Hazardous Air Pollutants Exposure Research Articles

Association of Residential Exposure to Hazardous Air Pollutants with Risk of Non-Hodgkin Lymphoma and Multiple Myeloma.

Certain hazardous air pollutants (HAP) are known or suspected to pose immunological or cancer risk to humans, but evidence is limited from the general population. We assessed associations between residential exposure to HAPs at the census tract level and incident non-Hodgkin lymphoma (NHL) and multiple myeloma in the Nurses' Health Study (NHS, 1986-2012) and NHSII (1989-2019). We used the covariate-adjusted proportional hazards model to estimate hazard ratios (HR) of NHL, major NHL subtypes, and multiple myeloma per interquartile range increase in exposure to a given HAP and pooled the cohort-specific estimates using fixed-effects meta-analyses. There were 810 NHL and 158 multiple myeloma cases in NHS (1,700,707 person-years) and 379 NHL and 59 multiple myeloma cases in NHSII (2,820,772 person-years). Most HRs approximated unity. Meta-analyses did not show consistent evidence of associations between any HAP exposure and risk of NHL or multiple myeloma. Exposure to HAPs was not consistently associated with risks of NHL or multiple myeloma in these nationwide prospective cohorts of women. This is the first nationwide study assessing associations between residential HAP exposures and risk of lymphoid malignances in prospective cohorts and focuses on women, who have frequently been underrepresented in (primarily occupational) studies of exposure to HAPs.

Inequalities in Exposure to Ambient Air Neurotoxicants and Disparities in Markers of Neurodevelopment in Children by Maternal Nativity Status.

Exposure levels to environmental pollutants vary significantly among different populations. These inequities in exposure to hazardous air pollutants (HAP) among different populations can contribute to disparities in neurodevelopmental outcomes. The aim of this study was to determine if exposure to HAP varies by maternal nativity status, a demographic marker often overlooked in the study of health disparities. We also assessed if those inequalities in exposure levels are associated with neurodevelopmental measures in young children. To do this, we obtained data from the Early Childhood Longitudinal Study-Birth cohort (ECLS-B), a nationally representative sample of children born in the U.S. in the year 2001 (n = 4750). Bayley’s Short Form-Research Edition (BSF-R) was used to measure cognitive development at 2 years of age. Using residential location at nine months of age, participants were assigned exposures to ten HAPs identified as potentially neurotoxic. Linear regression models were used to assess the joint effect of maternal nativity status and HAP exposure on neurodevelopment. Results showed inequities in exposure levels to ten different HAPs among the populations, as approximately 32% of children of foreign-born mothers were exposed to high levels of HAPs, compared to 21% of children born to U.S.-born mothers. Adjusting for socioeconomic factors, both isophorone exposure (a marker of industrial pollution) (−0.04, 95% CI, −0.12, 0.04) and maternal nativity status (−0.17, 95% CI, −0.27, −0.06) were independently associated with lower standardized BSF-R mental scores in children. Interaction between nativity status and isophorone was not statistically significant, but the change in mental scores associated with isophorone exposure was greater in children of foreign-born mothers compared to children of U.S.-born mothers (−0.12, vs. −0.03, p = 0.2). In conclusion, exposure to HAPs within the highest quartile was more commonly found among children of foreign-born mothers as compared to children of US-born mothers, indicating inequities in pollutant exposure by nativity status within urban populations. Exposures associated with nativity status may negatively contribute to children’s neurodevelopment.

Convergence of COVID-19 and chronic air pollution risks: Racial/ethnic and socioeconomic inequities in the U.S

Recent research suggests greater COVID-19 prevalence in areas burdened with higher exposure to chronic air pollution, but previous studies have not examined if socially disadvantaged populations are more likely to reside in communities located at the convergence of both COVID-19 and air pollution health risks. This article presents a national scale U.S. study that investigates whether racial/ethnic minorities, socioeconomically deprived residents, and other vulnerable groups are significantly overrepresented in counties where significantly higher COVID-19 incidence spatially coincides with higher respiratory health risks from outdoor exposure to hazardous air pollutants (HAPs). COVID-19 data from the Johns Hopkins Center for Systems Science and Engineering database are linked to respiratory risk estimates from the U.S. Environmental Protection Agency's National Air Toxics Assessment and variables from the 2018 American Community Survey. Bivariate local measures of spatial association are implemented to identify county clusters representing relationships between COVID-19 incidence rate and respiratory risk from HAP exposure. Socio-demographic characteristics of these clusters are compared using bivariate statistical tests and multivariable generalized estimating equations. Counties where greater COVID-19 incidence coincides significantly with higher HAP respiratory risk contain disproportionately higher percentages of non-Hispanic Black, socioeconomically deprived, and uninsured residents than all other U.S. counties, after controlling for spatial clustering, population density, older age, and other contextual factors. These significant socio-demographic inequities represent an important starting point for more detailed investigations of places facing the double burden of elevated COVID-19 prevalence and air pollution exposure, and also emphasize the urgent need to develop mitigation strategies for addressing both COVID-19 and chronic air pollution in socially vulnerable communities.

Hazardous air pollutant exposure as a contributing factor to COVID-19 mortality in the United States

To date, COVID-19 has claimed more than 100 000 American lives. Early inquiry suggests preexisting conditions are key risk factors contributing to COVID-19 mortality and air pollution exposure could exacerbate this relationship. Building on prior research linking deaths from respiratory viruses to air pollution exposures, we investigate how 2014 National Air Toxics Assessment hazardous air pollutants (HAPs) respiratory hazard quotient and respiratory hazard index are related to COVID-19 mortality. Our focus on HAPs builds upon the knowledge base linking poor air quality to COVID-19 mortality, since most (if not all) earlier studies only include criteria pollutants. Herein, we examine the relationship between HAP exposure and US-based COVID-19 mortality, while controlling for socioeconomic status, population health indicators, and exposure to PM2.5 and ozone. We fit county-level negative binomial mixed models, predicting COVID-19 mortality as a function of HAP respiratory toxicity levels and relevant covariates. We include models for combined exposure to HAPs, as well as for specific pollutants. We find that an increase in the respiratory hazard index is associated with a 9% increase in COVID-19 mortality. Although differing in magnitude, this association holds for individual HAPs acetaldehyde, and diesel PM. These findings help us to understand variation in US-based COVID-19 mortality rates, reinforce existing research linking air pollution to mortality, and emphasize the importance of regulatory efforts to limit air pollution exposure risk.

Hazardous Air Pollutants and Adverse Birth Outcomes in Portland, OR.

We used vital statistics records in the Portland Metropolitan Region from 2000 to 2014 (n = 279,051 births). Prenatal exposure to 19 HAPs was assessed using a dispersion model applied to maternal residential address at delivery. We used linear and logistic multivariate regression models to assess associations between individual and cumulative HAP exposures and preterm term (PTB), term birth weight (TBW), and small for gestational age (SGA), adjusting for several potential individual and neighborhood confounding factors. We observed no associations for composite HAP exposure metrics and adverse birth outcomes. Associations were observed in fully adjusted models comparing the highest to lowest quintiles of exposure for certain HAPs including chromium VI and TBW (-12.70; 95% confidence interval [CI]: -23.10, -2.31); 1,3-butadiene and TBW (-16.86; 95% CI: -29.66, -4.06) and SGA (1.18; 95% CI: 1.07, 1.30); and cadmium and TBW (-31.37; 95% CI: -56.20, -.54). For some HAP metrics, we observed higher HAP exposures for minority groups and large unadjusted associations between other HAPs and adverse birth outcomes, but most associations were attenuated in adjusted models. Adverse birth outcomes were not consistently associated with most HAP exposures in Portland, OR, although some specific air toxic exposures warrant further attention.

Downscaling Environmental Justice Analysis: Determinants of Household-Level Hazardous Air Pollutant Exposure in Greater Houston

Environmental justice (EJ) research has relied on ecological analyses of coarse-scale areal units to determine whether particular populations are disproportionately burdened by toxic risks. This article advances quantitative EJ research by (1) examining whether statistical associations found for geographic units translate to relationships at the household level; (2) testing competing explanations for distributional injustices never before investigated; (3) examining adverse health implications of hazardous air pollutant (HAP) exposures; and (4) applying an underutilized statistical technique appropriate for geographically clustered data. Our study makes these advances by using generalized estimating equations to examine distributive environmental inequities in the Greater Houston (Texas) metropolitan area, based on primary household-level survey data and census block–level cancer risk estimates of HAP exposure from the U.S. Environmental Protection Agency. In addition to main statistical effects, interaction effects are modeled to examine whether minority racial or ethnic status modifies the effects of other variables on HAP cancer risk. In terms of main effects, Hispanic and black status as well as the desire to live close to public transit exhibit robust associations with HAP cancer risk. Interaction results reveal that homeownership and homophily (i.e., the desire to live among people culturally similar to oneself) are associated with higher HAP cancer risk among Hispanics and blacks but with lower risk among whites. Disproportionate risks experienced by Hispanics and blacks are attributable neither to dampened risk perceptions nor the desire to live close to work. These findings have implications for EJ research and practice in Greater Houston and elsewhere.

Overview of the Benzene and Other Toxics Exposure (BEE-TEX) Field Study.

The Benzene and other Toxics Exposure (BEE-TEX) field study was an experimental campaign designed to demonstrate novel methods for measuring ambient concentrations of hazardous air pollutants (HAPs) in real time and to attribute these concentrations to quantified releases from specific emission points in industrial facilities while operating outside facility fence lines. BEE-TEX was conducted in February 2015 at three neighboring communities in the Houston Ship Channel of Texas, where a large number of petrochemical facilities are concentrated. The novel technologies deployed during BEE-TEX included: (1) tomographic remote sensing based on differential optical absorption spectroscopy; (2) real-time broadcasting of ambient air monitoring data over the World Wide Web; (3) real-time source attribution and quantification of HAP emissions based on either tomographic or mobile measurement platforms; and (4) the use of cultured human lung cells in vitro as portable indicators of HAP exposure.

Evaluating the effects of maternal exposure to benzene, toluene, ethyl benzene, and xylene on oral clefts among offspring in Texas: 1999–2008

There is evidence from previous studies that maternal occupational exposure to hazardous air pollutants (HAPs) is positively associated with oral clefts; however, studies evaluating the association between residential exposure to these toxicants and oral clefts are lacking. Therefore, our goal was to conduct a case-control study examining the association between estimated maternal residential exposure to benzene, toluene, ethyl benzene, and xylene (BTEX) and the risk of oral clefts among offspring. Data on 6045 nonsyndromic isolated oral cleft cases (3915 cleft lip with or without cleft palate [CL ± P] and 2130 nonsyndromic isolated cleft palate [CP] cases) delivered between 1999 and 2008 were obtained from the Texas Birth Defects Registry. The control group was a sample of unaffected live births, frequency matched to cases on year of birth. Census tract-level estimates of annual average exposures were obtained from the U.S. Environmental Protection Agency 2005 Hazardous Air Pollutant Exposure Model (HAPEM5) for each pollutant and assigned to each subject based on maternal residence during pregnancy. Logistic regression was used to assess the relationship between estimated maternal exposure to each pollutant (BTEX) separately and the risk of oral clefts in offspring. High estimated maternal exposure to benzene was not associated with oral clefts, compared with low estimated exposure (CL ± P adjusted OR = 0.95; 95% CI = 0.81 - 1.12; CP adjusted OR = 0.85; 95% CI = 0.67 - 1.09). Similar results were seen for the other pollutants. In our study, there was no evidence that maternal exposure to environmental levels of BTEX was associated with oral clefts.

Differential Exposure to Hazardous Air Pollution in the United States: A Multilevel Analysis of Urbanization and Neighborhood Socioeconomic Deprivation

Population exposure to multiple chemicals in air presents significant challenges for environmental public health. Air quality regulations distinguish criteria air pollutants (CAPs) (e.g., ozone, PM2.5) from hazardous air pollutants (HAPs)—187 chemicals which include carcinogens and others that are associated with respiratory, cardiovascular, neurological and numerous other non-cancer health effects. Evidence of the public’s cumulative exposure and the health effects of HAPs are quite limited. A multilevel model is used to assess differential exposure to HAP respiratory, neurological, and cancer hazards (2005) related to the Townsend Index of Socioeconomic Deprivation (TSI), after adjustment for regional population size and economic activity, and local population density. We found significant positive associations between tract TSI and respiratory and cancer HAP exposure hazards, and smaller effects for neurological HAPs. Tracts in the top quintile of TSI have between 38%–60% higher HAP exposure than the bottom quintile; increasing population size from the bottom quintile to the top quintile modifies HAP exposure hazard related to TSI, increasing cancer HAP exposure hazard by 6% to 20% and increasing respiratory HAP exposure hazard by 12% to 27%. This study demonstrates the value of social epidemiological methods for analyzing differential exposure and advancing cumulative risk assessment.

Combining Regional- and Local-Scale Air Quality Models with Exposure Models for Use in Environmental Health Studies

Population-based human exposure models predict the distribution of personal exposures to pollutants of outdoor origin using a variety of inputs, including air pollution concentrations; human activity patterns, such as the amount of time spent outdoors versus indoors, commuting, walking, and indoors at home; microenvironmental infiltration rates; and pollutant removal rates in indoor environments. Typically, exposure models rely upon ambient air concentration inputs from a sparse network of monitoring stations. Here we present a unique methodology for combining multiple types of air quality models (the Community Multi-Scale Air Quality [CMAQ] chemical transport model added to the AERMOD dispersion model) and linking the resulting hourly concentrations to population exposure models (the Hazardous Air Pollutant Exposure Model [HAPEM] or the Stochastic Human Exposure and Dose Simulation [SHEDS] model) to enhance estimates of air pollution exposures that vary temporally (annual and seasonal) and spatially (at census-block-group resolution) in an urban area. The results indicate that there is a strong spatial gradient in the predicted mean exposure concentrations near roadways and industrial facilities that can vary by almost a factor of 2 across the urban area studied. At the high end of the exposure distribution (95th percentile), exposures are higher in the central district than in the suburbs. This is mostly due to the importance of personal mobility factors whereby individuals living in the central area often move between microenvironments with high concentrations, as opposed to individuals residing at the outskirts of the city. Also, our results indicate 20–30% differences due to commuting patterns and almost a factor of 2 difference because of near-roadway effects. These differences are smaller for the median exposures, indicating the highly variable nature of the reflected ambient concentrations. In conjunction with local data on emission sources, microenvironmental factors, and behavioral and socioeconomic characteristics, the combined source-to-exposure modeling methodology presented in this paper can improve the assessment of exposures in future community air pollution health studies.

Modeling population exposures to outdoor sources of hazardous air pollutants

Accurate assessment of human exposures is an important part of environmental health effects research. However, most air pollution epidemiology studies rely upon imperfect surrogates of personal exposures, such as information based on available central-site outdoor concentration monitoring or modeling data. In this paper, we examine the limitations of using outdoor concentration predictions instead of modeled personal exposures for over 30 gaseous and particulate hazardous air pollutants (HAPs) in the US. The analysis uses the results from an air quality dispersion model (the ASPEN or Assessment System for Population Exposure Nationwide model) and an inhalation exposure model (the HAPEM or Hazardous Air Pollutant Exposure Model, Version 5), applied by the US. Environmental protection Agency during the 1999 National Air Toxic Assessment (NATA) in the US. Our results show that the total predicted chronic exposure concentrations of outdoor HAPs from all sources are lower than the modeled ambient concentrations by about 20% on average for most gaseous HAPs and by about 60% on average for most particulate HAPs (mainly, due to the exclusion of indoor sources from our modeling analysis and lower infiltration of particles indoors). On the other hand, the HAPEM/ASPEN concentration ratio averages for onroad mobile source exposures were found to be greater than 1 (around 1.20) for most mobile-source related HAPs (e.g. 1, 3-butadiene, acetaldehyde, benzene, formaldehyde) reflecting the importance of near-roadway and commuting environments on personal exposures to HAPs. The distribution of the ratios of personal to ambient concentrations was found to be skewed for a number of the VOCs and reactive HAPs associated with major source emissions, indicating the importance of personal mobility factors. We conclude that the increase in personal exposures from the corresponding predicted ambient levels tends to occur near locations where there are either major emission sources of HAPs or when individuals are exposed to either on- or nonroad sources of HAPs during their daily activities. These findings underscore the importance of applying exposure-modeling methods, which incorporate information on time-activity, commuting, and exposure factors data, for the purposes of assigning exposures in air pollution health studies.

Using CMAQ for Exposure Modeling and Characterizing the Subgrid Variability for Exposure Estimates

Abstract Atmospheric processes and the associated transport and dispersion of atmospheric pollutants are known to be highly variable in time and space. Current air-quality models that characterize atmospheric chemistry effects, for example, the Community Multiscale Air Quality model (CMAQ), provide volume-averaged concentration values for each grid cell in the modeling domain given the stated conditions. Given the assumptions made and the limited set of processes included in any model’s implementation, there are many sources of “unresolved” subgrid variability. This raises the question of the importance of the unresolved subgrid variations on exposure assessment results if such models were to be used to assess air toxics exposure. In this study, the Hazardous Air Pollutant Exposure Model (HAPEM) is applied to estimate benzene and formaldehyde inhalation exposure using ambient annually averaged concentrations predicted by CMAQ to investigate how within-grid variability can affect exposure estimates. An urban plume dispersion model was used to estimate the subgrid variability of annually averaged benzene concentration values within CMAQ grid cells for a modeling domain centered on Philadelphia, Pennsylvania. Significant (greater than a factor of 2) increases in maximum exposure impacts were seen in the exposure estimates in comparison with exposure estimates generated using CMAQ grid-averaged concentration values. These results consider only one source of subgrid variability, namely, the discrete location and distribution of emissions, but they do suggest the importance and value of developing improved characterizations of subgrid concentration variability for use in air toxics exposure assessments.

Childhood cancer incidence rates and hazardous air pollutants in California: an exploratory analysis.

Hazardous air pollutants (HAPs) are compounds shown to cause cancer or other adverse health effects. We analyzed population-based childhood cancer incidence rates in California (USA) from 1988 to 1994, by HAP exposure scores, for all California census tracts. For each census tract, we calculated exposure scores by combining cancer potency factors with outdoor HAP concentrations modeled by the U.S. Environmental Protection Agency. We evaluated the relationship between childhood cancer rates and exposure scores for 25 potentially carcinogenic HAPs emitted from mobile, area, and point sources and from all sources combined. Our study period saw 7,143 newly diagnosed cancer cases in California; of these, 6,989 (97.8%) could be assigned to census tracts and included in our analysis. Using Poisson regression, we estimated rate ratios (RRs) adjusted for age, race/ethnicity, and sex. We found little evidence for elevated cancer RRs for all sites or for gliomas among children living in high-ranking combined-source exposure areas. We found elevated RRs and a significant trend with increasing exposure level for childhood leukemia in tracts ranked highest for exposure to the combined group of 25 HAPs (RR = 1.21; 95% confidence interval, 1.03, 1.42) and in tracts ranked highest for point-source HAP exposure (RR = 1.32; 95% confidence interval, 1.11, 1.57). Our findings suggest an association between increased childhood leukemia rates and high HAP exposure, but studies involving more comprehensive exposure assessment and individual-level exposure data will be important for elucidating this relationship.