Abstract
The environmental justice (EJ) movement has called attention to the failure of government policies to address cumulative impacts (CI), the multiple and compounding social and environmental stressors that disproportionately affect low-income communities and communities of color. In recent years, driven by the organizing of EJ groups, there has been a proliferation, not only of CI mapping tools, but also of policy proposals to address CI in permitting, particularly at the state level. For the purpose of informing these efforts, we developed a database of state policies that codify a CI requirement in permitting decisions. Through web searches, consultation of existing databases, and direct knowledge, we collected state policies up through September 2024. Data were summarized on their purpose, scope of application, community definitions, and methodologies. The database includes information from eight states that have codified CI considerations in permitting decisions and 11 states with bills that have not passed. Our analysis reveals the design choices that arise in CI lawmaking and rulemaking, which may influence the efficacy of protections. A critical decision point is the strength of the legal mandate to deny permits, but we also documented multiple ways in which even a strong mandate can be diluted. We found many policy features offering opportunities to cater to local context, even while existing policies can serve as models. Moreover, we observed rulemaking to be a critical and not merely “technical” counterpart of legislation, needed not just for making implementation possible, but also for knowing the ultimate strength of the policy.
Keywords
INTRODUCTION
Cumulative impacts (CI) are the co-occurrence of multiple environmental pollution burdens alongside socioeconomic stressors that can heighten the impact of those burdens. As a key environmental justice (EJ) issue, CI is the lived reality affecting communities of color and low-income communities across the United States. 1
A key barrier to addressing CI is that environmental regulations largely focus on single pollutants or sources of pollution. Permitting and standard-setting insufficiently account for mutually exacerbating effects of co-occurring burdens and vulnerabilities.2,3,4 This includes risk assessment methodologies that, even while seeking to address more exposed or susceptible subpopulations or account for multiple exposure pathways, are limited by their inability to account for nonchemical stressors, their focus on singular direct health outcomes, and an assumed lack of bias in the toxicological and other studies that undergird risk assessments. 5
The crisis of CI has prompted decades-long EJ organizing efforts. These efforts gained traction in the 2000s into the 2010s, with reports like the 2004 National Environmental Justice Advisory Council report, which defined CI and highlighted the need to consider combined effects when evaluating projects and policies. 6
However, early CI responses largely focused on forming advisory committees to study the problem and developing quantitative methodologies to assess CI. 7 While such responses contributed to recognizing CI as a problem, they fell short of providing tangible protections, as they did not provide a mandate to prevent additional sources of pollution from being sited in already overburdened communities. In this early period, which included the 2013 launch of the first official state CI mapping tool (CalEnviroScreen), 8 no laws required that CI assessments be determinative in decisions to renew or site sources of pollution. California’s Senate Bill 673, passed in 2015, was a step in this direction, requiring the Department of Toxic Substances Control (DTSC) to “consider for inclusion” indicators of CI in permitting decisions for hazardous waste facilities. 9 However, DTSC’s rulemaking remains ongoing.
In 2020, following a 12-year advocacy effort led by local EJ groups, New Jersey (NJ) became the first jurisdiction to codify a requirement that permits be denied on the basis of the outcome of a CI assessment. 10 The state’s landmark EJ law brought a new wave, not only of CI assessment and mapping tools, but also of policies requiring CI to be addressed in permitting. This policymaking push has largely occurred at the state level, propelled by grassroots advocacy.
The history of our work on CI mirrors this trajectory of CI efforts. In 2019, the Tishman Center initially created a broad compilation of federal and state laws, policies, mapping tools, agency guidance, and gray literature on CI. 11 The positive feedback we received from EJ advocates and researchers on this work, alongside the momentum for state CI policies, motivated us to hone a version 2.0 of the database focused on state CI policies codifying a CI requirement in permitting decisions. 12 By analyzing CI permitting policies, this article and database seek to be a resource to EJ advocates as they come to decision points in policy design.
METHODOLOGY
Data collection
The 2.0 database used the initial database, whose data collection methodology is described in its accompanying report, 13 as a starting point. From April 2024 through September 2024, new entries were sourced from Google (using search term, “cumulative impacts”), news archives, legislative archives,14,15 existing databases,16,17 webinars and other public events, and direct knowledge.
For policies, we sought to include all enacted state laws, rules, and regulations that implement a CI requirement in the environmental permitting context. 18 For proposed laws, we sought to include those that were active, though some that were not (e.g., bills that had died in legislative session) were included in the database. 19 As an additional resource and to contextualize this policymaking, we also included state-adopted tools in those jurisdictions that map and calculate CI. 20
Data were extracted for each policy and tool and organized into the database as shown in Table 1. Column headings were refined as we determined the types of information most relevant to EJ advocates.
Data for Cumulative Impact Laws, Rules, and Tools
Data analysis
Qualitative thematic analysis
Once the database entries were compiled, we used an iterative process to identify patterns and themes and further refine the categories used in the database. An initial review of the database surfaced a list of key issues to analyze, which was then supplemented by ideas generated in a participatory analysis workshop conducted with additional Tishman Center staff. The workshop consisted of individual prework to review extracted policy language and then an open discussion to collectively surface the most salient policy features, commonalities, and distinctions. The research team then went back to the database entries to conduct a more thorough analysis of identified issues, which included patterns in community definitions, potential policy loopholes or weaknesses, and the relationship (or lack thereof) between CI policies and CI mapping tools within the same jurisdiction. We observed that a number of state policies employed a similar approach to define communities, sometimes called “EJ communities” or a similar term, where the CI permitting requirement would be triggered, and this prompted the additional quantitative analysis described below.
Quantitative analysis of “EJ community” definition coverage
A subset of 11 states was analyzed to determine the extent of coverage given their definition of an EJ community (see Supplementary Table S2). 21 These states were chosen because their policies employed a similar construction of an EJ community definition, namely applying thresholds—expressed as fixed percentages or relative to state averages—to one or more sociodemographic indicators, and then combining the indicators with an “and” or “or” construction. 22
The thresholds, indicators, and geographic unit specified in the policy were applied to the 2018–2022 5-year estimates from the American Community Survey (ACS) 23 for consistency. 24 All policies utilized census tracts (CTs) or census block groups (CBGs), and thus we calculated the percentage of CTs or CBGs in the state that would be considered an EJ community. 25 We also calculated the corresponding percentage of the state’s population living in EJ communities, using population counts obtained from the 2018–2022 ACS. 26 Individual indicators were also analyzed, and their thresholds were compared with state averages to understand how they contributed to a more limited or expansive community definition. 27
Analysis and visualizations were conducted in R and Python. The scripts, specific ACS tables used, and additional methodological details are available upon request.
RESULTS
Eight states (California, Colorado, Connecticut, Massachusetts, Minnesota, New Jersey, New York, and Vermont) have codified a requirement for CI to be considered in permitting. However, as of the end of 2024, only two (NJ and MA) have implemented regulations for their policy. 28 We found an additional 11 states (Arizona, DC, Delaware, Georgia, Illinois, Maryland, Michigan, Pennsylvania, Rhode Island, Washington, and Wisconsin) with proposed CI permitting bills that had not passed but had advanced sufficiently so as to offer interesting content to potential database users. To help contextualize the policymaking in these 19 states, we included in the database any state tools for mapping or calculating CI. The database’s inventory is captured in Table 2.
Content Covered in Cumulative Impacts 2.0 Database
Displayed chronologically (see Fig. 1), the proliferation of proposed and passed policies that have followed after NJ’s law in 2020 is evident, with many successive policies adopting the three-part structure of the NJ law and some even borrowing language (see subsections below). Another observation is that while the first state to have a CI tool, California, achieved this as early as 2013, it still lacks an enforceable CI permitting policy, as the implementing regulations for the CI component of SB 673 are pending. 29 Conversely, most states that have passed or made notable progress toward proposing CI permitting legislation have done so without having an official state CI tool. Although our intention was to include any official CI tools to help contextualize the policymaking, even when a state has both, the policy does not necessarily reference the tool. 30
Timeline of CI proposed laws, passed laws, and regulations.
Purpose and scope of CI policies
We found that CI policies generally follow a three-part structure. The first part entails the identification of the communities informing where the CI permitting requirement will apply (which some policies and we here refer to as “EJ communities” for brevity). 31 The second part is a requirement for a CI analysis to be conducted when certain kinds of facilities apply for permits in or near those EJ communities. The third part is the course of action pertaining to the permit that is triggered depending on the outcome of the CI analysis. The legislation also typically contains procedural provisions on timelines, notice requirements, and public participation. 32
Usually, the legislation itself does not contain the CI methodology; rather, this is left for agency rulemaking. Terminology varies by legislation, but the essence is that the specified CI methodology answers the question of whether issuing the permit will cause or contribute to CI in the EJ community and therefore triggers a course of action (such as denying or conditioning the permit). 33 Out of all the policies in the database, DC’s and WA’s include a methodology within their proposed laws, NJ has already adopted a rule with the methodology for its law, and MA is a special case where both the policy and methodology are contained in an agency regulation considered part of the state’s administrative law 34 ; the policies from the other 15 states are examples where methodology would have to be determined in rulemaking.
In its provisions specifying the course of action to be taken regarding the permit, the passed and proposed laws vary in strength, sometimes using weaker, discretionary language and other times providing for exceptions or loopholes. A necessary, but not sufficient, condition of a strong policy is language that obligates the decision maker to deny permits, at least of a certain type and under certain conditions, as evidenced by terminology like “must” or “shall.” Such policies were found in DC, GA, IL, MN, NJ, NY, and WA. This is in contrast to policies using discretionary language—e.g., “may” or “can” or “potentially” deny—as seen in the passed and proposed policies of AZ, CO, CT, DE, MA, MD, PA, RI, and WI. 35
In some cases, even policies using “must” or “shall” can be weakened by provisions allowing the approval to happen if there is a plan to mitigate harm, that is, applying conditions to permit approval. For example, DC’s bill provides that if the CI statement shows that the proposed project will cause disproportionate impact, the permit shall be disapproved, unless the applicant proposes mitigating measures or substitutes an alternative to avoid such impact. 36
We also found provisions related to compelling public interest and community benefit agreements (CBAs), sometimes used to change the decision outcome. For example, NJ’s law and the legislation proposed in MI, GA, and WA contain a “compelling public interest” exception, allowing states to approve permits that would otherwise be denied. Note, however, that the extent of these exceptions can be limited. For example, in NJ, the compelling public interest must accrue to the EJ community itself, and final rulemaking has excluded economic benefits from being considered a compelling public interest. WA includes similar limitations embedded in the bill itself, and GA’s proposed legislation copies NJ’s law nearly verbatim. Laws passed in MN and CT also provide for CBAs. In MN, the CBA serves as a loophole, as a permit that would otherwise be obligatorily denied can be approved if the facility owner or operator enters into a CBA. In CT, whose law does not require permit denials, CBAs function differently—they are a prerequisite in the process before a decision can be made on the permit, with applicants being required to consult with municipal officials on the need for a CBA and being required to reach one in certain circumstances. 37
Permits and facilities
The CI policies in the database cover various permit types, including those for new facilities, expansions of existing facilities, and renewals. In some cases, policies may offer different legal requirements based on the type of permit. For example, in NJ, permits for new facilities are mandatorily denied based on the CI analysis, whereas those for expansions and renewals may apply conditions that will mitigate harm. In NY, permits for new facilities are denied if the project will cause or contribute more than a de minimis amount of pollution to a disproportionate pollution burden on a disadvantaged community. However, permit renewals or modifications are denied if the project would significantly increase the existing disproportionate pollution burden on a disadvantaged community.
The CI policies analyzed usually have a corresponding universe of facility types to be covered. Common facility types include major sources of air pollution, 38 generators that exceed a certain capacity, incinerators, sewage treatment plants, scrap metal facilities, and waste transfer stations. Each policy may have a particular focus reflecting historic sources of harm in the state’s EJ communities. 39 This tailoring was a key part of the list of covered facilities in NJ’s law. We observed what seemed like tailoring in examples from other states, such as animal-feeding operations in Michigan, underground injection control wells in Pennsylvania, and asphalt or concrete plants in DC.40,41,42 At times, the law bypasses specifying a list of facilities and instead uses broader terms such as “state action.” 43 While this approach can be more inclusive—encompassing any project initiated—it also introduces a potential loophole if facilities maneuver outside the scope of the definition of an “action.”
EJ community definition
For most policies, the identification of EJ communities is crucial to informing where CI permitting requirements apply. Eleven states have an EJ community definition based on socioeconomic indicators, listed in their passed or proposed policy (see Supplementary Table S2). All definitions include one to five indicators, with household income and People of Color (POC) 44 population being the most common. Indicators vary in their application and thresholds. CBGs and CTs are the spatial units used for eight and three states, respectively. 45
Policies set indicator thresholds in terms of a state average or as a fixed number. 46 For thresholds set as fixed percentages, we examined these against state averages. NJ and GA are examples of states intentionally setting at least one fixed threshold at or close to state averages, while most set their thresholds above state averages, meaning that their approach to defining EJ communities is less inclusive. Another important aspect determining the definition’s inclusivity is whether a conjunctive or disjunctive approach is used in analyzing multiple indicators (see Fig. 2). Most policies use a purely disjunctive approach, and a community meeting the threshold for any one (or more) of the indicators thus qualifies as an EJ community. A conjunctive approach—requiring all indicator thresholds to be met—was less common, as was a mixed approach that would require a specific indicator to be met along with one of several possible other indicators (e.g., the community must meet the income criterion plus either the race/ethnicity or linguistic isolation criteria).
Conjunctive (“And”; left panel), disjunctive (“Or”; center panel), and mixed approaches (right panel) for EJ community definition indicators visualized as Venn diagrams.
Based on the full EJ community definition adopted in each state, we calculated the percentage of the population and spatial units meeting the definition. The population proportion covered under each EJ community definition varies significantly across states (see Table 3). DE and WI cover the highest and lowest proportions, 78.40% and 5.54%, respectively.
Overview of Coverage in the State Based on Policy’s EJ Community Definition
As explained in the Methodology section, we have used the readily available CBG indicators in the ACS, which do not exclude populations in dormitories, custody, or prison, as per Massachusetts’ “neighborhood” definition. Our estimate therefore approximates the true statewide coverage.
These states’ CI definition includes a dummy variable for American Indian land, which is not part of the quantitative analysis. Hence, the respective calculations represent a lower bound of the scope of the coverage by the definition, as detailed in the Methods.
As expected, the extent of coverage appears greatly influenced by the policy’s design. For instance, the two states with the lowest coverage—WI and MI—are the only ones using a conjunctive approach. As another example, while VT uses fixed percentage thresholds, it appears to fine-tune them according to the state’s demographics. VT’s thresholds include a minimum of 6% for POC populations and a minimum of 1% for limited English proficiency populations, reflecting the state averages of 7.48% and 0.62%, respectively. Consequently, its population coverage is relatively high (59.80%). WI, having the lowest coverage, employs thresholds significantly higher than its state averages: The threshold for POC and limited English proficiency status is 40%, compared with statewide averages of 18.66% and 1.51%, respectively. 47
Relationship between identified EJ communities and protected communities
The extent of EJ communities identified from the quantitative criteria is tied to the extent of protection they provide, but this relationship is not straightforward due to variations in policy design. For instance, some policies allow communities to self-designate as EJ areas, potentially expanding the scope of protection. 48 Other policies use geographic parameters, such as specified radii around facilities, to extend protection beyond the boundaries of designated EJ communities. 49 These measures may help ensure that facilities affecting EJ communities are subject to CI requirements. However, policies can also impose filters that constrain their protective scope. A notable example is MN, whose policy uses a statewide EJ community definition but limits the CI permitting requirements to specific counties and cities of a certain size.
CI assessment methodologies
For the 19 states in our database, we found that many of the policies did not yet lay out a CI assessment methodology because the policy had not passed and/or rulemaking was still pending. To help contextualize policymaking and glean insight into where future rulemaking might head, we gathered CI assessment methodologies contained in any existing state mapping tool, even if such a tool was not explicitly referenced yet by the policy. 50 Our review of all methodologies together surfaced several observations.
First, there are two general methodologies for assessing CI. One is what has been termed in the literature as a “Single Scoring Method,” which calculates an index score from environmental and social vulnerability indicators and determines a threshold score that designates an area as experiencing CI burdens. 51 This methodology requires several key considerations, including how to weigh each indicator and whether to multiply or add indicator scores together when calculating the score. 52
The second method for assessing CI is referred to as the “Matrix Method” or “NJ Method,” which evaluates environmental and social vulnerability indicators (or “stressors”) individually. 53 Each stressor in the EJ community is analyzed in comparison to the same stressor from a geographic point of comparison (GPC) to determine if the stressor is adversely affecting the community. 54 If the stressor value in the EJ community is higher than its GPC, it is considered “adverse.” If the total number of adverse stressors in the EJ community is higher than that of its GPC, the community is considered to experience CI. 55
Whether the first or second method is used, the setting of the threshold CI score or the GPCs, respectively, is key to determining how readily the course of action (denying a permit or conditioning a permit, for example) is triggered. (However, since rulemaking for many state policies is still pending, most states do not yet have explicit CI thresholds for action.) In any case, the majority of the indicators used fell into similar categories, including environmental exposures and pollution, environmental effects and public health impacts, sensitive populations, and socioeconomic factors. Climate hazards rarely appeared as indicators among the methodologies in our sample.
DISCUSSION
The development of CI permitting policies has marked an important step toward addressing environmental injustice, allowing an opportunity to disrupt entrenched practices of unequal siting of environmental burdens in low-income communities and communities of color. Our research underscores the fact that this type of CI policy intervention extends beyond (and is at times independent of) the creation of tools and methodologies, requiring the establishment of robust legal frameworks, enforcement mechanisms, and community-centered processes.
This article thus contributes to the body of CI research by taking a policy-focused approach. Prior research has highlighted the health considerations and motivations of addressing CI, the development of state-specific mapping tools, and the methodologies behind quantifying CI.56,57,58,59 Our goal here was not to systematically review all mapping tools. Besse and Rojas-Rueda recently provided such an overview, comparing the scope, breadth, and geographic resolution of tools across 25 states. 60 Compared with Besse and Rojas-Rueda and earlier reviews such as Balakrishnan et al. 61 and Konisky et al., 62 the database resource we have created emphasizes passed and proposed laws, responding to a need for policy ideas and “proofs of concept” that EJ advocates can bring to local policymakers. While much previous research and attention around the topic of CI has focused on CI mapping tools and methodologies, we have surfaced many examples of CI policies arising prior to the existence of—or without explicit reference to—official CI mapping tools or methodologies in the same jurisdiction.
Our results have highlighted the implications of policy design choices pertaining to topics like scope, mandatory versus discretionary authority, loopholes and exceptions, as well as quantitative and qualitative aspects of EJ community definitions. We observe how these choices may influence the coverage and efficacy of protections and, consequently, the experiences of EJ communities. The policy decision points are reflected by the columns in the database and arise in the context of lawmaking as well as rulemaking.
Within these decision points, arguably the most critical is whether permit denials are obligated, at least under some circumstances. It was perhaps surprising to find a number of proposed and even passed policies where denial is always discretionary, never required. Among the other decision points, we observed many ways in which even a strong legal mandate can be diluted. For example, there can be a weaker standard for certain types of permits, or there can be exceptions to the mandate based on “public interest,” mitigating actions, or CBAs. The use of CBAs, particularly in EJ communities, has been criticized due to concerns about representation (i.e., who speaks for the community), pressure on already marginalized communities, and unfairness in asking EJ communities to compromise essential rights, like health and clean air, for social and economic goods that more privileged communities readily access.63,64,65 Moreover, there can be a narrow universe of covered facilities or a restrictive definition of communities to be protected, or places where the policy applies. In moving from designating EJ communities to identifying communities benefiting from CI permitting scrutiny, divergent approaches are seen, some of which can broaden protections (e.g., through additional self-designation mechanisms or radii), but others of which can narrow them (e.g., limiting the policy to EJ communities in specific localities). A narrower scope would suggest a less protective policy overall; however, the relationship may not be straightforward in cases where there may have been a trade-off (in political terms) between the breadth of application and the strength of protection, or in situations where an overly broad EJ community definition dilutes the ability to focus on the most underserved or disadvantaged communities. 66 Understanding the strategic decisions of EJ advocates in various jurisdictions is beyond the scope of this research but would be a worthwhile objective of future research.
Another key takeaway deriving from the myriad decision points is that there is ample opportunity to cater to local context, even while new policies may look to existing policies as models. For example, the universe of facility types covered by a policy is one arena in which EJ advocates can cater their legislation to the polluting activities of their local context. The designation of EJ communities is another policy component where tailoring can happen and where we in fact observed substantial variation. States relying on sociodemographic indicators often draw on similar indicators (particularly race, income, and English proficiency); however; established thresholds yield a wide range in the proportion of the state’s population that is considered an EJ community. Thresholds are sometimes set close to state averages, but not always. A number of policies utilize other approaches to designate EJ communities, such as incorporating environmental indicators and/or composite indices that may have been created specifically for the state.
A final takeaway is that implementing rules and regulations is a critical component of the legislation, needed not just for the practical effect of making implementation possible but also for knowing the ultimate strength of the policy. There are fewer cases of completed rulemaking. However, examples suggest that rulemaking not only has the ability to undercut some of the legislation’s protections, but sometimes it can be used strategically to improve weaknesses in the law (for example, restricting what falls under a “compelling public interest” exception). Rulemaking can also be highly technical, as it will be the likely domain where the CI methodology—including quantitative thresholds for triggering a course of action—is determined. For both reasons, EJ advocates and the technical allies should expect to follow rulemaking closely.
LIMITATIONS
For the state CI policies collected, a separate thorough analysis of public participation requirements would be useful, especially given their potential to entrench or improve long-standing challenges of community access in environmental permitting. 67 In addition, as detailed in the Methods, our calculation of state coverage of EJ definitions is approximate for some states and was also not conducted for every state. We may also have missed a relevant state law or bill, though we will include additional policies as we receive feedback and refine the database. At a more local level, municipal CI policies have also been on the rise, and we hope to include an analysis of such policies in future work. Last, but not least of all, this research would be illuminated greatly by qualitative information from local EJ advocates, who can elucidate the decision-making behind policies, as well as the status of implementation.
CONCLUSION
Our research and database highlight the significant advancement in CI policy over the past five years. While much research and attention around the topic of CI has previously focused on CI mapping tools and methodologies, we have now seen many examples of CI policies arising prior to the existence of an official mapping tool or methodology in the same jurisdiction. CI permitting protections are a policy innovation that continues to gain traction, bringing both enormous potential and pitfalls. As the federal landscape for achieving environmental justice is threatened, local policies such as those detailed here are all the more critical, and it is our hope that this work contributes to their development.
AUTHORS’ CONTRIBUTIONS
A.I.B. contributed to project conceptualization, methodology, data analysis, and writing (editing). Y.L. contributed to project conceptualization, methodology, data collection, data analysis, writing (original draft and editing), and project supervision. A.Y. contributed to project conceptualization, methodology, data collection, data analysis, writing (original draft and editing), and project administration. M.K. contributed to methodology, data collection, data analysis, and writing (original draft and editing). C.S.B. contributed to methodology, data collection, data analysis, and writing (original draft and editing).
Footnotes
ACKNOWLEDGMENTS
The authors would like to thank Dr. Jennifer Santos Ramirez for contributing to the participatory analysis workshop and Drs. Nicky Sheats and Sacoby Wilson for sharing information on local CI developments in New Jersey and Maryland.
AUTHOR DISCLOSURE STATEMENT
The authors have no competing financial interests to declare.
FUNDING INFORMATION
This research received no external funding.
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