Exploring relationships between smoke exposure, housing characteristics, and preterm birth in California.

Pregnant people are vulnerable to air pollution exposure, including risk of preterm birth, low birth weight, and stillbirth. Understanding the infiltration of outdoor wildfire smoke into a residential space is critical for the accurate assessment of wildfire smoke exposure and associated health effects in pregnant people. Relying on ambient measurements of wildfire smoke alone can result in exposure misclassification. In this study, we examine the role of physical housing characteristics in the relationship between smoke exposure and preterm birth. In particular, we examine the effect of home size, year of construction, cooling type, and renovation status, as effect modifiers in the relationship between smoke exposure during pregnancy and preterm birth from 2007 to 2015 in California. To do this, we combined data on home characteristics from the California Tax Assessor, birth outcomes from the California birth records database, and the number of smoke days for each pregnancy from theNOAA (National Oceanic and Atmospheric Administration) Hazard Mapping System (HMS). We estimated the association between smoke day exposures and odds of preterm birth using logistic regression models and stratified by air basin and housing characteristics. Our findings reveal that cooling type and renovation status are key factors modifying the smoke exposure-preterm birth relationship. Notably, we found elevated associations for people living in unrenovated homes, those using evaporative cooling systems, and those using central air conditioning units. While we observed elevated odds of preterm birth associated with increasing smoke day exposure for residents of large and new homes, this effect does not significantly differ across home size and age quartiles. This study highlights the need to further examine the relative roles of housing characteristics as well as factors not measured here including behavioral factors, time spent outdoors, window use, and occupational exposures in driving adverse birth outcomes related to wildfire smoke exposure.

The Influence of Gentrification on Adverse Birth Outcomes in California.

Evidence has documented the effects of place on perinatal outcomes, but less is known about the sociopolitical mechanisms, such as gentrification, that shape neighborhood context and produce spatialized inequities in adverse birth outcomes. Leveraging a diverse sample in California, we assessed the associations between gentrification and birth outcomes: preterm birth, small-for-gestational-age, and low birth weight. Gentrification was measured using the Freeman method and the Displacement and Gentrification Typology. Descriptive analysis assessed outcome prevalence and race and ethnicity distribution by exposure and participant characteristics. Overall and race and ethnicity-stratified mixed effects logistic models examined associations between gentrification and birth outcomes, sequentially adjusting for sociodemographic status and pregnancy factors, with a random intercept to account for clustering by census tract. In a sample of 5,116,131 births, outcome prevalence ranged from 1.0% for very preterm birth, 5.0% for low birth weight, 7.9% for preterm birth, and 9.4% for small-for-gestational-age. Adjusting for individual-level factors, gentrification was associated with increased odds of preterm birth (Freeman OR = 1.09, 95% CI 1.07-1.10; Displacement and Gentrification Typology OR = 1.11, 95% CI 1.09-1.13). While Displacement and Gentrification Typology-measured gentrification was consistently associated with greater odds of adverse outcomes, Freeman-measured gentrification was associated with slightly lower odds of small-for-gestational-age and low birth weight. Furthermore, gentrification was associated with birth outcome odds across multiple racial and ethnic groups, but the directions and magnitudes of the associations varied depending on the gentrification assessment methodology and the outcome assessed. Results demonstrate that gentrification plays a role in shaping adverse birth outcomes in California.

Do small effects matter more in vulnerable populations? an investigation using Environmental influences on Child Health Outcomes (ECHO) cohorts.

BACKGROUND: A major challenge in epidemiology is knowing when an exposure effect is large enough to be clinically important, in particular how to interpret a difference in mean outcome in unexposed/exposed groups. Where it can be calculated, the proportion/percentage beyond a suitable cut-point is useful in defining individuals at high risk to give a more meaningful outcome. In this simulation study we compute differences in outcome means and proportions that arise from hypothetical small effects in vulnerable sub-populations. METHODS: Data from over 28,000 mother/child pairs belonging to the Environmental influences on Child Health Outcomes Program were used to examine the impact of hypothetical environmental exposures on mean birthweight, and low birthweight (LBW) (birthweight < 2500g). We computed mean birthweight in unexposed/exposed groups by sociodemographic categories (maternal education, health insurance, race, ethnicity) using a range of hypothetical exposure effect sizes. We compared the difference in mean birthweight and the percentage LBW, calculated using a distributional approach. RESULTS: When the hypothetical mean exposure effect was fixed (at 50, 125, 167 or 250g), the absolute difference in % LBW (risk difference) was not constant but varied by socioeconomic categories. The risk differences were greater in sub-populations with the highest baseline percentages LBW: ranging from 3.1-5.3 percentage points for exposure effect of 125g. Similar patterns were seen for other mean exposure sizes simulated. CONCLUSIONS: Vulnerable sub-populations with greater baseline percentages at high risk fare worse when exposed to a small insult compared to the general population. This illustrates another facet of health disparity in vulnerable individuals.

Historical Redlining, Contemporary Gentrification, and Severe Maternal Morbidity in California, 2005-2018.

Importance: Historically redlined neighborhoods may experience disinvestment, influencing their likelihood of gentrification, a process of neighborhood (re-)development that unequally distributes harms and benefits by race and class. Understanding the combined outcomes of redlining and gentrification informs how the mutually constitutive systems of structural racism and racial capitalism affect pregnancy outcomes. Objective: To examine if historical redlining and contemporary gentrification is associated with increased severe maternal morbidity (SMM) odds. Design, Setting, and Participants: This cross-sectional study used data from a statewide population-based sample of all live hospital births at 20 weeks' gestation or more between 2005 and 2018 in California. Analysis was conducted from March 2023 to January 2024. Exposure: Redlining (as characterized by the federal Home Owners' Loan Corporation mortgage security maps) and displacement (using present-day sociodemographic and housing market information). Main Outcomes and Measures: Mixed-effects logistic regression models were used to assess the association of census tract-level exposure to historical redlining and contemporary gentrification with increased SMM odds, adjusting for sociodemographic and pregnancy related factors. Outcome classification was based on the Centers for Disease Control and Prevention SMM index, which defines SMM as having any of the 21 procedures and diagnoses based on the International Classification of Diseases, Ninth Revision and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes. Results: The study sample included 1 554 837 births (median [SD] maternal age, 29.0 [6.4] years; 3464 American Indian or Alaskan Native [0.2%], 224 774 Asian [14.5%], 132 240 Black [8.5%], 880 104 Hispanic [56.6%], 312 490 White [20.1%]), with 22 993 cases of SMM (1.4%). Residents in historically redlined neighborhoods that were undergoing gentrification or displacement were more likely to be Black, Hispanic, and American Indian or Alaskan Native. Independent of individual-level characteristics, SMM odds were greater for individuals living in redlined neighborhoods that experienced displacement (OR, 1.21; 95% CI, 1.14-1.28) and in redlined neighborhoods undergoing gentrification (OR, 1.21; 95% CI, 1.13-1.29) compared with those in continuously advantaged neighborhoods. Conclusions and Relevance: Findings from this cross-sectional study demonstrate that the legacies of redlining, intertwined with current dynamics of displacement and gentrification, affect SMM. Place-based sociopolitical mechanisms that inequitably distribute resources may be important intervention points to address structural drivers of adverse pregnancy outcomes and their racial inequities.

Machine learning for environmental justice: Dissecting an algorithmic approach to predict drinking water quality in California.

The potential for machine learning to answer questions of environmental science, monitoring, and regulatory enforcement is evident, but there is cause for concern regarding potential embedded bias: algorithms can codify discrimination and exacerbate systematic gaps. This paper, organized into two halves, underscores the importance of vetting algorithms for bias when used for questions of environmental science and justice. In the first half, we present a case study of using machine learning for environmental justice-motivated research: prediction of drinking water quality. While performance varied across models and contaminants, some performed well. Multiple models had overall accuracy rates at or above 90 % and F2 scores above 0.60 on their respective test sets. In the second half, we dissect this algorithmic approach to examine how modeling decisions affect modeling outcomes - and not only how these decisions change whether the model is correct or incorrect, but for whom. We find that multiple decision points in the modeling process can lead to different predictive outcomes. More importantly, we find that these choices can result in significant differences in demographic characteristics of false negatives. We conclude by proposing a set of practices for researchers and policy makers to follow (and improve upon) when applying machine learning to questions of environmental science, management, and justice.

The Camp fire and perinatal health: An example of the generalized synthetic control method to identify susceptible windows of exposure.

BACKGROUND: The November 2018 Camp fire was the most destructive wildfire in California history, but its effects on reproductive health are not known. METHODS: We linked California birth records from 2017-2019 to daily smoke levels using U.S. EPA Air Quality System (AQS) PM2.5 data and NOAA Hazard Mapping System smoke plume polygons during the Camp fire. In the main analysis, pregnancies were considered exposed if they had median AQS PM2.5 levels above 50 µg/m3 for at least 7 days during November 8-22, 2018. We calculated rates of preterm birth and the infant sex ratio based on week of conception and used the generalized synthetic control method to estimate the average treatment effect on the treated and to propose a novel approach to identify potential critical weeks of exposure during pregnancy. RESULTS: We found associations between Camp fire-related smoke exposure and rates of preterm birth, with a risk difference (RD) = 0.005, 95% CI 0.001, 0.010. Exposure during week 10 of pregnancy was consistently associated with increased preterm birth (RD = 0.030, 95% CI 0.004, 0.056). We did not observe differences in the infant sex ratio. CONCLUSIONS: Camp fire smoke exposure was associated with increased rates of preterm birth, with sensitive windows in the first trimester.

California dreaming: Why environmental justice is integral to the success of climate change policy.

In the realm of climate policy, issues of environmental justice (EJ) are often treated as second-order affairs compared to overarching sustainability goals. We argue that EJ is in fact critical to successfully addressing our national and global climate challenges; indeed, centering equity amplifies the voices of the diverse constituencies most impacted by climate change and that are needed to build successful coalitions that shape and advance climate change policy. We illustrate this perspective by highlighting the experience of California and the contentious processes by which EJ became integrated into the state's climate action efforts. We examine the achievements and shortcomings of California's commitment to climate justice and discuss how lessons from the Golden State are influencing the evolution of current federal climate change policy.

Wildfires increasingly threaten oil and gas wells in the western United States with disproportionate impacts on marginalized populations.

The western United States is home to most of the nation's oil and gas production and, increasingly, wildfires. We examined historical threats of wildfires for oil and gas wells, the extent to which wildfires are projected to threaten wells as climate change progresses, and exposure of human populations to these wells. From 1984-2019, we found that cumulatively 102,882 wells were located in wildfire burn areas, and 348,853 people were exposed (resided ≤ 1 km). During this period, we observed a five-fold increase in the number of wells in wildfire burn areas and a doubling of the population within 1 km of these wells. These trends are projected to increase by late century, likely threatening human health. Approximately 2.9 million people reside within 1 km of wells in areas with high wildfire risk, and Asian, Black, Hispanic, and Native American people have disproportionately high exposure to wildfire-threatened wells.

Climate Justice Implications of Natech Disasters: Excess Contaminant Releases during Hurricanes on the Texas Gulf Coast.

Extreme weather events are becoming more severe due to climate change, increasing the risk of contaminant releases from hazardous sites disproportionately located in low-income communities of color. We evaluated contaminant releases during Hurricanes Rita, Ike, and Harvey in Texas and used regression models to estimate associations between neighborhood racial/ethnic composition and residential proximity to hurricane-related contaminant releases. Two-to-three times as many excess releases were reported during hurricanes compared to business-as-usual periods. Petrochemical manufacturing and refineries were responsible for most air emissions events. Multivariable models revealed sociodemographic disparities in likelihood of releases; compared to neighborhoods near regulated facilities without a release, a one-percent increase in Hispanic residents was associated with a 5 and 10% increase in the likelihood of an air emissions event downwind and within 2 km during Hurricanes Rita and Ike (odds ratio and 95% credible interval= 1.05 [1.00, 1.13], combined model) and Harvey (1.10 [1.00, 1.23]), respectively. Higher percentages of renters (1.07 [1.03, 1.11], combined Rita and Ike model) and rates of poverty (1.06 [1.01, 1.12], Harvey model) were associated with a higher likelihood of a release to land or water, while the percentage of Black residents (0.94 [0.89, 1.00], Harvey model) was associated with a slightly lower likelihood. Population density was consistently associated with a decreased likelihood of a contaminant release to air, land, or water. Our findings highlight social inequalities in the risks posed by natural-technological disasters that disproportionately impact Hispanic, renter, low-income, and rural populations.

PFAS-Contaminated Pesticides Applied near Public Supply Wells Disproportionately Impact Communities of Color in California.

Contaminated drinking water from widespread environmental pollutants such as perfluoroalkyl and polyfluoroalkyl substances (PFAS) poses a rising threat to public health. PFAS monitoring in groundwater is limited and fails to consider pesticides found to contain PFAS as a potential contamination source. Given previous findings on the disproportionate exposure of communities of Color to both pesticides and PFAS, we investigated disparities in PFAS-contaminated pesticide applications in California based on community-level sociodemographic characteristics. We utilized statewide pesticide application data from the California Department of Pesticide Regulation and recently reported concentrations of PFAS chemicals detected in eight pesticide products to calculate the areal density of PFAS applied within 1 km of individual community water systems' (CWSs) supply wells. Spatial regression analyses suggest that statewide, CWSs that serve a greater proportion of Latinx and non-Latinx People of Color residents experience a greater areal density of PFAS applied and greater likelihood of PFAS application near their public supply wells. These results highlight agroecosystems as potentially important sources of PFAS in drinking water and identify areas that may be at risk of PFAS contamination and warrant additional PFAS monitoring and remediation.

Historical redlining is associated with disparities in wildlife biodiversity in four California cities.

Legacy effects describe the persistent, long-term impacts on an ecosystem following the removal of an abiotic or biotic feature. Redlining, a policy that codified racial segregation and disinvestment in minoritized neighborhoods, has produced legacy effects with profound impacts on urban ecosystem structure and health. These legacies have detrimentally impacted public health outcomes, socioeconomic stability, and environmental health. However, the collateral impacts of redlining on wildlife communities are uncertain. Here, we investigated whether faunal biodiversity was associated with redlining. We used home-owner loan corporation (HOLC) maps [grades A (i.e., "best" and "greenlined"), B, C, and D (i.e., "hazardous" and "redlined")] across four cities in California and contributory science data (iNaturalist) to estimate alpha and beta diversity across six clades (mammals, birds, insects, arachnids, reptiles, and amphibians) as a function of HOLC grade. We found that in greenlined neighborhoods, unique species were detected with less sampling effort, with redlined neighborhoods needing over 8,000 observations to detect the same number of unique species. Historically redlined neighborhoods had lower native and nonnative species richness compared to greenlined neighborhoods across each city, with disparities remaining at the clade level. Further, community composition (i.e., beta diversity) consistently differed among HOLC grades for all cities, including large differences in species assemblage observed between green and redlined neighborhoods. Our work spotlights the lasting effects of social injustices on the community ecology of cities, emphasizing that urban conservation and management efforts must incorporate an antiracist, justice-informed lens to improve biodiversity in urban environments.

Mixture effects of prenatal exposure to polybrominated diphenyl ethers on urinary oxidative stress biomarkers in the Chemicals in Our Bodies Cohort.

Polybrominated diphenyl ethers (PBDEs) exposure is associated with preterm birth. Laboratory studies suggest that PBDEs lead to elevated oxidative stress, a known contributor to preterm birth in epidemiologic studies. We hypothesized that elevated levels of PBDEs would be associated with increased oxidative stress during human pregnancy. Participants in this analysis were enrolled in the Chemicals in Our Bodies cohort and resided in the San Francisco Bay Area (N=201). Four PBDEs (BDE-47, -99, -100, -153) were measured in second trimester serum. Urinary oxidative stress biomarkers were measured at two timepoints (second and third trimester) and included 8-isoprostane-prostaglandin-F2α [8-iso-PGF2α], 2,3-dinor-5,6-dihydro-8-iso-PGF2α, 2,3-dinor-8-iso-PGF2α, and prostaglandin-F2α [PGF2α]. Associations between individual PBDEs and oxidative stress biomarkers (averaged and trimester specific) were examined using linear regression. Quantile g-computation and Bayesian kernel machine regression (BKMR) were used to assess cumulative effects of PBDEs. Quantile g-computation showed that higher concentrations of PBDEs were associated with increasing 8-iso-PGF2α, 2,3-dinor-8-iso-PGF2α, and PGF2α. Associations were greatest in magnitude for second trimester levels of 2,3-dinor-8-iso-PGF2α (mean change per quartile increase=0.25, 95% confidence interval=0.09, 0.41). Associations were similar using BKMR and linear regression. Our findings suggest that oxidative stress may be a plausible biological pathway by which PBDE exposure might lead to preterm birth.

Metabolic Perturbations Associated with both PFAS Exposure and Perinatal/Antenatal Depression in Pregnant Individuals: A Meet-in-the-Middle Scoping Review.

PURPOSE OF REVIEW: Depression during the perinatal or antenatal period affects at least 1 in 10 women worldwide, with long term health implications for the mother and child. Concurrently, there is increasing evidence associating maternal exposure to per- and poly-fluoroalkyl substances (PFAS) to adverse pregnancy outcomes. We reviewed the body of evidence examining both the associations between PFAS exposure and perturbations in the maternal metabolome, and the associations between the maternal metabolome and perinatal/antenatal depression. Through this, we sought to explore existing evidence of the perinatal metabolome as a potential mediation pathway linking PFAS exposure and perinatal/antenatal depression. RECENT FINDINGS: There are few studies examining the metabolomics of PFAS exposure-specifically in pregnant women-and the metabolomics of perinatal/antenatal depression, let alone studies examining both simultaneously. Of the studies reviewed (N = 11), the majority were cross sectional, based outside of the US, and conducted on largely homogenous populations. Our review identified 23 metabolic pathways in the perinatal metabolome common to both PFAS exposure and perinatal/antenatal depression. Future studies may consider findings from our review to conduct literature-derived hypothesis testing focusing on fatty acid metabolism, alanine metabolism, glutamate metabolism, and tyrosine metabolism when exploring the biochemical mechanisms conferring the risk of perinatal/antenatal depression due to PFAS exposure. We recommend that researchers also utilize heterogenous populations, longitudinal study designs, and mediation approaches to elucidate key pathways linking PFAS exposures to perinatal/antenatal depression.

Cross-Sectional Associations between Prenatal Per- and Poly-Fluoroalkyl Substances and Bioactive Lipids in Three Environmental Influences on Child Health Outcomes (ECHO) Cohorts.

Prenatal per- and poly-fluoroalkyl substances (PFAS) exposure may influence gestational outcomes through bioactive lipids─metabolic and inflammation pathway indicators. We estimated associations between prenatal PFAS exposure and bioactive lipids, measuring 12 serum PFAS and 50 plasma bioactive lipids in 414 pregnant women (median 17.4 weeks' gestation) from three Environmental influences on Child Health Outcomes Program cohorts. Pairwise association estimates across cohorts were obtained through linear mixed models and meta-analysis, adjusting the former for false discovery rates. Associations between the PFAS mixture and bioactive lipids were estimated using quantile g-computation. Pairwise analyses revealed bioactive lipid levels associated with PFDeA, PFNA, PFOA, and PFUdA (p < 0.05) across three enzymatic pathways (cyclooxygenase, cytochrome p450, lipoxygenase) in at least one combined cohort analysis, and PFOA and PFUdA (q < 0.2) in one linear mixed model. The strongest signature revealed doubling in PFOA corresponding with PGD2 (cyclooxygenase pathway; +24.3%, 95% CI: 7.3-43.9%) in the combined cohort. Mixture analysis revealed nine positive associations across all pathways with the PFAS mixture, the strongest signature indicating a quartile increase in the PFAS mixture associated with PGD2 (+34%, 95% CI: 8-66%), primarily driven by PFOS. Bioactive lipids emerged as prenatal PFAS exposure biomarkers, deepening insights into PFAS' influence on pregnancy outcomes.

Water Fluoridation and Birth Outcomes in California.

BACKGROUND: There is a lack of research on the relationship between water fluoridation and pregnancy outcomes. OBJECTIVES: We assessed whether hypothetical interventions to reduce fluoride levels would improve birth outcomes in California. METHODS: We linked California birth records from 2000 to 2018 to annual average fluoride levels by community water system. Fluoride levels were collected from consumer confidence reports using publicly available data and public record requests. We estimated the effects of a hypothetical intervention reducing water fluoride levels to 0.7 ppm (the current level recommended by the US Department of Health and Human Services) and 0.5 ppm (below the current recommendation) on birth weight, birth-weight-for-gestational age z-scores, gestational age, preterm birth, small-for-gestational age, large-for-gestational age, and macrosomia using linear regression with natural cubic splines and G-computation. Inference was calculated using a clustered bootstrap with Wald-type confidence intervals. We evaluated race/ethnicity, health insurance type, fetal sex, and arsenic levels as potential effect modifiers. RESULTS: Fluoride levels ranged from 0 to 2.5 ppm, with a median of 0.51 ppm. There was a small negative association on birth weight with the hypothetical intervention to reduce fluoride levels to 0.7 ppm [-2.2g; 95% confidence interval (CI): -4.4, 0.0] and to 0.5 ppm (-5.8g; 95% CI: -10.0, -1.6). There were small negative associations with birth-weight-for-gestational-age z-scores for both hypothetical interventions (0.7 ppm: -0.004; 95% CI: -0.007, 0.000 and 0.5 ppm: -0.006; 95% CI: -0.013, 0.000). We also observed small negative associations for risk of large-for-gestational age for both the hypothetical interventions to 0.7 ppm [risk difference (RD)=-0.001; 95% CI: -0.002, 0.000 and 0.5 ppm (-0.001; 95% CI: -0.003, 0.000)]. We did not observe any associations with preterm birth or with being small for gestational age for either hypothetical intervention. We did not observe any associations with risk of preterm birth or small-for-gestational age for either hypothetical intervention. CONCLUSION: We estimated that a reduction in water fluoride levels would modestly decrease birth weight and birth-weight-for-gestational-age z-scores in California. https://doi.org/10.1289/EHP13732.

Pregnancy exposure to PM2.5 from wildland fire smoke and preterm birth in California.

BACKGROUND: Wildfires in the Western United States are a growing and significant source of air pollution that is eroding decades of progress in air pollution reduction. The effects on preterm birth during critical periods of pregnancy are unknown. METHODS: We assessed associations between prenatal exposure to wildland fire smoke and risk of preterm birth (gestational age < 37 weeks). We assigned smoke exposure to geocoded residence at birth for all live singleton births in California conceived 2007-2018, using weekly average concentrations of particulate matter ≤ 2.5 µm (PM2.5) attributable to wildland fires from United States Environmental Protection Agency's Community Multiscale Air Quality Model. Logistic regression yielded odds ratio (OR) for preterm birth in relation to increases in average exposure across the whole pregnancy, each trimester, and each week of pregnancy. Models adjusted for season, age, education, race/ethnicity, medical insurance, and smoking of the birthing parent. RESULTS: For the 5,155,026 births, higher wildland fire PM2.5 exposure averaged across pregnancy, or any trimester, was associated with higher odds of preterm birth. The OR for an increase of 1 µg/m3 of average wildland fire PM2.5 during pregnancy was 1.013 (95 % CI:1.008,1.017). Wildland fire PM2.5 during most weeks of pregnancy was associated with higher odds. Strongest estimates were observed in weeks in the second and third trimesters. A 10 µg/m3 increase in average wildland fire PM2·5 in gestational week 23 was associated with OR = 1.034; 95 % CI: 1.019, 1.049 for preterm birth. CONCLUSIONS: Preterm birth is sensitive to wildland fire PM2.5; therefore, we must reduce exposure during pregnancy.

Historical Redlining Is Associated with Disparities in Environmental Quality across California.

Historical policies have been shown to underpin environmental quality. In the 1930s, the federal Home Owners' Loan Corporation (HOLC) developed the most comprehensive archive of neighborhoods that would have been redlined by local lenders and the Federal Housing Administration, often applying racist criteria. Our study explored how redlining is associated with environmental quality across eight California cities. We integrated HOLC's graded maps [grades A (i.e., "best" and "greenlined"), B, C, and D (i.e., "hazardous" and "redlined")] with 10 environmental hazards using data from 2018 to 2021 to quantify the spatial overlap among redlined neighborhoods and environmental hazards. We found that formerly redlined neighborhoods have poorer environmental quality relative to those of other HOLC grades via higher pollution, more noise, less vegetation, and elevated temperatures. Additionally, we found that intraurban disparities were consistently worse for formerly redlined neighborhoods across environmental hazards, with redlined neighborhoods having higher pollution burdens (77% of redlined neighborhoods vs 18% of greenlined neighborhoods), more noise (72% vs 18%), less vegetation (86% vs 12%), and elevated temperature (72% vs 20%), than their respective city's average. Our findings highlight that redlining, a policy abolished in 1968, remains an environmental justice concern by shaping the environmental quality of Californian urban neighborhoods.

Measuring long-term exposure to wildfire PM2.5 in California: Time-varying inequities in environmental burden.

Wildfires have become more frequent and intense due to climate change and outdoor wildfire fine particulate matter (PM2.5) concentrations differ from relatively smoothly varying total PM2.5. Thus, we introduced a conceptual model for computing long-term wildfire PM2.5 and assessed disproportionate exposures among marginalized communities. We used monitoring data and statistical techniques to characterize annual wildfire PM2.5 exposure based on intermittent and extreme daily wildfire PM2.5 concentrations in California census tracts (2006 to 2020). Metrics included: 1) weeks with wildfire PM2.5 < 5 µg/m3; 2) days with non-zero wildfire PM2.5; 3) mean wildfire PM2.5 during peak exposure week; 4) smoke waves (≥2 consecutive days with <15 µg/m3 wildfire PM2.5); and 5) mean annual wildfire PM2.5 concentration. We classified tracts by their racial/ethnic composition and CalEnviroScreen (CES) score, an environmental and social vulnerability composite measure. We examined associations of CES and racial/ethnic composition with the wildfire PM2.5 metrics using mixed-effects models. Averaged 2006 to 2020, we detected little difference in exposure by CES score or racial/ethnic composition, except for non-Hispanic American Indian and Alaska Native populations, where a 1-SD increase was associated with higher exposure for 4/5 metrics. CES or racial/ethnic × year interaction term models revealed exposure disparities in some years. Compared to their California-wide representation, the exposed populations of non-Hispanic American Indian and Alaska Native (1.68×, 95% CI: 1.01 to 2.81), white (1.13×, 95% CI: 0.99 to 1.32), and multiracial (1.06×, 95% CI: 0.97 to 1.23) people were over-represented from 2006 to 2020. In conclusion, during our study period in California, we detected disproportionate long-term wildfire PM2.5 exposure for several racial/ethnic groups.

Multiple Dimensions of Environmental Justice and Oil and Gas Development in Pennsylvania.

Background: Community socioeconomic deprivation (CSD) may be related to higher oil and natural gas development (OGD) exposure. We tested for distributive and benefit-sharing environmental injustice in Pennsylvania's Marcellus Shale by examining (1) whether OGD and waste disposal occurred disproportionately in more deprived communities and (2) discordance between the location of land leased for OGD and where oil and gas rights owners resided. Materials and Methods: Analyses took place at the county subdivision level and considered OGD wells, waste disposal, and land lease agreement locations from 2005 to 2019. Using 2005-2009 American Community Survey data, we created a CSD index relevant to community vulnerability in suburban/rural areas. Results: In adjusted regression models accounting for spatial dependence, we observed no association between the CSD index and conventional or unconventional drilled well presence. However, a higher CSD index was linearly associated with odds of a subdivision having an OGD waste disposal site and receiving a larger volume of waste. A higher percentage of oil and gas rights owners lived in the same county subdivision as leased land when the community was least versus most deprived (66% vs. 56% in same county subdivision), suggesting that individuals in more deprived communities were less likely to financially benefit from OGD exposure. Discussion and Conclusions: We observed distributive environmental injustice with respect to well waste disposal and benefit-sharing environmental injustice related to oil and rights owner's residential locations across Pennsylvania's Marcellus Shale. These results add evidence of a disparity between exposure and benefits resulting from OGD.