Decades of environmental social science research points to metrics, criteria, and methods vital to accurately identifying people and communities most affected by environmental hazards, but the beta version of the White House’s Climate and Economic Justice Screening Tool, released in February 2022, is missing some of those key elements. Addressing these omissions would ensure the tool more effectively serves the administration’s goals of supporting local, state, and federal stakeholders in prioritizing investments that advance environmental justice in communities exposed to the most serious environmental hazards.
The screening tool is core to the administration’s Justice40 Initiative, which promises to deliver 40 percent of the overall benefits from energy and climate investments across 21 federal agencies to what it calls “disadvantaged” communities, defined as census tracts experiencing disproportionate pollution, poverty, and underinvestment.
We shared our analysis in a public comment in response to the White House Council on Environmental Quality’s (CEQ) request for feedback on the beta version of the tool and offered recommendations to strengthen the tool’s measurement, accuracy, and methodology. Here we highlight three of our nine key insights that can inform the Climate and Economic Justice Screening Tool and other federal and state environmental justice data tools that have recently been released or are under development.
1. Include measures for race to increase the validity of environmental justice measurement.
Race metrics are not included as an indicator of disadvantage in the tool, and the administration has expressed concerns of legal challenges if they were included. But because race is one of the most significant and consistent predictors of environmental hazard exposure, failing to include race could jeopardize the tool’s measurement validity and alignment with environmental justice principles.
Omitting race as an indicator obscures racial disparities and thus risks perpetuating patterns of disadvantage. Race-neutral measures produce different results than race-conscious measures, as evidenced by the modeled impacts of the proposed changes to the US Department of Housing and Urban Development’s Affirmatively Furthering Fair Housing rule in 2020.
In a recent panel on Justice40 and environmental justice measurement cohosted by the Urban Institute and Resources for the Future, experts discussed precedent for including race in other federal tools, such as the US Department of Health and Human Services (HHS) Healthy People 2030 interactive data tool. Similar to environmental outcomes, research consistently shows race is a strong predictor of disparity in health outcomes. Considering both the social science and federal precedent, including race is empirically justified, and the HHS Healthy People tool could be a model for the inclusion of race in the Climate and Economic Justice Screening Tool.
2. Measure cumulative impacts to prioritize communities with the greatest environmental hazard exposure and greatest economic and public health burdens.
Unlike other state and federal tools that are not attached to a specific policy or regulatory mandate, the tool was developed to direct resources to communities that meet the administration’s criteria for disadvantaged and help identify those who should be prioritized for federal investments under Justice40. Of the more than 80,000 census tracts nationwide, nearly one-third qualify as disadvantaged under the administration’s current eligibility criteria. But eligibility is a binary category, meaning it is not possible to identify communities bearing the most significant environmental burdens to proportionally target investments to them.
Communities often face more than one environmental, economic, and health stressor, resulting in cumulative burden. For example, people living near pollution sources can experience depressed property values, poor air quality, poor water quality, greater health burdens, and related sociopsychological impacts from living with these hazard exposures. Without identifying and prioritizing communities with the greatest environmental, economic, and health burdens, there is a risk that communities with comparatively few stressors could outcompete communities with the greatest cumulative burdens for investment resources. This outcome runs the risk of diluting the impact of Justice40 and is inconsistent with well-established environmental justice principles.
To address this concern, the tool could shift to a cumulative impact model similar to state environmental justice screening tools like California’s CalEnviroScreen and Maryland’s EJScreen. These state tools use an index scoring methodology that comparatively ranks and prioritizes communities according to environmental hazard and pollution burdens and population vulnerability characteristics.
3. Consider state-level, rural, and tribal metrics to address urban bias and expand the tool’s representativeness.
Data that aren’t available nationwide aren’t included in the tool. This national scale effectively erases environmental justice hazards at finer geographic scales and fails to capture many rural- and tribal-specific environmental justice hazards, like mining and reclamation hazards, pesticide exposures, or deforestation. Rural and tribal communities exposed to these and other environmental hazards would not be captured in the tool unless they meet other national-scale criteria. This could also result in rural and tribal communities qualifying for priority investment because of environmental justice exposures or vulnerabilities that are captured in the tool but that are less locally relevant than other noneligible but more serious hazards, resulting in investments that don’t align with community needs.
We raise concerns about the contribution and value of standardized national data that do not capture key environmental justice challenges facing rural and tribal communities. Incorporating a screening process to allow for the submission of relevant state-level hazard data that roll up into the tool’s existing hazard categories would improve the tool’s representativeness. This strategy is employed in Maryland’s EJScreen, which includes eligibility metrics for rural, unincorporated communities that would not otherwise be captured in a national tool. To ensure environmental hazard interests in such communities are not lost in the final tool, the CEQ could incorporate eligibility metrics specific to rural and tribal communities.
Just a first step
In our full public comment, we underscore that measuring race, accounting for cumulative impacts, and including state, rural, and tribal metrics are just a few first steps the CEQ can take to ensure the tool more fully supports the goals of Justice40. A more comprehensive suite of public health and climate change–related metrics—as well as an accountability structure for monitoring and evaluating environmental, health, and social benefits, as well as unintended consequences—is also necessary to achieve its goals.
By implementing these recommendations, the Justice40 Initiative can be better positioned to meet its commitment to redress historical disparities and maximize restorative investments in communities most harmed by environmental burdens.
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