits of Soulardarity Exhibit SOU-23 Page 2 of 10 KEY FINDINGS households experienced an energy burden greater than 10% while earning less than 150% of the FPL.3 • 35% of Michigan residents qualify for Low- For low-income households, the average home Income Energy Waste Reduction (EWR) energy affordability gap (HEAG) is $1,250 per year, programs; this ranges widely (30-40%), totalling $1.7 billion in 2016 for Michigan.4 Energy depending upon utility territory. poverty has been shown to lead to negative mental • One key policy consideration for MI low-income and physical health impacts, recurring debt, and consumers: In approving utility EWR Plans, homelessness.5 In severe cases, as described in the the Michigan Public Service Commission, must NAACP report, Lights Out in the Cold (2017), the consider, “the extent to which the plan provides struggle to afford heating bills in Michigan winters, programs that are available, affordable, and useful has resulted in hypothermia and death.6 Similarly, to all customers.” -P.A. 342 populations unable to afford cooling their homes, are • There is a $73.4 million gap in utility investment vulnerable to the health impacts of urban heat islands.7 levels between equitable (E3B) and actual low- income program investments. This gap is only Policy & Social Problems of Energy $1.0 million gas LI programs (2010-2016). State and federal policies to address the social • On average, utilities invested 3 times less on concerns surrounding energy affordability include

Low-Income (electric) programs per capita, energy shut-off protections, bill-payment assistance and near equitable levels for Low-Income gas programs, home weatherization and energy 8 programs . efficiency programs. Major federal policies include • Low-income consumers overall recieved 10 times Low Income Home Energy Assistance Program less home energy savings (electric) and 3.4 times (LIHEAP), and the Weatherization Assistance less home energy savings (gas) when compared Program (WAP). While many states such as to high-income consumers. The greatest Michigan have legislated bill-payment assistance difference found, by utility, was 22 times higher. programs, policy targeting the reduction of energy waste at the household level presents an alternative I. BACKGROUND approach that empowers households facing energy poverty and reduces the home energy affordability Energy Poverty gap. For many low-income energy advocates, these state energy efficiency programs offer hope The relationship between residents and energy for a sustainable path towards eliminating energy use varies between sociodemographic groups and poverty. Yet, while reports claim widespread social the homes in which they live. This study focuses on and economic benefits, concerns have been raised income, as distinguished by state policy, however, the in regards to utility investment levels in programs social perspective applied in this study can also be targeting low-income residents and the impact on applied to groups by race, age, ability, and tenure. achieving an equitable energy future. Low-income consumers, defined as households earning below 200% of the federal poverty level (FPL), oftentimes occupy older homes which are energy inefficient. This contributes to a high energy- use-intensity (EUI), a proxy for energy waste, when compared to higher-income households. Nearly one- third of US homes struggle to afford adequat energy, and one in five homes trade-off energy use with other necessies such as food or medicine.1 When a household’s energy burden, or the percentage of income allocated towards energy bills, surpasses10%, Source: Amanda Voisard, Washington Post (2016) the home is considered to suffer energy poverty.2 Above 6%, the burden is considered unaffordable. Urban Energy Justice Lab In Michigan studies show that in 2016, 999,442 University of Michigan

2 U-20471 Official Exhibits of Soulardarity Exhibit SOU-23 Page 3 of 10 MI Energy Efficiency Policy: the state resulted in consumer electricity savings of Goals & Accomplishments 1.1 million MWh and natural gas savings of 4.58 The social, economic and environmental benefits million Mcf. Utility companies spent $262 million of energy efficiency have driven policy changes in of rate-payer funds on these programs, and captured efficiency standards in residential building, appliance a life cycle savings of $1.1 billion for consumers, and vehicles over the past several decades. These demonstrating an aggregate return of $4.35 for every policies have led to substantial social benefits $1 invested across the state as a whole. including reductions in atmospheric emissions, To incentivize energy savings beyond legislated consumer economic gains, and national security standards, utilities exceeding these goals are granted through reduced dependency on foreign energy. financial incentives up to the lesser amount of: However, to understand the relative impact of energy Utility Financial Incentives: efficiency policies from a social perspective, the 20% of the annual EWR program expenditures OR distribution of costs and benefits between population 30% of the net-present-value of life-cycle cost subgroups must be clearly understood to avoid reductions -P.A. 342 unintended social consequenses. Energy efficiency legislation was first signed into Michigan law in 2008 as the Clean, Renewable Program Revenue & Spending and Efficient Energy Act, and amended in 2016 To fund these programs, energy providers, whose as the Clean and Renewable Energy and Energy rates are regulated by the state, are allowed to recover Waste Reduction Act. This establishes standards program costs from two distinct customer classes: for utility companies to achieve energy savings Residential (including low-income residents), and equivalent to 0.75% and 1% of retail sale volumes Commercial and Industrial (C&I). Base revenue, from the previous year for natural gas and electricity is generated through an on-bill surcharge to respectively. Regulatory agency reports show that consumers. The residential consumer class is charged the energy savings resultant of this policy (Subpart volumetrically, dependent upon energy use (kWh, C. Energy Waste Reduction), has saved billions of ccf), while C&I consumers are charged on a per- dollars in energy costs to commercial, industrial, and meter basis. The allocation of base revenue funds residential consumers through these state regulated, are restricted on a customer class basis. In other utility managed, energy efficiency programs. As in words, funds generated in the residential class were many other state energy efficiency policies, energy not allocated towards C&I programs. Both customer providers are required to achieve these annual classes contribute to low-income programs. energy savings targets through EWR Plans, which Similarly, utilities recover performance-based outline the utility’s portfolio composed of various financial incentives through an on-bill surcharge. Residential and Commercial & Industrial (C&I) programs. Policy Goals: Policy: Low-Income Consumer “Help customers reduce energy waste” & Outcomes The Residential customer class in Michigan is “To reduce the future costs of provider service to composed of 9.7 million residents, 3.4 million customers” -P.A. 342 (35%) of which qualify as low-income, face gaps in Utility companies accomplish this through their unaffordability and are likely to experience energy range of programs targeting various consumer poverty. While not officially recognized within state markets and employing a variety of energy legislation, regulatory agencies, energy providers, savings interventions. For residential energy and low-income advocacy groups frequently cite consumers, these programs are tailored towards two the benefits of energy efficiency policy in reducing socioeconomic groups: low-income and non-low- the impacts of energy poverty. However, the broad income (higher-income). impact on energy poverty remains unclear.

In 2016, the Michigan Licensing and Regulatory Urban Energy Justice Lab Affairs (LARA) reported that EWR programs across University of Michigan

3 U-20471 Official Exhibits of Soulardarity Exhibit SOU-23 Page 4 of 10 MI EWR Act requires that utility companies acessibility, affordability and usefulness, and suggests offer programs for low-income residents, calling the need for a Low Income oriented cost-benefit for “an established spending level” on Low-Income analysis tool. programs. While this study was unable to identify From an energy justice perspective, energy a standardized spending level, this requirement efficiency policies have the significant potential appears to be met through the EWR plan filing to reduce energy poverty and the home energy process, which requires Michigan Public Service affordability gap, but is shown here, that these Commission (MPSC) approval. EWR stipulates that policies are susceptible to furthering social in order to approve an EWR plan: inequities. As energy efficiency forms an integral Michigan Public Service Commission role in planning for state energy demands, it is must consider: “The extent to which the energy essential that policy makers, regulatory agencies and waste reduction plan provides programs that are utility companies examine the impact from a social available, affordable, and useful to all customers” perspective in order to reach a more just energy (PA 342) future. Metrics for availability, affordability and usefulness were unable to be identified in this study, and are II. STUDY SCOPE & METHODS addressed in the Policy Recommendation section. Once approved, Low-Income program investment This tudys establishes a metric tool, the Equitable levels are subject to change. Commission Order Energy Efficiency baseline (E3b), to quantify the U-15806 allows energy providers to reallocate up to gap between equitable and actual levels in utility 30% of any program’s designated funds elsewhere. program investments and houehold energy savings. Because residential programs employ tailored Trends from Michigan’s two main investor-owned approaches for incentivizing participation, funding utility (IOU) providers, refered to as Utility A low-income specific programs is crucial to reach and Utility B, are compared spanning the policy these households. While Low-Income programs implementation period from 2010-2016. are often free, non-low-income progams provide Data on utility investments and energy savings subsidized rates for incentives to participate. were extracted from annual regulatory reports Commonly, identical or similar programs are offered detailing electric and gas EWR programs for each separately as Low-Income or “Residential” (referred utility. 2009 data was excluded as a partial (first) to henceforth as “High-Income” programs). year with incompatible data reports for the purposes Policy also requires that collectively, program of this study. Slight variation between utility spending must prove to be cost-effective. However, reporting required minor data revisions, specifically this excludes Low-Income programs. The cost- the removal of Utility B pilot program data which benefit is measured as the Utility-Resource-Cost- did not differentiate Residential and C&I pilot Test (URCT), however, this cost-benefit metric does programs comparably to Utility A). not account for the non-energy impacts (NEI’s), and Each utility territory, or coverage area, is unique reduced demand for bill payment assistance that in terms of population characteristics (figures 1 result from Low-Income programs. and 2). To assess equitable distribution program In this study, the social disparities in distribution spending and energy savings between utility (between Low and High-Income programs) of rate- providers, these variables were normalized by the payer revenue (utility investments) and program proporton of low-income residents in each utility benefits (household energy savings) are quantified. territory. Spatial data describing energy provider The results show wide variation in equity achieved coverage area at the subtownship level was provided by energy type (electric/gas) and provider (Utility by the Michigan Agency for Energy and paired A/Utility B), raising social and economic concerns with US Census Bureau 5-year ACS data (2015) for policy efficacy for providing household energy to accurately differentiate variation in low-income savings benefits to one-third of the state’s population. This study demonstrates the necessity for developing Urban Energy Justice Lab University of Michigan metrics for EWR plan approval on the basis of

4 U-20471 Official Exhibits of Soulardarity Exhibit SOU-23 Page 5 of 10 population levels. Populations in subtownships Table 1. Percent population low-income by utility territory. which had multiple, or overlapping energy providers, (Source: Michigan Agency for Energy, US Census ACS 5-year 2015) were attributed to both utility populations as Population State of Utility A Utility B Utility A Utility B consumer choices were indiscernible in these Michigan Electric Electric Gas Gas areas. Actual data for utilities’ customer population To t al 9,677,170 4,348,955 4,675,213 4,785,515 3,577,483 Population socioeconomic composition were unavailable. Low-Income 3,390,700 1,584,048 1,549,477 1,435,612 1,428,006 To quantify disparities in utility investments in Population (35.04%) (36.42%) (33.14%) (30.00%) (39.92%) Low-Income programs, the E3b was established for Minority 2,076,696 651,989 1,361,406 825,571 1,087,962 each utility by energy type (Utility A electric, Utility Population (20.98%) (14.5%) (28.73%) (17.13%) (29.71%) A gas, Utility B electric, Utility B gas). This was consumers ranges between 30.0-39.9% and 14.5- done for each provider, by multiplying the annual 29.7% for minority populations (table 1). sum of residential program investments (Low and Low-income populations for electric coverage High-Income) with the proportion of low-income area varies between 36.4% (Utility A) and 33.1% residents in the respective territory. Investment (Utility B) and racial composition varies by minority deficit/surplus was calculated as the difference populations composing 14.5% (Utility A) and 28.7% between actual spending and the E3b. (Utility B). Utility B territory encompasses 1.4 To compare disparities in per capita investments million non-white Michigan residents, including and energy savings by energy provider, utility the largest black population in the state located in reported data were compared to the territory Detroit. population. Given the imprecision in determining Population socioeconomc characteristics vary actual utility customer populations, these values more greatly for gas service providers. Utility A Gas should be used for relative comparison only. territory includes 4.8 million residents of which, The focus of this study is limited to quantifying 30.0% qualify for Low-Income programs, while disparities in investments and energy savings Utility B gas, with 3.6 million residents, encompasses between programs targeting low- and high-income 39.9% low-income. Utility B gas also has 12.6% residents. While it is plausible that “Residential higher proportion of minority residents. (non-low-income programs) may spill-over to low-income consumers, this study distinguishes these programs with the assumption that this impact is minimal. Further studies are necessary to better assess the accessibility and impact of non-low-income residential programs on low- income customers. As previously noted, several non-low-income residential programs, have similar or identical counterparts offered as Low Income programs. Hence this study distinguishes the two as High Income and Low Income programs based upon their targeted markets.

III.RESULTS Variation in Low-Income Population by Utility Territory There are 3,390,700 Michigan residents who qualify for Low-Income EWR programs, however, they are not evenly distributed across geographic Figure 1. Low-income population distribution for Utility A and Utility B territories. (Source: US Census, Michigan Agency for Energy) space (eg. utility coverage area). Spatial variation in income levels are illustrated in Figures 1 and 2 Urban Energy Justice Lab for electric provider territories. Depending on the University of Michigan service and provider, the percentage of low-income 5 U-20471 Official Exhibits of Soulardarity Exhibit SOU-23 Page 6 of 10 Investments in Energy Efficiency Electric Programs Investment trends for both the Utility A and Utility B electric programs demonstrate a substantial deficit between actual and E3b levels from 2010- 2016. Yearly, deficits ranged from $1.5 million to $7.4 million (Utility A) or 40%-82% under the E3b, and for Utility B: $3.5 to $6.9 million, or 39%-61% under the E3b (figures 3-7). Recently (2016), the equitable investment deficit for electric programs totalled $13.6 million for Utility A ($6.7 million or 64% under E3b) and Utility B ($6.9 million or 51% under E3b). The total spending deficit for electric Low-Income programs from 2010-2016 was $73.4 million, approximately 55.5% under the equitable baseline (table 2). Investments in Energy Efficiency Figure 2. Low-income population distribution for Utility A and Utility B Gas territories. (Source: US Census, Michigan Agency for Energy) Disparities in Equitable Utility Investments and Consumer Benefits Summatively, Utility A and Utility B spent $596 million on EWR Residential programs between 2010-2016. For electric programs, Utility A invested $160 million total, ($18.7 million Low-Income). Utility B invested $237 million total ($40 million Low-Income). For gas programs, Utility A invested Figure 3. Actual vs. Equitable (E3b) spending for Utility A $187 million, ($62 million Low-Income) and Utility electric EWR programs between 2010-2016. Source: EWR B $112 million total ($38 million Low-Income). Annual Reconciliation Reports (Utility A, 2010-2016), US Comparing the actual investment levels in Low- Census Bureau 5-year ACS 2015, Michigan Agency for Energy. Income programs to the territory tailored E3b, a deficit for Low-Income program investments of $74.3 million (electric) and $1.0 million (gas) was identified (Table 2). Figure 7 demonstrates that there is a high degree of variability in proximity to E3b investments by energy type and provider. On average, gas programs were funded closer to E3b (1% below) than electric programs (56% below).

Figure 4. Actual vs. Equitable (E3b) spending for Utility B electric EWR programs between 2010-2016. Source: EWR Annual Reconciliation Reports (Utility B, 2010-2016), US Census Bureau 5-year ACS 2015, Michigan Agency for Energy. Urban Energy Justice Lab University of Michigan

6 U-20471 Official Exhibits of Soulardarity Exhibit SOU-23 Page 7 of 10 Gas Programs Table 2. Summary of EWR program investments, Actual vs. Equitable (E3b), 2010-2016. Investment trends for gas programs show a much Low-Income Actual Equitable Investment Proportional different pattern than electric programs, with actual Program Investment Investment Deficit Deficit investment levels near or surpassing the E3b. The Utility-A $18,670,697 $58,268,333 -$39,597,636 -68.0% cumulative spending deficit for EWR gas Low- Electric Utility-B $40,070,000 $73,828,290 -$33,758,290 -45.7% Income programs from 2010-2016 is $1.0 million, Electric reflecting an under investment of only 1%. This Total $58,740,697 $132,096,623 -$73,355,926 -55.5% Electric was composed of Utility A surpassing the E3b by Utility-A $62,151,372 $56,223,498 +$5,927,874 +10.5% $5.9 million and Utility B investing $6.9 million Gas under the baseline, relatively 10.5% over and 15.4% Utility-B $37,811,000 $44,711,541 -$6,900,541 -15.4% Gas under respectively (Table 2). Low-Income program Total $99,962,372 $100,935,039 -$972,667 -1.0% spending ranged yearly, from $1.7 million under to Gas Total $158,703,069 $233,031,662 -$74,328,593 -31.9% $4.7 million over the E3b. In 2016, Low-Income Electric/Gas investments by Utility A gas was $0.4 million, or 5% above, and $1.2 million or 18% below for Utility B (Figure 5-7). E3b

Figure 7. Summary comparison of EWR program investments (Actual vs. Equitable) between 2010-2016. Source: EWR Annual Reconciliation Reports (Utility A & Utility B, 2010-2016), US Census Bureau 5-year ACS 2015, Michigan Agency for Energy MPSC Approved Plan vs. Actual Figure 7. Actual vs. Equitable (E3b) spending for Utility A The difference between MPSC approved EWR Plan gas EWR programs between 2010-2016. Source: EWR Annual investment and actual investments varied between Reconciliation Reports (Utility A Energy, 2010-2016), US energy type and provider. In electric programs, the Census Bureau 5-year ACS 2015, Michigan Agency for Energy. greatest yearly decreases were found in Utility B Low-Income programs, where reductions in three of seven years ranged from 25-31% (figures 8 & 9). No other program exceeded a 10% increase or decrease any year. Utility A electric Low and High-Income programs showed an average spending change of less than 1%. Utility B electric programs showed an average increase of 1% in High-Income and an average decrease of 14% in Low-Income programs. Variance in gas program spending included increases in Low-Income programs for Utility A (2010) and Utility B (2013), with a decrease in High-Income Figure 6. Actual vs. Equitable (E3b) spending for Utility B gas programs Utility B (2013). Average variance for EWR programs between 2010-2016. Source: EWR Annual Rec- Low-Income gas programs was 2% (Utility A and onciliation Reports (Utility B Energy, 2010-2016), US Census Bureau 5-year ACS 2015, Michigan Agency for Energy. Urban Energy Justice Lab University of Michigan

7 U-20471 Official Exhibits of Soulardarity Exhibit SOU-23 Page 8 of 10 Utility B), while High-Income programs increased by 1% and decreased by 4% respectively. Policy Benefits: Household Energy Savings BENEFITS: While the allocation of energy savings are not as direct as utility investment allocations in the decision-making process, the energy savings outcomes for both electric and gas EWR programs show severe disparities when comparing Low- and High-Income program results. Total energy savings deficits, representing disparities in outcomes, show outcomes 84.2% (total electric), and 60.7% (total gas) below E3b (Table 3). Again, patterns vary substantially by energy type and utility (figure 10). On an annual basis, electric programs ranged from 88-97% (Utility A) and 71-89% (Utility B) under E3b for Low-Income programs, with weighted Figure 8. Variance in Electric Program spending (%) between averages at 93% (Utility A) and 79% (Utility B). EWR Plan approved and Actual spending for Utility A and Utility B (2010-2016). For gas programs, annual disparities in energy savings ranged from 39-81% (Utility A) and 45-62% (Utility B), with weighted averages of 67% and 55% respectively.

E3b

Figure 9. Variance in Gas Program spending (%) between EWR Figure 10. Summary comparison of EWR program energy Plan approved and Actual spending for Utility A and Utility B savings (Actual vs. Equitable) between 2010-2016. Source: EWR (2010-2016). Annual Reconciliation Reports (Utility A & Utility B, 2010- 2016), US Census Bureau 5-year ACS 2015, Michigan Agency Table 3. Summary of variance between Actual energy savings for Energy. and Equitable (E3b) energy savings achieved (2010-2016). Per Capita Comparison: Utility EWR Actual Equitable Energy Proportional Program Energy Energy Savings Deficit Investments & Consumer Benefits Savings Savings Deficit Results show that for EWR Residential electricity Utility-A 26,352 374,615 -348,263 -93.0% programs overall, utilities are investing 3.1 times as Electric (Mwh) much per capita on High-Income programs. This Utility-B 130,851 618,160 -487,309 -78.8% Electric (Mwh) varied between energy providers, where Utility A Total 157,203 992,775 -835,572 -84.2% invested 4.3 and Utility B invested 2.4 times greater Electric (Mwh) in High-Income programs (Table 4). For EWR Utility-A 670,513 2,023,135 -1,352,622 -66.9% Gas (Mcf) Residential gas programs overall, utilities invested Utility-B 842,927 1,858,773 -1,015,846 -54.7% Gas (Mcf) Urban Energy Justice Lab Total 973,778 2,476,933 -1,503,155 -60.7% University of Michigan Gas (Mcf)

8 U-20471 Official Exhibits of Soulardarity Exhibit SOU-23 Page 9 of 10 Table 4. Summary comparison of per capita investments and energy savings between Low- (LI) and High- (HI) income populations. LI Investment HI Investment Investment LI Energy Saved HI Energy Saved Energy Saved ($ per capita) ($ per capita) ratio (LI:HI) (per capita) (per capita) Ratio (LI:HI) Utility A $11.79 $51.14 4.34 16.6 362.7 21.85 Electric Utility B $25.86 $63.13 2.44 84.4 594.0 7.04 Electric Total $18.75 $57.50 3.07 50.1 485.5 9.69 Electric Utility A $43.29 $37.39 0.86 467.1 1,813.0 3.88 Gas Utility B $26.48 $34.54 1.30 590.3 1,775.2 3.01 Gas Total $34.91 $36.28 1.04 528.5 1,798.2 3.40 Gas only 1.04 times greater in High-Income programs. investment standards, whether as a percentage of This also varied between gas providers, with Utility total program spending (ie. MA) or dependent upon A and Utility B investing 0.86 and 1.30 times as utility size (ie. IL), this study demonstrates the need much in High-Income programs. for further alignment in policy, regulatory processes In terms of per capita energy savings, high-income and the underlying mechanisms for measuring costs electric consumers received on average, 9.7 times and capturing bnefits in order to achieve socially greater household savings than low-income equitable outcomes. Further studies on alternative consumers. For natural gas, high-income received policy measures are necessary to guide policy 3.4 times greater savings. Particularly high, was makers, regulatory agencies and utility decision- Utility A’s ratio of 22:1 (High/Low-Income) electric makers towards a more just energy future. savings while Utility B programs produced electric savings at a 7:1 ratio. For gas programs, Utility V. RECOMENDATIONS A produced a savings ratio of 4:1, while Utility B performed at a 3:1 ratio. To achieve greater social equity in energy efficiency and consumption in the household across socio- IV. DISCUSSION economic groups, this study concludes with the following policy and regulatory recommendations: Impacts Across Residential • Establish investment standards for Low-Income Socioeconomic Groups programs that reflect the E3b tailored spatial and The results of this study demonstrate the socioeconomic approach for each utility. occurance of severe disparities in Michigan’s state • Set a ceiling for inequiable policy outcomes (e.g. energy efficiency policy between 2010-2016. The a max ratio of household energy savings benefits degree of social equity highly depended upon per capita, resulting from High and Low-Income energy type and the utility provider. The disparities programs. in program outcomes can partially be attributed • Develop further metrics for current state policy to sustantialy lower investments in Low Income requiring the Commission to approve or reject programs and repeated reallocation of Low-Income proposed EWR plans based upon: availability, funds from MPSC plan approved spending levels. affordability, usefulness. However, one utility’s investments in EWR Low • Create Low-Income specific cost-benefit Income gas programs exceeded equitable investment measures that capture the full social benefits levels. Yet, low-income consumer savings produced of reducing severe home energy burdens. This were four times less per capita. This demonstrates includes non-energy imacpts (NEIs) such as that while equitable investments are important, it health, employment, education, safety. will not lead to equitable policy outcomes. While some states have addressed social concerns Urban Energy Justice Lab through the establishment Low-Income program University of Michigan

9 U-20471 Official Exhibits of Soulardarity Exhibit SOU-23 Page 10 of 10 About the Authors References Ben Stacey is a graduate student at the School for 1. Energy Information Agency (EIA): Residential Environment and Sustainability, as well as Taubman Energy Consumption Survey (2015) College for Urban and Regional Planning at the 2. Simon, R (2008) Energy, Equity and the Future of the University of Michigan. He has been a member of the Fuel Poor. Energy Policy (36):12, 4471-4474. Urban Energy Justice Lab since 2016. 3. Michigan 2016 HEAG Fact Sheet (2017) Fisher Sheehan and Colton: Public Finance and General Tony Reames is the Director of the Urban Energy Justice Economics Lab and an Assistant Professor who instructs the “Energy 4. Ibid. Justice” course at the School for Environment and 5. Liddell C, Morris C (2010) Fuel Poverty and Human Sustainability at the University of Michigan. Health: A Review of Recent Evidence. Energy Policy (38)6:2987-2997. Acknowledgements: 6. Franklin M, Kurtz C (2017) Lights Out in the Cold: A special thanks to the Edna Bailey Sussman Grant Reforming Utility Shut-off Policies as If Human for providing the opportunity to conduct research at Rights Matter. Environmental and Climate Justice the intersection of environment and society and to Program, NAACP our community partner, Ecoworks Detroit, for their 7. Gronlund, C (2014) racial and Socioeconoimc invaluable insights to the Low-Income Energy Waste Disparities in Heat-Related Effects and Their Mechanisms: a Review. Current Epidemiology Reports. Reduction programs in Michigan. (1)3: 165-173. 8. Drehobl A, Ross L (2016) Lifting the High Energy Burden in America’s Largest Cities: How Energy Efficiency can Improve Low Income and Underserved Communities. ACEEE Report. Data Sources 1. Michigan Licensing and Regulatory Agency Annual EWR Report (2016) 2. US Cencus Bureau American Communities Survey data (2010-2015) 3. Michigan Agency for Energy 4. DTE Annual EWR Reconciliation Reports (2010- 2016) 5. Consumers Energy Annual EWR Reconciliation Reports (2010-2016)

Urban Energy Justice Lab University of Michigan

10 U-20471 Official Exhibits of Soulardarity Exhibit SOU-24 Page 1 of 10 Energy Policy 97 (2016) 549–558

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Energy Policy

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Targeting energy justice: Exploring spatial, racial/ethnic and socioeconomic disparities in urban residential heating energy efﬁciency

Tony Gerard Reames

School of Natural Resources & Environment, University of Michigan, 440 Church Street, Ann Arbor, MI 48109-1041, USA

HIGHLIGHTS

Develops statistical model to predict block group (BG) residential heating energy use intensity (EUI), an energy efﬁciency proxy. Bivariate and multivariate analyses explore racial/ethnic and socioeconomic relationships with heating EUI. BGs with more racial/ethnic minority households had higher heating EUI. BGs with lower socioeconomics had higher heating EUI. Mapping heating EUI can facilitate effective energy efﬁciency intervention targeting. article info abstract

Article history: Fuel poverty, the inability of households to afford adequate energy services, such as heating, is a major Received 1 April 2016 energy justice concern. Increasing residential energy efficiency is a strategic fuel poverty intervention. Received in revised form However, the absence of easily accessible household energy data impedes effective targeting of energy 24 July 2016 efficiency programs. This paper uses publicly available data, bottom-up modeling and small-area esti- Accepted 26 July 2016 mation techniques to predict the mean census block group residential heating energy use intensity (EUI), Available online 12 August 2016 an energy efficiency proxy, in Kansas City, Missouri. Results mapped using geographic information Keywords: systems (GIS) and statistical analysis, show disparities in the relationship between heating EUI and fi Energy ef ciency spatial, racial/ethnic, and socioeconomic block group characteristics. Block groups with lower median Fuel poverty incomes, a greater percentage of households below poverty, a greater percentage of racial/ethnic min- Residential heating ority headed-households, and a larger percentage of adults with less than a high school education were, Spatial analysis fi Energy justice on average, less energy ef cient (higher EUIs). Results also imply that racial segregation, which continues to influence urban housing choices, exposes Black and Hispanic households to increased fuel poverty vulnerability. Lastly, the spatial concentration and demographics of vulnerable block groups suggest proactive, area- and community-based targeting of energy efficiency assistance programs may be more effective than existing self-referral approaches. & 2016 Elsevier Ltd. All rights reserved.

1. Introduction uninterrupted energy service. For the many US households suffering in fuel poverty, nearly 14 million with unpaid utility bills Climate change concerns highlight a number of serious social and 2.2 million with disconnected utilities, these rights are un- and environmental inequalities that can be traced to energy con- fulfilled promises (Seibens, 2013). Fuel poverty (also known as sumption. These concerns form the foundation of a growing field energy poverty or energy insecurity) is the inability of households of scholarship, and activism, on energy justice. For instance, Her- to afford energy services for adequate heating and cooling re- nández (2015) issued “A Call for Energy Justice,” which acknowl- sulting in uncomfortable indoor temperatures, material depriva- edged four basic human rights to energy: the right to a healthy, tion, and accumulated utility debt (Li et al., 2014, Hernández 2013, Buzar, 2007; Boardman, 2012). More than a matter of mere com- sustainable energy production; the right to best available energy fort, indoor temperatures that are too cold in winter or too hot in infrastructure; the right to affordable energy; and the right to summer have detrimental mental and physical health impacts, including death, for vulnerable populations like children, the el- E-mail address: [email protected] derly, and racial/ethnic minorities (Anderson et al., 2012; Liddell http://dx.doi.org/10.1016/j.enpol.2016.07.048 0301-4215/& 2016 Elsevier Ltd. All rights reserved. U-20471 Official Exhibits of Soulardarity Exhibit SOU-24 Page 2 of 10 550 T.G. Reames / Energy Policy 97 (2016) 549–558 and Morris, 2010, Howden-Chapman et al., 2009, Howden-Chap- spatial disparities in the distribution of fuel poverty vulnerability man et al., 2007, Klinenberg, 2002; Taylor et al., 2001). A key and energy consumption to facilitate policymaking and interven- measurement of fuel poverty is the proportion of gross income tion targeting (Pereira and de Assis, 2013; Walker et al., 2013; spent on home energy costs, or the energy burden. Low-income Fahmy et al., 2011; Morrison and Shortt, 2008). US households have an average heating energy burden of 4.7% that In the US, while fuel poverty is neither recognized colloquially is more than double the 2.3% national average and more than four or politically, a few studies have modeled the spatial distribution times the 1.1% average burden for high-income households (US of residential energy consumption, including socioeconomic and Department of Health and Human Services [HHS] 2011). Analysts demographic control variables in their models (Howard et al., consider a heating energy burden greater than 2% unaffordable 2012; Min et al., 2010; Heiple and Sailor, 2008). Others have ex- (Fisher et al., 2014). plored the socioeconomic and demographic relationships of na- However, fuel poverty is more than a straightforward re- tional residential energy consumption patterns (Health and Hu- lationship between household income and energy costs. The man Services [HHS] 2011; Steemers and Yun, 2009; Ewing and concept became prominent in the 1980s and has been well-stu- Rong, 2008; Adua and Sharp, 2011; Newman and Day, 1975). died in the UK (see special issue Volume 49 of this journal) and Generally, these studies concluded that, all else being equal, low- even codified in law with the passage of the Warm Homes and income households consume less energy. This broad assessment of Energy Conservation Act of 2000. Investigations of fuel poverty, consumption rather than efficiency, tends to mask fuel poverty including those beyond the UK, demonstrate that a pure financial vulnerability. Instead, when analyzing energy use intensity (EUI), assessment of its prevalence does not account for the variety of or energy consumption normalized by building square area, as a factors and relationships that produce and sustain it. Buzar (2007) proxy for energy efficiency, national data from the US Energy In- advocated a “relational approach” to studying fuel poverty, one formation Administration (EIA) show that low-income household, that combines understanding energy policy, housing infra- on average, are less efficient, with an EUI 27% greater than high- structures, and the lived experience of the fuel poor. Hernandez income households. The spatial distribution of energy efficiency is and Bird (2010) found the incidence of high inner-city energy further complicated by a persistent system of racial and income burdens was due in part to a lack of energy assistance funding, a residential segregation that defines housing development and lack of housing and energy policy coordination, and a lack of un- consumption patterns in many US metropolitan areas. A sub- derstanding the social and economic benefits of energy con- stantial amount of research is aimed at understanding the causes servation and efficiency. Harrison and Popke (2011) suggested fuel and consequences of residential segregation, primarily from the poverty be understood “as a geographical assemblage of net- fields of sociology and public health (Sampson, 2012; Sharkey, worked materialities and socioeconomic relations” determined by 2011; Anthopolos et al., 2011; Sampson and Wilson, 1995; Wilson, household socioeconomic characteristics, material conditions of 1987). But very little of this research is connected to energy-re- the home, and the structure that defines the provision of energy. lated research in meaningful ways that illustrates the critical im- The conceptualization of fuel poverty as an energy justice portance of place to the presence of energy efficiency disparities concern speaks to the energy-related distribution, procedure, and and fuel poverty vulnerability. recognition of “what constitutes the basic rights and entitlements This paper uses publicly available data to model residential of sufficient and healthy everyday life” (Walker and Day, 2012). heating energy efficiency, as a function of various housing and Consequently, fuel poverty violates the basic principle of dis- household characteristics for a tri-county metropolitan area. The tributive justice. Distributive justice is the idea that all members of study extends previous energy consumption and social justice society have the right to equal treatment, and that outcomes oriented research by predicting small-area estimation of end use should be fairly distributed, and provides moral guidance for the energy efficiency, and then examining racial/ethnic and socio- political processes and structures that affect the distribution of economic relationships. This analysis not only furthers our un- economic benefits and burden across and within society (Rawls, derstanding of the dynamics and distribution of energy efficiency 1971; Sen, 1999 Schlosberg, 2013). As a distributive injustice, fuel disparities, it has practical applications that may assist policy- poverty results from three interconnected inequalities: income makers and practitioners with developing and implementing more inequality, inequality in energy prices, and inequalities in housing equitable, efficient, and effective targeting of energy assistance and energy efficiency (Walker and Day, 2012). Although funda- programs and weather-related vulnerability prevention activities. mentally, fuel poverty is a problem of distributional injustice, its This study seeks to answer two research questions. First, does production and persistence are also the result of an injustice in residential heating energy efficiency vary within a metropolitan recognition of the specific energy-related needs of vulnerable area? And if so, what are the spatial characteristics of that varia- populations, and procedural injustice related to access to in- tion? Second, what are the patterns of association between re- formation, meaningful participation in decision-making, and ac- sidential heating energy efficiency and racial/ethnic, and socio- cess to legal processes for achieving redress or challenging deci- economic characteristics? The remainder of the paper summarizes sion-making processes (Walker and Day, 2012). the modeling and mapping of residential heating energy efficiency Addressing the distributive injustice of fuel poverty requires and analysis of the spatial, racial/ethnic, and socioeconomic pat- first determining what should be fairly distributed. Since in- terns. Section 2 describes the study area, and methods for devel- equalities in income and energy prices require larger social and oping a model for heating energy efficiency and small-area pre- economic solutions, residential energy efficiency retrofits have dictions. Section 3 presents the results of the geographic and become a key fuel poverty intervention strategy (Howden-Chap- statistical analyses. Section 4 concludes with policy implications. man et al., 2007, Howden-Chapman et al., 2009, Bird and Her- nández 2012, Gibson et al., 2011, Harrison and Popke, 2011). However, the absence of easily accessible data on individual 2. Methodology household energy consumption and efficiency, and an incomplete understanding of the spatial distribution of vulnerability presents 2.1. Description of study area an impediment to effectively targeting those most in need (Walker et al., 2013; Sefton, 2002). Recently, scholars have conducted Kansas City is the largest city in the State of Missouri and lies small-scale, area-based studies using readily available public data mostly in Jackson, Clay, and Platte counties (see Fig. 1). This tri- and geographic information systems (GIS) to offer visualizations of county region also represents the service area for United Services, U-20471 Official Exhibits of Soulardarity Exhibit SOU-24 Page 3 of 10 T.G. Reames / Energy Policy 97 (2016) 549–558 551

Fig. 1. Study area: Kansas City, Missouri (Jackson, Clay and Platte counties). one of nation's roughly 1000 Community Action Agencies (CAAs). According to the 2010 decennial census, the counties had a CAAs are mostly nonprofit, anti-poverty social service organiza- total population of 985,419 in 398,124 households. The area covers tions covering nearly 96% of US counties. CAAs are responsible for urban, suburban, and rural landscapes. In addition to the urbani- administering federal low-income energy assistance programs, zation gradient, socioeconomic characteristics in the area vary such as, the Department of Health and Human Services Low-in- greatly. Median block group income ranged from $14,250 to come Home Energy Assistance Program which provides utility bill $154,250. The household racial composition included 77.1% White assistance and the Department of Energy Weatherization Assis- households, 17.3% Black households, and 5.2% Hispanic house- tance Program which provides no-cost energy efficiency retrofits. holds, as identified by the head of household. Kansas City is con- According to Building America, which determines building prac- sistently identified as one of the nation's twenty-five most racially tices based on climate zones to achieve the most energy savings in segregated metropolitan areas due to its high placement on a a home, the counties are located in Climate Zone 4, which has a range of housing segregation indices, most recently ranking 23rd range of 4000–5499 heating degree days (HDDs) annually, and based on black-white segregation (Logan and Stults, 2011; Denton, where the average monthly outdoor temperature drops below 1994; Massey and Denton, 1993). Kansas City also exhibits a high, 47 °F(7°C) during the winter (U.S. Department of Energy, 2015).1 and increasing, level of residential segregation by income. Ac- Hence, homes in the area exhibit relatively high usage of heating cording to Pew Research on Social and Demographic Trends, equipment. In fact, space heating accounts for 41% of total Kansas City's Residential Income Segregation Index score in- household energy consumption in Missouri. The main heating fuel creased from 38 in 1980 to 47 in 2010 (Fry and Taylor, 2012). sources are natural gas (52%) and electricity (35%). Overall, the average Missouri household total energy consumption is roughly 2.2. Data 100 million BTUs per year, approximately 12% more than the national average (EIA, 2013a). In the absence of detailed individual household energy data, the EIA's Residential Energy Consumption Survey (RECS) provides household-level energy consumption data for a representative 1 Climate zones range from 1 (warmest) to 7 (coldest). Heating degree days sample of occupied, primary residences in the US. The RECS em- (HDDs), commonly used in calculations relating to the energy consumption required to heat buildings, is a measurement of the difference in temperature be- ploys a multi-stage area probability design to ensure the selection tween the mean outdoor temperature, over a 24-h period, and a given base tem- of a representative sample of housing units, carefully controlled at perature for if a building's indoor temperature fell below would require heating, specified levels of precision, to allow analysis of housing unit ° ° typically 65 F(18 C) in the US. For example, if the mean outdoor temperature for a characteristics and energy consumption and expenditures at the day is 35 °F, the HDDs measurement for that day is 6535¼30. Essentially, areas with a larger number of HDDs have colder outdoor temperatures and require more following geographic levels: national, census region, census divi- energy for heating. sion, groups of states within a census division, and individual U-20471 Official Exhibits of Soulardarity Exhibit SOU-24 Page 4 of 10 552 T.G. Reames / Energy Policy 97 (2016) 549–558 states (EIA, 2013b). The RECS, first conducted in 1978, collects data 2.3. Specifying a robust regression model for heating energy on energy consumption, expenditure and behavior along with a efficiency number of household demographics and housing unit characteristics. In the past, the RECS sample size has not been particularly The ordinary least square (OLS) method was used to analyze useful for analyzing energy patterns at spatial scales lower than how housing unit and household characteristics in fluence re- the census region, except for the most populous US states; Cali- sidential heating energy efficiency. Heating energy efficiency is fornia, Texas, New York, and Florida. The 13th iteration of the operationalized as annual heating energy use intensity (EUI). survey, conducted in 2009 and released in 2013, nearly tripled in Generally, a lower EUI signifies relatively efficient performance. sample size to 12,083 housing units (up from 4382 in 2005) re- The EUI is defined as the quantity of energy used in producing a presenting the US Census Bureau's statistical estimate of 113.6 given level of service, expressed as energy consumed per unit of million occupied primary residences. Subsequently, the 2009 RECS output. The heating EUI (kBtu/m2) was calculated for each RECS allows for additional state-level analysis with the collection of observation by dividing the total annual heating consumption representative samples in 12 additional states, including Missouri. (kBtu) by the housing unit square area (m2). Trained interviewers A sample of 686 households were surveyed to represent the 2.35 use a standardized method for measuring and collecting the di- million occupied housing units in Missouri. For geographic domain mensions of the housing unit. Total annual heating consumption is estimation purposes, base sampling weights were applied to each the aggregation of a household's space heating consumption from housing unit, which was the reciprocal of the probability of se- all fuel types (i.e. natural gas, electricity, liquefied petroleum gas lection into the sample and is the number of households in the (LPG), fuel oil, and/or kerosene). The RECS captures consumption population each observation represents (EIA, 2013b). Each sam- data from actual utility bills. Of the Missouri RECS sample, 676 pling weight value was used as a weighting factor in the weighted observations had total annual heating consumption greater than regression model. zero kBtu. Another observation was dropped as it was the only Data for spatial modeling and mapping of the study area were housing unit in the sample reporting fuel oil/kerosene as the pri- obtained from the U.S. Census Bureau 2006–2010 American mary heating source. Fuel oil/kerosene are not major sources of Community Survey (ACS) 5-year estimates. The census block group heat in the tri-county area; only 0.09% of homes use fuel oil/ker- was used as the unit of analysis for this research. Census block osene as their primary heating source (US Census 2016). Upon groups are a contiguous cluster of blocks within a census tract and testing for outliers, an additional observation was dropped that generally consist of between 600–3000 people. The census block exhibited an extremely high EUI for a relatively small footprint. group is the smallest spatial resolution for which household and The final data set consisted of a sample of 674 Missouri housing 2 housing unit characteristics similar to RECS variables are publically units. available from the U.S. Census Bureau. In addition, it is assumed The OLS model can be formulated as, that physical and social homogeneity are more likely at the smaller n block group level than larger spatial levels, such as, census tracts lnE =+ββχ0,∑ iiRECS * +ε or zip codes. A GIS data layer of census block groups for the study i area was created by clipping data from the U.S. Census Bureau where E is the annual heating EUI, and χiREC, S is the predictor TIGER/Line Shapefiles with demographic and economic data from variable χi from the RECS dataset (Min et al., 2010). The dependent the 2006–2010 ACS 5-year estimates. Block groups were retained variable was natural logged to better fit the nonlinear relationship for analysis only if data values for both population and number of between heating EUI and the independent variables (Min et al., occupied housing units were greater than zero. Subsequently, 757 2010; Ewing and Rong, 2008). of 763 block groups in the three-county study area were included Since many of the predictors of heating EUI are themselves in this analysis. correlated, it is important to consider their simultaneous effects The RECS microdata set can be used to develop a bottom up using multivariate analysis techniques. This approach therefore statistical model. Bottom up statistical models use input data at a requires determining the best subset of predictors of heating EUI. granular level, such as a sample of individual households, for ex- Initial selection of independent variables was guided by previous trapolation to a geographic area of interest. These statistical studies using OLS to understand residential energy consumption. models have been used to establish relationships between various The two major themes on factors that contribute to residential characteristics of household energy consumption (i.e. specific end energy consumption are categorized as the physical-technical- use consumption, total consumption, energy use intensity) while economic model (PTEM) and the lifestyle and social-behavior controlling for exogenous variables such as housing unit char- tradition (LSB) (Adua and Sharp, 2011). Many models include acteristics, household characteristics, urban form and climatic variables from the PTEM perspective which explains energy con- conditions (Min et al., 2010; Ewing and Rong, 2008; Tso and Yau, sumption as a result of housing unit characteristics, or the buil- 2007). Min et al. (2010) developed a statistical framework for ding's physical structure and equipment characteristics, and eco- modeling residential space heating (and other end use) con- nomic and environmental factors. These variables include: type of sumption at a zip code- level resolution using the 2005 RECS home, year home built, home size, household income, price of microdata. Their results were validated against residential energy energy, geographic location, and climate variables (Ewing and sales data. This study extends their framework to estimate re- Rong, 2008; Min et al., 2010; Adua and Sharp, 2011, Valenzuela sidential heating efficiency by creating a state-level regression et al., 2014). The LSB tradition draws on the importance of human model using the Missouri sample of housing units in the 2009 occupants to energy consumption, or household characteristics. RECS microdata set and exploring small-area spatial, racial/ethnic, LSB-related variables often include: race/ethnicity, household size, and socioeconomic patterns. Since many of the variables identified age of householder, and sex of householder (Ewing and Rong, in the RECS can also be found in the Census ACS, relationships 2008; Min et al., 2010; Adua and Sharp, 2011, Valenzuela et al., derived from the statistical model, known as direct estimators, can be applied to the block group level dataset as indirect estimators 2 fi for constructing small-area estimates, under the assumption that A sample size of 674 can predict with accuracy at a 95% con dence interval and 74 confidence level, for 2,339,684 housing units (population size). Based on the small areas have the same characteristics as the large areas the assigned sampling weights, the final sample represents 2,286,868 housing (Rao and Molina, 2015). The next two sections detail this process. units. U-20471 Official Exhibits of Soulardarity Exhibit SOU-24 Page 5 of 10 T.G. Reames / Energy Policy 97 (2016) 549–558 553

Table 1 5-year estimates. The derived regression weights are therefore OLS regression model for small-scale heating EUI estimation. intended to reflect the observed pattern of influence at the household level, which is essential to the small area estimation. DV ¼ ln (EUI ) Coeff. Robust Std. Err. heat fi Regression coef cients βi are applied to block group level data, Type of Housing χiCENSU, S, for each of the 757 block groups in the study area (Min Multi-Family Reference et al., 2010), using ARCMap (v.10.3.1) software (ESRI, Inc) to predict *** Mobile Home 0.68 0.09 ^ Single Family Dettached – block group level heating EUI estimates E: – Single Family Attached ^ lnE = ββχ^ + ∑ ^* Decade Constructed 0,.iiCENSUS i Before 1950 Reference 1950s – Since this modeling approach involves matching two different *** 1960s -0.24 0.07 datasets (RECS and ACS), these sources must first be harmonized 1970s -0.18** 0.07 1980s -0.34*** 0.08 with respect to their measurement and weighting. Each census 1990s -0.26*** 0.07 variable was weighted by the percentage (or ratio) of its presence 2000s -0.29*** 0.07 in the Census block group. For example, if the number of housing Primary Heat units heated by electricity in census block group 1 is 100 and the Natural Gas Reference block group has 200 housing units, the variable is standardized as *** Electricity -1.10 0.05 100/200¼0.5, which is comparable to the binary variable for Wood -2.07*** 0.23 Liquid Petroleum Gas – whether or not an observation in the RECS data set uses electricity as its primary heating source. The ratio for each block group is Control Variables then multiplied by the coefficient for electricity from the regres- Household Income -0.03* 0.01 Home ownership -0.15** 0.05 sion model. *** ^ No. of rooms -0.09 0.01 Lastly, to simply exponentiate the log-linear model, lnE, will Model Statistics systematically underestimate the expected value of EUI, thus the *** Intercept 6.57 0.08 ⎛ RMSE2 ⎞ scaling value exp⎜ ⎟ is needed (Wooldridge, 2009: 211). RMSE N674 ⎝ 2 ⎠ F (11, 662) 85.9*** 2 is the root mean square error of the model. From the estimated log Adjusted R 0.62 ^ RMSE 0.523 values lnE, the actual estimated EUI is obtained by the equation

⎛ 2 ⎞ -dropped from stepwise regression ^ RMSE ^ E =*(exp⎜ ⎟ exp lnE) . * Significance p o0.05. ⎝ 2 ⎠ ** Significance p o0.01. *** Significance p o0.001. 2.5. Statistical analysis 2014). For this model, variables representing housing unit char- The relationships between the predicted mean block group acteristic included three dummy-coded variables for housing type heating EUI and measures of race/ethnicity, and socioeconomic (mobile home, single family detached, and single family attached, status are examined using bivariate and multivariate analyses. with multifamily as the reference category), six dummy-coded First, correlation analysis was conducted between heating EUI and variables for decade constructed (1950s through 2000s, with demographic and socioeconomic characteristics. Next multivariate homes built before 1950 as the reference category), and three regression was used to explore the relationship between predicted dummy-coded variables for primary heating fuel (liquid petroleum heating EUI and block group racial/ethnic and socioeconomic gas (LPG), electricity, and wood, with natural gas as the reference characteristics. Lastly, logistic regression was used to model how category). Household characteristic variables included one interval the proportion of racial/ethnic minority headed households, and variables for number of rooms, one categorical variable for other block group socioeconomic characteristics affect the prob- household income (divided into eight categories), and one dum- fi my-coded variable for home ownership coded as “1″, otherwise ability of block group vulnerability, thus prime for energy ef - “0″. Final model selection of independent variables was based ciency intervention targeting. upon backward stepwise selection.

2.4. Utilizing census data for small area heating EUI estimation 3. Results

Since the goal of this study is to explore heating energy effi- The final regression model for estimating annual heating EUI, ciency at a geographical domain smaller than the RECS microdata expressed as natural log, is presented in Table 1. The final model (collected with adequate precision at the state-level), the second consisted of 11 statistically significant variables representing step involves using the model above to estimate and map heating housing unit type, decade housing unit was constructed, primary EUI for Kansas City. This technique, known as small-area estima- heating fuel, and control variables for household income, home tion, combines individual level data (i.e. household surveys) and ownership, and housing unit size. The model explained a con- spatial characteristic estimates (i.e. Census data). There have been siderable proportion of variability in heating EUI (R2 ¼0.62, F(11, significant theoretical advances in small-area estimation meth- 662)¼85.9, po0.001). Based on the F value of the model, the final odologies for modeling and mapping (Fay and Herriot, 1979; sample size of 674 is large enough to make the model significant. Fahmy et al., 2011; Rao and Molina, 2015). To accomplish this, Cross-sectional studies are at greater risk of exhibiting hetero- resultant weights derived from the regression model are applied skedasticity. Weighted regression is one method to correct re- to spatial data (e.g., housing units by type, housing units built in siduals and the model's residual versus fit plot exhibits a constant each decade, housing units using each fuel type for heating, variance and shows no evidence of heteroskdasticity. Additionally, median household income), from the US Census 2006–2010 ACS robust standard errors were used and are reported in Table 1 U-20471 Official Exhibits of Soulardarity Exhibit SOU-24 Page 6 of 10 554 T.G. Reames / Energy Policy 97 (2016) 549–558

Fig. 2. Predicted block group mean annual heating EUI (kBtus/m2).

(Wooldridge, 2009). Multicollinearity can also be a major problem Table 2 for statistical models of residential energy use, and can result in Pearson's correlation between race/ethnicity, socioeconomics and predicted heat- poor predictions of certain end uses (Swan and Ugursal, 2009). ing energy use intensity (EUI). Multicollinearity commonly arises with variables that tend to be Category Description Pearson's correlated, such as household income and housing unit size. correlation However, correlations between any two variables in the final model did not exceed 0.45, and the variance inflation factor is 1.32. Economic status Median household income -0.62 Percent households below poverty 0.47 Thus, the model did not indicate a noticeable presence of level multicollinearity. Education Percent population with less than 0.51 Fig. 2 illustrates the spatial distribution, in quintiles, of the high school diploma predicted mean annual heating EUI for each block group, darker Age Percent households with householder 0.12 shading represents higher predicted heating EUI. The six unin- aged 65þ habited block groups were left uncolored. It is important to note Race/Ethnicity Percent white householders -0.37 fl Percent black householders 0.32 that predicted values re ect the mean heating EUI of all housing Percent Hispanic householders 0.31 units in the block group rather than any specific house (Min et al., Tenure Percent renters 0.40 2010). Among the 757 block groups there was significant differ- 2 ence in values of heating EUI, ranging from 88 to 481 kBtus/m . All coefficients significant at po0.001 The metropolitan mean heating EUI, 269.6 kBtu/m2 (SD¼66.7 k/ 2 Btus/m ), was higher than the state mean heating EUI, 218.9 kBtus/ Pearson correlations, shown in Table 2, revealed statistically m2. The heating EUI variation, nearly 400 kBtus/m2, is quite large. significant relationships between socioeconomics, race/ethnicity This means that within the same metropolitan region, homes in and predicted heating EUI (po0.001). Heating EUI is positively some areas were far less efficient than others. While block groups correlated with block groups with a higher number of adults with higher heating EUIs are scattered throughout the three without a diploma (0.51), higher number of households in poverty counties, the majority of block groups with the highest EUIs were (0.47), more renters (0.40), more Black householders (0.32), more concentrated within the Kansas City limits and its urban core. Of Hispanic householders (0.31), and more senior householders the 151 block groups with the highest (fifth quintile) predicted (0.12). Furthermore, heating EUI was negatively correlated with heating EUI, 119 (78.8%) were located within the city limits. median household income (0.62) and percentage of White U-20471 Official Exhibits of Soulardarity Exhibit SOU-24 Page 7 of 10 T.G. Reames / Energy Policy 97 (2016) 549–558 555

Table 3 Relationship between estimated heating EUI and block group race/ethnicity, segregration and socioeconomic characteristics.

Model 1 Model 2 Model 3 Model 4 b S.E. b S.E. b S.E. b S.E.

Percent black householders 0.75*** 0.07 0.19* 0.09 Percent Hispanic householders 2.58*** 0.29 0.71* 0.32 Percent households below poverty level 1.24*** 0.20 Percent population with less than high school diploma 1.47*** 0.28 Percent households with householder aged 65þ 0.75*** 0.17 Black residential segregation 90.93*** 7.19 37.09*** 9.19 Hispanic residential segregation 238.68*** 22.03 94.27** 29.92 Proportion households below poverty level 98.37*** 22.87 Proportion population with less than high school diploma 146.14*** 29.97 Proportion households with householder aged 65þ 64.32*** 16.89 Intercept 240.13*** 3.29 210.56*** 4.75 232.34*** 3.39 210.09*** 4.82 N 757 757 757 757 R2 0.21 0.33 0.23 0.33

* Significance po0.05. ** Significance po0.01. *** Significance po0.001. householders (0.37). Thus, census block groups with lower so- built environment (Anthopolos et al., 2011). Model 3 shows that cioeconomics, lower median household incomes, and higher per- RRS has a strong positive relationship with heating EUI. Each unit centages of Black or Hispanic households are more likely to have increase in Black isolation increases heating EUI by roughly higher heating EUIs. Additionally, Kruskal-Wallis tests were con- 91 kBtu/m2. Hispanic isolation has an even greater effect on ducted to determine if heating EUI was different among block heating EUI. Every unit increase in Hispanic isolation increases groups divided into quintiles by the socioeconomic and race/eth- heating EUI 239 kBtu/m2. In Model 4 the relationship between nicity variables of interest. Individual Kruskal-Wallis tests showed segregation and heating EUI remains strong even after controlling there were statistically significant differences in heating EUI be- for the socioeconomic characteristics of the block group. Given tween the quintiles of median household income (χ2¼330.9), that the isolation index is a value between 0 and 1, the socio- percent poverty (χ2 ¼171.1), percent less high school education economic block group characteristics in Model 4 are in proportions (χ2 ¼195.2), percent senior headed households (χ2¼20.2), percent rather than percentages. The Black and Hispanic isolation indexes renters (χ2 ¼168.2), percent White householders (χ2 ¼78.1), per- maintain a strong positive relationship with heating EUI but are cent Black householders(χ2¼97.2), and percent Hispanic house- slightly moderated by block group socioeconomic characteristics. holders (χ2¼94.7), (DF¼4, po0.001). Once socioeconomic characteristics- poverty (t¼4.3), less high Regression models examining how race/ethnicity are related to school (t¼4.9), senior households (t¼3.8)- are taken into account, heating EUI are shown in Table 3. Model 1 in Table 3 shows this the effect that a unit increase in Black and Hispanic isolation in- relationship when socioeconomic characteristics of the block creases heating EUI drops to 37 (t¼4.0) and 94 (t¼3.2) kBtu/m2, group are not taken into account. This model reveals a strong re- respectively. lationship between race/ethnicity and heating EUI. The model Fig. 3 illustrates the spatial distribution of high-risk block shows that as the percentage of Black households and Hispanic groups, which would be prime candidates for energy efficiency households in a block group increase, heating EUI increases by interventions. High-risk block groups are defined as those where 0.75 and 2.58 kBtu/m2, respectively. predicted heating EUI was greater than study area mean The second model in Table 3 (Model 2) shows how race/eth- (269.6 kBtu/m2), median year home built was less than the study nicity are related to heating EUI when the effects of socioeconomic area mean (1966.5), and median household income was less than characteristics of the block group (percent poverty, percent less the study area mean ($51411.50). There were 263 block groups than high school diploma and percent senior householders) are meeting these criteria (34.7% of block groups). More than a quarter held constant. In this model, while the positive relationship be- of the area's population (26.6%) resided in high-risk block groups. tween race/ethnicity and heating EUI remain, as in Model 1, the The racial composition included 49.7% of the Black population, effects are moderated by the socioeconomic characteristics of the 46.9% of the Hispanic population, and 18.7% of the White popu- block group with percent of households below poverty, percent of lation. Black and Hispanic households within the high-risk block population with less than a high school diploma, and percent se- groups are highly overrepresented compared to their representa- nior headed households having a larger effect on heating EUI, 1.24 tion within the entire study area (29.6% Black, and 8.6% Hispanic), (t¼6.3), 1.47 (t¼5.4), and 0.75 (t¼4.5) kBtu/m2, respectively. After while White households are underrepresented (62.4%). If there controlling for socioeconomics, the effect of a percent increase in were no disparities in heating EUI this would not be the case. Black or Hispanic households increasing a block group's heating To understand the odds that the racial/ethnic and socio- EUI drops to 0.19 (t¼2.2) and 0.71 (t¼2.2) kBtu/m2, respectively. economic characteristics of a block group contribute to that block The final two models reported in Table 3 (Models 3 and 4) group's likelihood of being high-risk, logistic regression results are exchange the percentage of Black and Hispanic households in the presented in Table 4. Table 4 suggests that a 10% difference in block group with a measure of the block group's level of Black and percent households in poverty increased the odds by 2.7% Hispanic racial residential segregation (RRS). The RRS, a measure (po0.01) that the block group is high-risk. Racial/ethnic char- of the geographic isolation of race/ethnicity from other racial acteristics (percentages of Black and Hispanic households) are groups (Massey and Denton, 1993, Reardon and O’Sullivan, 2004, significant predictors of high-risk block groups (po0.001). For Anthopolos et al., 2011). RRS has received increased attention as a instance, a 10% increase in Hispanic households increased the major social determinant in poor outcomes (i.e. health effects) and high-risk odds by a factor of 10.8. Logistic regression results may be a proxy for concentrated neighborhood disadvantage, in- showed that high-risk block groups are poorer, have less educa- cluding exposure to socio-physical environmental stressors in the tional attainment, have more households headed by seniors, and U-20471 Official Exhibits of Soulardarity Exhibit SOU-24 Page 8 of 10 556 T.G. Reames / Energy Policy 97 (2016) 549–558

Fig. 3. High-risk block groups. High-risk block groups are deﬁned as those where heating EUI, median age of home, and median household income were worse than the study area average. There are 263 high-risk block groups identiﬁed.

Table 4 higher EUI signals relatively less efﬁciency when compared to si- Logistic regression – high-risk block groups. milar sized homes. Predictions reveal that block groups with lower median incomes, a greater percentage of households below pov- Odds ratio S.E. erty, a greater percentage of racial/ethnic minority headed Percent black householders 1.014*** 0.004 households, and a larger percentage of the population with less Percent Hispanic householders 1.079*** 0.023 than a high school education experienced higher mean heating ** Percent households below poverty level 1.027 0.010 EUIs. Essentially, homes in block groups exhibiting these demo- Percent population with less than high school diploma 1.050*** 0.013 Percent households with householder aged 65þ 1.021** 0.008 graphic and socioeconomic characteristics are more likely to be Intercept 0.060*** less energy efﬁcient when compared to other block groups in the Pseudo R2 0.24 region. N757This analysis also reveals an association between the enduring

*Significance po0.05 effects of residential racial and income segregation and the dis- fi ** Significance po0.01. tribution of residential energy disparities. The gures above il- *** Significance po0.001. lustrate that past institutionalized residential segregation continues to influence urban housing consumption and translates have greater percentages of Black and Hispanic households. directly to energy-related disparities. Urban sociologists often associate residential segregation with concentrated social and economic disadvantage (Sharkey, 2013; Sampson, 2012; Klinenberg, 4. Conclusion and policy implications 2002). The results of this study follow decade-old reports by two major African American organizations about the relationship be- This study estimated the mean heating EUI for 757 census block tween Blacks, energy and climate change. Both the Congressional groups in Kansas City, Missouri (Jackson, Clay, and Platte counties). Black Congress Foundation and the American Association of Blacks The findings demonstrate that disparities exist in the relationships in Energy released reports in 2004 assessing the disproportionate between the spatial, racial/ethnic, and socioeconomic character- effects of energy inequities on Blacks. Since these reports, there istics of census block groups and the estimated mean block group has been little research conducted on this issue and virtually heating EUI (kBtu/m2), a proxy for energy efficiency where a no policy advances. Recognizing that the uneven development U-20471 Official Exhibits of Soulardarity Exhibit SOU-24 Page 9 of 10 T.G. Reames / Energy Policy 97 (2016) 549–558 557 patterns and high levels of residential segregation evident in the rollout was slow and inconsistent (Grunwald, 2012). In part, Kansas City occur in other US urban areas, such as St. Louis and the lack of comprehensive accounting of local energy consumption Detroit, this study should be replicated to explore if similar energy and efficiency disparities, forced weatherization agencies to rely disparity patterns exist and determine the need for a national on prevailing practices of first-come, first-served self-referral op- urban energy justice policy. erating procedures (Fuller et al., 2010; Madrid and James, 2012). A Space heating remains the largest, single end use, accounting growing body of research demonstrates that the spatial con- for 41% of residential energy consumption (EIA, 2013c). Modeling centration of fuel poverty risk factors, justifies taking proactive, the efficiency of residential space heating (and cooling) is im- targeted, area- or community-based approaches for implementing portant because of its responsiveness to weather. Prioritizing energy assistance programs to overcome participation barriers, heating energy efficiency and targeting building envelope retrofits, including those that are social and cultural, and to more efficiently before appliance and lighting efficiency, may have greater poten- and effectively deliver services in vulnerable communities tial as the lifespan of a housing unit most likely outlasts the cur- (Reames, 2016; Walker et al., 2013; Hallinan et al., 2012). rent occupant and appliances. Additionally, in dominant discus- Moreover, modeling energy use intensity rather than total en- sions on climate change, global warming specifically, winter ergy consumption provides more meaningful information for weather and cold conditions receive far less attention. Never- analyzing disparities and targeting the most appropriate inter- theless, recent studies have found that the effects of global vention to the appropriate location. The residential sector has warming (i.e. the loss of Arctic sea ice) can be linked to extreme made energy efficiency progress, continuing a three-decade de- and prolonged cold weather patterns in mid-latitudes, such as the cline in average consumption per home even as the number and cold spells experienced by northeastern and Midwestern states average size of housing units increase. This trend is primarily a during the polar vortex of winter 2014 (Peings and Magnusdottir, result of efficiency improvements for newer homes. While ag- 2014, Tang, 2013, Francis and Vavrus, 2012). Subsequently, as cli- gregate residential sector statistics and analyses are useful for mate change adaptation discourse becomes more prevalent, it is policy and program development, they often mask the hetero- necessary to understand the material experience of changing en- geneity of energy users, resulting in a lack of equity considera- vironmental conditions, the effect on everyday life, and the po- tions. The use of bottom-up statistical models and mapping, ex- tential ways in which communities are threatened (Schlosberg, trapolated to smaller-scale spatial areas allows a more nuanced 2013). analysis of energy consumption. While several energy-mapping Furthermore, energy related disparities increase the sensitivity projects are in various stages of development and implementation of low-income and other vulnerable households to extreme tem- across the nation (e.g., Twin Cities Energy Mapping Tool in Min- perature exposure resulting in detrimental health implications nesota), a barrier to more of these projects remains the proprietary (Noe, Jin and Wolkin, 2012; Centers for Disease Control [CDC], nature of individual energy data, as utilities express concerns 2006; Taylor et al., 2001). The Centers for Disease Control (CDC) about customer privacy, or have little incentive to participate in found that between 2006 and 2010, 63% of weather-related deaths projects that have the potential reduce revenue. In the meantime, were attributed to extreme cold exposure, compared to 31% at- using readily available public data and the methodological pro- tributed to heat-related causes (Berko et al., 2014). Weather-re- cedures presented in this study, offer an alternative for community lated death rates varied by age, race/ethnicity, sex, location, and energy mapping when local utility energy data are unavailable. income (Berko et al., 2014). For vulnerable populations like the elderly, extremely cold temperatures can be deadly, even indoors. Elderly patients admitted to the intensive care unit for hy- References pothermia are more severely affected and die more frequently when found indoors compared to those found outside with Adua, L., Sharp, J.S., 2011. Explaining residential energy consumption: a focus on equivalent body temperatures (Mégarbane et al., 2000). In another location and race differences in natural gas use. J. Rural Soc. Sci. 26 (1), 107–141. study, almost half of hypothermia-related deaths occurred in- Anderson, W., et al., 2012. Coping with low incomes and cold homes. Energy Policy 49, 40–52. doors, with death rates particularly high among Blacks aged 80 Anthopolos, R., James, S.A., Gelfand, A.E., Miranda, M.L., 2011. A spatial measure of years or older (Taylor et al., 2001). Despite these findings, there is a neighborhood level racial isolation applied to low birthweight, preterm birth, lack of recognition of the magnitude of problems associated with and birthweight in North Carolina. Spat. Spatio-Tempo. Epidemiol. 2 (4), 235–246. dangerous indoor temperatures when homes are not adequately Berko, Jeffrey, Ingram, Deborah D., Saha, Shubhayu, Parker, Jennifer D., 2014. Deaths heated. Instead, public health agencies often issue broad cold- attributed to heat, cold, and other weather events in the United States, 2006– – weather injury risk reduction precautions primarily focused on 2010. Natl. Health Stat. Rep. 76, 1 16. Bird, S., Hernández, D., 2012. Policy options for the split incentive: increasing en- outdoor protection, like layering clothes and keeping emergency ergy efficiency for low-income renters. Energy Policy 48, 506–514. kits and blankets in the car (CDC, 2006). Mapping heating energy Boardman, B., 2012. Fuel poverty synthesis: lessons learned, action needed. Energy efficiency can be combined with hypothermia health data for ad- Policy 49, 143–148. fi Buzar, S., 2007. Energy poverty in Eastern Europe: Hidden Geographies of Depri- ditional analysis on the connection between ef ciency and winter- vation. Ashgate Publishing, Ltd.. related injuries and death. Centers for Disease Control (CDC), 2006. Hypothermia-Related Deaths – United To the disadvantage of the millions of Americas who struggle to States, 1999–2002 and 2005. Cent. Dis. Control 55 (10), 282–284 (Available from): 〈http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5510a5.htm〉. access and maintain affordable heating energy services, the con- Denton, Nancy, 1994. Are African-Americans Still Hypersegregated in 1990?. In: sequence of not identifying distinct forms of social inequality in Bullard, Robert, Lee, Charles, Grigsby III, J. Eugene (Eds.), Residential Apartheid: residential energy efficiency means more broad-based energy The American Legacy. UCLA Center For Afro-American Studies, Los Angeles. policies that fail to serve those with the greatest need. For in- Ewing, R., Rong, F., 2008. The impact of urban form on US residential energy use. Hous. Policy Debate 19 (1), 1–30. stance, the passage of the 2009 economic stimulus bill created Fahmy, E., Gordon, D., Patsios, D., 2011. 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ENERGY STORAGE (/ARTICLES/CATEGORY/STORAGE) Another California City Drops Gas Peaker in Favor of Clean Portfolio Glendale’s municipal utility quickly got comfortable with big batteries, distributed energy, efficiency and a few reciprocating engines.

JULIAN SPECTOR JULY 30, 2019

Glendale: Fastest energy transition ever?

The Southern California city of Glendale officially dropped a $500 million gas peaker project that it nearly approved last spring, and instead picked up the mantle of clean energy leadership.

The city council voted in April 2018 to pause development on the 262-megawatt repowering of the Grayson Power Plant and examine clean energy alternatives (https://www.greentechmedia.com/articles/read/glendale-shelves-500-million-gas-plant-to-examine- clean-alternatives#gs.su7q8m). Now, the municipal utility has completed an examination of 34 clean energy proposals and selected a diverse portfolio it says will meet reliability needs and save ratepayers $125 million compared to the old portfolio.

In other words, Glendale Water & Power (GWP) went through an energy transition in a little over a year.

"The future envisioned herein represents a complete transformation of the way GWP provides reliable, affordable and clean energy resources to the citizens of Glendale," the utility wrote in a new integrated resource plan (https://www.ci.glendale.ca.us/government/council_packets/CC_HA_072319/CC_8a_072319.pdf) approved last week.

When the earlier planning process started back in 2014, batteries were not on the menu of cost-effective options, so a recognized capacity need — in this case, the retirement of a plant that dates back to the 1940s — essentially guaranteed a gas plant solution. U-20471 Official Exhibits of Soulardarity Exhibit SOU-25 Page 2 of 4

"At that point in time, thinking about reliability, the storage market was still very much in its infancy and very expensive still," GWP General Manager Steve Zurn said in an interview.

Since then, large-scale batteries have become competitive, but so have networks of small-scale energy devices located in homes and businesses.

The final portfolio, proposed in Glendale Water & Power's new integrated resource plan, would repower the Grayson Power Plant with a 75-megawatt/300-megawatt-hour Tesla battery installation and up to 93 megawatts of fast-ramping Wärtsilä engines.

Customer-focused resources will add another 50 megawatts, including 12.8 megawatts from home solar and batteries installed by Sunrun, 10.5 megawatts of demand response by Franklin Energy and 20.4 megawatts of energy efficiency and demand response from Lime Energy Services. That demand reduction constitutes about 14 percent of the utility's roughly 350-megawatt peak load.

The new capacity was needed as backup in case the local grid lost its first- and second-largest power sources at the same time — not an outlandish possibility, given the fire risk in the dry hills surrounding the city. That role meant the expensive gas peaker would have had little to do most of the time.

Instead, the batteries, solar PV and efficiency investments will provide other benefits regularly, lowering peaks and reducing customer bills, in addition to serving local capacity during extreme events.

"It’s an astounding victory," said Earthjustice attorney Angela Johnson Meszaros, who testified against the original gas-plant proposal on behalf of the Sierra Club. "It really does highlight what it looks like when the community turns out and demands better. And good on the Glendale City Council for letting better happen."

Once the city council called for clean alternatives, GWP put its original plan on hold and got a request for clean proposals out and back in three months. Then the methodical vetting process began, which happened to coincide with the utility's new IRP deadline.

"It was like, 'OK, let’s do this; these are good points,'" Zurn recalled of the decision to set aside the old plan. "Nobody made a mistake; it was just that technologies have advanced and it’s worth stepping back and taking another look."

Wärtsilä's shift toward green energy

The final proposal does include some fossil fuel infrastructure, but the choice of Wärtsilä engines is notable. U-20471 Official Exhibits of Soulardarity Exhibit SOU-25 Page 3 of 4

The company, a Finnish manufacturer of engines for ships and power production, has adopted a long-term decarbonization strategy (https://www.greentechmedia.com/articles/read/wartsila- goes-green-loses-top-exec-to-highview-power#gs.sdn15m) that envisions running its equipment on synthetic biofuels one day. It also acquired energy storage integrator Greensmith and has been active in storage projects as another form of flexible power.

Similarly, GWP expects to be able to convert the engines to run on biogas, renewable natural gas or even hydrogen, depending on the commercial maturation of those fuels. In the meantime, 18.5-megawatt units give the utility more precision to meet peaks than firing up much larger turbines. And if it's possible to reduce the number of engines and still meet reliability needs, Zurn said he's happy to do that.

The city council gave preliminary approval for the new batch of contracts. Now, GWP has to finalize the contracts and conduct a new round of environmental review. The company is working toward earning final approval next spring, which would allow demolition at Grayson to start next summer.

With Grayson's original repowering off the table, viable new gas plant proposals appear to be extinct in California.

Calpine in May abandoned its Mission Rock peaker (https://www.greentechmedia.com/articles/read/calpine-drops-mission-rock-application-as-californias- gas-plant-pipeline-dw#gs.sdl4qv) on the Santa Clara River, and local opposition scuttled NRG's Puente Plant (https://www.greentechmedia.com/articles/read/commissioners-rejecting-puente-gas- plant#gs.sdlaj4), which would have occupied the beach at Oxnard. Los Angeles Mayor Garcetti canceled the renovation of three gas plants (https://www.greentechmedia.com/articles/read/garcetti-la-5-billion- rebuild-coastal-gas-plants#gs.sdllwz) in his city's municipal utility territory, committing to entirely clean energy instead.

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A community-based approach to low-income residential energy efﬁciency participation barriers Tony Gerard Reames School of Natural Resources & Environment, University of Michigan, Ann Arbor, MI, USA

ABSTRACT ARTICLE HISTORY Financial barriers are often cited as the principle impediment to the Received 26 August 2015 adoption of energy efficiency measures. Since 1976, the US Department Accepted 22 December 2015 of Energy’s Weatherisation Assistance Programme (WAP) has provided KEYWORDS state block grants for no-cost, low-income energy efficiency retrofits. Yet, Policy implementation; millions of low-income American households lack affordable, reliable, and fi community-based energy ef cient energy access. The American Recovery and Reinvestment Act of efficiency; weatherisation; 2009 boosted WAP’s annual appropriation from $230 million to $5 billion, American Recovery and requiring states to explore innovate approaches to quickly increasing Reinvestment Act programme participation. Community-based energy programmes have shown success for overcoming various barriers and increasing participation in the adoption of energy technologies. This case study explores a community-based approach to scaling WAP-funded energy efficiency retrofits in a cluster of five urban, low-income, majority African- American neighbourhoods, known as the Green Impact Zone (GIZ), in Kansas City, Missouri. Findings from interviews with GIZ stakeholders suggest that local context is important to how energy efficiency participation barriers manifest. The targeted, community-based approach to WAP created institutional capabilities for increased recognition of participation challenges and facilitated opportunities for alternative solutions that may otherwise have been overlooked under the standard self-referral implementation of WAP. Lastly, effective implementation of WAP required policy workarounds that recognised the unique characteristics and needs of the target community.

Introduction The US residential sector consumes approximately 21 quadrillion British thermal units (BTUs) per year, accounting for 22% of both the nation’s total energy consumption and energy-related CO2 emissions (US Energy Information Administration [EIA] 2011, 2012a, 2012b). Consequently, improving residential energy efﬁciency is widely acknowledged for its potential to save energy and reduce greenhouse gases. By 2030, residential energy efﬁciency efforts could save the US 6.4 quadrillion BTUs per year– a

30% reduction in energy use (National Academies 2010, p. 3). In a scenario evaluating CO2 emissions from the nine largest residential energy end-use services (heating and cooling systems, clothes washers and dryers, dishwashers, hot water heaters, stoves and ovens, refrigerators, freezers, and lighting), Azevedo et al. (2013) found that an overnight, full stock replacement of all major residential appliances, with the most efﬁcient model, could result in a 56% reduction in emissions attributable to residential consumption.

CONTACT Tony Gerard Reames [email protected] This article was originally published with errors. This version has been corrected. Please see Corrigendum 10.1080/135498 39.2016. 1166567

Complementary to environmental benefits are the economic and social benefits of energy efficiency efforts. Predictions of economic savings from energy efficiency are substantial. Analysts found that deployment of all net present value-positive energy efficiency improvements could save the residential sector $41 billion in annual energy costs by 2020 (McKinsey & Company 2009). Studies also show strong connections between energy efficiency interventions and improvements in health (Kuholski et al. 2010, Gibson et al. 2011, Howden-Chapman and Chapman 2012). On average, 63% of American households report having adequate or poor insulation, as opposed to their homes being well insulated; the health benefits from insulation retrofits would result in 240 fewer deaths, 6500 fewer asthma attacks, and health savings of $1.3 billion annually (Levy et al. 2003, EIA 2013a). The residential sector has made energy efficiency progress, continuing a three-decade decline in average consumption per home even as the number and average size of housing units increase (EIA 2012c). This trend is primarily a result of efficiency improvements in space heating, air conditioning, major appliances, insulation, and thermal envelope (e.g. double-pane windows) for newer homes (EIA 2012c). Recent Federal legislation has pursued energy efficiency efforts that benefit the residential sector. For example, both the Energy Policy Act of 2005 and the Energy Independence and Security Act of 2007 increased a number of efficiency standards, and the American Recovery and Reinvest- ment Act of 2009 (ARRA) directed $25 billion towards energy efficiency (Dixon et al. 2010, Alliance to Save Energy 2013). Yet, even in the presence of widely acknowledged benefits and federal funding, consumer adoption of energy efficiency technologies remains low, penetrating only a fraction of the potential market – 2% by some estimates (McKinsey & Company 2009, Michaels 2009). This wedge between the inherent benefits of energy efficiency and the level actually realised, or more broadly defined, the slower than socially optimal rate of energy efficiency technology diffusion, is known as the “energy efficiency gap” (Hirst and Brown 1990, Jaffe and Stavins 1994, Allcott and Greenstone 2012, Gillingham and Palmer 2014). Contributors to the energy efficiency gap are known as barriers and impede individual adoption of technologies and participation in programmes. Though treatments on the topic tend to categorise barriers differently, the overarching principles are generally agreed upon. Barriers are grouped in various categories to include market, social/cultural, institutional, behavioural, and political/regulatory (Hirst and Brown 1990, Brown 2004, Sovacool 2008, Sovacool 2009). The most commonly cited barriers to adoption of energy efficiency technologies include higher first cost, access to capital, information deficits, and split incentives (Anderson and Claxton 1982, Hirst and Brown 1990, Brown 2004, Sovacool 2008, Sovacool 2009).

Community-based energy projects To achieve full energy efficiency savings potential, participation in energy efficiency programmes must increase. Therefore, programmes designed and implemented to overcome barriers must acknowledge that complex decision-making processes guide energy choices and cannot be described using a simple rational-economic model (Wilk and Wilhite 1985, McKenzie-Mohr and Smith 2011, Anda and Temmen 2014). In response, there has been growing support for community-based (also known as area-based or place-based) energy projects which have shown moderate to significant effectiveness as a method for overcoming barriers to adoption and increasing participation (Hallinan et al. 2012). According to energy-sector non-profit, Wisconsin Energy Conservation Corporation, “community-based energy efficiency programmes foster social connectedness to trans- form the way people consume energy – relying on group interaction, peer support, and communal resolve to impact behavior” (Wisconsin Energy Conservation Corporation n.d.). Community-based energy projects recognise that individual barriers alone may not fully explain inaction on energy efficiency, but taken together they impede the potential for improvements and therefore must be addressed collectively. U-20471 Official Exhibits of Soulardarity Exhibit SOU-26 Page 3 of 19 LOCAL ENVIRONMENT 1451

Community-based energy projects are purported to support equity and justice. Catney et al. (2013) call for “community knowledge networks” as a way to recognise the broader social context (social relations and social practices) within which households use energy and make decisions, focusing on “community” as an approach to energy and justice. The key justice component of a community-based energy project is recognition. As Schlosberg (2007, p. 14) argued, a “lack of recognition in the social and political realms, demonstrated by various forms of insults, degradation, and deva- luation at both the individual and cultural level, inflicts damage to oppressed individuals and communities”. This is important as people tend to be economically and culturally place-bound and social deprivation is often concentrated in identifiable areas. Targeting these areas can be effective in addressing multiple problems. For example, African Americans experience much higher rates of housing and energy hardships than non-African Americans. When compared to white households, twice as many African Americans experienced eviction and were behind on their utility bills, and more than three times as many African Americans actually had their utilities cut off (Lerman and Zhang 2014). One contributing factor to these hardships may be that African Americans are more likely to live in less efficient homes. Exploring racial differences in energy consumption from 1993 to 2005, Adua and Sharp (2011) found that when compared to whites, African Americans lived in homes that were older, less well insulated, and less likely to have double pane windows. Conse- quently, African Americans consumed significantly more natural gas than whites per annum, even after controlling for housing characteristics (e.g. age of home, number of bedrooms, size, and type of housing unit) and investment in energy efficiency (e.g. insulation level, window types, and thermostat operated heat) (Adua and Sharp 2011). Thus, a community-based approach to energy efficiency targeting low-income, African-American communities could improve equity and justice by recognising the unique characteristics and needs of these communities, rather than the dominant broad- based, homogeneous view of energy users, which tends to undermine equitable programme development and implementation (Higgins and Lutzenhiser 1995, Walker and Day 2012). Community-based energy projects also create institutional capabilities. Institutional capabilities refer to the competence of an organisation to work effectively to deliver services, and recognise and respond to fluid conditions (Berry 2010). Berry (2010) suggested that the institutional capabilities created by community-based energy projects are based upon several factors: community involvement; access to volunteers; use of social networks for outreach; developing partnerships with other organisations; learning by doing; and attainment of sufficient scale. Community-based strategies generate demand through grass-roots mobilisation and community organisation, focusing on educating and empowering (Villao et al. 2012). Mobilising community members and utilising existing relationships and networks in a community enable disseminating information by “trusted mes- sengers” (Fuller et al. 2010, Villao et al. 2012). Community organisations often best understand local residents, their needs, assets, interests, how best to communicate with them, and how to motivate participation in energy programmes (Fuller 2009, Villao et al. 2012). As the application of community-based energy projects increases, most have targeted middle- and upper-income communities, resulting in creative mechanisms for overcoming participation barriers, such as, reducing the information deficit (e.g. exploiting existing social networks) and funding energy efficiency improvements (e.g. on-bill financing and low-interest loans) (Hallinan et al. 2012). Yet, we know little about using this approach in low-income communities, or with government-sponsored, no-cost programmes. Do barriers still exist if the greatest barrier, financing energy efficiency retrofits, is eliminated? It may seem straightforward to assume that little effort would be needed to encourage households to participate in a programme that provides free energy efficiency retrofits; however, this is far from the case (Higgins and Lutzenhiser 1995). As Stobaugh and Yergin (1979, p. 137) suggested, “[a]lthough some of the barriers are economic, they are in most cases institutional, political and social”. To this end, this study uses a case study approach to explore two primary research questions. First, what barriers to energy efficiency participation continue to manifest in the absence of financial impediments? Second, can a community-based approach effectively identify and overcome those barriers? It is common in the community-based energy programme literature to explore questions via U-20471 Official Exhibits of Soulardarity Exhibit SOU-26 Page 4 of 19 1452 T. G. REAMES case study (Hallinan et al. 2012). However, the context for this case study is unique, in that while community-based energy programmes are touted as a way to increase equity, few studies have explored cases of implementing free retrofits in urban, low-income, minority communities. In this study, community is defined geographically, and where energy efficiency efforts are being targeted and implemented by community organisations. In 1976, the US Department of Energy (DOE) began operating what is now the largest and longest running national energy efficiency programme for low-income households. The Weather- isation Assistance Programme (WAP) is a federally funded, state block grant created to increase energy efficiency, reduce energy expenditures, and improve health and safety, especially for vulnerable households such as those with children, persons with disabilities, and the elderly. Although more than 7.4 million households have received WAP retrofits over the last 40 years, this is just a fraction of the approximately 39.5 million eligible households (Oak Ridge National Laboratory [ORNL] 2014, National Association for State Community Services Programs 2015). Similar programmes that address fuel poverty exist globally, such as the Warm Front programme in the UK and the Warm Homes retrofit programme in Ireland. Fuel poverty (also known as, energy poverty or energy insecurity) is the inability of a household to afford adequate energy services, for heating and cooling, resulting in unhealthy indoor temperatures and accumulated debt (Board- man 1991, Harrison and Popke 2011,Liet al. 2014, Hernández 2015). Millions of American households are fuel poor – nearly 14 million households had unpaid utility bills, and another 2.2 million households experienced utility disconnects (U.S. Census 2013). Moreover, low-income households had a mean energy burden of 16.3% of household income compared to 3.5% for non-low-income households (ORNL 2014).1 Analysts consider an energy burden of greater than 6% to be unaffordable (Fisher, Sheehan, and Colton 2013). Thus, greater efforts towards expanding low-income energy efficiency programs are needed to help fuel poor households reduce their energy expenditures and improve overall quality of life (Hernández and Bird 2010, Harrison and Popke 2011). The ARRA boosted WAP’s annual appropriation from approximately $230 million to $5 billion, to be spent over a three-year period (ORNL 2015b). The ARRA-era funding with the general principle of “commencing expenditures and activities as quickly as possible”, created an immediate need to grow demand for energy efficiency retrofits in low-income communities.2 However, there was limited programme experience for scaling up low-income weatherisation, more than 1000%, in the midst of diminished state capacity as governors slashed administrative staff levels due to the economic recession, and a host of other political and bureaucratic challenges (Grunwald 2012, Carley et al. 2015, Terman 2015). With no proven formula for motivating massive WAP participation, states exercised considerable discretion in the strategies they used to meet performance goals and disperse their substantial increases in grant funds, such as increasing the number of local subgrantees (e.g. community action agencies, non-profit organisations, and local government agencies) and expanding multifamily unit retrofits (Carley et al. 2015, ORNL 2015b, Terman 2015). There is a large, international body of literature on the effectiveness of these kinds of interventions for increasing home energy efficiency and disposable income, increasing indoor comfort, reducing anxiety about fuel costs, and improving health (Howden-Chapman et al. 2007, Green and Gilbertson 2008, Howden-Chapman et al. 2009, Hernandez and Bird 2010, Kuholski et al. 2010, Gibson et al. 2011, Harrison and Popke 2011, Howden-Chapman and Chapman 2012). Analysis of WAP shows that every dollar invested in the programme returns $2.51 in energy savings and non-energy-related benefits (DOE 2010). On average, single-family homes retrofitted through the WAP had first-year energy savings of $223 (or 12%), and reduced CO2 emissions by 2.65 metric tons per year, per home (DOE 2010, ORNL 2015a).

Case study area and methods The case study object, the Green Impact Zone (GIZ) initiative in Kansas City, Missouri, was an ARRA- era, national model for place-based investment, demonstrating how concentrating resources in an U-20471 Official Exhibits of Soulardarity Exhibit SOU-26 Page 5 of 19 LOCAL ENVIRONMENT 1453 area with decades of disinvestment and neglect could lead to signiﬁcant, sustainable improvements. In April 2009, US Representative Emanuel Cleaver II of Missouri’s 5th Congressional District proposed leveraging $200 million in ARRA funding for a green-based urban renewal project in ﬁve co-located low-income, majority African-American neighbourhoods (see Figure 1). The GIZ neighbourhoods suf- fered from concentrated poverty, high unemployment, high vacancy rates, low population density, a lack of commercial services, deterioration of the physical environment, and high crime. A selection of socio-economic and demographic characteristics of the GIZ compared to that of Kansas City is shown in Table 1. The GIZ initiative operated from 1 September 2009 to 24 January 2014. The overarching vision was

to develop a sustainable community; one that is environmentally, economically and socially stronger tomorrow than it is today … using a comprehensive green strategy … coordinated programs with innovative delivery mechanisms … and intense resident engagement … to more rapidly push community change, build community capacity, and make the Green Impact Zone a place where people want to live, work and play, by focusing on eight priorities: housing, weatherisation, employment and training, infrastructure, energy efficiency, urban agriculture, public safety and community services, and youth.3 A major component of that vision was to weatherise every home, which needed it, in the 150-block zone (Brook- ings 2009). The Mid-America Regional Council (MARC) was given responsibility for managing GIZ operations. As the metropolitan planning organisation, MARC facilitated the majority of the Kansas City region’s ARRA grants. The Kansas City Council funded GIZ administration and operations costs for $4.2 million. MARC hired eight GIZ staff members – a Director, Assistant Director, five community ombudsmen, and an administrative assistant. The community ombudsmen, one for each of the five neighbourhoods, supported neighbourhood association capacity building, such as grant writing,

Figure 1. GIZ map. Source: Mid-America Regional Council. U-20471 Official Exhibits of Soulardarity Exhibit SOU-26 Page 6 of 19 1454 T. G. REAMES

Table 1. Comparative demographics: GIZ vs. Kansas City. Census tract GIZ Kansas City Population 10,742 474,396 % Black (non-Hispanic) 86.2 28.1 % White (non-Hispanic) 9.5 57.7 Total housing units 5810 225,569 % Vacant housing 27.8 13.3 Home ownership 49.1 61.4 Median household income ($) 24,125 44,436 % Below poverty 35.2 19.1 Unemployment rate (20–64) 16.3 7.7 Source: US Census Bureau, ACS (5-Year) 2005–2009. volunteer recruitment, monthly neighbourhood meeting assistance, and identiﬁcation of additional resources to support neighbourhood goals.

Weatherisation in the GIZ

The State of Missouri received just over $128 million in ARRA-era WAP funding, a signiﬁcant increase over its $9 million appropriation the previous year (US Department of Energy 2011). The state committed to weatherising 20,150 housing units.4 Missouri allocated $25.6 million to the Energize Mis- souri Housing Initiative, a state-wide competitive grant encouraging large-scale weatherisation initiatives, such as low-income multifamily housing units, or neighbourhood-based projects.5 In October 2010, MARC secured a $4.5 million grant from the Energize Missouri Housing Initiative to weatherise a proposed 659 homes in the GIZ. However, in September 2011, the State terminated MARC’s grant, citing slower than expected progress, and transferred the remaining funds to Kansas City for continued operation through March 2012.6 At the time of termination, MARC had spent $1.7 million and completed weatherisation of 115 homes, another 44 were in progress, and 176 were at some stage of the intake and audit process (Green Impact Zone 2011, Helling 2011). In the end, 329 homes were weatherised in the GIZ.7 Given that just less than 50% of the zone’s weatherisation goal was met, the GIZ offered an excellent case for exploring not only the opportunities, but also the challenges, of a community- based approach to no-cost energy retroﬁts in urban, low-income, minority communities.

Data collection and analysis

Inquiry into this case study was approached using grounded theory as part of a larger GIZ evaluation project in which data were collected between 2010 and 2014 from two principal sources: interviews with stakeholders engaged in GIZ, and grey literature pertaining to the GIZ. A total of 21 interviews, conducted between January 2010 and January 2012, were analysed for this study. Interview participants were selected based on their participation in the GIZ development and implementation. First, to understand early perceptions of the initiative, semi-structured face-to-face and telephone interviews were conducted with GIZ staff members, community development and metropolitan planning leaders, government staff, university faculty, and utility representatives between April 2010 and November 2010. Next, walk-along interviews were conducted with each of the five neighbourhood association leaders in early 2010, before weatherisation retrofitting began in the zone. The walk-along interview is a qualitative research tool by which the researcher accompanies individuals in their environment, and through asking questions, listening, and observing, the researcher is actively exposed to the experiences and perceptions of the individual’s physical and social environment (Kusenbach 2003, Jones et al. 2008, Carpiano 2009, Evans and Jones 2011). Lastly, to explore perceptions of weatherisation implementation, from the neighbourhood perspective, follow-up interviews U-20471 Official Exhibits of Soulardarity Exhibit SOU-26 Page 7 of 19 LOCAL ENVIRONMENT 1455 were conducted with the five neighbourhood association leaders between October 2011 and January 2012. In addition, an assimilation of over 100 secondary documents directly related to GIZ creation and implementation was collected. These secondary documents included news articles, policy documents, GIZ performance reports, and neighbourhood association newsletters. The goal of secondary document analysis was to understand the variance in contextual rhetoric surrounding the initiative, trace funding sources, review project status updates, and match goals with outcomes – information that was not gathered during the interview process. All study participants authorised recording of their interview, which allowed for verbatim tran- scription. Each interview was transcribed into separate documents. Along with the secondary data documents, interview transcriptions were loaded into the qualitative data analysis software package ATLAS.ti. I employed an iterative process of open coding interviews and secondary documents using the search words (e.g. housing, homes, residential, energy, energy efficiency, weatherisation, heat, cool, and audit) to identify segments of text for additional review. I noted whether the segment of text appeared to convey a positive, negative, or neutral message. In order to refine the open coding, I explored co-locations of search words and attitudes conveyed (Emerson, Fretz, and Shaw 1995, pp. 26–27). For instance, all paragraphs containing the word weatherisation and convey- ing a negative message were considered a theme for further analysis. This led to several analytically interesting themes that initially did not appear to go together. The following sections contain findings from the data collection and analysis described above. Quotes from interview participants are included with minimum editing, except when needed for clar- ification or confidentiality purposes. For instance, exact names and titles, and in some cases, a participant’s organisation’s name have been removed. There were six key barriers that GIZ stakeholders described as initial impediments to resident participation in WAP. These barriers can be categorised as follows: two social barriers (public priorities and public distrust), two market barriers (information gap and split-incentive), and two regulatory barriers (pre-weatherisation repairs and previous weatherisation ineligibility). I explain how the community-based approach facilitated both recognition of and working to overcome these barriers.

Social barriers Moving beyond narrow technocratic views of energy efﬁciency towards a people-centred approach that is interlinked with social policies is vital to ensuring affordable access to energy, promoting well- being, and reducing social inequality (Golubchikov and Deda 2012). Thus, the pursuit of equity in energy efﬁciency participation requires recognition of social diversities that may impede the adoption of energy technologies. While social barriers are often hidden, they are no less important than other barriers (Stobaugh and Yergin 1979, Sovacool 2009). In fact, early recognition of the role social barriers played in inhibiting WAP participation was essential for GIZ stakeholders. There were two social barriers that multiple interviewees addressed: public priorities and public distrust.

Public priorities barrier

The first challenge was making green relevant in the GIZ. Energy unaffordability is a fact of life in low- income minority communities, forcing them to prioritise spending of limited resources and resort to various coping mechanisms (e.g. non-payment, buying less food, and limiting heating use) (Hernan- dez and Bird 2010, Harrison and Popke 2011). Consequently, it was no surprise that in early GIZ planning meetings, social and economic, not environmental, issues were expressed as the top concerns of neighbourhood residents. GIZ stakeholders knew that unless a direct connection was made between residents’ social and economic priorities and weatherisation, it would be difficult to motivate a large number of households to participate. Thus, the environmental benefits of weatherisation became a co-benefit of focusing on other priorities. U-20471 Official Exhibits of Soulardarity Exhibit SOU-26 Page 8 of 19 1456 T. G. REAMES

Although recognising that the green vision would be a tough sell in general, and especially in the neighbourhoods, GIZ stakeholders firmly believed that success in applying for competitive ARRA grants required their applications have a cohesive framework. One city staff member explained that even if energy efficiency was not a top neighbourhood priority, there was such great potential in applying a green framework to the area that financial investments from other sources would be so drawn to the initiative and those funds could then be used to address economic and social issues beyond weatherisation:

Understanding that there are certain resources available to promote energy efficiency and transportation and transit and some things that might not necessarily be the top priority items for them but certainly creates a framework where it’s possible to hopefully stimulate additional sources of federal, state, local, and private capital to make investments in that area because it’s been a period of decades of significant disinvestment … If you ask a lot of people in the Green Impact Zone, energy efficiency of their homes isn’t going to be near the top list of their priority. But we have an opportunity of using that as a way of stimulating other investments. The “GIZ” framework created a unified community and vision for these five distinct neighbourhoods. The GIZ staff relied heavily on the local knowledge of neighbourhood association leaders to understand how best to frame and implement WAP. Neighbourhood association leaders advised staff to begin by focusing on overall quality of life improvements, and then gradually intro- duce the environmental elements of the programme. Equipped with this recommendation, GIZ staff ensured that all zone programmes were promoted along those lines. As one GIZ staff member explained, “we have a baseline that is environmental and energy conservation, but a vision and a mission that speaks to working with and through people to raise their quality of life”. On all electronic and printed material, the three reasons why residents should weatherise were purposefully ordered as (1) to save money on heating and cooling your home; (2) to have a healthier home with better indoor air quality; and (3) to help protect the environment by reducing energy consumption and pollution.8 The economic benefits of weatherisation, in the form of lower utility bills, targeted the top priority for residents. Weatherisation was also discussed in terms of improved health and comfortability. The GIZ stakeholders acknowledged the neighbourhoods’ higher rates of childhood asthma, and relied on the health and safety benefits of WAP to appeal to parents. Neighbour- hood association leaders knew improving comfortability appealed to senior residents, especially during cold weather. In a testimonial video, used as a marketing tool, one senior resident exclaimed, “My basement was cold, all the time, now I can go in that basement, almost, with just a dress on”. The GIZ employed what is known as community-based social marketing (CBSM), relying on the principles of social network theory to encourage participation by having well-known, trusted community residents to share their positive experience participating in the weatherisation programme (McKenzie- Mohr and Smith 2011).

Public distrust barrier

The novelty of an environmental and energy-focused urban renewal was not lost on GIZ staff. The perception about public investment in the community was that they were always last on the list. One staff member, a lifelong Kansas City resident, emphasised the rarity that these particular neighbourhoods would be leading the wave of energy efﬁciency and garner national attention for its efforts:

And then speciﬁcally home weatherization is an issue for a number of reasons … the country is now recognizing the importance of energy and environmental conservation, and our residents understanding this and having an opportunity to participate in discussions or any kind of projects or demonstration on how all of us, regardless of where we live will be dealing with those two issues going forward, really puts our residents at the front of the line and therefore gives them an opportunity to be in the know and to be participatory early on in what we are calling a revolution in our country. As opposed to what often happens with disinvested areas and people who are struggling economically, are typically, are kind of like at the tail end of anything that is coming into view as being very important and very powerful. U-20471 Official Exhibits of Soulardarity Exhibit SOU-26 Page 9 of 19 LOCAL ENVIRONMENT 1457

Public distrust was another barrier that required immediate and initial attention. In fact, trust can often eclipse other barriers to acceptance of energy technologies (Ricci et al. 2010). Interviewees identiﬁed two levels of public distrust that presented barriers to weatherisation participation. First was distrust of government. The second was a general distrust of others. It was important to acknowledge the historical context within which this community-based energy project was operating. The GIZ neighbourhoods had not become neglected overnight. Several interviewees drew comparisons between the state of GIZ neighbourhoods and New Orleans in the aftermath of Hurricane Katrina, referencing both the devastation and the opportunity of a green-centred rebuilding. One neighbourhood association leader also likened the neighbourhood conditions to the 2007 tornado that destroyed the small town of Greensburg, Kansas; however, he differentiated the two by acknowledging the gradual process of urban decline:

Congressman Cleaver took us to Greensburg to show us the devastation and how they were coming back green. And I liken that to what is happening in our urban core. The only problem is, is that they had one single disaster in a matter of minutes that devastated that place. Ours has occurred over a number of decades. And so the thing about human beings is that they can get used to anything we have gradually gotten used to this, ok. The people in Greensburg woke up one morning, there wasn’t no gradually getting used to that, they woke up and every- thing was gone. But see ours is so slow and insidious. Even as national attention surrounded GIZ, including a Kansas City visit and mention by President Barack Obama in July 2010, feelings of political and economic neglect remained pervasive in the neighbourhoods. MARC had to consider the appropriate response to neighbourhood sentiment. A MARC staff member summed up the unrelenting feelings of distrust as more pressing than whether residents cared about weatherisation:

I think that it is as much an issue of trust in anything and so … is something really going to happen? Is this real? When’s it going to happen? Is this all talk? Are we just going to plan some more? I’ve been to so many planning meetings, so many false promises, so many efforts, so many people who come and go. I think it’s more a believ- ability issue than it is about whether they care more about weatherization. The task of overcoming years of broken political promises did not fall lightly on GIZ staff. One staff member discussed not only this challenge, but also the rewarding feeling of ﬁnally being able to offer tangible information to residents about what GIZ was actually going to do for their community:

As employees of the Green Impact Zone and people who go out and carry this message to a group of people who have been promised diamonds and have always received sand, or who often received sand. It’s rewarding to be able to say a grant was awarded. It’s very rewarding. But it’s more rewarding to say, and this is exactly how it’s going to impact your neighborhood. Beyond distrust in government, distrust in others can be a major barrier to accepting energy technologies (Ricci et al. 2010). While crime is not often considered as a barrier to energy efﬁciency, it can manifest as a barrier to acceptance of in-home installations in urban communities that suffer from high crime activity. The GIZ neighbourhoods experienced crime at levels higher than other parts of the city, causing a local newspaper to label one GIZ zip code as the “murder factory” (Rizzo 2009). Crime also compromises the objectives of sustainable communities, often limiting social inter- actions (Wilson 1987). Some described GIZ neighbourhoods as having blocks where “people would not come out of their houses” and would “not speak to their neighbors”. Neighbourhood association leaders experienced residents not answering the door, rejecting marketing information and freebies, and refusing to listen to their spiels. This concern also encompassed the idea of having unknown contractors visit homes. In the resident testimonial, mentioned above, the senior resident assured her neighbours that allowing weatherisation contractors into their homes should not inhibit participation. In the video she stated, “I didn’t have to worry about clean up, they made no messes, anything, whatever they did, they cleaned up behind themselves, so I am very happy … I can recommend it to anybody, everybody, they won’t have anything to worry about”. Again, the strategic goal of this message was to U-20471 Official Exhibits of Soulardarity Exhibit SOU-26 Page 10 of 19 1458 T. G. REAMES assuage apprehensions residents, especially elderly female residents who lived alone, had concerning WAP participation. Often overlooked is the level of acceptance of “outsiders” in racially homogenous neighbourhoods. During the early stages of GIZ rollout, eager volunteers came from all over to assist. It was clear that many volunteers were not residents of these majority African-American neighbourhoods. GIZ stakeholders quickly acknowledged how signiﬁcant who knocked on a resident’s door was to delivering of information on WAP. As one long-time community advocate so bluntly put it:

Let’s be honest, I’m a blue-eyed, white woman, and we’re talking about 99.9 percent African-American neighborhoods. Now I’ve got a lot of cred with those neighborhood leaders but they really needed to have a strong African-American presence and leadership in those neighborhoods. MARC hired an all-African-American staff, acknowledging that residents would be more trusting of the initiative if the faces of the zone resembled theirs. Neighbourhood association leaders and neighbourhood residents were seen as the most credible and trusted sources to advocate weatherisation within their own neighbourhoods. Therefore, GIZ staff focused on neighbourhood association capacity building and assisting neighbourhoods develop a system of block captains to expand their breadth and depth. Block captains became an integral component of GIZ weatherisation outreach efforts.

Market barriers With the financial barrier to energy efficiency removed by the no-cost nature of WAP, two other market barriers were magnified during implementation in the GIZ: the information gap, and the split-incentive problem. The lack of sufficient information, or information deficit, impedes participation in energy efficiency programmes, even households who qualify for low- or no-cost energy efficiency assistance. This is especially true in urban, low-income, minority communities, which often lack access to technical information and knowledge (Kellogg and Mathur 2003). Additionally, poor, African-American neighbourhoods are stereotypically defined as communities derived of social and political institutions and where antisocial behaviour is prevalent, which can limit access to vital information and services (Wilson 1987). While more than a third of GIZ households had incomes below the federal poverty level, qualifying them for WAP services, many eligible homes had never been weatherised. Annually, Kansas City advertised weatherisation application periods, typically through social service organisations, community non-profits, and neighbourhood associations. Staff and neighbourhood association leaders explained this as a core factor creating an information deficit in the neighbourhoods. Neighbourhood association leaders expressed concerns that residents were disengaged, which contributed to them being uninformed. In one instance, a neighbourhood association leader, whose neighbourhood’s boundary was not wholly within the geographical boundaries of the GIZ, described an experience during a neighbourhood meeting where a local utility representative presented energy efficiency programmes available to GIZ residents; however, all those in attendance happened to live outside the GIZ boundaries:

But you’d be surprised that the people who live in the Green Impact Zone do not come to the meetings … It’s hard to imagine … So when the people like the [utility company] came to talk to us, they really needed to be talking to that group, those people. And those people weren’t there. So that’s why they received so much flack was because it didn’t pertain to them. They were not in the Green Impact Zone. Recognising the correlation between neighbourhood association engagement and information, staff had to simultaneously increase the capacity of neighbourhood associations and launch a massive information campaign. Working through the neighbourhood associations, block captains, and other neighbourhood volunteers, GIZ instituted intense outreach mechanisms in order to shrink the information gap. This included, as one GIZ staffer noted, a “door-to-door, neighborhood-by-neighborhood” approach. In the first year, GIZ coordinated a massive outreach effort to encourage residents to apply for weatherisation assistance, including 17,166 door-to-door visits, outreach at community events, and sending electronic media (Green Impact Zone 2011). These efforts U-20471 Official Exhibits of Soulardarity Exhibit SOU-26 Page 11 of 19 LOCAL ENVIRONMENT 1459 generated 3098 weatherisation applications, approximately 74% of occupied housing units in the zone (Green Impact Zone 2013). Additionally, neighbourhood association leaders were equipped with skills beyond simply providing information. The GIZ facilitated a two-hour energy efficiency and advocacy training session. The workshop increased the capacity of neighbourhood association leaders and volunteers to knowledgeably promote the benefits of weatherisation and provide detailed information on the participation process.

Split-incentive barrier

This community-based approach to WAP magnified a major barrier prohibiting a majority of homes from receiving retrofits. The no-cost aspect of WAP most often benefits owner-occupied units (82%, ORNL 2015a); however, 51% of the housing units in the GIZ were renter-occupied. Under programme guidelines, landlords may be required to cover up to 50% of weatherisation costs. For private landlords, making energy efficiency improvements becomes as an unprofitable proposition, when you consider 86% of renters pay all or some of their own energy costs (i.e. neither heat nor electricity is paid by the landlord) (EIA 2013b). This is known as the split-incentive barrier, a principal–agent problem, occurring when landlords, as the energy efficiency improvement decision-maker, decide against making the investment because they receive no direct benefit from doing so (Bird and Hernandez 2012). Although the split-incentive barrier is a common energy barrier, it is especially acute in communities like the GIZ where there is a concentration of privately owned, low-income rental housing (Bird and Hernandez 2012). To overcome the split-incentive barrier, a discount incentive was created for landlords to increase the weatherisation of zone rental properties. To encourage more landlords to participate, the shared cost of weatherisation by landlords was substantially reduced to only 5% for dwellings with less than five units, as explained by one GIZ staff member:

And when you have an area where 50 percent or more of your people are renters and you’re saying that you’re wanting to upgrade all of the housing stock … as pertains to weatherized homes, to not deal with the landlords is to right away miss out on 50 percent of where people are living … The city also will work with the landlords but it’s at a much lower subsidy … A landlord has to bring 50 percent of the funding with the city’s program. With the Green Impact Zone LIWAP, if the landlord has 1–4 units in a building, he or she only has to provide 5 percent of the cost to weatherize and if it’s a larger complex then it’s 25 percent but that’s a far cry from 50 so there’s real incentive there for them to get on board with weatherizing their units at this time. Again, GIZ stakeholders relied on CBSM, filming a short video testimonial of a landlord who participated in the programme encouraging other landlords. What was most interesting about the tes- timony was that it implied a level of empowerment for tenants to be able to inform their landlords about the weatherisation programme. This dynamic introduced the potential to reverse the split- incentives barrier, by equipping tenants with a reasonable proposal for their landlord. Typically, tenants may be reluctant to request that their landlord improve the home’s energy efficiency for fear of increased rent or retaliatory eviction. Below is a portion of the transcript from the landlord’s video, in which he mentioned that the tenant brought the programme information to him and discussed the mutual benefit of having weatherised the home:

The home is one of the older homes in the neighborhood and it wasn’t very energy efficient, but through the Green Impact Zone I was able to take advantage of the program and actually have the contractors come out and make sure the home was energy efficient. Well the tenant actually brought the program to me, told me about the program, and it’s been very positive for both us … very, very beneficial to me and again it makes the home energy efficient, which means it helps out on the cost for the tenant.

Regulatory barriers Regulatory barriers manifest as policy and bureaucratic rules that impede participation in energy programmes (e.g. eligibility requirements). Even after addressing social and market barriers, U-20471 Official Exhibits of Soulardarity Exhibit SOU-26 Page 12 of 19 1460 T. G. REAMES

“bureaucratic” and “red tape” obstacles were the most frustrating set of barriers for GIZ stakeholders. An axiom for GIZ stakeholders was “doing things in a new way with old rules”, acknowledging that things had to be done differently in order to get different, and better results. This was an arduous task, as a significant portion of ARRA-funding operated through existing programmes and rules. Rules and regulations embedded within WAP often proved counter to the lofty weatherisation goals set by GIZ stakeholders. It was no surprise that challenges were magnified during a community-based approach that may not have been as evident in the typical non-spatially targeted, individual referral approach to WAP. There were two dominant regulatory barriers to WAP implementation in the GIZ: the pre-weatherisation repair requirement and the previous weatherisation disqualification. Often older homes require repairs before weatherisation improvements can be made. Pre-weatherisation repairs can include the removal of lead, asbestos, and mould; the replacement of knob and tube wiring; general combustion safety; and repairing physical structure damage. Some conventional energy efficiency improvements can unintentionally increase health risks without countermeasures to ensure adequate ventilation and avoid degrading indoor air quality (Richardson and Eick 2006, Howden-Chapman et al. 2007). Thus, WAP energy auditors typically evaluate the whole house, examining the physical structure, holistically considering air movement, heating and cooling, insulation, indoor air quality, mould and moisture, and other health and safety concerns (e.g. inspection of fur- naces including testing for carbon monoxide) (Eick 2006, Richardson and Eick 2006). Conditions that can make it difficult to successfully weatherise or insulate a home can also have adverse health consequences. For example, lead paint was banned for residential use in 1978; for an area where nearly all homes (91.4% compared to 48.3% citywide) were built before the 1980s, the potential for pre-weatherisation repair barriers was magnified (see Figure 2). This combination of older housing stock and low household incomes increased the likelihood of deferred maintenance. GIZ staff discovered that weatherisation applicants were often unaware either that required repairs would halt their weatherisation process, or that the repair issues even existed. On the other hand, homeowners with knowledge of their deferred maintenance issues were fearful and apprehensive about applying for weatherisation and subjecting themselves to an energy audit. This was often the case for senior-headed households. In fact, research shows that for some homeowners, the term energy “audit” prompts negative connotations (Junk, Jones and Kessel 1984).

Figure 2. Age of housing stock, GIZ vs. Kansas City, MO. Sources: US Census Bureau, ACS (5-Year) 2005–2009; Author. U-20471 Official Exhibits of Soulardarity Exhibit SOU-26 Page 13 of 19 LOCAL ENVIRONMENT 1461

An advantage of the community-based approach to WAP was the ability of GIZ staff and neighbourhood association leaders, as trusted advisors facilitating the weatherisation process, to ease homeowners’ fears and assure them that an energy audit offered beneﬁts, as opposed to penalisation for being ﬁnancially unable to maintain their homes. A GIZ staffer described an interaction with an eligible senior homeowner who chose not to apply for WAP fearing discovery of a hole in her roof:

Ok you’re not doing it because you’re afraid when they come in the house and see that you have a hole in the roof that they’re going to condemn your home. Well, that’s a legitimate fear, ok well here’s what’s not going to happen, they’re not going to condemn your home, in fact, now the minor home [repair] program, you’re probably eligible for that. So let’s do the minor home repair program so you can get your roof fixed, then you can get your home weatherized. So really helping residents understand that the city, whatever they may have been in the past, right now, here’s what the programs are, here’s where you can benefit, and let us help. Although pre-weatherisation repairs were initially viewed as a regulatory impediment to weatherising homes, fixing problems such as moisture or mould issues, structural causes of deteriorating leaded paint, both rendered a home weatherisation ready and addressed household health and safety concerns. In addition to pre-weatherisation repairs, previous weatherisation ineligibility prevented a number of the GIZ households from participating. Prior to ARRA, WAP regulation stipulated that if a home was weatherised using federal assistance any time after 30 September 1979, the home was ineligible for re-weatherisation assistance. ARRA amended the previous date to 30 September 1994. Although the extended period increased the number of homes eligible for weatherisation, GIZ implementers felt date-based ineligibility was inappropriate for a couple of reasons. First, this rule prevailed regardless of the type of weatherisation work previously completed. Second, the rule disregarded whether or not the current occupant was the initial beneficiary of the weatherisation services. Neighbourhood association leaders recalled a general sentiment of frustration from residents ineligible to participate in WAP because of the previous weatherisation rule:

A few people have been unhappy because they couldn’t get their homes weatherized … if any weatherization work had been done at the address, not necessarily for the owner of the property, but at the address since 1994 they were ineligible. So … the work they had done could have been as simple as caulking or weather-strip- ping … whereas the way we were trying to do weatherization was to do the test to see what was needed and if needed a furnace, put the furnace in, … But if you had had any kind of work done since 1994 then you were ineligible, so that’s been frustrating for people. For GIZ staff this rule was a major obstruction to its core objectives. Aside from limiting participation, political and regulatory barriers impede innovation. One GIZ staff member articulated that staff’sability to innovate was thwarted by policy and bureaucracy. When asked to detail the most discouraging experience since being hired, the pre-weatherisation ineligibility rule was the topic of choice:

I’m going to lump it into policy and bureaucracy. It’s really difficult to be innovative and make changes when there is something like the federal guidelines to weatherizing a home that says if it was weatherized in 1994 to now it can’t be weatherized again. Well you might have put new windows on but that has nothing to do with insulating the walls, which you have learned over the years is really the way to best efficiently affect the house in the way in which it seeps energy. That is a very frustrating thing to talk to somebody about and then find out, oh that the only way we can really affect that change is through federal policy. So that is one of those bureaucratic policy hiccups that it’s frustrating at times and we continue to be tenacious and finding ways around that, not around it to circumvent it, but to help that neighbor, and to help that resident more efficiently energize this older home that they have. With a common goal, fortified by a community-based approach, even when frustrated and disap- pointed, GIZ staff and neighbourhood association leaders found means to overcome barriers. Although it took more than a year, an alternative funding source was located to work around the 1994 pre-weatherisation rule. After MARC lost its weatherisation grant, GIZ advocates requested that the city council develop a plan to continue the weatherisation work in the GIZ. While the City could not target its weatherisation funds specifically to GIZ neighbourhoods, city leaders U-20471 Official Exhibits of Soulardarity Exhibit SOU-26 Page 14 of 19 1462 T. G. REAMES realised they could target a $1.2 million weatherisation grant received from local electric and gas utilities. While applicants still had to meet income requirements, these funds had fewer restrictions than WAP funds, which allowed for adjustment to the previous weatherisation threshold. In Septem- ber 2011 the city council contracted with a local non-profit, to administer the $1.2 million grant to continue weatherisation efforts in the GIZ. The contract loosened the restriction on previous weatherised homes to 2002. Residents who met federal income guidelines to qualify for WAP, but were ineligible because of previous weatherisation assistance, were directed to this programme. Ulti- mately, the community-based nature of implementing WAP in the GIZ magnified the impact of regulatory barriers and facilitated the capability to seek solutions, which may otherwise have been unlikely.

Conclusion and policy implications With the passage of the ARRA, the federal WAP received its largest ever appropriation, a $5 billion funding boost, which created an immediate need to grow consumer demand for low-income residential energy efficiency improvements. This allowed states to experiment with innovative implementation approaches. This article presented in a case study one such approach. The GIZ initiative in Kansas City, Missouri, was a targeted, community-based approach to weatherise 659 homes in a 150-block area of five low-income, majority African-American neighbourhoods through the ARRA- funded Energize Missouri Housing Initiative. Although the GIZ did not meet its weatherisation goal, only 329 homes were weatherised, there were significant lessons learned from this nontradi- tional approach to WAP implementation. The key research questions were (1) what barriers to energy efficiency participation continue to manifest in the absence of financial impediments, and (2) can a community-based approach effectively identify and overcome those barriers? The findings of this study demonstrate that even when financial impediments to energy efficiency are removed, a host of other barriers to participation exist. There were six key barriers that GIZ stakeholders had to overcome: two social barriers (public priorities and public distrust); two market barriers (information gap and split-incentive); and two regulatory barriers (pre-weatherisation repairs and previous weatherisation ineligibility). Additionally, a community-based approach to low-income energy efficiency provided the institutional capabilities to recognise the magnitude of effect of these barriers, and to respond appropriately with innovative strategies to overcome the barriers. Community-based, spatially targeted energy efficiency efforts recognise both the unique assets and challenges of place for more effective delivery of programmes to meet the distinct needs of the target population. This is especially critical in underserved and disadvantaged communities who often lack access to and information about traditional programmes. In these communities, special care is needed to address social barriers such as competing social and economic priorities, and pervasive distrust and fear. It is important that community-based energy efficiency projects build lasting institutional capabilities. Although projects may be short term and funding sources vary, building institutional capabilities in neighbourhood associations not only facilitates working through current challenges and barriers, but also develops the capacity to carry out future work. The GIZ staff and neighbourhood association leaders were able to respond more effectively to market and regulatory barriers because of the capacity built by working collaboratively through each issue as they arose. In follow-up interviews, the five GIZ neighbourhood leaders described ways in which they partnered with each other on other initiatives, something that never occurred prior to the GIZ. A community-based approach helps establish a unifying vision that can then be used to leverage additional support and resources for the community. Finally, this case study highlights the challenges of a community-based approach to an individual- benefit policy. The US DOE’s WAP policy framework is not written to account for the particular needs of any one community, but rather individual low-income households. Numerous challenges arose, as U-20471 Official Exhibits of Soulardarity Exhibit SOU-26 Page 15 of 19 LOCAL ENVIRONMENT 1463 the concentrated implementation effort revealed magnified manifestations of barriers. These issues would be viewed as isolated events under normal, non-spatially targeted, individual-based implementation. Implementing an existing policy in a new way, without major policy changes or flexi- bility, requires a fair amount of workarounds, which leads to implementation delays and lower participation, resulting in underserving the target population. The key policy implication of this case study is that while there is great potential for WAP implementation to benefit from a community- based approach, the most effective implementation requires a policy framework flexible enough to allow for the unique physical, social, and institutional environments of target communities.

Limitations

The analysis presented here is from a top-down, or policy elite perspective. Omitted are the perspectives of residents, which adds some bias to the analysis. For example, conclusions about resident behaviour and their disengagement were drawn from the accounts of neighbourhood association leaders. This study could have been improved with interviews with neighbourhood residents, both that received weatherisation services and those that did not. Additionally, data were not collected on the extent of energy efficiency improvements made in homes or how the level of energy efficiency was measured. A household survey would also expand this study, allowing a quantitative analysis of the effects of community-based energy efficiency projects.

Notes 1. The income of low-income households as provided in the 2009 Residential Energy Consumption Survey and adjusted for inflation was estimated at $18,773 compared to $71,755 for non-low-income households (Oak Ridge National Lab- oratory 2014). 2. Text from ARRA: H.R.1-32 Section 3(b) General principles concerning use of funds. 3. The GIZ, http://www.greenimpactzone.org/Plan/vision.aspx [last accessed 13/1/16]. 4. According to the DOE, Missouri completed weatherisation of 20,319 homes between calendar year 2009 and 30 November 2011, http://energy.gov/downloads/arra-homes-weatherized-grantee [last accessed 13/1/16]. 5. Missouri Department of Natural Resources, https://energy.mo.gov/energy/stay-informed/energize-missouri [last accessed 13/1/16]. 6. The month prior to the State ending its grant contract with MARC, the DOE Inspector General’sOffice (DOE IG) released an audit report that found the State “had not always adequately managed its Weatherization Program and noted problems in the quality of weatherization work” and required the state to take action (DOE 2011). Across the country, states struggled to make progress with the huge increase in funding. The DOE IG found that recession-driven budget shortfalls, state hiring freezes, and state-wide planned furloughs delayed weatherization programme implementation – and created barriers to meeting spending and home weatherisation targets. The leader of a Kansas City employment agency that received stimulus funding for workforce training of GIZ workers was quoted in the local newspaper saying, “[y]ou don’t create a whole industry overnight” as he discussed the difficulty of readying a new workforce in the short amount of time required for quick spending of stimulus funds (Helling 2011). In March 2012, the US House of Representatives’ Committee on Oversight and Government Reform release a staff report titled “The Department of energy’s Weatherization Program: Taxpayer Money Spent, Taxpayer Money Lost”, in which it cited the Missouri Audit and issues in other states it felt deemed the overall stimulus-era weatherisation programme a failure. 7. See the GIZ, www.greenimpactzone.org/images/infographic.pdf [last accessed 13/1/16]. 8. The GIZ, www.greenimpactzone.org/Energy/liwap.aspx [last accessed 13/1/16].

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US Energy Information Administration, 2012a. Annual energy review 2011. Washington, DC: US Energy Information Administration. US Energy Information Administration, 2012b. Annual energy review 2011. Washington, DC: US Energy Information Administration, DOE/EIA-0384(2011). US Energy Information Administration, 2012c. Residential energy consumption survey data show decreased energy consumption per household. Available from: http://www.eia.gov/todayinenergy/detail.cfm?id=6570. US Energy Information Administration, 2013a. 2009 residential energy consumption survey – Table HC2.1 Structural and geographic characteristics of U.S. homes, by housing unit type, 2009. Available from: http://www.eia.gov/ consumption/residential/data/2009/. US Energy Information Administration, 2013b. 2009 residential energy consumption survey – Table HC9.2 household demographics of U.S. Homes, by Owner/Renter Status, 2009. Available from: http://www.eia.gov/consumption/residential/ data/2009/. Villao, D., Sarmiento, S., and Le, U., 2012. Generating demand for green jobs: transforming the residential, commercial, and institutional energy efficiency retrofit markets through community partnerships. Available from: http://aceee.org/files/ proceedings/2012/data/papers/0193-000213.pdf. Walker, G. and Day, R., 2012. Fuel poverty as injustice: integrating distribution, recognition and procedure in the struggle for affordable warmth. Energy Policy, 49, 69–75. Wilk, R.R. and Wilhite, H.L., 1985. Why don’t people weatherize their homes? An ethnographic solution. Energy, 10 (5), 621–629. Wilson, W.J., 1987. The truly disadvantaged: the inner city, the underclass, and public policy. Chicago, IL: University of Chicago. Wisconsin Energy Conservation Corporation, n.d. Community-based energy efficiency programs: two storeys of success. Available from: http://www.weccusa.org/sites/www.weccusa.org/files/pdfs/sell%20sheets/communitybasedsellsheet. pdf. U-20471 Official Exhibits of Soulardarity Exhibit SOU-26 Page 19 of 19

Copyright of Local Environment is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. U-20471 Official Exhibits of Soulardarity Exhibit SOU-27 Page 1 of 9

ECONOMIC POTENTIAL FOR PEAK DEMAND REDUCTION IN MICHIGAN

Prepared for Advanced Energy Economy Institute By Demand Side Analytics, LLC & Optimal Energy, Inc.

February 16, 2017

San Francisco | Washington D.C. | Boston www.aee.net | @aeenet

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ACKNOWLEDGMENTS

PRINCIPAL CONSULTANTS  Jesse Smith, Demand Side Analytics  Jeffrey Loiter, Optimal Energy  Bill Bland, Energy Analytics

CONSULTANTS  Cliff McDonald, Optimal Energy

QUANTITATIVE ANALYSTS  Steve Morris, Demand Side Analytics

San Francisco | Washington D.C. | Boston www.aee.net | @aeenet

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ABOUT ADVANCED ENERGY ECONOMY INSTITUTE Advanced Energy Economy Institute (AEE Institute) is a 501(c)(3) charitable organization whose mission is to raise awareness of the public benefits and opportunities of advanced energy. AEE Institute provides critical data to drive the policy discussion on key issues through commissioned research and reports, data aggregation and analytical tools. AEE Institute also provides a forum where leaders can address energy challenges and opportunities facing the Unite States. AEE Institute is affiliated with Advanced Energy Economy, a 501(c)(6) business association, whose purpose is to advance and promote the common business interests of its members and the advanced energy industry as a whole. www.aee.net/aeei

AEE INSTITUTE’S RESEARCH PARTNERS Demand Side Analytics was formed in 2016 to help utilities and regulatory agencies navigate the technical, economic, and policy challenges of building a smarter and cleaner energy future. Through cutting edge research design and analysis methods DSA provides program administrators with data driven insights into how various technologies and interventions affect the way homes and businesses use energy. http://www.demandsideanalytics.com

Founded in 1996, Optimal Energy provides a full range of energy efficiency consulting services to investor and municipally owned utilities, program administrators, state and federal energy offices, regulatory commissions, advisory councils, and advocacy groups. Optimal Energy specializes in assessing, developing, designing, planning and launching efficiency programs that effectively address the needs of all stakeholders in a cost effective, balanced fashion. http://www.optenergy.com

San Francisco | Washington D.C. | Boston www.aee.net | @aeenet

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EXECUTIVE SUMMARY

The electric power sector in Michigan is changing 2016, load exceeded 95% of the annual peak for just quickly. Policy decisions made over the coming months 76 hours. This means nearly 2,000 MW of capacity will shape the state’s energy outlook for years to was needed to serve load in just 0.4% of hours. come. The retirement of coal plants, reduced Demand reductions are less capital-intensive and often competitive generation supply, increased penetration more economic for meeting demand during these peak of smart meters, and changes to Midwest electricity hours than investment in traditional “peaker” power markets will all fundamentally alter infrastructure plants, which sit idle for most the year. investment strategies moving forward. Findings from this analysis commissioned by Advanced Energy Figure 1: Load Duration Curve, Michigan MISO Zones Economy (AEE) Institute show that a combination of 2 and 7, 2015-2016 demand reduction strategies could entirely offset the projected 2,000 megawatt (MW) growth in summer peak demand in the Lower Peninsula from 2017 to 2026, avoid or defer the need to construct additional power plants, and save the state as much as $1 billion over the next decade. To date, challenges in Michigan’s power sector have been characterized mainly as potential shortfalls in generating capacity to meet projected electricity demand. The Midcontinent Independent System Operator (MISO) has identified a need for capacity imports to Michigan. The Michigan Public Service Commission’s Chairman has also voiced adequacy concerns, stating “load serving entities in the Lower Peninsula do not have adequate capacity within the Our analysis examined the potential for various state to meet reserve requirements.”1 summer peak demand reduction strategies across three market scenarios that looked at different levels of But resource constraints on the electricity system in the avoided costs that would come from reducing demand Lower Peninsula are largely driven by hot weather instead of investing in additional generating capacity: and air conditioning loads in the summer. This means peak demand events that drive potential capacity  Low Avoided Cost: Assumes that generation shortfalls are predictable and good candidates for supply remains sufficient and capacity prices management. stay flat over the study horizon at We examined the potentially constrained areas of approximately $30/kW-year. No benefit is Michigan’s electricity system – MISO load resource assigned to the transmission or distribution zones 2 and 7 – for the past two years. (Figure 1) The systems. power system must be sized to meet loads in the  Medium Avoided Cost: Values avoided highest hour plus a reserve margin of approximately generation capacity at approximately 15%, meaning that a lot of system capacity is utilized $60/kW-year, or halfway between recent for a very small number of peak hours. In 2015 and market prices and construction of a new natural gas power plant. Includes a $10/kW- year benefit each for avoided transmission 1Palnau Judy (2016), "MPSC: State's and region's electric and distribution capacity. capacity supplies tightening," July 22, 2016, available at  High Avoided Cost: Avoided generation http://www.michigan.gov/mpsc/0,4639,7-159- capacity is valued at approximately 16400_17280-389567--,00.html.

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$90/kW-year, representing the cost of a new when needed. Direct thermostat control and time power plant as determined by the Cost of varying rates are not mutually exclusive strategies, but New Entry (CONE). Avoided transmission and do target common loads. Because the potential distribution capacity valued at $20/kW-year estimates are not completely additive, the ‘Total’ each. column excludes the connected thermostat potential. Estimates of peak demand reduction potential were The modeling was structured so that the avoided cost developed for three separate strategies across each was the primary independent variable in the estimates of the three scenarios (Table 1). Commercial and of potential. With that as the primary input we Industrial (C&I) demand response (DR) represents a estimated the amount of cost-effective demand program where C&I customers who are willing and response that would maximize net benefits, resulting in able to reduce their power usage are notified the day market estimates that correspond to strongly positive prior to a curtailment event. For residential customers, benefit-cost ratios. two program designs were considered. The time- varying rate potential is based on critical peak pricing The variation between estimates by scenario shows the (CPP), under which electricity prices are substantially importance of cost assumptions when comparing raised at times of unusually high demand. Also planning options, especially when they include estimated is a program whereby the smart thermostats expensive and long-term investments. It is worth noting of participating customers are used to reduce demand that, even in the Low Avoided Cost scenario, there are savings to be had by reducing peak demand.

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Table 1: 2026 Peak Demand Reduction Potential by Strategy and Avoided Cost Scenario

Non-Residential Residential Avoided Commercial and Cost Connected Thermostat Time-Varying Rate Total* Industrial DR Potential Scenario Control Potential (MW) Potential (MW) (MW) Low 310 76 289 599 Medium 969 151 382 1,351 High 1,595 202 723 2,318 * Time-varying rate (TVR) potential estimates are for critical peak pricing. The Total column reflects C&I plus TVR only.

the dispatch request occurs in the morning for an COMMERCIAL AND INDUSTRIAL afternoon peak. SECTORS The C&I DR potential is significant – in the Medium Large commercial and industrial (C&I) customers avoided cost scenario, there is C&I load curtailment represent a sizable and cost-effective demand potential of almost 1,000 MW in the Lower Peninsula response opportunity. Weather-driven summer peaks for a day-ahead notification model with up to 40 like Michigan’s can be forecast hours or days in hours of dispatch per year. (Figure 2) The opportunity advance with reasonable accuracy thanks to is roughly halved if customer lead-time is reduced to improvements in weather forecasting technology. The day-of notification. The modeling approach used for amount of notification time affects the magnitude of this analysis assumes incentive levels set below the response, so two options were examined. A ‘day- avoided costs to optimize net benefits. In the Medium ahead’ model involves identifying forecasted peak avoided cost scenario, our analysis shows a 10-year conditions and dispatching participants to shed load net benefit (savings) of $316 million for the day- the following day during the expected peak hours. The ahead notification design and $174 million for the ‘day-of’ design shortens notification time and assumes day-of notification design.

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Figure 2: Commercial & Industrial Demand Reduction Potential by Notification Time and Avoided Cost Scenario, 2026

owned utilities (IOUs) could drive adoption even higher RESIDENTIAL SECTOR and generate additional energy savings and peak In the residential market, existing load management load reductions. programs in Michigan have relied on switches Beyond a “Bring Your Own Thermostat” program, the deployed by the utilities that allow them to directly increasing deployment of advanced metering control certain appliances, such as air conditioners and infrastructure (AMI) in Michigan enables significant water heaters. Continuing to leverage these existing opportunities to reform residential rates in a way that programs is an effective strategy, but the emergence encourages additional electric load-shifting from peak of the “smart grid” presents new and larger to off-peak hours. Time-of-use rates, critical peak opportunities. For example, rapid customer adoption pricing, and/or peak time rebates all increase the of internet-connected “smart” thermostats represents a economic efficiency of the system over standard flat fundamental shift in the residential opportunity. rate pricing by using price signals to discourage excess Homeowners are purchasing and installing the necessary equipment, eliminating a large driver of use of electricity during peak hours. Under time- varying rate structures, total customer consumption utility program costs. Based on interviews with major remains the same or lower but usage patterns shift, thermostat vendors, we estimate there are over flattening the load curve, lowering peak demand, 70,000 connected thermostats currently installed in the reducing customer bills, and avoiding increases in Lower Peninsula. By 2026 we estimate this number will system infrastructure costs. In this way, not only do exceed 500,000 and could deliver 150 MW of peak participating customers benefit, but so do all demand reduction potential in the Medium avoided customers, through lower overall electricity prices. cost scenario. Coupling a ‘Bring Your Own Thermostat’ demand response offering with the current energy Once AMI is in place, time-varying rates (TVRs) can be efficiency rebates of $100 from the Michigan investor- rolled out at little additional cost. We have developed

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estimates of the residential peak demand reduction a per-participant basis, but will reach significantly that could be provided by different TVRs by 2026. fewer homes than a default rate where customers can (Table 2) Opt-in rates deliver the largest reductions on opt-out of the rate.

Table 2: 2026 Residential Peak Demand Reduction Potential by Rate Type

Average % Reduction per 2026 Reduction as % of Total 2026 MW Reduction TVR Scenario Participant Residential Peak Forecast TOU CPP PTR TOU CPP PTR TOU CPP PTR Opt-in, no 5.0% 15.4% 12.4% 94 289 233 1.0% 3.1% 2.5% thermostats Opt-in thermostats 10.0% 25.9% 20.9% 138 382 308 1.5% 4.1% 3.3% Opt-out, no 2.8% 8.6% 7.0% 221 679 548 2.4% 7.2% 5.9% thermostats Opt-out, 5.6% 14.5% 11.7% 243 723 584 2.6% 7.7% 6.2% thermostats TOU = Time of Use. CPP = Critical Peak Pricing. PTR = Peak Time Rebate.

The other key differentiator for time-varying rates is are difficult to estimate, once the Michigan AMI the inclusion of enabling technology in the form of network is in place, costs should represent a small connected thermostats. Smart devices like connected fraction of the capacity benefits. thermostats and other home automation tools allow customers to program an energy response to pricing CONCLUSION conditions rather than taking direct action themselves. Adding enabling technology to dynamic rates has Michigan faces important decisions over the next been shown to double the peak demand reduction decade as the electric grid modernizes. Our analysis compared to rates alone. Time-varying pricing has shows that aggressively pursuing summer peak already proven successful in Michigan – a DTE demand reduction is a smart and cost-effective evaluation of 1,500 customers on time-of-use rates strategy. In our Medium avoided cost scenario, a combined with critical peak pricing shows an average combination of residential and non-residential peak demand reduction of about 15%. strategies returns approximately $900 million in benefits compared to $400 million in costs over a 10- Notably, when combined with a smart thermostat, the year period. (Table 3) In the High avoided cost reduction jumped to almost 50% per home without scenario our modeling shows $2.2B in benefits against any direct set point control. Whether through more $1B in costs over 10-year. It is important for the state passive approaches like rate design, or direct load to recognize demand response opportunities that are control, strategies that leverage enabling technology available and consider policies that capture the like smart thermostats will increase DR cost- benefits of these resources. effectiveness. The potential for peak demand reduction through residential DR is substantial. In the Medium avoided cost scenario, our model estimates a connected thermostat strategy would deliver $55 million in benefits from $34 million in costs and deliver net savings of $21 million annually over the next decade. For TVR with critical peak pricing, we estimate almost $200 million in potential benefits for a TVR over the next decade. Although implementation costs for TVRs

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Table 3: Summary of costs and benefits, 2017-2026

Low Avoided Cost Scenario Sector Costs ($M) Benefits ($M) Net Benefits ($M) C&I $48 $79 $31 Residential Connected $9 $9 $0 Thermostats Residential Time Varying $40 $62 $22 Rates* Total** $88 $141 $53 Medium Avoided Cost Scenario Sector Costs ($M) Benefits ($M) Net Benefits ($M) C&I $371 $693 $322 Residential Connected $34 $55 $21 Thermostats Residential Time Varying $50 $189 $139 Rates* Total** $421 $882 $461 High Avoided Cost Scenario Sector Costs ($M) Benefits ($M) Net Benefits ($M) C&I $978 $1,875 $897 Residential Connected $64 $123 $59 Thermostats Residential Time Varying $60 $318 $258 Rates* Total** $1,038 $2,193 $1,155 * Residential TVR potential based on Critical Peak Pricing Option. ** The Total column reflects C&I plus TVR only.