US Environmental Protection Agency Air Research Articles

Effects of fine particulate matter from wildfire and non-wildfire sources on emergency-department visits in people who were housed and unhoused in San Diego County (CA, USA) during 2012–20: a time-stratified case–crossover study

Being unhoused can increase vulnerability to adverse health effects due to air pollution. We aimed to quantify changes in emergency-department visits during and after exposure to wildfire-specific and non-wildfire particulate matter 2·5 μm or less in diameter (PM2·5) in San Diego County (CA, USA) in people who were both unhoused and housed. For this time-stratified case-crossover study, we used data on exposure to wildfire-specific PM2·5 in California and individual-level data for people admitted to the emergency departments of two hospitals (UC San Diego Health emergency departments at La Jolla and Hillcrest, San Diego) in San Diego County between July 1, 2012, and Dec 31, 2020. People with a postcode outside of San Diego County were excluded. Demographic information was age group, race or ethnicity, and transport to the emergency department. Wildfire-specific PM2·5 concentration at the postcode level was previously estimated using an ensemble model that combined multiple machine-learning algorithms and explanatory variables obtained via data on 24-h mean PM2·5 concentrations from the US Environmental Protection Agency Air Quality System. Conditional logistic regression models were applied, adjusting for specific humidity, wind velocity, and maximum temperature extracted from the US Gridded Surface Meteorological Dataset. Housing status was established by registration staff or triage nurses on arrival at the emergency department. For people who were unhoused, exposure was defined based on the weighted mean PM2·5 concentration at the city level proportional to the number of people who were unhoused in each specific city across urban centres in San Diego County. For people who were housed, we used residence postcode to measure exposure. We assessed the association between PM2·5 from wildfire and non-wildfire sources and emergency-department visits in people who were housed and unhoused. There were 587 562 emergency-department visits at the two hospitals, 76 407 (13·0%) of which were by people who were unhoused. People who were housed had a higher exposure to overall PM2·5 (24-h mean over the study period of 9·904 mg/m3, SD 3·445) and non-wildfire PM2·5 (9·663, 2·977) than people who were unhoused (9·863, 3·221; 9·557, 2·599). However, people who were unhoused had a higher exposure to wildfire-specific PM2·5 (0·305, 1·797) than people who were housed (0·240, 1·690). Overall PM2·5 exposure was associated with increased odds of emergency-department visits for both people who were housed (odds ratio 1·003, 95% CI 1·001-1·004 per 1 μg/m3 PM2·5 for 0-3 days after exposure) and people who were unhoused (1·004, 1·000-1·008 for 0-3 days after exposure). We found that non-wildfire PM2·5 was associated with emergency-department visits among people who were housed (1·003, 1·002-1·005 for 0-3 days after exposure) and wildfire-specific PM2·5 was associated with emergency-department visits in people who were unhoused (1·006, 1·001-1·011 for 0-3 days after exposure). People who were unhoused in San Diego County were more likely to visit emergency departments after exposure to increased wildfire-specific PM2·5. As the intensity and frequency of wildfires increase, understanding risk factors for vulnerable populations, such as people who are unhoused, is crucial to develop effective adaptation strategies. US National Institutes of Health, National Institute on Aging.

Public Health Relevance of US EPA Air Quality Index Activity Recommendations

Reducing exposure to fine particulate matter (<2.5 μm [PM2.5]) air pollution improves cardiopulmonary morbidity and mortality. However, the public health relevance of air quality index (AQI) activity guidelines under present-day environmental conditions in the US has not been critically assessed. To evaluate the public health relevance of following PM2.5 AQI activity guidance in preventing serious atherosclerotic cardiovascular disease (ASCVD) and pulmonary events among adults in the US. This cross-sectional modeling study involved the general adult population and sensitive individuals as designated by the US Environmental Protection Agency (EPA), including adults with preexisting ASCVD or lung disease (asthma or chronic obstructive pulmonary disease). The study was conducted between August 1, 2023, and January 31, 2024. Daily AQI strata for PM2.5 and the corresponding activity recommendations. The main outcome was the number needed to treat (NNT) per day by following activity guidance across daily AQI strata to prevent 1 serious ASCVD or pulmonary event among relevant populations. To calculate PM2.5-induced excess disease event rates per day, estimated baseline disease-specific daily event rates for each group were multiplied by the increase in risks due to PM2.5 levels at each AQI stratum. The number of events prevented per day was calculated by multiplying each excess disease event rate by the percentage in exposure reduction plausibly incurred by following population-specific activity guidance at each AQI level. The NNT is the reciprocal of the number of events prevented. The NNT to prevent ASCVD events was high for the general population and for patients with ASCVD across all AQI strata. The range of values was comparatively lower to prevent pulmonary events among adults with lung disease. During most days (96%) when activity recommendations were promulgated due to elevated PM2.5 (AQI, 101-200), the NNT to prevent a serious disease event remained very high for the general population (>18 million), patients with ASCVD (approximately 1.6-5 million), and adults with lung disease (approximately 66 000-202 000). These findings suggest that existing PM2.5 AQI activity recommendations are of questionable public health relevance in present-day conditions and merit consideration for updating to improve their potential effectiveness.

Towards a hygroscopic growth calibration for low-cost PM2.5 sensors

Abstract. Low-cost particulate matter (PM) sensors continue to grow in popularity, but issues such as aerosol-size-dependent sensitivity drive the need for effective calibration schemes. Here we devise a time-evolving calibration method for the Plantower PMS5003 PM2.5 mass concentration measurements. We use 2 years of measurements from the Berkeley Environmental Air-quality and CO2 Network sensors deployed in San Francisco and Los Angeles in our analysis. The calibration uses a hygroscopic growth correction factor derived from κ-Köhler theory, where the calibration parameters are determined empirically using US Environmental Protection Agency Air Quality System (EPA AQS) reference data at co-location sites during the period from 2021–2022. The parameters are found to vary cyclically through the seasons, and the seasonal cycles match changes in sulfate and elemental carbon PM composition fractions throughout the year. In both regions, the seasonal RH dependence calibration performs better than the uncalibrated data and data calibrated with the EPA's national Plantower calibration algorithm. In the San Francisco Bay Area, the seasonal RH dependence calibration reduces the root mean square error (RMSE) by ∼40 % from the uncalibrated data and maintains a mean bias much smaller than the EPA national calibration scheme (−0.90 vs −2.73 µg m−3). We also find that calibration parameters forecasted beyond those fit with the EPA reference data continue to outperform the uncalibrated data and EPA calibration data, enabling real-time application of the calibration scheme even in the absence of reference data. While the correction greatly improves the data accuracy, non-Gaussian distribution of the residuals suggests that other processes besides hygroscopic growth can be parameterized for future improvement of this calibration.

Longitudinal Effect of Ambient Air Pollution and Pollen Exposure on Asthma Control: The Patient-Reported Outcomes Measurement Information System (PROMIS) Pediatric Asthma Study

ObjectiveAlthough exposure to air pollution and pollen is associated with asthma exacerbation and increased health care use, longitudinal effects of fine particulate matter 2.5 (PM2.5), ozone (O3), and pollen exposure on asthma control status in pediatric patients are understudied. This study investigated effects of exposure to PM2.5, O3, and pollen on asthma control status among pediatric patients with asthma. MethodsA total of 229 dyads of pediatric patients with asthma and their parents were followed for 15 months. The Asthma Control and Communication Instrument was used to measure asthma control, which was reported weekly by parents during a 26-week period. PM2.5 and O3 data were collected from the US Environmental Protection Agency Air Quality System. Pollen data were obtained from Intercontinental Marketing Services Health. Mean air pollutant and pollen exposures within 7 days before the reporting of asthma control were used to estimate weekly exposures for each participant. Linear mixed-effects models were performed to test associations of PM2.5, O3, and pollen exposure with asthma control status. Sensitivity analyses were performed to evaluate the robustness of findings by different exposure monitoring days per week and distances between monitoring sites and participants’ residences. ResultsElevated PM2.5 concentration and pollen severity were associated with poorer asthma control status (P < .05), yet elevated O3 concentration was marginally associated with better asthma control (P < .1). ConclusionsPoorer asthma control status was associated with elevated PM2.5 and pollen severity. Reducing harmful outdoor environmental ambient exposure may improve asthma outcomes in children and adolescents.

Long-Term NO2 Exposures and Cause-Specific Mortality in American Older Adults

The impact of long-term exposure to nitrogen dioxide (NO2) on all-cause mortality and cause-specific mortality is poorly understood. We examined the association between long-term NO2 exposure and cause-specific mortality among about 14 million Medicare beneficiaries living close to US Environmental Protection Agency air quality monitoring sites in the conterminous US from 2000 to 2008. After controlling for age, gender, race, and state, we found significant positive associations between 12-month NO2 exposure and all-cause mortality [Hazard Ratio (HR): 1.06; 95%CI: 1.06, 1.06; per 10 ppb]. Additionally, long-term NO2 exposure was associated with the three most common causes of death: mortality from cardiovascular (1.14; 95%CI: 1.14, 1.14) and respiratory disease (1.05; 95%CI: 1.04, 1.06) and from cancer (1.02; 95%CI: 1.02, 1.02). Twelve-month moving average NO2 exposure was also associated with increased mortality from ischemic heart disease (1.22; 95%CI: 1.18, 1.20), cerebrovascular disease (1.10; 95%CI: 1.10, 1.10), and pneumonia (1.24; 95%CI: 1.24, 1.25). As expected, NO2 was not positively associated with accidental mortality risk. When we additionally adjusted for county level behavioral variables (using the BRFSS data), we found similar patterns of association. When we extended our analysis to the 64 million beneficiaries living in the conterminous US from 2000 to 2008 as a sensitivity analysis, we similarly found association between long-term NO2 exposure-associated mortality from all-cause, and cause-specific mortality.In our large cohort of U.S. Medicare beneficiaries, we provide additional evidence of the increased risk posed by long-term NO2 exposures on mortality from all-causes, cardiovascular and respiratory disease, and cancer and provide new evidence of the impact of long-term NO2 exposure on pneumonia.

Estimating the associations of apparent temperature and inflammatory, hemostatic, and lipid markers in a cohort of midlife women

Associations between temperature and cardiovascular (CVD) mortality have been reported, but the underlying biological mechanisms remain uncertain. We explored the association between apparent temperature and serum biomarkers for CVD. Using linear mixed effects models, we examined the relationships between residence-proximate apparent temperature (same day and 1, 7, and 30 days prior) and several inflammatory, hemostatic, and lipid biomarkers for midlife women from 1999 through 2004. Our study population consisted of 2,306 women with mean age of 51 years (± 3 years) enrolled in Study of Women's Health Across the Nation (SWAN) in Chicago, Illinois; Detroit, Michigan; Los Angeles and Oakland, California; Newark, New Jersey; and Pittsburgh, Pennsylvania. Mean daily apparent temperature was calculated using temperature and relative humidity data provided by the National Climatic Data Center and the US Environmental Protection Agency, while daily data for fine particles, ozone, carbon monoxide, and nitrogen dioxide from the US Environmental Protection Agency Air Quality Data Mart were considered as confounders. All analyses were stratified by warm and cold seasons.More significant (p < 0.10) negative associations were found during the warm season for various lag times, including hs-CRP, fibrinogen, tissue plasminogen activator antigen (tPA-ag), tissue plasminogen activator antigen (PAI-1), Factor VIIc, high-density lipoprotein (HDL), and total cholesterol. During the cold season, significant negative associations for fibrinogen and HDL, but significant positive associations for tPA-ag, PAI-1, and triglycerides were observed for various lag times. With the exception of ozone, pollutants did not confound these associations. Apparent temperature was associated with several serum biomarkers of CVD risk in midlife women, shedding light on potential mechanisms.

Associations between exposure to ambient benzene and PM2.5 during pregnancy and the risk of selected birth defects in offspring

ObjectiveA growing number of studies have investigated the association between air pollution and the risk of birth defects, but results are inconsistent. The objective of this study was to examine whether maternal exposure to ambient PM2.5 or benzene increases the risk of selected birth defects in Florida. MethodsWe conducted a retrospective cohort study of singleton infants born in Florida from 2000 to 2009. Isolated and non-isolated birth defect cases of critical congenital heart defects, orofacial clefts, and spina bifida were identified from the Florida Birth Defects Registry. Estimates of maternal exposures to PM2.5 and benzene for all case and non-case pregnancies were derived by aggregation of ambient measurement data, obtained from the US Environmental Protection Agency Air Quality System, during etiologically relevant time windows. Multivariable Poisson regression was used to estimate adjusted prevalence ratios (aPRs) and 95% confidence intervals (CIs) for each quartile of air pollutant exposure. ResultsCompared to the first quartile of PM2.5 exposure, higher levels of exposure were associated with an increased risk of non-isolated truncus arteriosus (aPR4th Quartile, 8.80; 95% CI, 1.11–69.50), total anomalous pulmonary venous return (aPR2nd Quartile, 5.00; 95% CI, 1.10–22.84), coarctation of the aorta (aPR4th Quartile, 1.72; 95% CI, 1.15–2.57; aPR3rd Quartile, 1.60; 95% CI, 1.07–2.41), interrupted aortic arch (aPR4th Quartile, 5.50; 95% CI, 1.22–24.82), and isolated and non-isolated any critical congenital heart defect (aPR3rd Quartile, 1.13; 95% CI, 1.02–1.25; aPR4th Quartile, 1.33; 95% CI, 1.07–1.65). Mothers with the highest level of exposure to benzene were more likely to deliver an infant with an isolated cleft palate (aPR4th Quartile, 1.52; 95% CI, 1.13–2.04) or any orofacial cleft (aPR4th Quartile, 1.29; 95% CI, 1.08–1.56). An inverse association was observed between exposure to benzene and non-isolated pulmonary atresia (aPR4th Quartile, 0.19; 95% CI, 0.04–0.84). ConclusionOur results suggest a few associations between exposure to ambient PM2.5 or benzene and specific birth defects in Florida. However, many related comparisons showed no association. Hence, it remains unclear whether associations are clinically significant or can be causally related to air pollution exposures.

The sensitivity of health effect estimates from time-series studies to fine particulate matter component sampling schedule

The US Environmental Protection Agency air pollution monitoring data have been a valuable resource commonly used for investigating the associations between short-term exposures to PM2.5 chemical components and human health. However, the temporally sparse sampling on every third or sixth day may affect health effect estimation. We examined the impact of non-daily monitoring data on health effect estimates using daily data from the Denver Aerosol Sources and Health (DASH) study. Daily concentrations of four PM2.5 chemical components (elemental and organic carbon, sulfate, and nitrate) and hospital admission counts from 2003 through 2007 were used. Three every-third-day time series were created from the daily DASH monitoring data, imitating the US Speciation Trend Network (STN) monitoring schedule. A fourth, partly irregular, every-third-day time series was created by matching existing sampling days at a nearby STN monitor. Relative risks (RRs) of hospital admissions for PM2.5 components at lags 0-3 were estimated for each data set, adjusting for temperature, relative humidity, longer term temporal trends, and day of week using generalized additive models, and compared across different sampling schedules. The estimated RRs varied somewhat between the non-daily and daily sampling schedules and between the four non-daily schedules, and in some instances could lead to different conclusions. It was not evident which features of the data or analysis were responsible for the variation in effect estimates, although seeing similar variability in resampled data sets with relaxation of the every-third-day constraint suggests that limited power may have had a role. The use of non-daily monitoring data can influence interpretation of estimated effects of PM2.5 components on hospital admissions in time-series studies.

Ammonia emissions from broiler production in the San Joaquin Valley

Ammonia is the primary basic gas in the atmosphere and has the most important role in the neutralization of atmospheric acids generated by fossil fuel combustion. The reaction product forms a NH(4)(+) aerosol, which is a major component of atmospheric particulates. These NH(4)(+) particulates are part of atmospheric haze and may be transported long distances from the production site before returning to the surface by dry deposition or scavenged by precipitation. Animal production produces a significant component of anthropogenic NH(3) emissions and the National Academy of Sciences concluded that NH(3) emissions estimates from animal feeding operations have not been characterized sufficiently, leading the US Environmental Protection Agency to institute studies in the United States to obtain NH(3) emissions from animal feeding operations under the US Environmental Protection Agency Air Consent Agreement. The objective of this study is to obtain additional broiler NH(3) emissions estimates using a backward Lagrangian stochastic technique. This technique uses NH(3) concentrations measured upwind and downwind of the farm, wind observations, and atmospheric dispersion model calculations to obtain whole-farm emissions. Ammonia emissions were low at bird placement and increased steadily after about the third week of growth. At the end of the flock (47 d, ~297,000 birds), cumulative emissions for the flock cycle period were 0.016 kg of NH(3).bird(-1).flock(-1). Between-flock emissions, including bird harvest, cleanout, temporary storage of litter outside of the buildings, and downtime (buildings closed), added another 0.003 kg of NH(3).bird(-1).flock(-1). Emissions from this broiler farm were less than from some eastern US broiler farms but were comparable to broiler farms in Europe. Based on the results of this study and a similar winter study at this same farm, total flock wintertime and summertime (flock cycle plus between-flock) NH(3) emissions from this farm represented 7.8 and 8.3% of feed N as NH(3)-N, respectively, or an annual average of 8.1%.

Effect of air quality on assisted human reproduction

Air pollution has been associated with reproductive complications. We hypothesized that declining air quality during in vitro fertilization (IVF) would adversely affect live birth rates. Data from US Environmental Protection Agency air quality monitors and an established national-scale, log-normal kriging method were used to spatially estimate daily mean concentrations of criteria pollutants at addresses of 7403 females undergoing their first IVF cycle and at the their IVF labs from 2000 to 2007 in the Northeastern USA. These data were related to pregnancy outcomes. Increases in nitrogen dioxide (NO(2)) concentration both at the patient's address and at the IVF lab were significantly associated with a lower chance of pregnancy and live birth during all phases of an IVF cycle from medication start to pregnancy test [most significantly after embryo transfer, odds ratio (OR) 0.76, 95% confidence interval (CI) 0.66-0.86, per 0.01 ppm increase]. Increasing ozone (O(3)) concentration at the patient's address was significantly associated with an increased chance of live birth during ovulation induction (OR 1.26, 95% CI 1.10-1.44, per 0.02 ppm increase), but with decreased odds of live birth when exposed from embryo transfer to live birth (OR 0.62, 95% CI 0.48-0.81, per 0.02 ppm increase). After modeling for interactions of NO(2) and O(3) at the IVF lab, NO(2) remained negatively and significantly associated with live birth (OR 0.86, 95% CI 0.78-0.96), whereas O(3) was non-significant. Fine particulate matter (PM(2.5)) at the IVF lab during embryo culture was associated with decreased conception rates (OR 0.90, 95% CI 0.82-0.99, per 8 microg/m(3) increase), but not with live birth rates. No associations were noted with sulfur dioxide or larger particulate matter (PM(10)). The effects of declining air quality on reproductive outcomes after IVF are variable, cycle-dependent and complex, though increased NO(2) is consistently associated with lower live birth rates. Our findings are limited by the lack of direct measure of pollutants at homes and lab sites.

Development of an Exposure Assessment Method for Epidemiological Studies of New York State Personnel who Responded to the World Trade Center Disaster

An exposure assessment method was developed for use in assigning an exposure score to New York State personnel who responded to the World Trade Center disaster site after the 11 September 2001 terrorist attacks. The method consists of an algorithm with two instantiations. Each represents a major component of the overall exposures at the site: dust and smoke. The algorithm uses US Environmental Protection Agency air monitoring data collected between 23 September 2001 and 28 February 2002, as well as information on duration, location and time period of work assignment and type and frequency of personal protective respiratory equipment (PPE) use, collected by a self-administered mailed questionnaire. These data were used to calculate an overall exposure score for each participant. For each time period/location combination, individuals provided average number of hours and number of days worked. This was multiplied by a weighting factor derived from the median of the air monitoring data for the time period/location. Calcium was chosen as a surrogate for the dust exposure, so the weighting factors for the dust instantiation were calculated from calcium air monitoring data. Total hepta-chlorinated dibenzo-p-dioxin was chosen as a surrogate for the smoke exposure and was similarly used in the smoke instantiation. More individuals in the highest exposure score category performed tasks such as search/rescue and hand digging than those in the lowest exposure category. Also, those in the highest exposure category had a higher mean number of hours at the site than other exposure groups. The exposure assessment method presented accounts for PPE use, amount of time at the site, proximity to the site and ambient air monitoring results taken in the immediate vicinity. The algorithm can be used to rank individuals in the same study with very different patterns of exposure, such as high-level, short-term exposures and low-level, long-term exposures. The concepts could be modified for use in other epidemiological studies where long-term chronic exposure is a concern.

Estimating Outside Air Concentrations surrounding Fumigated Grain Mills

Fumigation is often performed in grain-milling facilities and warehouses to control unwanted insect pests. Fumigants are typically gases or liquids having a high vapour pressure such that the fumigant permeates throughout the facility. Multiple fumigant field studies using commercial mill structures were performed using sulphuryl fluoride (SF). Internal building concentrations, SF leakage rates, and external air concentrations at specific setback distances from the treated structure were quantified. However, field studies are limited to the parametric combinations of management practices, mill geometry, and meteorological conditions that occurred during the experiment. The use of two existing US Environmental Protection Agency air dispersion models [Building Profile Input Program (BPIP) and the Industrial Source Complex dispersion model (ISCST3)], with custom applications of Visual Basic and Monte Carlo algorithms were employed to calculate different exposure scenarios and to extrapolate external SF air concentrations for parameter ranges not used/observed in the field trials. Different inputs included application rate, application date, application timing, meteorological variability, and parameters quantifying building leakage and aeration processes. Results from the numerical system were validated against observations from three US mill field studies located in Kansas, Texas, and Indiana with excellent agreement (average difference from 32·9% to 42·7%), giving credence that the modelling can expand field observations to other diverse situations where mill fumigation may be used. Sensitive input parameters were allowed to vary by Monte Carlo techniques to quantify parametric uncertainty. It was found that the orientation of wind speed and direction surrounding a fumigated mill can influence external air concentrations due to the effect of neighbouring buildings and silos.