Recent years have seen a proliferation of mapping and data tools characterizing the cumulative impacts (CI) of environmental and social stressors. The development of these tools by governmental and nongovernmental organizations has been motivated by the need to address multiple, persistent environmental disparities and identify overburdened communities. These mapping and data tools empower policymakers to make informed decisions on where to focus their attention and resources in addressing environmental health inequities. This article examines some of the concerns and debates surrounding CI mapping tools from the perspectives of two established tools, the California Environmental Protection Agency’s CalEnviroScreen and the Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry’s Environmental Justice Index. We discuss the importance of balancing statistical rigor with community engagement, transparency, and ease of use, and we discuss the processes behind indicator selection and evaluation. Furthermore, we explore persistent data gaps and trade-offs between specificity and generalizability, as well as precision and accuracy in CI tools. Our discussion is framed by a commitment to achieving equity through prioritizing meaningful community engagement and collaboration. To mitigate common limitations of CI mapping, we propose strategies such as statistical validation, the use of plain language communication, and community collaboration for increased adoption and use. We conclude with recommendations for future tool enhancements and underscore the importance of transparent methodologies and community-driven approaches in CI screening, all while continuing the development of principles that guide equitable environmental decision making to address environmental and health disparities.

People of color and with lower socioeconomic status are more likely to live near pollution sources. We present a framework for assessing whether disparities in residential proximity to multiple environmental hazards are improving and illustrate the approach using CalEnviroScreen, a geographic screening tool used by the State of California to designate disproportionately burdened (‘disadvantaged’) communities. In this proof-of-concept, we derived a benchmarked composite index from a subset of four CalEnviroScreen indicators (traffic, cleanup sites, pesticide use, and toxic releases) and assess inequality with respect to disadvantaged community designation and race and ethnicity over time (2014-2021). The average absolute and relative gap between disadvantaged and non-disadvantaged communities shrank over this period – signaling improvement – but grew among the most impacted communities (95th percentile). Disadvantaged communities were 51% more likely to experience better-than-average improvement in cumulative environmental burdens than non-disadvantaged communities. Gaps also shrank among tracts with high proportions of people of color relative to Whites, with the exception of Hawaiians and Pacific Islanders. Expanding our approach to encompass additional indicators could help policymakers prioritize investments in communities falling further behind and make greater progress towards health equity.

Diesel exhaust (DE) is a major traffic-related pollutant linked to adverse health outcomes, but existing methods for estimating indoor DE exposure fall short, as common surrogates like black carbon (BC), NOx, and PM2.5 are not sufficiently specific to diesel sources. 1-Nitropyrene (1-NP), a nitro-PAH preferentially formed during diesel combustion, has rarely been studied as an indoor exposure indicator. We measured 1-NP and isomeric nitro-PAHs (2-nitropyrene, 2-nitrofluoranthene) in indoor air and house dust from 40 homes in the eastern San Francisco Bay Area, CA, across two sampling events, alongside continuous indoor BC monitoring. We assessed 1-NP’s utility as a DE proxy using summary statistics, diagnostic nitro-PAH ratios, correlations with monitored pollutants, and single-predictor mixed-effects models relating 1-NP to spatial DE predictors. 1-NP was frequently detected in air (74%) and dust (97%), with median concentrations of 0.42 pg/m³ (IQR 0.32 - 0.54) and 340 pg/g (IQR 190 - 620), respectively. Air and dust 1-NP were moderately correlated (r=0.40, p = 0.02), as was BC with 1-NP (air r=0.38, dust r=0.47; p<0.01). Diagnostic ratios (2-NFl:1-NP <5) indicated dominant primary emission sources. Dust 1-NP showed numerous significant associations with spatial DE predictors, while air 1-NP showed fewer. Overall, 1-NP shows promise as a diesel-specific indoor exposure proxy integrating longer-term exposure and aligning with spatial DE predictors.

Diesel exhaust (DE) is a major traffic-related pollutant linked to adverse health outcomes, but existing methods for estimating indoor DE exposure are not validated. DE exposure indicators such as black carbon (BC), NOx, and PM_2.5 are not sufficiently specific to diesel sources. 1-Nitropyrene (1-NP), an NPAH preferentially formed during diesel combustion, has rarely been studied as an indoor exposure indicator. We measured 1-NP and isomeric NPAHs (2-nitropyrene, 2-nitrofluoranthene) in indoor air and house dust from 40 homes in the eastern San Francisco Bay Area, CA, and conducted continuous indoor BC monitoring. We assessed 1-NP’s utility as a DE exposure indicator using summary statistics, diagnostic NPAH ratios, correlations with monitored pollutants, and single-predictor mixed-effects models relating 1-NP to spatial DE predictors. 1-NP was frequently detected in air (74%) and dust (97%), with median concentrations of 0.42 pg/m³ (IQR 0.32–0.54) and 340 pg/g (IQR 190–620), respectively. Air and dust 1-NP were moderately correlated (r = 0.40, p = 0.02), as was BC with 1-NP (air r = 0.38, dust r = 0.47; p < 0.01). Diagnostic ratios (2-NFl:1-NP < 5) indicated dominant primary emission sources. Dust 1-NP showed numerous significant associations with spatial DE predictors, while air 1-NP showed fewer. Overall, 1-NP shows promise as a diesel-specific indoor exposure indicator. Future studies with larger, geographically diverse cohorts are needed to further validate this metric.