Proceedings of a Workshop—in Brief

Representing Lived Experience in the Climate and Economic Justice Screening Tool

Proceedings of a Workshop—in Brief

INTRODUCTION

The National Academies of Sciences, Engineering, and Medicine Committee on Utilizing Advanced Environmental Health and Geospatial Data and Technologies to Inform Community Investment¹ was tasked with analyzing how environmental health and geospatial data and environmental screening tools can inform the White House Council on Environmental Quality’s (CEQ’s) Climate and Economic Justice Screening Tool (CEJST).² The study committee was tasked with conducting a data assessment to assist CEQ in considering the climate and economic disparities that it has prioritized. The committee will ultimately prepare a consensus report including recommendations to be incorporated into an overall data strategy for CEQ’s tool(s).

On June 1, 2023, the committee held a 1-day hybrid workshop to explore how well data used within Version 1.0 of the CEJST represent the lived experiences of historically marginalized and overburdened communities across the Nation.³ An overview of the CEJST Categories of Burden (see Box 1) and the datasets used by the tool was presented. Participants received a demonstration of how to navigate to and use CEJST, followed by hands-on experience incorporating their lived experiences in the tool and discussing the results in breakout groups. Workshop participants related how information developed by CEJST reflects conditions within these communities and considered some measures absent from the tool that relate thematically to the Justice40 Initiative (see Box 1). A plenary discussion was held on data gaps and overlapping issues.

The information gathered during the workshop is part of a larger effort to inform the study committee’s deliberations and final report recommendations. Some elements of the committee’s statement of task, such as efforts related to the committee’s scan of other existing screening tools, were not discussed at the workshop and therefore are not part of this proceedings. Instead, this proceedings summarizes the workshop sessions, which focused on the data included in CEJST and how well CEJST represents conditions in communities.

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This proceedings has been prepared by the workshop rapporteur as a factual summary of what occurred at the workshop. No recommendations are provided in this document. The study committee’s role was limited to planning and convening the workshop. The views contained in the proceedings are those of individual workshop participants and do not necessarily represent the views of all workshop participants, the study committee, or the National Academies. The committee’s final report will be informed by all of the committee’s information gathering and will include discussion of each element of the statement of task. The committee’s recommendations will be provided in its final report.

THE CEJST CATEGORIES OF BURDEN

The objective of the first session of the workshop was to briefly summarize the CEJST Categories of Burden (see Box 1) and the datasets used by the tool as they are described in its technical documentation. Committee member Jay Chakraborty (University of Texas at El Paso) introduced the Categories of Burden and their associated datasets.⁴ He specified that CEJST utilizes publicly available and nationally consistent (i.e., across all 50 states and U.S. territories) datasets to identify disadvantaged communities at the census-tract level. Box 1 summarizes his description of the CEJST Categories of Burden and how they are used to identify disadvantaged census tracts.

Committee member Susan Anenberg (Associate Professor, George Washington University) served as moderator for the session and initiated discussion on the poverty indicators. Regarding a question on how CEJST approaches variations in this indicator across the country, Chakraborty remarked that CEJST “uses the federal poverty rate uniformly across all census tracts in the country; it does not account for cost-of-living differences or other geographic disparities.” Participants Khalil Shahyd (Managing Director, Environmental and Equity Strategies, Natural Resources Defense Council) and Quentin Cummings (Climate Analytics Lead, Federal Emergency Management Agency [FEMA]) wondered why FEMA’s National Risk Index (NRI)⁵ data on expected annual loss (for agriculture and buildings) are included under the Climate Change category since these datasets focus on physical structure loss in dollars and may be outdated. Shahyd elaborated that NRI’s annual loss data are also based on property assessments and values in which communities of color face discrimination and long-term disinvestment. Discussion among participants progressed to the possibility of including other types of indicators in the Categories of Burden, such as

• Access to safe and clean drinking water—in the Water and Wastewater category;
• Labor census data—in the Workforce Development category;
• Exposure to extreme heat, including its associated economic loss and health impacts—in the Climate Change category; and
• Proximity to energy project or infrastructure, including planned projects—in the Energy category.

PANEL DISCUSSION: HOW DOES CEJST REFLECT CONDITIONS IN YOUR COMMUNITY?

Committee member Marcos Luna (Professor, Salem State University) moderated a session in which each panelist gave brief presentations on the lived experiences of the communities in which they reside and work. The objective of this session was to understand how well CEJST data and outputs represent community experiences.

Participant Nayamin Martinez (Executive Director, Central California Environmental Justice Network) spoke about the experiences of communities in California’s Central Valley that are disproportionately exposed to air pollution, poor drinking water, pesticides, and extreme heat. These issues are notably interconnected, and she provided the example that many residences rely on evaporative (“swamp”) cooling systems that do not properly cool houses. Such cooling systems also bring pesticides, wildfire smoke, and other pollutants into homes. Martinez asserted that the data in CEJST reflect some, but not all, of these issues. The tool does not include proximity to oil drilling sites in its category of Legacy Pollution. It also does not consider data related to pesticide exposure, ozone as an air pollutant, access to clean drinking water, or access to public transportation. She expressed an interest in seeing these included in future iterations of the tool.

Participant Loka Ashwood (Associate Professor, University of Kentucky) discussed issues facing many rural communities, including pollution and persistent poverty. She provided the example of Burke County, Georgia, an area on which she has worked and published. It hosts four nuclear reactors in one census tract.⁶ CEJST

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does not recognize this census tract as disadvantaged because data on nuclear reactors are not considered under the category of Legacy Pollution. Ashwood added that the American Community Service (ACS) data used in the low-income threshold in CEJST do not accurately reflect the transient community that comes to work at these nuclear power plants; therefore, the tool does not accurately reflect the income condition in this community. According to Ashwood, persistent poverty is another issue that disproportionately affects rural communities. In Burke County and other agricultural communities, poverty is associated with the increasing percentage of absentee landownership; because the landowners live outside of the local communities, they are not circulating resources back into them. Absentee land ownership and persistent poverty metrics could be useful in CEJST, Ashwood said, in rural and urban settings alike, to understand intergenerational wealth and socioeconomic power, which relate to environmental injustices.⁷ She suggested that CEJST consider adding agriculture as a category of burden itself, with absentee landownership falling under that category along with pesticide exposure and presence of concentrated animal feeding operations, using animal inventory data which, she said, can be obtained from the U.S. Department of Agriculture Farm Service Agency.

Participant Neza Xiuhtecutli (General Coordinator, Farmworker Association of Florida, Inc.) spoke about his experiences working with agricultural communities. Conversely to Dr. Ashwood, he recognized that CEJST accurately represents these communities in the categories of low income and climate change, particularly the “expected agriculture loss rate” indicator. Xiuhtecutli noted that pesticides and other agricultural chemicals could be considered legacy pollutants in the tool. CEJST could more accurately represent the water and wastewater issues experienced by rural communities. For example, Xiuhtecutli discussed these communities’ reliance on septic tanks in conjunction with underground water storage. He also mentioned inaccuracies in census data on agricultural workers, who are often temporary workers and thus not reflected in this data. According to Xiuhtecutli, these workers are “more vulnerable to pesticide and heat exposure, as well as labor violations that may include poor housing conditions due to their isolation.”

Vi Waghiyi (Member, White House Environmental Justice Advisory Council) is a Sivuqaq Yupik grandmother and tribal citizen of the Native village of Savoonga, Alaska. She said that CEJST does not adequately represent the lived experience of her family in the Arctic. She described the issues that her people face as “some of the most highly contaminated populations on the planet.” The military toxins and massive spills along with persistent organic pollutants (POPs) from ocean currents contaminate their food and water supplies, especially since the community relies on traditional subsistence farming and hunting. The rapidly melting ice due to climate change releases sequestered POPs, which are not accounted for in the CEJST or measured elsewhere. Food security in her community is also affected as marine mammals lose their habitat. Waghiyi expressed interest in CEJST incorporating data on access (or lack thereof) to healthcare, which is another issue of importance in remote areas such as the Arctic.

Multiple panelists noted that there are indicators in CEJST that accurately represent communities, but there are more datasets that CEQ can include that could better represent conditions in communities. Many panelists also discussed the interconnectedness of several variables; sometimes the presence of one burden may exacerbate another, such as in the case of extreme heat and air pollution in rural communities, as depicted by Martinez. She suggested that adding qualitative data may strengthen the tool by filling in gaps from quantitative data. Another participant, Sacoby Wilson (Professor, University of Maryland, College Park) echoed that sentiment. He also suggested that a national-level tool may be useful as a first screen, but ultimately regional tools with more community-specific components would be best for identifying where and how to distribute benefits to disadvantaged communities.

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CEJST DEMONSTRATION AND HANDS-ON EXERCISE

The workshop continued with committee member Walker Wieland (Research Scientist, California Environmental Protection Agency) demonstrating how to navigate to and use CEJST to identify communities defined as disadvantaged by the tool, using Fresno, California, as an example. Workshop participants were divided into six breakout groups for a hands-on exercise; each group included at least one committee member. Participants were asked to find CEJST results for communities with which they are familiar and to reflect on how consistent information presented by CEJST was with their knowledge of real-world conditions. Participants were given an activity handout, prepared by the committee, that included the Fresno example and questions to prompt reflection, such as “Does your community show up in CEJST with multiple high burdens (blue dots)?” Committee member Ibraheem Karaye (Assistant Professor, Hofstra University) moderated the report-outs from each breakout group. The following are examples of key takeaways from the breakout group discussions as presented by their rapporteurs.

The concept of false negatives—the idea that a highly burdened census tract was mistakenly not classified as disadvantaged—was discussed in all breakout groups. Participant Chitra Balakrishnan (Research Analyst, University of Illinois Urbana-Champaign) mentioned a census tract not identified as disadvantaged by CEJST because it did not meet the low-income threshold, but it was surrounded to the north and south by areas that were identified as disadvantaged. Because CEJST does not incorporate the cost of living into its data analysis, the income threshold alone may disqualify an area from being disadvantaged even if it meets thresholds for multiple other burden indicators. For this and other reasons, many participants took issue with the binary designation of disadvantaged used in CEJST. One group discussed using a scoring system for measuring status as disadvantaged. Balakrishnan added that the designation process creates a situation in which communities that are disproportionately burdened compete for finite funding opportunities with communities on the cusp of being designated as disadvantaged. Allowing communities to self-designate their disadvantage or to self-report data, including qualitative data, was encouraged by some participants throughout the workshop to reduce gaps in data that excluded a community from being identified as disadvantaged in CEJST. These participants suggested that not incorporating these community-driven data may produce a constant lag between the data needed to capture a burden and the nationally consistent data that are available for use in the tool. Participant Alexis Schulman (Assistant Research Professor, Drexel University) said that communities can demonstrate disadvantage “through cumulative hazards or particular variables that are not accessible nationally or [are not] standardized, although [this information] could or do[es] exist at a local level.”

False-positive cases—instances in which less-burdened communities are designated as disadvantaged—were also discussed in a few groups, especially in the context of gentrification. For example, a highly gentrified area in Delaware, with many high-rises and condos, is well resourced but still designated as disadvantaged by CEJST. As noted by Larry Lambert (State Representative of Delaware’s 7th District) the census data used in CEJST represent a snapshot in time before rapid development in that area took place; thus the community will continue to be defined as disadvantaged until the data are updated.

Cummings identified the “fallacy of averages” as the misclassification of a census tract based on grouping communities with very different experiences. He cited the example of Annapolis, Maryland, where public housing communities are not identified as disadvantaged because they share a census tract with million-dollar homes. He went on to say, “Income metrics nationally lack the ability to indicate housing burdens, such as cost-burdened housing which takes up a large percentage of a family’s income.” In further conversation of income metrics, several groups noted that income and poverty are not adequately captured using the low-income threshold or ACS data.

Other examples of datasets that may not represent lived experiences were discussed. One group used the example of PM_2.5 (fine particulate matter with a diameter of 2.5 micrometers or less, a measure of air quality) in

Philadelphia. Schulman indicated that there are only 10 air quality monitors around the city, yet those data are generalized across its hundreds of census tracts. Another group expressed how one indicator of burden can be dominant, blurring the varying issues that different parts of the region face. Participant Marilee Davenport (Senior Director of Capacity and Collaboration, Natural Resources Defense Council) described her group’s example of El Paso, Texas, in which the dominance of the linguistic isolation indicator made it seem as if all of the city was more disadvantaged than the reality. Several groups noted that CEJST does not adequately characterize water issues in general; it could incorporate measures of water and wastewater infrastructure and access to safe drinking water. Participant Deborah Sunter (Senior Advisor on Energy Justice, U.S. Department of Energy) also mentioned that CEJST, like most geospatial tools, is not able to categorize disadvantaged groups that are not localized in one area, for example, previously incarcerated people.

The user experience, or how one interacts with CEJST, was mentioned several times. One breakout group rapporteur stated that using CEJST requires a certain level of education and familiarity with indicators to navigate this tool. Conversely, other participants noted that the tool could be more dynamic in its ability to analyze communities, such as by filtering by a certain indicator or category. A group also raised issues about accessibility relative to 508 compliances⁸ of the web portal for persons with vision impairment.

After the rapporteurs spoke, participants discussed the degree to which the tool is open source. One participant said that even though CEJST is made open source via the GitHub platform, it is not being used to the degree that it could be, adding that it has the potential to hold agencies accountable for decision making. Participants stated that the tool has data transparency and downloading capabilities, but it does not include the ability for the public to directly collaborate on the software. Another participant commented that open source does not necessarily have to be collaborative in a technical sense; open-source collaboration can be reflected in a comment box for feedback from the community. Participant Marisa Sotolongo (Ph.D. candidate, Northeastern University School of Public Policy) noted that “community engagement exists on a vast spectrum” and should be incorporated at every level, from tool creation to implementation, in how it is being used.

PANEL DISCUSSION: DEFINING DISADVANTAGED COMMUNITIES

Committee member Lauren Bennett (Group Product Engineering Lead, Esri, Inc.) led a panel discussion in which speakers were asked to address the following questions: How should a disadvantaged community be defined? Is CEJST accurately identifying communities you know are disadvantaged, and if not, how can it better identify them?

The first panelist, Mathy Stanislaus, Esq. (Vice Provost and Executive Director of the Environmental Collaboratory, Drexel University) questioned the exclusive use of CEJST results for decision making because its binary designation does not distinguish subpopulations within a region facing greater burdens from those with lesser burdens. He suggested that these mapping tools incorporate the practice of community-based mapping, which includes the perspectives of communities “to map the neighborhood as they see it.” Stanislaus and his colleague, Alexis Schulman, presented these issues by showing CEJST beside the Justice40 maps that they developed for use in Philadelphia.⁹ Their maps utilized an Expanded Environmental Justice Index consisting of criteria for chronic disinvestment and cumulative environmental hazards. They based their index on CEJST’s census-tract data in conjunction with qualitative input from community-based organizations, considering pockets outside of ZIP codes in which communities self-defined areas of greater disparity. They demonstrated how CEJST designates more tracts as disadvantaged than the priority areas outlined by their lab’s map. Stanislaus described this as CEJST identifying “too large of a geographic area” and not focusing on areas with the highest disparity. Their maps also showed how layered

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data can be used to highlight cumulative burdens that a community is facing. Stanislaus emphasized that grant applicants can use this layering technique to tailor their applications and tell their story to the federal agency that might be providing funding.

Sotolongo spoke about state-level initiatives similar to Justice40. To show the potential for CEJST to combine the identification of disadvantaged communities with the allocation of benefits to these communities, she used the examples of Illinois’s Solar For All¹⁰ and California’s CalEnviroScreen.¹¹ She explained that these states “developed multiple reports, mapping tools, and databases that show how funding is being distributed in these communities all across these states.” Sotolongo raised questions about how funding is being matched to need since CEJST does not include funding allocation on its map, only whether a community is disadvantaged or not. In addition, she pointed out the top-down approach of its designation process, noting that communities could have more input on how they are being defined and what needs they have when it comes to benefits allocation.

Panelist Jack Ding (Volunteer for Environmental Justice Technology, Anthropocene Alliance) echoed previous concerns about the tool. He described Casa, Arkansas, a small community with specific climate change challenges, as an example. Ding questioned the use of census tract as the best unit of analysis. Casa is not designated by CEJST as disadvantaged because it is in a tract that does not meet the low-income threshold. Casa is “being averaged by their neighbors,” according to Ding. He also recalled that since the tool does not incorporate water data into its analyses, it is potentially underrepresenting the burden that many communities face.

Representative Lambert applauded the efforts of CEJST while also sharing opportunities for improvement. Lambert helped establish an oversight committee in his state’s General Assembly to track the investment benefits coming into Delaware in response to the Justice40 Initiative. He expressed concern about the tool’s ability to capture communities that may be “historically disregarded.” He emphasized the importance of ensuring that the 40% of investment benefits are getting to communities that need it the most.

Wilson, who helped develop an environmental justice screening tool similar to CEJST for the state of Maryland, shared critiques of the beta version of CEJST. Regarding the binary labeling of disadvantaged communities, Wilson said, “You have a whole bucket of folks who you say are disadvantaged, but you’re not … ranking, prioritizing, and micro-targeting communities with the most need. You can’t get at cumulative impacts with the current approach. And you’re really not integrating community voice.” He further suggested the inclusion of race or a proxy for race, such as racial disparities, in the tool as the most potent predicator of environmental hazards. While acknowledging that historic underinvestment data were added to the tool, based on redlining maps from the Home Owners’ Loan Corporation that instituted legal racial segregation, he said that the data are not as up-to-date as they could be at capturing racism and environmental injustice.¹² Wilson mentioned data that are not represented in the tool, including lack of basic amenities such as water, more accurate air quality data, health disparities, and energy burden and energy infrastructure. Ultimately, he said, the tool is about “centering the people who are most impacted, and making sure we have the most impact.”

When asked which is the biggest area for improvement that they would like to see in the tool, several panelists noted that the tool could improve the way it pictures and designates which communities are disadvantaged. The tool could have the option to look at different categories of burden and perhaps have a graded scoring for level of disadvantage. Ding reemphasized that there could be a focus on cumulative burdens for directing funding to places that need it most, while being careful not to leave out those who experience persistent burden.

PLENARY DISCUSSION: ADDRESSING DATA GAPS

In the final session of the day, committee member Monica Unseld (Founder and Executive Director, Until

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Justice Data Partners) led a discussion about both common and unique observations about data gaps. Participants raised overlapping issues such as addressing and measuring racism, tracking cumulative burdens, and how to deal with variations in experiences among rural and urban communities.

Regarding environmental racism, Wilson brought up the importance of a focus on differential enforcement of policy and differential access to resources. He noted that racism has led to wealth inequality. The tool could have “more emphasis on wealth,” said Ashwood, as opposed to income, indicating that it can reveal populations with greater access to ownership of their labor and land. She pointed to tax parcel data and housing data in urban areas, regarding who rents, who owns, and the kinds of houses in which they live. A health equity lens was also mentioned as a critical component in thinking about health disparities within a tract and across tracts. Xiuhtecutli discussed the potential for using data from the Bureau of Labor Statistics’ Occupational Employment and Wage Statistics Data program because it has information on who is doing what kind of work and therefore to what they are exposed.¹³

The concept of cumulative burdens (or how burdens may interact in the presence of many at the same time) was raised. Several participants discussed whether burdens are additive or multiplicative; some asked whether one burden drives another. “You have to really dig to find out what the context is,” emphasized Sotolongo. Through an example in Boston, she compared her census tract around Northeastern University, which is identified as disadvantaged based on indicators of the Workforce Development category, to East Boston, which is identified as disadvantaged based on linguistic isolation along with several energy and infrastructure indicators, air pollution, and noise pollution. She explained that these communities have very different conditions, particularly noting the multiple burdens that East Boston experiences as a known environmental justice community, yet the tool identifies both as disadvantaged. “[The reality is] reflected in some ways in these indicators, but when you look at the map it’s all the same,” she added, speaking of the binary nature of the tool.

A participant noted that there is no distinction between how urban and rural communities are assessed within CEJST; the same calculations, indicators, and burdens are used for the entire country. Wilson suggested use of separate urban and rural tools to stress how different the experience is for each community. He also said that aside from the circumstances themselves, census tract is probably not the right unit of analysis for rural communities. Balakrishnan pointed to state-level tools, created by Mapping for Environmental Justice, that incorporate specific rural scenarios, such as Colorado including an oil and gas indicator and Virginia using mining data.¹⁴ In rebuttal, a participant said that perhaps CEJST does capture a greater breath of experiences (even the differences among urban and rural communities) because only one burden indicator is needed to reach the threshold (along with a socioeconomic factor)—allowing a greater number of communities to be identified as disadvantaged with a wide range of indicators. Wilson stated that because of that inclusivity, using CEJST for decision-making would be difficult without a way to rank, prioritize, and micro-target communities.

Access to data and data ownership were also mentioned. Many organizations, including private companies, have potentially important data for this tool but place them behind a paywall.¹⁵ Amen Mashariki (Director of Data Strategies, Bezos Earth Fund) brought forth the example of Alabama Power, a utility company, that “had more data about Birmingham than the City of Birmingham had about itself.” Academia may also perpetuate this paywall—Stanislaus called it “publicly funded data that [are] not made available to the public.” He suggested that academia and others open their data to the communities they serve.

CLOSING REMARKS

Co-chair of the committee, Harvey Miller (Professor and Chair in GIS, The Ohio State University), delivered

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closing remarks and introduced Dr. Cecilia Martinez (Chief of Environmental and Climate Justice, Bezos Earth Fund). Dr. Martinez discussed the history of CEJST, the “enormity of the task” set forth by the White House to develop it, and how CEJST has laid the foundation for meaningful work. She mentioned that the White House Environmental Justice Advisory Council provided recommendations for the tool in the early stages of development, which along with public engagement, led to Version 1.0. Martinez underscored that, “Now is the moment for all of us to contribute our best to develop these methodologies.”

Participants’ contributions included stressing the importance of incorporating community input, indicating that communities often know best about their needs and the injustices they face. Many participants indicated the difficulties that CEJST may face in accurately identifying disadvantaged communities and sufficiently contributing to the goals of Justice40 since programs spanning a variety of fields (such the eight categories of burden) will be utilizing CEJST. These challenges may include what data should be incorporated or through which approach communities should be identified as disadvantaged, ultimately deciding which communities may be able to benefit from additional federal funding. The committee was urged by several participants to consider their task carefully, as the implications of CEJST and its results may lie beyond funding opportunities alone.

DISCLAIMER This Proceedings of a Workshop—in Brief was prepared by Anthony DePinto as a factual summary of what occurred at the workshop. The statements made are those of the rapporteur(s) or individual workshop participants and do not necessarily represent the views of all workshop participants; the planning committee; or the National Academies of Sciences, Engineering, and Medicine.

COMMITTEE MEMBERS Harvey J. Miller (Co-Chair), Reuche Chair in Geographic information Science, The Ohio State University; Eric Tate (Co-Chair), Professor, Princeton University; Susan Anenberg, Associate Professor, George Washington University; Lauren Bennett, Group Product Engineering Lead, Esri, Inc.; Jayajit Chakraborty, Professor and Director, Department of Sociology and Anthropology, University of Texas at El Paso; Ibraheem Karaye, Assistant Professor, Hofstra University; Marcos Luna, Professor, Salem State College; Bhramar Mukherjee (NAM), John D. Kalbfleisch Collegiate Professor and Chair, Department of Biostatistics, University of Michigan; Kathleen Segerson (NAS), Board of Trustees Distinguished Professor, University of Connecticut; Monica E. Unseld, Founder and Executive Director, Until Justice Data Partners; Walker Wieland, Research Scientist, California Environmental Protection Agency.

REVIEWERS To ensure that it meets institutional standards for quality and objectivity, this Proceedings of a Workshop—in Brief was reviewed by Amy W. Ando, Professor, University of Illinois Urbana-Champaign; Chitra Balakrishnan, Research Analyst, Urban Institute; and Mathy (Vathanaraj) Stanislaus, Esq., Vice Provost and Executive Director, The Environmental Collaboratory, Drexel University. We also thank staff member Anne Stykas, for reading and providing helpful comments on this manuscript. Lauren Everett, National Academies of Sciences, Engineering, and Medicine, served as the review coordinator.

STAFF Sammantha Magsino, Senior Program Officer; Anthony DePinto, Associate Program Officer; Oshane Orr, Program Assistant; Sarah Hartman, Mirzayan Fellow.

SPONSOR This workshop was supported by the Bezos Earth Fund.

SUGGESTED CITATION National Academies of Sciences, Engineering, and Medicine. 2023. Representing Lived Experience in the Climate and Economic Justice Screening Tool: Proceedings of a Workshop—in Brief. Washington, DC: The National Academies Press. https://doi.org/10.27158.

Division on Earth and Life Studies Copyright 2023 by the National Academy of Sciences. All rights reserved.