Changes in Transportation-Related Air Pollution Exposures by Race-Ethnicity and Socioeconomic Status: Outdoor Nitrogen Dioxide in the United States in 2000 and 2010

The Role of Neighborhood Air Pollution in Disparate Racial and Ethnic Asthma Acute Care Use

Rationale: The share of Black or Latinx residents in a census tract remains associated with asthma-related emergency department (ED) visit rates after controlling for socioeconomic factors. The extent to which evident disparities relate to the within-city heterogeneity of long-term air pollution exposure remains unclear. Objectives: To investigate the role of intraurban spatial variability of air pollution in asthma acute care use disparity. Methods: An administrative database was used to define census tract population-based incidence rates of asthma-related ED visits. We estimate the associations between census tract incidence rates and 1) average fine and coarse particulate matter, nitrogen dioxide (NO2), and sulfur dioxide (SO2), and 2) racial and ethnic composition using generalized linear models controlling for socioeconomic and housing covariates. We also examine for the attenuation of incidence risk ratios (IRRs) associated with race/ethnicity when controlling for air pollution exposure. Measurements and Main Results: Fine and coarse particulate matter and SO2 are all associated with census tract-level incidence rates of asthma-related ED visits, and multipollutant models show evidence of independent risk associated with coarse particulate matter and SO2. The association between census tract incidence rate and Black resident share (IRR, 1.51 [credible interval (CI), 1.48-1.54]) is attenuated by 24% when accounting for air pollution (IRR, 1.39 [CI, 1.35-1.42]), and the association with Latinx resident share (IRR, 1.11 [CI, 1.09-1.13]) is attenuated by 32% (IRR, 1.08 [CI, 1.06-1.10]). Conclusions: Neighborhood-level rates of asthma acute care use are associated with local air pollution. Controlling for air pollution attenuates associations with census tract racial/ethnic composition, suggesting that intracity variability in air pollution could contribute to neighborhood-to-neighborhood asthma morbidity disparities.

Associations Between Early-Life Adversity, Ambient Air Pollution, and Telomere Length in Children

OBJECTIVE

Examine the independent associations and interaction between early-life adversity and residential ambient air pollution exposure on relative buccal telomere length (rBTL).

METHODS

Experiences of abuse, neglect, household challenges, and related life events were identified in a cross-sectional sample of children aged 1 to 11 years ( n = 197) using the 17-item Pediatric ACEs and Related Life Event Screener (PEARLS) tool. The PEARLS tool was analyzed both as a total score and across established domains (Maltreatment, Household Challenges, and Social Context). Ground-level fine particulate matter (PM 2.5 ) concentrations were matched to residential locations for the 1 and 12 months before biospecimen collection. We used multivariable linear regression models to examine for independent associations between continuous PM 2.5 exposure and PEARLS score/domains with rBTL. In addition, effect modification by PEARLS scores and domains on associations between PM 2.5 exposure and rBTL was examined.

RESULTS

Study participants were 47% girls, with mean (standard deviation) age of 5.9 (3.4) years, median reported PEARLS score of 2 (interquartile range [IQR], 4), median 12-month prior PM 2.5 concentrations of 11.8 μg/m 3 (IQR, 2.7 μg/m 3 ), median 1-month prior PM 2.5 concentrations of 10.9 μg/m 3 (IQR, 5.8 μg/m 3 ), and rBTL of 0.1 (IQR, 0.03). Mean 12-month prior PM 2.5 exposure was inversely associated with rBTL ( β = -0.02, 95% confidence interval = -0.04 to -0.01). Although reported PEARLS scores and domains were not independently associated with rBTL, we observed a greater decrement in rBTL with increment of average annual PM 2.5 as reported Social Context domain items increased ( p -interaction < .05).

CONCLUSIONS

Our results suggest that adverse Social Context factors may accelerate the association between chronic PM 2.5 exposure on telomere shortening during childhood.

Clustering by chemicals: A novel examination of chemical pollutants and social vulnerability in children and adolescents

BACKGROUND

Inhaled air pollutants are environmental determinants of health with negative impacts on human health. Air pollution has been linked to the incidence and progression of disease, with its effects unequally distributed across the population. Children compared to adults are a highly vulnerable group and suffer disproportionately from systemic environmental inequities exacerbated by social determinants.

OBJECTIVE

To explore air pollution cluster patterns among 6- to 19-year-olds from the 2015-2016 National Health and Nutrition Examination Survey (NHANES) and examine chemical cluster associations with social vulnerability.

METHODS

NHANES data was extracted for 697 children and adolescents. Social vulnerability characteristics from questionnaires were assembled to construct a modified social vulnerability index (SVI). Thirty-four air pollutant exposure chemicals were measured in urine and available from the laboratory sub-sample A data. K-means clustering classified the sample into three groups: low, medium, and high chemical exposure groups. Logistic regression was used to examine associations between high chemical group membership and SVI after adjusting for age, biological sex, and BMI. Complex survey analysis was conducted using SAS v9.4 to reflect population effects.

RESULTS

Air pollution clusters revealed significant differences in mean concentrations between groups for 31 analytes with minimal distinction in mixture profiles. SVI scores differed significantly between the three groups (P = .002), and with each point increase in their SVI, the odds of a child being assigned to the highest-chemical exposure group increased by 11.55% (95% CI: 1.02-1.31), after adjustment.

CONCLUSION

Unsupervised clustering of environmental sub-sample specimens from NHANES provides an innovative, multi-pollutant model that can be used to explore exposure patterns in this population. Utilizing the modified SVI allows for the identification of children that may be highly susceptible to air pollution. It is imperative to interpret the research findings in light of historical structural and discriminatory inequalities to develop beneficial and sustainable solutions.

GWAS reveals Genetic Susceptibility to Air Pollution-Related Asthma Exacerbations in Children of African Ancestry

Background

The relationship between ambient air pollution (AAP) exposure and asthma exacerbations is well-established. However, mitigation efforts have yielded mixed results, potentially due to genetic variability in the response to AAP. We hypothesize that common single nucleotide polymorphisms (SNPs) are linked to AAP sensitivity and test this through a Genome Wide Association Study (GWAS).

Methods

We selected a cohort of pediatric asthma patients frequently exposed to AAP. Patients experiencing exacerbations immediately following AAP spikes were deemed sensitive. A GWAS compared sensitive versus non-sensitive patients. Findings were validated using data from the All of Us program.

Results

Our study included 6,023 pediatric asthma patients. Due to the association between AAP exposure and race, GWAS analysis was feasible only in the African ancestry cohort. Seven risk loci reached genome-wide significance, including four non-intergenic variants. Two variants were validated: rs111970601 associated with sensitivity to CO (odds ratio [OR], 6.58; PL=L1.63L×L10-8; 95% CI, 3.42-12.66) and rs9836522 to PM2.5 sensitivity (OR 0.75; PL=L3,87 ×L10-9; 95% CI, 0.62-0.91).

Interpretation

While genetic variants have been previously linked to asthma incidence and AAP exposure, this study is the first to link specific SNPs with AAP-related asthma exacerbations. The identified variants implicate genes with a known role in asthma and established links to AAP. Future research should explore how clinical interventions interact with genetic risk to mitigate the effects of AAP, particularly to enhance health equity for vulnerable populations.

What is already known on this topic

The relationship between ambient air pollution (AAP) exposure and asthma exacerbations is well-established. However, efforts to mitigate the impact of AAP on children with asthma have yielded mixed results, potentially due to genetic variability in response to AAP.

What this study adds

Using publicly available AAP data, we identify which children with asthma experience exacerbations immediately following spikes in AAP. We then conduct a Genome Wide Association Study (GWAS) comparing these patients with those who have no temporal association between AAP spikes and asthma exacerbations, identifying several Single Nucleotide Polymorphisms (SNPs) significantly associated with AAP sensitivity.

How this study might affect research practice or policy

While genetic variants have previously been linked to asthma incidence and AAP exposure, this study is the first to link specific SNPs with AAP-related asthma exacerbations. This creates a framework for identifying children especially at risk when exposed to AAP. These children should be targeted with policy interventions to reduce exposure and may require specific treatments to mitigate the effects of ongoing AAP exposure in the interim.

Environmental Impact of a Pediatric and Young Adult Virtual Medicine Program: A Lesson from the COVID-19 Pandemic

OBJECTIVES

The Coronavirus Disease 2019 (COVID-19) pandemic led to the expansion of virtual medicine as a method to provide patient care. We aimed to determine the impact of pediatric and young adult virtual medicine use on fossil fuel consumption, greenhouse gas, and nongreenhouse traffic-related air pollutant emissions.

METHODS

We conducted a retrospective analysis of all virtual medicine patients at a single quaternary-care children's hospital with a geocoded address in the Commonwealth of Massachusetts prior to (March 16, 2019-March 15, 2020) and during the COVID-19 pandemic (March 16, 2020-March 15, 2021). Primary outcomes included patient travel distance, gasoline consumption, carbon dioxide and fine particulate matter emissions as well as savings in main hospital energy use.

RESULTS

There were 3,846 and 307,273 virtual visits performed with valid Massachusetts geocoded addresses prior to and during the COVID-19 pandemic, respectively. During 1 year of the pandemic, virtual medicine services resulted in a total reduction of 620,231 gallons of fossil fuel use and $1,620,002 avoided expenditure as well as 5,492.9 metric tons of carbon dioxide and 186.3 kg of fine particulate matter emitted. There were 3.1 million fewer kilowatt hours used by the hospital intrapandemic compared to the year prior. Accounting for equipment emissions, the combined intrapandemic emission reductions are equivalent to the electricity required by 1,234 homes for 1 year.

CONCLUSIONS

Widespread pediatric institutional use of virtual medicine provided environmental benefits. The true potential of virtual medicine for decreasing the environmental footprint of health care lies in scaling this mode of care to patient groups across the state and nation when medically feasible.

Formaldehyde Exposure Racial Disparities in Southeast Texas

Formaldehyde (HCHO) exposures during a full year were calculated for different race/ethnicity groups living in Southeast Texas using a chemical transport model tagged to track nine emission categories. Petroleum and industrial emissions were the largest anthropogenic sources of HCHO exposure in Southeast Texas, accounting for 44% of the total HCHO population exposure. Approximately 50% of the HCHO exposures associated with petroleum and industrial sources were directly emitted (primary), while the other 50% formed in the atmosphere (secondary) from precursor emissions of reactive compounds such as ethylene and propylene. Biogenic emissions also formed secondary HCHO that accounted for 11% of the total population-weighted exposure across the study domain. Off-road equipment contributed 3.7% to total population-weighted exposure in Houston, while natural gas combustion contributed 5% in Beaumont. Mobile sources accounted for 3.7% of the total HCHO population exposure, with less than 10% secondary contribution. Exposure disparity patterns changed with the location. Hispanic and Latino residents were exposed to HCHO concentrations +1.75% above average in Houston due to petroleum and industrial sources and natural gas sources. Black and African American residents in Beaumont were exposed to HCHO concentrations +7% above average due to petroleum and industrial sources, off-road equipment, and food cooking. Asian residents in Beaumont were exposed to HCHO concentrations that were +2.5% above average due to HCHO associated with petroleum and industrial sources, off-road vehicles, and food cooking. White residents were exposed to below average HCHO concentrations in all domains because their homes were located further from primary HCHO emission sources. Given the unique features of the exposure disparities in each region, tailored solutions should be developed by local stakeholders. Potential options to consider in the development of those solutions include modifying processes to reduce emissions, installing control equipment to capture emissions, or increasing the distance between industrial sources and residential neighborhoods.

Air Pollution and Racial Disparities in Pregnancy Outcomes in the United States: A Systematic Review

BACKGROUND

Exposure to air pollutants and other environmental factors increases the risk of adverse pregnancy outcomes. There is growing evidence that adverse outcomes related to air pollution disproportionately affect racial and ethnic minorities. The objective of this paper is to explore the importance of race as a risk factor for air pollution-related poor pregnancy outcomes.

METHODS

Studies investigating the effects of exposure to air pollution on pregnancy outcomes by race were reviewed. A manual search was conducted to identify missing studies. Studies that did not compare pregnancy outcomes among two or more racial groups were excluded. Pregnancy outcomes included preterm births, small for gestational age, low birth weight, and stillbirths.

RESULTS

A total of 124 articles explored race and air pollution as risk factors for poor pregnancy outcome. Thirteen percent of these (n=16) specifically compared pregnancy outcomes among two or more racial groups. Findings across all reviewed articles showed more adverse pregnancy outcomes (preterm birth, small for gestational age, low birth weight, and stillbirths) related to exposure to air pollution among Blacks and Hispanics than among non-Hispanic Whites.

CONCLUSION

Evidence support our general understanding of the impact of air pollution on birth outcomes and, specifically, of disparities in exposure to air pollution and birth outcomes for infants born to Black and Hispanic mothers. The factors driving these disparities are multifactorial, mostly social, and economic factors. Reducing or eliminating these disparities require interventions at individual, community, state, and national level.

An environmental justice analysis of air pollution emissions in the United States from 1970 to 2010

Over the last decades, air pollution emissions have decreased substantially; however, inequities in air pollution persist. We evaluate county-level racial/ethnic and socioeconomic disparities in emissions changes from six air pollution source sectors (industry [SO2], energy [SO2, NOx], agriculture [NH3], commercial [NOx], residential [particulate organic carbon], and on-road transportation [NOx]) in the contiguous United States during the 40 years following the Clean Air Act (CAA) enactment (1970-2010). We calculate relative emission changes and examine the differential changes given county demographics using hierarchical nested models. The results show racial/ethnic disparities, particularly in the industry and energy generation source sectors. We also find that median family income is a driver of variation in relative emissions changes in all sectors-counties with median family income >$75 K vs. less generally experience larger relative declines in industry, energy, transportation, residential, and commercial-related emissions. Emissions from most air pollution source sectors have, on a national level, decreased following the United States CAA. In this work, we show that the relative reductions in emissions varied across racial/ethnic and socioeconomic groups.

Corridor-Level Impacts of Battery-Electric Heavy-Duty Trucks and the Effects of Policy in the United States

Electrifying freight trucks will be key to alleviating air pollution burdens on disadvantaged communities and mitigating climate change. The United States plans to pursue this aim by adding vehicle charging infrastructure along specific freight corridors. This study explores the coevolution of the electricity grid and freight trucking landscape using an integrated assessment framework to identify when each interstate and drayage corridor becomes advantageous to electrify from a climate and human health standpoint. Nearly all corridors achieve greenhouse gas emission reductions if electrified now. Most can reduce health impacts from air pollution if electrified by 2040 although some corridors in the Midwest, South, and Mid-Atlantic regions remain unfavorable to electrify from a human health standpoint, absent policy support. Recent policy, namely, the Inflation Reduction Act, accelerates this timeline to 2030 for most corridors and results in net human health benefits on all corridors by 2050, suggesting that near-term investments in truck electrification, particularly drayage corridors, can meaningfully reduce climate and health burdens.

Observational studies generate misleading results about the health effects of air pollution: Evidence from chronic air pollution and COVID-19 outcomes

Several observational studies from locations around the globe have documented a positive correlation between air pollution and the severity of COVID-19 disease. Observational studies cannot identify the causal link between air quality and the severity of COVID-19 outcomes, and these studies face three key identification challenges: 1) air pollution is not randomly distributed across geographies; 2) air-quality monitoring networks are sparse spatially; and 3) defensive behaviors to mediate exposure to air pollution and COVID-19 are not equally available to all, leading to large measurement error bias when using rate-based COVID-19 outcome measures (e.g., incidence rate or mortality rate). Using a quasi-experimental design, we explore whether traffic-related air pollutants cause people with COVID-19 to suffer more extreme health outcomes in New York City (NYC). When we address the previously overlooked challenges to identification, we do not detect causal impacts of increased chronic concentrations of traffic-related air pollutants on COVID-19 death or hospitalization counts in NYC census tracts.

The Built Environment and Pediatric Health

Buildings, parks, and roads are all elements of the "built environment," which can be described as the human-made structures that comprise the neighborhoods and communities where people live, work, learn, and recreate (https://www.epa.gov/smm/basic-information-about-built-environment). The design of communities where children and adolescents live, learn, and play has a profound impact on their health. Moreover, the policies and practices that determine community design and the built environment are a root cause of disparities in the social determinants of health that contribute to health inequity. An understanding of the links between the built environment and pediatric health will help to inform pediatricians' and other pediatric health professionals' care for patients and advocacy on their behalf. This technical report describes the range of pediatric physical and mental health conditions influenced by the built environment, as well as historical and persistent effects of the built environment on health disparities. The accompanying policy statement outlines community design solutions that can improve pediatric health and health equity, including opportunities for pediatricians and the health care sector to incorporate this knowledge in patient care, as well as to play a role in advancing a health-promoting built environment for all children and families.

Ambient Air Pollution and Outpatient Morbidities in Bronchopulmonary Dysplasia

Rationale: Bronchopulmonary dysplasia (BPD) is the most common long-term complication of prematurity. Although socioeconomic status is associated with BPD morbidities, the drivers of this association are poorly understood. In the United States, ambient air pollution (AAP) exposure is linked to both race/ethnicity and socioeconomic status. Furthermore, AAP exposure is known to have a detrimental effect on respiratory health in children. Objectives: To assess if AAP exposure is linked to BPD morbidity in the outpatient setting. Methods: Participants with BPD were recruited from outpatient clinics at Johns Hopkins University and the Children's Hospital of Philadelphia between 2008 and 2021 (N = 800) and divided into low, moderate, and high AAP exposure groups, based on publicly available U.S. Environmental Protection Agency data. Clinical data were obtained by chart review and caregiver questionnaires. Results: Non-White race, home ventilator use, and lower median household income were associated with higher degrees of air pollution exposure. After adjustment for these factors, moderate and high air pollution exposure were associated with requiring systemic steroids (odds ratio, 1.78 and 2.17, respectively) compared with low air pollution. Similarly, high air pollution exposure was associated with emergency department visits (odds ratio, 1.59). Conclusions: This study demonstrates an association between AAP exposure and BPD morbidity after initial hospital discharge. AAP exposure was closely linked to race and median household income. As such, it supports the notion that AAP exposure may be contributing to health disparities in BPD outcomes. Further studies directly measuring exposure and establishing a link between biomarkers of exposure and outcomes are prerequisites to developing targeted interventions protecting this vulnerable population.

State-of-the-Science Data and Methods Need to Guide Place-Based Efforts to Reduce Air Pollution Inequity

BACKGROUND

Recently enacted environmental justice policies in the United States at the state and federal level emphasize addressing place-based inequities, including persistent disparities in air pollution exposure and associated health impacts. Advances in air quality measurement, models, and analytic methods have demonstrated the importance of finer-scale data and analysis in accurately quantifying the extent of inequity in intraurban pollution exposure, although the necessary degree of spatial resolution remains a complex and context-dependent question.

OBJECTIVE

The objectives of this commentary were to a) discuss ways to maximize and evaluate the effectiveness of efforts to reduce air pollution disparities, and b) argue that environmental regulators must employ improved methods to project, measure, and track the distributional impacts of new policies at finer geographic and temporal scales.

DISCUSSION

The historic federal investments from the Inflation Reduction Act, the Infrastructure Investment and Jobs Act, and the Biden Administration's commitment to Justice40 present an unprecedented opportunity to advance climate and energy policies that deliver real reductions in pollution-related health inequities. In our opinion, scientists, advocates, policymakers, and implementing agencies must work together to harness critical advances in air quality measurements, models, and analytic methods to ensure success. https://doi.org/10.1289/EHP13063.

Changes in traffic congestion and air pollution due to major roadway infrastructure improvements in Texas

Traffic-related air pollution (TRAP) is an established health hazard, and roadway construction has the potential to affect TRAP by relieving congestion. The relationship between roadway construction and congestion is of policy importance, but few studies examine it using large samples of construction projects and detailed traffic and air pollution data. We create a dataset of construction projects in Texas and link them to data on air pollution and three variables operationalizing congestion: average annual daily traffic (AADT), AADT per lane, and delay in hours. We use difference-in-difference methods to estimate the effect of widening and intersection improvements on congestion and air pollution. On average over the period during construction, we find that widening increases delay by 42% (95% CI: 30, 56%), but intersection projects do not affect delay. On average and over the first three years post-construction, we find that widening reduces delay by 33% (95% CI: -41, -24%) and reduces NO2 levels within 500 m by 13% (95% CI: -22, -2%), and intersection projects reduce delay by 52% (95% CI: -65, -35%) and reduce NO2 levels within 500 m by 12% (95% CI: -18, -5%). These short-term impacts are relevant for understanding the impact of roadway construction on human health.

Examining the geographical distribution of air pollution disparities across different racial and ethnic groups: Incorporating workplace addresses

BACKGROUND

Most previous studies on air pollution exposure disparities among racial and ethnic groups in the US have been limited to residence-based exposure and have given little consideration to population mobility and spatial patterns of residences, workplaces, and air pollution. This study aimed to examine air pollution exposure disparities by racial and ethnic groups while explicitly accounting for both the work-related activity of the population and localized spatial patterns of residential segregation, clustering of workplaces, and variability of air pollutant concentration.

METHOD

In the present study, we assessed population-level exposure to air pollution using tabulated residence and workplace addresses of formally employed workers from LEHD Origin-Destination Employment Statistics (LODES) data at the census tract level across eight Metropolitan Statistical Areas (MSAs). Combined with annual-averaged predictions for three air pollutants (PM2.5, NO2, O3), we investigated racial and ethnic disparities in air pollution exposures at home and workplaces using pooled (i.e., across eight MSAs) and regional (i.e., with each MSA) data.

RESULTS

We found that non-White groups consistently had the highest levels of exposure to all three air pollutants, at both their residential and workplace locations. Narrower exposure disparities were found at workplaces than residences across all three air pollutants in the pooled estimates, due to substantially lower workplace segregation than residential segregation. We also observed that racial disparities in air pollution exposure and the effect of considering work-related activity in the exposure assessment varied by region, due to both the levels and patterns of segregation in the environments where people spend their time and the local heterogeneity of air pollutants.

CONCLUSIONS

The results indicated that accounting for workplace activity illuminates important variation between home- and workplace-based air pollution exposure among racial and ethnic groups, especially in the case of NO2. Our findings suggest that consideration of both activity patterns and place-based exposure is important to improve our understanding of population-level air pollution exposure disparities, and consequently to health disparities that are closely linked to air pollution exposure.

Contributions of non-tailpipe emissions to near-road PM2.5 and PM10: A chemical mass balance study

As the importance of non-tailpipe particles (NTP) over tailpipe emissions from urban traffic has been increasing, there is a need to evaluate NTP contributions to ambient particulate matter (PM) using representative source profiles. The Brake and Tire Wear Study conducted in Los Angeles, California in the winter of 2020 collected 64 PM2.5 and 64 PM10 samples from 32 pairs of downwind-upwind measurements at two near-road locations (I-5 in Anaheim and I-710 in Long Beach). These samples were characterized for inorganic and organic markers and, along with locally-developed brake wear, tire wear, and road dust source profiles, subject to source apportionment using the effective-variance chemical mass balance (EV-CMB) model. Model results highlighted the dominance of resuspended dust in both PM2.5 (23-33%) and PM10 (32-53%). Brake and tire wear contributed more to PM2.5 than tailpipe exhausts (diesel + gasoline) for I-5 (29-30% vs. 19-21%) while they were comparable for I-710 (15-17% vs. 15-19%). For PM10, the brake and tire wear contributions were 2-3 times the exhaust contributions. Different fleet compositions on and near I-5 and I-710 appeared to influence the relative importance of NTP and exhaust sources. The downwind-upwind differences in source contributions were often insignificant, consistent with small and/or nearly equal impacts of adjacent highway traffic emissions on the downwind and upwind sites. The utility of sole markers, such as barium and zinc, to predict brake and tire wear abundances in ambient PM is evaluated.

Ambient NO2 Air Pollution and Public Schools in the United States: Relationships with Urbanicity, Race-Ethnicity, and Income

Schools may have important impacts on children's exposure to ambient air pollution, yet ambient air quality at schools is not consistently tracked. We characterize ambient air quality at home and school locations in the United States using satellite-based empirical model (i.e., land use regression) estimates of outdoor annual nitrogen dioxide (NO2). We report disparities by race-ethnicity and impoverishment status, and investigate differences by level of urbanicity. Average NO2 levels at home and school for racial-ethnic minoritized students are 18-22% higher than average (and 37-39% higher than for non-Hispanic, white students). Minoritized students are less likely than their white peers to live (0.55 times) and attend school (0.58 times) in areas below the World Health Organization's NO2 guideline. Predominantly minoritized schools (i.e., >50% minoritized students) are less likely than predominantly white schools (0.43 times) to be in locations below the guideline. Income and race-ethnicity impacts are intertwined, yet in large cities, racial disparities persist after controlling for income.

Modeling and Analysis of Air Pollution and Environmental Justice: The Case for North Carolina's Hog Concentrated Animal Feeding Operations

BACKGROUND

Concentrated animal feeding operations (CAFOs) emit pollutants that can cause negative impacts on human health. The concentration of hog production in North Carolina raises concerns regarding the disproportionate exposure of vulnerable communities to air pollution from CAFOs.

OBJECTIVES

We investigated whether exposure to gaseous ammonia (NH 3 ) and hydrogen sulfide (H 2 S ) (in 2019) differs between subpopulations by examining demographics, including race/ethnicity, age, educational attainment, language proficiency, and socioeconomic status.

METHODS

We used an Air Monitoring Station (AMS)/Environmental Protection Agency (EPA) Regulatory Model (AERMOD)-based Human Exposure Model (version 3) to estimate ambient concentrations of NH 3 and H 2 S from hog farms in Duplin County and its surrounding counties in North Carolina and estimate subsequent exposures of communities within 50 km of Duplin County, North Carolina, or the Duplin County Region. We combined estimated exposures with 2016 American Community Summary Census data, at the block group level, using spatial analysis to investigate whether exposures to these pollutants differ by race and ethnicity, age, income, education, and language proficiency. Based on these estimations, we assessed associated exposure risks to the impacted communities and used multivariable regression modeling to evaluate the relationship between average ammonia exposures from Duplin regional hog farms and the presence of vulnerable populations.

RESULTS

The average [± standard deviation  ( SD ) ] annual estimated concentration of NH 3 and H 2 S in the Duplin County Region is 1.75 ± 2.81   μ g / m 3 and 0.0087 ± 0.014   μ g / m 3 , respectively. The maximum average annual ambient concentrations are estimated at 54.27 ± 4.12   μ g / m 3 and 0.54 ± 0.041   μ g / m 3 for NH 3 and H 2 S , respectively. Our descriptive analysis reveals that people of low income, people of color, people with low educational attainment, and the linguistically isolated in the Duplin Region are disproportionately exposed to higher levels of pollutants than the average exposure for residents. Alternatively, our statistical results suggests that after adjusting for covariates, communities of color are associated with 1.70% (95% CI: - 3.79 , 0.44) lower NH 3 concentrations per 1-SD increase. One-standard deviation increases in the adults with low educational attainment and children < 19 years of age is associated with 1.26% (95% CI: - 0.77 , 3.33) and 1.20% (95% CI: - 0.62 , 3.05) higher NH 3 exposure per 1-SD increase, respectively.

DISCUSSION

Exposures to NH 3 and H 2 S differed by race and ethnicity, educational attainment, language proficiency, and socioeconomic status. The observed associations between exposure to CAFO-generated pollutants and sociodemographic indicators differed among demographics. The disproportionate distribution of hog facilities and resulting pollutant exposures among communities may have adverse environmental and human health impacts, raising environmental justice concerns. https://doi.org/10.1289/EHP11344.

Changes in Socioeconomic Disparities for Traffic-Related Air Pollution Exposure During Pregnancy Over a 20-Year Period in Texas

Importance

Air pollution presents clear environmental justice issues. However, few studies have specifically examined traffic-related air pollution (TRAP), a source driven by historically racist infrastructure policies, among pregnant individuals, a population susceptible to air pollution effects. How these disparities have changed over time is also unclear but has important policy implications.

Objective

To examine changes in TRAP exposure by sociodemographic characteristics among recorded pregnancies over a 20-year period.

Design, Setting, and Participants

This population-based birth cohort study used descriptive analysis among pregnant individuals in Texas from 1996 to 2016. All pregnant individuals with valid residential address, socioeconomic, and demographic data were included. Individual-level race and ethnicity, education, and maternal birthplace data were extracted from birth certificates and neighborhood-level household income and historical neighborhood disinvestment (ie, redlining) data were assessed via residential addresses. Data analysis occurred between June 2022 and June 2023.

Main Outcomes and Measures

The main outcome, TRAP exposure at residential addresses, was assessed via traffic levels, represented by total and truck-specific vehicle miles traveled (VMT) within 500 m; nitrogen dioxide (no2) concentrations from a spatial-temporal land use regression model (ie, vehicle tailpipe emissions); and National Air Toxic Agency cancer risk index from on-road vehicle emissions. TRAP exposure differences were assessed by sociodemographic indicators over the 1996 to 2016 period.

Results

Among 7 043 598 pregnant people (mean [SD] maternal age, 26.8 [6.1] years) in Texas from 1996 to 2016, 48% identified as Hispanic or Latinx, 4% identified as non-Hispanic Asian or Pacific Islander, 12% identified as non-Hispanic Black, and 36% identified as non-Hispanic White. There were differences in TRAP for pregnant people by all sociodemographic variables examined. The absolute level of these disparities decreased from 1996 to 2016, but the relative level of these disparities increased: for example, in 1996, non-Hispanic Black pregnant individuals were exposed to a mean (SD) 15.3 (4.1) ppb of no2 vs 13.5 (4.4) ppb of no2 for non-Hispanic White pregnant individuals, compared with 2016 levels of 6.7 (2.4) ppb no2 for Black pregnant individuals and 5.2 (2.4) ppb of no2 for White pregnant individuals. Large absolute and relative differences in traffic levels were observed for all sociodemographic characteristics, increasing over time. For example, non-Hispanic Black pregnant individuals were exposed to a mean (SD) of 22 836 (32 844) VMT within 500 m of their homes, compared with 12 478 (22 870) VMT within 500 m of the homes of non-Hispanic White pregnant individuals in 2016, a difference of 83%.

Conclusions and Relevance

This birth cohort study found that while levels of air pollution disparities decreased in absolute terms over the 20 years of the study, relative disparities persisted and large differences in traffic levels remained, requiring renewed policy attention.

Developing a National-Scale Exposure Index for Combined Environmental Hazards and Social Stressors and Applications to the Environmental Influences on Child Health Outcomes (ECHO) Cohort

Tools for assessing multiple exposures across several domains (e.g., physical, chemical, and social) are of growing importance in social and environmental epidemiology because of their value in uncovering disparities and their impact on health outcomes. Here we describe work done within the Environmental influences on Child Health Outcomes (ECHO)-wide Cohort Study to build a combined exposure index. Our index considered both environmental hazards and social stressors simultaneously with national coverage for a 10-year period. Our goal was to build this index and demonstrate its utility for assessing differences in exposure for pregnancies enrolled in the ECHO-wide Cohort Study. Our unitless combined exposure index, which collapses census-tract level data into a single relative measure of exposure ranging from 0-1 (where higher values indicate higher exposure to hazards), includes indicators for major air pollutants and air toxics, features of the built environment, traffic exposures, and social determinants of health (e.g., lower educational attainment) drawn from existing data sources. We observed temporal and geographic variations in index values, with exposures being highest among participants living in the West and Northeast regions. Pregnant people who identified as Black or Hispanic (of any race) were at higher risk of living in a "high" exposure census tract (defined as an index value above 0.5) relative to those who identified as White or non-Hispanic. Index values were also higher for pregnant people with lower educational attainment. Several recommendations follow from our work, including that environmental and social stressor datasets with higher spatial and temporal resolutions are needed to ensure index-based tools fully capture the total environmental context.

Exposure Disparities by Income, Race and Ethnicity, and Historic Redlining Grade in the Greater Seattle Area for Ultrafine Particles and Other Air Pollutants

BACKGROUND

Growing evidence shows ultrafine particles (UFPs) are detrimental to cardiovascular, cerebrovascular, and respiratory health. Historically, racialized and low-income communities are exposed to higher concentrations of air pollution.

OBJECTIVES

Our aim was to conduct a descriptive analysis of present-day air pollution exposure disparities in the greater Seattle, Washington, area by income, race, ethnicity, and historical redlining grade. We focused on UFPs (particle number count) and compared with black carbon, nitrogen dioxide, and fine particulate matter (PM 2.5 ) levels.

METHODS

We obtained race and ethnicity data from the 2010 U.S. Census, median household income data from the 2006-2010 American Community Survey, and Home Owners' Loan Corporation (HOLC) redlining data from the University of Richmond's Mapping Inequality. We predicted pollutant concentrations at block centroids from 2019 mobile monitoring data. The study region encompassed much of urban Seattle, with redlining analyses restricted to a smaller region. To analyze disparities, we calculated population-weighted mean exposures and regression analyses using a generalized estimating equation model to account for spatial correlation.

RESULTS

Pollutant concentrations and disparities were largest for blocks with median household income of < $ 20,000 , Black residents, HOLC Grade D, and ungraded industrial areas. UFP concentrations were 4% lower than average for non-Hispanic White residents and higher than average for racialized groups (Asian, 3%; Black, 15%; Hispanic, 6%; Native American, 8%; Pacific Islander, 11%). For blocks with median household incomes of < $ 20,000 , UFP concentrations were 40% higher than average, whereas blocks with incomes of > $ 110,000 had UFP concentrations 16% lower than average. UFP concentrations were 28% higher for Grade D and 49% higher for ungraded industrial areas compared with Grade A. Disparities were highest for UFPs and lowest for PM 2.5 exposure levels.

DISCUSSION

Our study is one of the first to highlight large disparities with UFP exposures compared with multiple pollutants. Higher exposures to multiple air pollutants and their cumulative effects disproportionately impact historically marginalized groups. https://doi.org/10.1289/EHP11662.

Spatial Decomposition of Air Pollution Concentrations Highlights Historical Causes for Current Exposure Disparities in the United States

Racial-ethnic disparities in exposure to air pollution in the United States (US) are well documented. Studies on the causes of these disparities highlight unequal systems of power and longstanding systemic racism-for example, redlining, white flight, and racial covenants-which reinforced racial segregation and wealth gaps and which concentrated polluting land uses in communities of color. Our analysis is based on empirical estimates of ambient concentrations for two important pollutants (NO2 and PM2.5). We show that spatially decomposed concentrations can be used to infer and quantify types of root causes for local- to national-scale disparities. Urban-scale segregation is important yet reflects less than half of the overall national disparities. Other historical causes of national exposure disparities include those that led current populations of Black, Asian, and Hispanic Americans to live in larger cities; those outcomes are consistent with, for example, greater economic opportunity in large cities, land-takings from non-White farmers, and racism in homesteading and between-state migration. Our results suggest that contemporary national exposure disparities in the US reflect a broad set of historical local- to national-scale mechanisms-including racist laws and actions that include, but also extend beyond, urban-scale aspects-and offer a first attempt to quantify their relative importance.

Environmental Health, Racial/Ethnic Health Disparity, and Climate Impacts of Inter-Regional Freight Transport in the United States

We quantify and compare three environmental impacts from inter-regional freight transportation in the contiguous United States: total mortality attributable to PM2.5 air pollution, racial-ethnic disparities in PM2.5-attributable mortality, and CO2 emissions. We compare all major freight modes (truck, rail, barge, aircraft) and routes (∼30,000 routes). Our study is the first to comprehensively compare each route separately and the first to explore racial-ethnic exposure disparities by route and mode, nationally. Impacts (health, health disparity, climate) per tonne of freight are the largest for aircraft. Among nonaircraft modes, per tonne, rail has the largest health and health-disparity impacts and the lowest climate impacts, whereas truck transport has the lowest health impacts and greatest climate impacts─an important reminder that health and climate impacts are often but not always aligned. For aircraft and truck, average monetized damages per tonne are larger for climate impacts than those for PM2.5 air pollution; for rail and barge, the reverse holds. We find that average exposures from inter-regional truck and rail are the highest for White non-Hispanic people, those from barge are the highest for Black people, and those from aircraft are the highest for people who are mixed/other race. Level of exposure and disparity among racial-ethnic groups vary in urban versus rural areas.

Daily Satellite Observations of Nitrogen Dioxide Air Pollution Inequality in New York City, New York and Newark, New Jersey: Evaluation and Application

Urban air pollution disproportionately harms communities of color and low-income communities in the U.S. Intraurban nitrogen dioxide (NO₂) inequalities can be observed from space using the TROPOspheric Monitoring Instrument (TROPOMI). Past research has relied on time-averaged measurements, limiting our understanding of how neighborhood-level NO₂ inequalities co-vary with urban air quality and climate. Here, we use fine-scale (250 m × 250 m) airborne NO₂ remote sensing to demonstrate that daily TROPOMI observations resolve a major portion of census tract-scale NO₂ inequalities in the New York City-Newark urbanized area. Spatiotemporally coincident TROPOMI and airborne inequalities are well correlated (r = 0.82-0.97), with slopes of 0.82-1.05 for relative and 0.76-0.96 for absolute inequalities for different groups. We calculate daily TROPOMI NO₂ inequalities over May 2018-September 2021, reporting disparities of 25-38% with race, ethnicity, and/or household income. Mean daily inequalities agree with results based on TROPOMI measurements oversampled to 0.01° × 0.01° to within associated uncertainties. Individual and mean daily TROPOMI NO₂ inequalities are largely insensitive to pixel size, at least when pixels are smaller than ∼60 km², but are sensitive to low observational coverage. We statistically analyze daily NO₂ inequalities, presenting empirical evidence of the systematic overburdening of communities of color and low-income neighborhoods with polluting sources, regulatory ozone co-benefits, and worsened NO₂ inequalities and cumulative NO₂ and urban heat burdens with climate change.

Location-specific strategies for eliminating US national racial-ethnic [Formula: see text] exposure inequality

Air pollution levels in the United States have decreased dramatically over the past decades, yet national racial-ethnic exposure disparities persist. For ambient fine particulate matter ([Formula: see text]), we investigate three emission-reduction approaches and compare their optimal ability to address two goals: 1) reduce the overall population average exposure ("overall average") and 2) reduce the difference in the average exposure for the most exposed racial-ethnic group versus for the overall population ("national inequalities"). We show that national inequalities in exposure can be eliminated with minor emission reductions (optimal: ~1% of total emissions) if they target specific locations. In contrast, achieving that outcome using existing regulatory strategies would require eliminating essentially all emissions (if targeting specific economic sectors) or is not possible (if requiring urban regions to meet concentration standards). Lastly, we do not find a trade-off between the two goals (i.e., reducing overall average and reducing national inequalities); rather, the approach that does the best for reducing national inequalities (i.e., location-specific strategies) also does as well as or better than the other two approaches (i.e., sector-specific and meeting concentration standards) for reducing overall averages. Overall, our findings suggest that incorporating location-specific emissions reductions into the US air quality regulatory framework 1) is crucial for eliminating long-standing national average exposure disparities by race-ethnicity and 2) can benefit overall average exposures as much as or more than the sector-specific and concentration-standards approaches.

Differences in Metabolomic Profiles Between Black and White Women and Risk of Coronary Heart Disease: an Observational Study of Women From Four US Cohorts

BACKGROUND

Racial differences in metabolomic profiles may reflect underlying differences in social determinants of health by self-reported race and may be related to racial disparities in coronary heart disease (CHD) among women in the United States. However, the magnitude of differences in metabolomic profiles between Black and White women in the United States has not been well-described. It also remains unknown whether such differences are related to differences in CHD risk.

METHODS

Plasma metabolomic profiles were analyzed using liquid chromatography-tandem mass spectrometry in the WHI-OS (Women's Health Initiative-Observational Study; 138 Black and 696 White women), WHI-HT trials (WHI-Hormone Therapy; 156 Black and 1138 White women), MESA (Multi-Ethnic Study of Atherosclerosis; 114 Black and 219 White women), JHS (Jackson Heart Study; 1465 Black women with 107 incident CHD cases), and NHS (Nurses' Health Study; 2506 White women with 136 incident CHD cases). First, linear regression models were used to estimate associations between self-reported race and 472 metabolites in WHI-OS (discovery); findings were replicated in WHI-HT and validated in MESA. Second, we used elastic net regression to construct a racial difference metabolomic pattern (RDMP) representing differences in the metabolomic patterns between Black and White women in the WHI-OS; the RDMP was validated in the WHI-HT and MESA. Third, using conditional logistic regressions in the WHI (717 CHD cases and 719 matched controls), we examined associations of metabolites with large differences in levels by race and the RDMP with risk of CHD, and the results were replicated in Black women from the JHS and White women from the NHS.

RESULTS

Of the 472 tested metabolites, levels of 259 (54.9%) metabolites, mostly lipid metabolites and amino acids, significantly differed between Black and White women in both WHI-OS and WHI-HT after adjusting for baseline characteristics, socioeconomic status, lifestyle factors, baseline health conditions, and medication use (false discovery rate <0.05); similar trends were observed in MESA. The RDMP, composed of 152 metabolites, was identified in the WHI-OS and showed significantly different distributions between Black and White women in the WHI-HT and MESA. Higher RDMP quartiles were associated with an increased risk of incident CHD (odds ratio=1.51 [0.97-2.37] for the highest quartile comparing to the lowest; Ptrend=0.02), independent of self-reported race and known CHD risk factors. In race-stratified analyses, the RDMP-CHD associations were more pronounced in White women. Similar patterns were observed in Black women from the JHS and White women from the NHS.

CONCLUSIONS

Metabolomic profiles significantly and substantially differ between Black and White women and may be associated with CHD risk and racial disparities in US women.

National and Intraurban Air Pollution Exposure Disparity Estimates in the United States: Impact of Data-Aggregation Spatial Scale

Air pollution exposure disparities by race/ethnicity and socioeconomic status have been analyzed using data aggregated at various spatial scales. Our research question is this: To what extent does the spatial scale of data aggregation impact the estimated exposure disparities? We compared disparities calculated using data spatially aggregated at five administrative scales (state, county, census tract, census block group, census block) in the contiguous United States in 2010. Specifically, for each of the five spatial scales, we calculated national and intraurban disparities in exposure to fine particles (PM_2.5) and nitrogen dioxide (NO₂) by race/ethnicity and socioeconomic characteristics using census demographic data and an empirical statistical air pollution model aggregated at that scale. We found, for both pollutants, that national disparity estimates based on state and county scale data often substantially underestimated those estimated using tract and finer scales; in contrast, national disparity estimates were generally consistent using tract, block group, and block scale data. Similarly, intraurban disparity estimates based on tract and finer scale data were generally well correlated for both pollutants across urban areas, although in some cases intraurban disparity estimates were substantially different, with tract scale data more frequently leading to underestimates of disparities compared to finer scale analyses.

Mortensen L, Requia W, Lange T, Loft S, Kuenzli N, Schwartz J, Amini H. Stringency of COVID-19 Containment Response Policies and Air Quality Changes: A Global Analysis across 1851 Cities

The COVID-19 containment response policies (CRPs) had a major impact on air quality (AQ). These CRPs have been time-varying and location-specific. So far, despite having numerous studies on the effect of COVID-19 lockdown on AQ, a knowledge gap remains on the association between stringency of CRPs and AQ changes across the world, regions, nations, and cities. Here, we show that globally across 1851 cities (each more than 300 000 people) in 149 countries, after controlling for the impacts of relevant covariates (e.g., meteorology), Sentinel-5P satellite-observed nitrogen dioxide (NO₂) levels decreased by 4.9% (95% CI: 2.2, 7.6%) during lockdowns following stringent CRPs compared to pre-CRPs. The NO₂ levels did not change significantly during moderate CRPs and even increased during mild CRPs by 2.3% (95% CI: 0.7, 4.0%), which was 6.8% (95% CI: 2.0, 12.0%) across Europe and Central Asia, possibly due to population avoidance of public transportation in favor of private transportation. Among 1768 cities implementing stringent CRPs, we observed the most NO₂ reduction in more populated and polluted cities. Our results demonstrate that AQ improved when and where stringent COVID-19 CRPs were implemented, changed less under moderate CRPs, and even deteriorated under mild CRPs. These changes were location-, region-, and CRP-specific.

Adoption of low-carbon fuels reduces race/ethnicity disparities in air pollution exposure in California

An environmental justice (EJ) analysis shows that adoption of low-carbon energy sources in the year 2050 reduces the race/ethnicity disparity in air pollution exposure in California by as much as 20% for PM_2.5 mass and by as much as 40% for PM_0.1 mass. An ensemble of six different energy scenarios constructed using the energy-economic optimization model CA-TIMES were evaluated in future years. Criteria pollutant emissions were developed for each energy scenario using the CA-REMARQUE model using 4 km spatial resolution over four major geographic areas in California: the greater San Francisco Bay Area including Sacramento (SFBA&SAC), the San Joaquin Valley (SJV), Los Angeles (LA), and San Diego (SD). The Weather Research & Forecasting (WRF) model was used to predict future meteorology fields by downscaling two different climate scenario (RCP4.5 and RCP8.5) generated by two different GCMs (the Community Climate System Model and the Canadian Earth Systems Model). Simulations were performed over 32 weeks randomly selected during the 10 year window from the year 2046 to 2055 to build up a long-term average in the presence of ENSO variability. The trends associated with low-carbon energy adoption were relatively stable across the ensemble of locations and scenarios. Deeper reductions in the carbon intensity of energy sources progressively reduced exposure to PM_2.5 mass and PM_0.1 mass for all California residents. The greater adoption of low-carbon fuels also reduced the racial disparity in the PM exposure. The three energy scenarios that achieved an ~80% reduction in GHG emissions relative to 1990 levels simultaneously produced the greatest reduction in PM exposure for all California residents and the greatest reduction in the racial disparity of that exposure. These findings suggest that the adoption of low-carbon energy can improve public health and reduce racial disparities through an improvement in air quality.

The impact of urban environmental exposures on health: An assessment of the attributable mortality burden in Sao Paulo city, Brazil

BACKGROUND

Currently, more than half of the global population lives in cities. Contemporary urban planning practices result in environmental risk factors (e.g. air pollution, noise, lack of green space, excess heat) that put health and well-being of city dwellers at risk and contribute to chronic diseases and premature death. Despite a growing body of evidence on adverse health impacts related to current urban and transport planning practices, especially for cities in the Global North, not much is known about associated health impacts in South American cities. Therefore, we estimated the mortality burden attributable to breaching internationally-recommended or locally-preferable exposure levels of urban planning related environmental exposures in Sao Paulo, Brazil.

METHODS

We carried out a health impact assessment study, following the comparative risk assessment framework, to assess preventable mortality impacts of breaching exposure recommendations for air pollution, green spaces and temperature at the census tract (CT) level (n = 18,363). We also assessed the distribution thereof by socioeconomic vulnerability.

RESULTS

We estimated that annually 11,372 (95% CI: 7921; 15,910) attributable deaths could be prevented by complying with recommended exposure levels. The largest proportion of preventable mortality was due to breaching air pollution limits (i.e. 8409 attributable deaths), followed by insufficient green space (i.e. 2593), and excess heat (i.e. 370). Adverse health impacts were larger in CTs of lower socioeconomic vulnerability, due to demographic profile, traffic density and residential area configurations.

DISCUSSION

Not complying with the health limits for air pollution, green space and temperature exposures resulted in a considerable preventable mortality burden (i.e. 17% of total expected deaths) in Sao Paulo. This burden can be reduced by improving current urban and transport planning practices.

Cancer Mortality Patterns by Birthplace and Generation Status of Mexican Latinos: The Multiethnic Cohort

BACKGROUND

Latinos are the largest minority group in the United States. We assessed cancer mortality by birthplace and generation status of Mexican Latinos in the Multiethnic Cohort.

METHODS

We included 26 751 Latinos of Mexican origin and 6093 non-Latino Whites aged 45-74 years at cohort entry (1993-1996) from the California Multiethnic Cohort component. The Mexican Latinos comprised 42% first-generation Mexico-born immigrants, 42% second-generation (28% US-born with both parents Mexico-born and 14% US-born with 1 parent US-born and 1 parent Mexico-born), and 16% third-generation or more who were US-born with both parents US-born. Multivariable Cox models were used to calculate covariate adjusted hazard ratios and 95% confidence intervals for overall and site-specific cancer mortality by birthplace and generation status. All statistical tests were 2-sided.

RESULTS

Cancer death rate was highest among the US-born with 1 parent US-born and 1 parent Mexico-born (age-adjusted rate = 471.0 per 100 000 person-years) and US-born with both parents US-born (age-adjusted rate = 469.0 per 100 000 person-years) groups. The US-born with both parents Mexico-born group had a 30% (hazard ratio = 1.30, 95% confidence interval = 1.18 to 1.44) higher risk of cancer death than the first-generation Mexico-born immigrants group, showing US birthplace was associated with an elevated cancer mortality. For cancer-specific mortality, US birthplace was positively associated with colorectal, liver and lung, and ovarian cancer (P values ranged from .04 to .005). Among US-born Mexican Latinos, generation status was not statistically significantly associated with overall cancer or site-specific cancer mortality.

CONCLUSIONS

Our findings suggest that US birthplace is a risk factor for cancer death in Mexican Americans. Identification of the contributing factors is important to curtail patterns of increasing cancer mortality in US-born Mexican Latinos.

Toward Cleaner Transport Alternatives: Reduction in Exposure to Air Pollutants in a Mass Public Transport

Commuters are often exposed to higher concentrations of air pollutants due to its proximity to mobile sources. Despite recent trends in urban transport toward zero- and low-tailpipe emission alternatives, the assessments of the impact of these transformations on commuter exposure are limited by the low frequency of such studies. In this work, we use a unique data set of personal exposure concentration measurements collected over the span of 5 years to analyze changes due to the introduction of a new fleet for Bogotá's Bus Rapid Transit System. In that system, over a thousand Euro-II and -III diesel-powered buses were replaced with Euro-VI compressed natural gas and filter-equipped Euro-V diesel buses. We measured personal exposure concentrations of equivalent black carbon (eBC), fine particulate (PM_2.5), and ultra fine particles (UFP) during and after the retirement of old buses and the introduction of new ones. Observations collected prior to the fleet renewal were used as baseline and later compared to data collected over two follow-up campaigns in 2019 and 2020. Significant reductions in the concentration of PM_2.5 and eBC were observed during the 2019 campaign, with a 48% decrease for mean in-bus eBC (89.9 to 46.4 μg m^-3) and PM_2.5 (180.7 to 95.4 μg m^-3) concentrations. Further reductions were observed during the 2020 follow-up, when the fleet renovation was completed, with mean in-bus eBC decreasing to 17.7 μg m^-3 and PM_2.5 to 42.3 μg m^-3. These observations imply nearly a 5-fold reduction in eBC exposure and a 4-fold decrease in PM_2.5. There was a much smaller reduction of in-bus UFP concentration between 2019 and 2020, indicating a persistent presence of high particle number concentrations in the near-road environment despite the fleet renovation process. In-bus UFP concentrations ranged between 65 000 and 104 500 cm^-3 during the follow-up campaigns. The results in this work illustrate the immediate benefits of reducing personal exposure through the adoption of vehicles with more stringent emission standards.

Ambient Air Pollution and Socioeconomic Status in China

BACKGROUND

Air pollution disparities by socioeconomic status (SES) are well documented for the United States, with most literature indicating an inverse relationship (i.e., higher concentrations for lower-SES populations). Few studies exist for China, a country accounting for 26% of global premature deaths from ambient air pollution.

OBJECTIVE

Our objective was to test the relationship between ambient air pollution exposures and SES in China.

METHODS

We combined estimated year 2015 annual-average ambient levels of nitrogen dioxide (NO 2 ) and fine particulate matter [PM ≤ 2.5 μ m in aerodynamic diameter (PM 2.5 )] with national demographic information. Pollution estimates were derived from a national empirical model for China at 1 -km spatial resolution; demographic estimates were derived from national gridded gross national product (GDP) per capita at 1 -km resolution, and (separately) a national representative sample of 21,095 individuals from the China Health and Retirement Longitudinal Study (CHARLS) 2015 cohort. Our use of global data on population density and cohort data on where people live helped avoid the spatial imprecision found in publicly available census data for China. We quantified air pollution disparities among individual's rural-to-urban migration status; SES factors (education, occupation, and income); and minority status. We compared results using three approaches to SES measurement: individual SES score, community-averaged SES score, and gridded GDP per capita.

RESULTS

Ambient NO 2 and PM 2.5 levels were higher for higher-SES populations than for lower-SES population, higher for long-standing urban residents than for rural-to-urban migrant populations, and higher for the majority ethnic group (Han) than for the average across nine minority groups. For the three SES measurements (individual SES score, community-averaged SES score, gridded GDP per capita), a 1-interquartile range higher SES corresponded to higher concentrations of 6 - 9   μ g / m 3 NO 2 and 3 - 6   μ g / m 3 PM 2.5 ; average concentrations for the highest and lowest 20th percentile of SES differed by 41-89% for NO 2 and 12-25% for PM 2.5 . This pattern held in rural and urban locations, across geographic regions, across a wide range of spatial resolution, and for modeled vs. measured pollution concentrations.

CONCLUSIONS

Multiple analyses here reveal that in China, ambient NO 2 and PM 2.5 concentrations are higher for high-SES than for low-SES individuals; these results are robust to multiple sensitivity analyses. Our findings are consistent with the idea that in China's current industrialization and urbanization stage, economic development is correlated with both SES and air pollution. To our knowledge, our study provides the most comprehensive picture to date of ambient air pollution disparities in China; the results differ dramatically from results and from theories to explain conditions in the United States. https://doi.org/10.1289/EHP9872.

Historical Redlining Is Associated with Present-Day Air Pollution Disparities in U.S. Cities

Communities of color in the United States are systematically exposed to higher levels of air pollution. We explore here how redlining, a discriminatory mortgage appraisal practice from the 1930s by the federal Home Owners' Loan Corporation (HOLC), relates to present-day intraurban air pollution disparities in 202 U.S. cities. In each city, we integrated three sources of data: (1) detailed HOLC security maps of investment risk grades [A ("best"), B, C, and D ("hazardous", i.e., redlined)], (2) year-2010 estimates of NO₂ and PM_2.5 air pollution levels, and (3) demographic information from the 2010 U.S. census. We find that pollution levels have a consistent and nearly monotonic association with HOLC grade, with especially pronounced (>50%) increments in NO₂ levels between the most (grade A) and least (grade D) preferentially graded neighborhoods. On a national basis, intraurban disparities for NO₂ and PM_2.5 are substantially larger by historical HOLC grade than they are by race and ethnicity. However, within each HOLC grade, racial and ethnic air pollution exposure disparities persist, indicating that redlining was only one of the many racially discriminatory policies that impacted communities. Our findings illustrate how redlining, a nearly 80-year-old racially discriminatory policy, continues to shape systemic environmental exposure disparities in the United States.

Historical Redlining Is Associated with Present-Day Air Pollution Disparities in U.S. Cities

Communities of color in the United States are systematically exposed to higher levels of air pollution. We explore here how redlining, a discriminatory mortgage appraisal practice from the 1930s by the federal Home Owners' Loan Corporation (HOLC), relates to present-day intraurban air pollution disparities in 202 U.S. cities. In each city, we integrated three sources of data: (1) detailed HOLC security maps of investment risk grades [A ("best"), B, C, and D ("hazardous", i.e., redlined)], (2) year-2010 estimates of NO₂ and PM_2.5 air pollution levels, and (3) demographic information from the 2010 U.S. census. We find that pollution levels have a consistent and nearly monotonic association with HOLC grade, with especially pronounced (>50%) increments in NO₂ levels between the most (grade A) and least (grade D) preferentially graded neighborhoods. On a national basis, intraurban disparities for NO₂ and PM_2.5 are substantially larger by historical HOLC grade than they are by race and ethnicity. However, within each HOLC grade, racial and ethnic air pollution exposure disparities persist, indicating that redlining was only one of the many racially discriminatory policies that impacted communities. Our findings illustrate how redlining, a nearly 80-year-old racially discriminatory policy, continues to shape systemic environmental exposure disparities in the United States.

Air Pollution in American Indian Versus Non-American Indian Communities, 2000-2018

Objectives. To compare fine particulate matter (PM2.5) concentrations in American Indian (AI)-populated with those in non-AI-populated counties over time (2000-2018) in the contiguous United States. Methods. We used a multicriteria approach to classify counties as AI- or non--AI-populated. We ran linear mixed effects models to estimate the difference in countywide annual PM2.5 concentrations from well-validated prediction models and monitoring sites (modeled and measured PM2.5, respectively) in AI- versus non-AI-populated counties. Results. On average, adjusted modeled PM2.5 concentrations in AI-populated counties were 0.38 micrograms per cubic meter (95% confidence interval [CI] = 0.23, 0.54) lower than in non-AI-populated counties. However, this difference was not constant over time: in 2000, modeled concentrations in AI-populated counties were 1.46 micrograms per cubic meter (95% CI = 1.25, 1.68) lower, and by 2018, they were 0.66 micrograms per cubic meter (95% CI = 0.45, 0.87) higher. Over the study period, adjusted modeled PM2.5 mean concentrations decreased by 2.13 micrograms per cubic meter in AI-populated counties versus 4.26 micrograms per cubic meter in non-AI-populated counties. Results were similar for measured PM2.5. Conclusions. This study highlights disparities in PM2.5 trends between AI- and non-AI-populated counties over time, underscoring the need to strengthen air pollution regulations and prevention implementation in tribal territories and areas where AI populations live. (Am J Public Health. 2022;112(4): 615-623. https://doi.org/10.2105/AJPH.2021.306650).

Selecting Data Analytic and Modeling Methods to Support Air Pollution and Environmental Justice Investigations: A Critical Review and Guidance Framework

Given the serious adverse health effects associated with many pollutants, and the inequitable distribution of these effects between socioeconomic groups, air pollution is often a focus of environmental justice (EJ) research. However, EJ analyses that aim to illuminate whether and how air pollution hazards are inequitably distributed may present a unique set of requirements for estimating pollutant concentrations compared to other air quality applications. Here, we perform a scoping review of the range of data analytic and modeling methods applied in past studies of air pollution and environmental injustice and develop a guidance framework for selecting between them given the purpose of analysis, users, and resources available. We include proxy, monitor-based, statistical, and process-based methods. Upon critically synthesizing the literature, we identify four main dimensions to inform method selection: accuracy, interpretability, spatiotemporal features of the method, and usability of the method. We illustrate the guidance framework with case studies from the literature. Future research in this area includes an exploration of increasing data availability, advanced statistical methods, and the importance of science-based policy.

The Co-occurrence of Specialty Vape Shops, Social Disadvantage, and Poor Air Quality in the United States: An Assessment of Cumulative Risks to Youth

Introduction: We conducted a cumulative environmental health risk assessment of whether specialty vape shops and poor air quality are more likely to co-occur in socially disadvantaged neighborhoods where racial/ethnic minority youth live.

Methods: We examined the population-adjusted incidence of specialty vape shops in relation to youth race/ethnicity, neighborhood socioeconomic status (SES), and air quality (nitrogen dioxide [NO₂]) at the census tract level across the conterminous United States for 2018.

Results: We did not find disparity in vape shop incidence related to minority youth race/ethnicity. Vape shop incidence was significantly negatively associated with all the youth race/ethnicities examined. The two lowest SES quintiles had nearly double the rate of specialty vape shop incidence compared with the highest SES quintile. Specialty vape shop incidence increased with NO₂ concentration, with more vape shops in poor air quality neighborhoods.

Conclusions: Specialty vape shops are disproportionately present in neighborhoods with poor air quality and where socially disadvantaged youth live. The increased incidence of vape shops in poor air quality neighborhoods, particularly in an urban context with increased traffic emissions, further points to potentially disproportionate impacts on disadvantaged populations due to cumulative social and environmental risks. This raises environmental justice and health equity concerns. Retailer-focused strategies aimed at limiting youth exposure to electronic cigarettes' labeling and advertising, preventing sales to minors, and limiting the number of retailers in low-SES neighborhoods may reduce initiation and help prevent tobacco-related health disparities among youth.

Evaluating the Performance of Low-Cost Air Quality Monitors in Dallas, Texas

The emergence of low-cost air quality sensors may improve our ability to capture variations in urban air pollution and provide actionable information for public health. Despite the increasing popularity of low-cost sensors, there remain some gaps in the understanding of their performance under real-world conditions, as well as compared to regulatory monitors with high accuracy, but also high cost and maintenance requirements. In this paper, we report on the performance and the linear calibration of readings from 12 commercial low-cost sensors co-located at a regulatory air quality monitoring site in Dallas, Texas, for 18 continuous measurement months. Commercial AQY1 sensors were used, and their reported readings of O₃, NO₂, PM_2.5, and PM₁₀ were assessed against a regulatory monitor. We assessed how well the raw and calibrated AQY1 readings matched the regulatory monitor and whether meteorology impacted performance. We found that each sensor’s response was different. Overall, the sensors performed best for O₃ (R² = 0.36–0.97) and worst for NO₂ (0.00–0.58), showing a potential impact of meteorological factors, with an effect of temperature on O₃ and relative humidity on PM. Calibration seemed to improve the accuracy, but not in all cases or for all performance metrics (e.g., precision versus bias), and it was limited to a linear calibration in this study. Our data showed that it is critical for users to regularly calibrate low-cost sensors and monitor data once they are installed, as sensors may not be operating properly, which may result in the loss of large amounts of data. We also recommend that co-location should be as exact as possible, minimizing the distance between sensors and regulatory monitors, and that the sampling orientation is similar. There were important deviations between the AQY1 and regulatory monitors’ readings, which in small part depended on meteorology, hindering the ability of the low-costs sensors to present air quality accurately. However, categorizing air pollution levels, using for example the Air Quality Index framework, rather than reporting absolute readings, may be a more suitable approach. In addition, more sophisticated calibration methods, including accounting for individual sensor performance, may further improve performance. This work adds to the literature by assessing the performance of low-cost sensors over one of the longest durations reported to date.

Place Is Power: Investing in Communities as a Systemic Leverage Point to Reduce Breast Cancer Disparities by Race

Racial disparities in breast cancer present a vexing and complex challenge for public health. A diverse array of factors contributes to disparities in breast cancer incidence and outcomes, and, thus far, efforts to improve racial equity have yielded mixed results. Systems theory offers a model that is well-suited to addressing complex issues. In particular, the concept of a systemic leverage point offers a clue that may assist researchers, policymakers, and interventionists in formulating innovative and comprehensive approaches to eliminating racial disparities in breast cancer. Naming systemic racism as a fundamental cause of disparities, we use systems theory to identify residential segregation as a key leverage point and a driver of racial inequities across the social, economic, and environmental determinants of health. We call on researchers, policymakers, and interventionists to use a systems-informed, community-based participatory approach, aimed at harnessing the power of place, to engage directly with community stakeholders in coordinating efforts to prevent breast cancer, and work toward eliminating disparities in communities of color.

Disparities in Air Pollution Exposure in the United States by Race/Ethnicity and Income, 1990-2010

BACKGROUND

Few studies have investigated air pollution exposure disparities by race/ethnicity and income across criteria air pollutants, locations, or time.

OBJECTIVE

The objective of this study was to quantify exposure disparities by race/ethnicity and income throughout the contiguous United States for six criteria air pollutants, during the period 1990 to 2010.

METHODS

We quantified exposure disparities among racial/ethnic groups (non-Hispanic White, non-Hispanic Black, Hispanic (any race), non-Hispanic Asian) and by income for multiple spatial units (contiguous United States, states, urban vs. rural areas) and years (1990, 2000, 2010) for carbon monoxide (CO), nitrogen dioxide (NO 2 ), ozone (O 3 ), particulate matter with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ; excluding year-1990), particulate matter with aerodynamic diameter ≤ 10 μ m (PM 10 ), and sulfur dioxide (SO 2 ). We used census data for demographic information and a national empirical model for ambient air pollution levels.

RESULTS

For all years and pollutants, the racial/ethnic group with the highest national average exposure was a racial/ethnic minority group. In 2010, the disparity between the racial/ethnic group with the highest vs. lowest national-average exposure was largest for NO 2 [54% (4.6  ppb )], smallest for O 3 [3.6% (1.6  ppb )], and intermediate for the remaining pollutants (13%-19%). The disparities varied by U.S. state; for example, for PM 2.5 in 2010, exposures were at least 5% higher than average in 63% of states for non-Hispanic Black populations; in 33% and 26% of states for Hispanic and for non-Hispanic Asian populations, respectively; and in no states for non-Hispanic White populations. Absolute exposure disparities were larger among racial/ethnic groups than among income categories (range among pollutants: between 1.1 and 21 times larger). Over the period studied, national absolute racial/ethnic exposure disparities declined by between 35% (0.6 6 μ g / m 3 ; PM 2.5 ) and 88% (0.35  ppm ; CO); relative disparities declined to between 0.99 × (PM 2.5 ; i.e., nearly zero change) and 0.71 × (CO; i.e., a ∼ 29 % reduction).

DISCUSSION

As air pollution concentrations declined during the period 1990 to 2010, absolute (and to a lesser extent, relative) racial/ethnic exposure disparities also declined. However, in 2010, racial/ethnic exposure disparities remained across income levels, in urban and rural areas, and in all states, for multiple pollutants. https://doi.org/10.1289/EHP8584.

The impact of environmental injustice and social determinants of health on the role of air pollution in asthma and allergic disease in the United States

There is clear evidence that exposure to environmental air pollution is associated with immune dysregulation, asthma, and other allergic diseases. However, the burden of air pollution exposure is not equally distributed across the United States. Many social and environmental factors place communities of color and people who are in poverty at increased risk of exposure to pollution and morbidity from asthma and allergies. Here, we review the evidence that supports the relationship between air pollution and asthma, while considering the social determinants of health that contribute to disparities in exposures and outcomes.

High-Resolution Modeling and Apportionment of Diesel-Related Contributions to Black Carbon Concentrations

Exposure to diesel-related air pollution, which includes black carbon (BC) as a major component of the particulate matter emitted in engine exhaust, is a known human health hazard. The resulting health burden falls heavily on vulnerable communities located close to major sources including highways, rail yards, and ports. Determination of source contributions to the overall pollution burden is challenging due to collinearity in the exhaust composition profiles for relevant sources including heavy-duty diesel trucks, railroad locomotives, cargo-handling equipment, and marine engines. Additionally, the impact of each source depends not just on the magnitude of emissions but on its location relative to receptors as well as on meteorology. We modeled source-resolved BC concentrations in West Oakland, California, at a high (150 m) spatial resolution using the Weather Research and Forecasting model. The ability of the model to predict hourly and 24 h average BC concentrations is evaluated for a 100-day period in summer 2017 when BC was measured at 100 sites within the community. We find that a community monitoring site is representative of population-weighted average BC exposure in the community. Major contributing sources to BC in West Oakland include on-road diesel trucks (44 ± 5%) and three off-road diesel sources: ocean-going vessels (19 ± 1%), railroad locomotives (16 ± 2%), and harbor craft such as tugboats and ferries (11 ± 1%).

The Impact of an Urban Scrapyard Fire on Respiratory-Related Pediatric Emergency Department Visits

OBJECTIVE

In Philadelphia, a scrapyard fire generated PM2.5 concentrations >1000 μg/m. We assessed whether this was associated with pediatric emergency department visits for respiratory diagnoses.

DESIGN/METHODS

Retrospective observational study using electronic health record data from a local, academic pediatric hospital.

RESULTS

Compared to the two-week period before the fire, patients living directly north of the fire (downwind) had a significant difference in all asthma diagnoses (OR = 3.02, P = 0.03); asthma and upper respiratory infection (OR = 17.3, P = 0.01); overall admissions (OR = 3.04, P = 01); asthma admissions (OR = 4.45, P = .01); and asthma and upper respiratory infection admissions (OR = 15.0, P = 0.01). We did not observe any significant differences among visits or admissions from patients residing in other adjacent zip codes.

CONCLUSION

A localized, transient increase in PM2.5 was associated with increased pediatric emergency department visits for asthma among patients living downwind of the fire.

COVID-19 pandemic reveals persistent disparities in nitrogen dioxide pollution

We leverage the unparalleled changes in human activity during COVID-19 and the unmatched capabilities of the TROPOspheric Monitoring Instrument to understand how lockdowns impact ambient nitrogen dioxide (NO2) pollution disparities in the United States. The least White communities experienced the largest NO2 reductions during lockdowns; however, disparities between the least and most White communities are so large that the least White communities still faced higher NO2 levels during lockdowns than the most White communities experienced prior to lockdowns, despite a ∼50% reduction in passenger vehicle traffic. Similar findings hold for ethnic, income, and educational attainment population subgroups. Future strategies to reduce NO2 disparities will need to target emissions from heavy-duty vehicles.

The unequal spatial distribution of ambient nitrogen dioxide (NO2), an air pollutant related to traffic, leads to higher exposure for minority and low socioeconomic status communities. We exploit the unprecedented drop in urban activity during the COVID-19 pandemic and use high-resolution, remotely sensed NO2 observations to investigate disparities in NO2 levels across different demographic subgroups in the United States. We show that, prior to the pandemic, satellite-observed NO2 levels in the least White census tracts of the United States were nearly triple the NO2 levels in the most White tracts. During the pandemic, the largest lockdown-related NO2 reductions occurred in urban neighborhoods that have 2.0 times more non-White residents and 2.1 times more Hispanic residents than neighborhoods with the smallest reductions. NO2 reductions were likely driven by the greater density of highways and interstates in these racially and ethnically diverse areas. Although the largest reductions occurred in marginalized areas, the effect of lockdowns on racial, ethnic, and socioeconomic NO2 disparities was mixed and, for many cities, nonsignificant. For example, the least White tracts still experienced ∼1.5 times higher NO2 levels during the lockdowns than the most White tracts experienced prior to the pandemic. Future policies aimed at eliminating pollution disparities will need to look beyond reducing emissions from only passenger traffic and also consider other collocated sources of emissions such as heavy-duty vehicles.

COVID-19 pandemic reveals persistent disparities in nitrogen dioxide pollution

The unequal spatial distribution of ambient nitrogen dioxide ([Formula: see text]), an air pollutant related to traffic, leads to higher exposure for minority and low socioeconomic status communities. We exploit the unprecedented drop in urban activity during the COVID-19 pandemic and use high-resolution, remotely sensed [Formula: see text] observations to investigate disparities in [Formula: see text] levels across different demographic subgroups in the United States. We show that, prior to the pandemic, satellite-observed [Formula: see text] levels in the least White census tracts of the United States were nearly triple the [Formula: see text] levels in the most White tracts. During the pandemic, the largest lockdown-related [Formula: see text] reductions occurred in urban neighborhoods that have 2.0 times more non-White residents and 2.1 times more Hispanic residents than neighborhoods with the smallest reductions. [Formula: see text] reductions were likely driven by the greater density of highways and interstates in these racially and ethnically diverse areas. Although the largest reductions occurred in marginalized areas, the effect of lockdowns on racial, ethnic, and socioeconomic [Formula: see text] disparities was mixed and, for many cities, nonsignificant. For example, the least White tracts still experienced ∼1.5 times higher [Formula: see text] levels during the lockdowns than the most White tracts experienced prior to the pandemic. Future policies aimed at eliminating pollution disparities will need to look beyond reducing emissions from only passenger traffic and also consider other collocated sources of emissions such as heavy-duty vehicles.

Assessing the effectiveness of vehicle emission regulations on improving perinatal health: a population-based accountability study

BACKGROUND

Since the 1990s, extensive regulations to reduce traffic-related air pollution (TRAP) have been implemented, yet the effectiveness of these regulations has not been assessed with respect to improving infant health. In this study, we evaluate how infant health risks associated with maternal residences near highways during pregnancy have changed over time.

METHODS

We created a population-based retrospective birth cohort with geocoded residential addresses in Texan metropolitan areas from 1996 through 2009 (n = 2 259 411). We compared term birthweight (37-42 weeks of gestation) among maternal residences <300 m from a highway (high TRAP exposure) (n = 394 346) and 500-3500 m from a highway (comparison group) (n = 1 865 065). We implemented linear regressions to evaluate interactions between high TRAP exposure and birth year, adjusting for demographics, socioeconomic status and neighbourhood context. In addition, we used propensity score matching to further reduce residual confounding.

RESULTS

From 1996 to 2009, outdoor NO2 decreased by 51.3%, based on regulatory monitoring data in Texas. Among pregnant women who resided in the high TRAP zone during pregnancy, interaction terms between residential location and birth year show that birthweight increased by 1.1 g [95% confidence interval CI): 0.7, 1.5) in unadjusted models and 0.3 g (95% CI: 0.0, 0.6) in matched models. Time-stratified models also show decreasing impacts of living in high TRAP areas on birthweight when comparing infants born in 1996-97 with 2008-09. Sensitivity analyses with alternative exposure and control groups show consistent results.

CONCLUSIONS

Infant health risks associated with maternal residence near highways have reduced over time, paralleling regulatory measures to improve exhaust pipe emissions.

Confounding by Socioeconomic Status in Epidemiological Studies of Air Pollution and Health: Challenges and Opportunities

BACKGROUND

Despite a vast air pollution epidemiology literature to date and the recognition that lower-socioeconomic status (SES) populations are often disproportionately exposed to pollution, there is little research identifying optimal means of adjusting for confounding by SES in air pollution epidemiology, nor is there a strong understanding of biases that may result from improper adjustment.

OBJECTIVE

We aim to provide a conceptualization of SES and a review of approaches to its measurement in the U.S. context and discuss pathways by which SES may influence health and confound effects of air pollution. We explore bias related to measurement and operationalization and identify statistical approaches to reduce bias and confounding.

DISCUSSION

Drawing on the social epidemiology, health geography, and economic literatures, we describe how SES, a multifaceted construct operating through myriad pathways, may be conceptualized and operationalized in air pollution epidemiology studies. SES varies across individuals within the contexts of place, time, and culture. Although no single variable or index can fully capture SES, many studies rely on only a single measure. We recommend examining multiple facets of SES appropriate to the study design. Furthermore, investigators should carefully consider the multiple mechanisms by which SES might be operating to identify those SES indicators that may be most appropriate for a given context or study design and assess the impact of improper adjustment on air pollution effect estimates. Last, exploring model contraction and expansion methods may enrich adjustment, whereas statistical approaches, such as quantitative bias analysis, may be used to evaluate residual confounding. https://doi.org/10.1289/EHP7980.

Changes in criteria air pollution levels in the US before, during, and after Covid-19 stay-at-home orders: Evidence from regulatory monitors

The widespread and rapid social and economic changes from Covid-19 response might be expected to dramatically improve air quality. However, national monitoring data from the US Environmental Protection Agency for criteria pollutants (PM_2.5, ozone, NO₂, CO, PM₁₀) provide inconsistent support for that expectation. Specifically, during stay-at-home orders, average PM_2.5 levels were slightly higher (~10% of its multi-year interquartile range [IQR]) than expected; average ozone, NO₂, CO, and PM₁₀ levels were slightly lower (~30%, ~20%, ~27%, and ~1% of their IQR, respectively) than expected. The timing of peak anomaly, relative to the stay-at-home orders, varied by pollutant (ozone: 2 weeks before; NO₂, CO: 3 weeks after; PM₁₀: 2 weeks after); but, by 5-6 weeks after stay-at-home orders, the concentration anomalies appear to have ended. For PM_2.5, ozone, CO, and PM₁₀, no US state had lower-than-expected pollution levels for all weeks during stay-at-home-orders; for NO₂, only Arizona had lower-than-expected levels for all weeks during stay-at-home orders. Our findings show that the enormous changes from the Covid-19 response have not lowered PM_2.5 levels across the US beyond their normal range of variability; for ozone, NO₂, CO, and PM₁₀ concentrations were lowered but the reduction was modest and transient.