Protection Agency Air Quality Research Articles

Ambient particulate matter and frequency of outpatient visits for chronic rhinosinusitis in the United States.

Emerging evidence has underscored the harmful effects of air pollution on the upper airway. We investigated the relationship between ambient particulate matter (PM) level and the frequency of outpatient visits for chronic rhinosinusitis (CRS). We conducted an ecological cohort study of US adults enrolled in The Merative MarketScan outpatient database from 2007 to 2020. For each geographical subunit (core-based statistical area [CBSA]), we calculated the annual rate of CRS-related outpatient visits per 1000 well-patient checkup visits (CRS-OV). Using data from the Environmental Protection Agency's Air Quality System, we mapped the rolling statistical average of daily PM2.5 and PM10 over the preceding year onto each CBSA×year combination. We employed multivariable negative binomial regression modeling to estimate the association between PM levels and subsequent CRS-OV. Across 3933 observations (CBSA×year combinations), encompassing ∼4 billion visits, the median CRS-OV was 164 (interquartile range 110-267). The mean PM2.5 level was 8.9µg/m3 (SD 2.6) and the mean PM10 level was 20.2µg/m3 (SD 7.2). Adjusting for patient demographics and respiratory comorbidities, a compounded rise in subsequent CRS-OV was observed with increasing PM levels. Each µg/m3 rise in PM2.5 independently predicted a 10% increase in CRS-OV (adjusted incidence rate ratio [aIRR]) 1.10, 95% confidence interval [CI] 1.08-1.13) and each µg/m3 rise in PM10 independently predicted a 3% increase in CRS-OV (aIRR 1.03, 95% CI 1.02-1.04). Elevated ambient PM2.5 and PM10 levels are associated with a subsequent compounded increase in the frequency of CRS-OV, with PM2.5 predicting a more pronounced rise compared to PM10.

Revisiting day-of-week ozone patterns in an era of evolving US air quality

Abstract. Past work has shown that traffic patterns in the USA and resulting NOx emissions vary by day of week, with NOx emissions typically being higher on weekdays than weekends. This pattern of emissions leads to different levels of ozone on weekends versus weekdays and can be leveraged to understand how local ozone formation changes in response to NOx emission perturbations in different urban areas. Specifically, areas with lower NOx but higher ozone on the weekends (the weekend effect) can be characterized as NOx-saturated and areas with both lower NOx and ozone on weekends (the weekday effect) can be characterized as NOx-limited. In this analysis, we assess maximum daily 8 h average (MDA8) ozone weekend–weekday differences across 51 USA nonattainment areas using 18 years of observed and modeled data from 2002–2019, using the following two metrics: mean MDA8 ozone and percentage of days with MDA8 ozone > 70 ppb (parts per billion). In addition, we quantify the modeled and observed trends in these weekend–weekday differences across this period of substantial NOx emission reductions in the USA. The model assessment is carried out using U.S. Environmental Protection Agency (EPA)'s Air QUAlity TimE Series Project (EQUATES) Community Multiscale Air Quality (CMAQ) model dataset. We identify three types of MDA8 ozone trends occurring across the USA, namely transitioning chemical regime, disappearing weekday effect, and no trend. The transitioning chemical regime trend occurs in a subset of large urban areas that were NOx-saturated (i.e., volatile organic compound (VOC)-limited) at the beginning of the analysis period but transitioned to mixed chemical regimes or NOx-limited conditions by the end of the analysis period. Nine areas have strong transitioning chemical regime trends using both modeled and observed data and with both metrics indicating strong agreement that they are shifting to more NOx-limited conditions: Milwaukee, Houston, Phoenix, Denver, the Northern Wasatch Front, the Southern Wasatch Front, Las Vegas, Los Angeles – San Bernardino County, Los Angeles – South Coast, and San Diego. The disappearing weekday effect was identified for multiple rural and agricultural areas of California which were NOx-limited for the entire analysis period but appear to become less influenced by local day-of-week emission patterns in more recent years. Finally, we discuss a variety of reasons why there are no trends in certain areas including complex impacts of heterogeneous source mixes and stochastic impacts of meteorology. Overall, this assessment finds that the EQUATES modeling simulations indicate more NOx-saturated conditions than the observations but do a good job of capturing year-to-year changes in weekend–weekday MDA8 ozone patterns.

Quantifying diurnal changes in NO2 due to COVID-19 stay-at-home orders in New York City

IntroductionPolicy responses to the COVID-19 pandemic, such as the NY on Pause stay-at-home order (March 22 – June 8, 2020), substantially reduced traffic and traffic-related air pollution (TRAP) in New York City (NYC). We evaluated the magnitude of TRAP decreases and examined the role of modifying factors such as weekend/weekday, road proximity, location, and time-of-day. MethodsHourly nitrogen dioxide (NO2) concentrations from January 1, 2018 through June 8, 2020 were obtained from the Environmental Protection Agency's Air Quality System for all six hourly monitors in the NYC area. We used an interrupted time series design to determine the impact of NY on Pause on NO2 concentrations, using a mixed effects model with random intercepts for monitor location, adjusted for meteorology and long-term trends. We evaluated effect modification through stratification. ResultsNO2 concentrations decreased during NY on Pause by 19% (-3.2 ppb, 95% confidence interval [CI]: -3.5, -3.0), on average, compared to pre-Pause time trends. We found no evidence for modification by weekend/weekday, but greater decreases in NO2 at non-roadside monitors and weak evidence for modification by location. For time-of-day, we found the largest decreases for 5 am (27%, -4.5 ppb, 95% CI: -5.7, -3.3) through 7 am (24%, -4.0 ppb, 95% CI: -5.2, -2.8), followed by 6 pm and 7 pm (22%, -3.7 ppb, 95% CI: -4.8, -2.6 and 22%, -4.8, -2.5, respectively), while the smallest decreases occurred at 11 pm and 1 am (both: 11%, -1.9 ppb, 95% CI: -3.1, -0.7). ConclusionNY on Pause's impact on TRAP varied greatly diurnally. Decreases during early morning and evening time periods are likely due to decreases in traffic. Our results may be useful for planning traffic policies that vary by time of day, such as congestion tolling policies.

Maternal exposure to ambient ozone and congenital diaphragmatic hernia: A population-based retrospective cohort study from Florida, 1998–2012

BackgroundCongenital diaphragmatic hernia (CDH) is a rare birth defect with a global prevalence of 2.3 per 10,000 (range: 1.1–8.0 per 10,000). Ambient ozone has been associated with several birth defects; however, there is limited evidence for its role in the etiology of CDH. We examined the role of maternal exposure to ambient ozone as a risk factor for CDH (overall and stratified by isolated and complex) in the State of Florida. MethodsWe conducted a population-based, retrospective cohort study using data from the 1998–2012 Florida Birth Defects Registry and the Environmental Protection Agency's Air Quality System. Maternal exposure was estimated by combining data to determine ozone concentrations during pregnancy for maternal census tract (at delivery) using a space-time inverse distance squared weighting method. Multilevel Poisson regression models were used to calculate the risk of CDH, overall and stratified by isolated and complex. ResultsThe study population consisted of 2,649,846 singleton live births including 814 cases of CDH. The findings indicate insufficient evidence for an association between maternal exposure to ambient ozone and CDH during the etiologically relevant time window for CDH (4–12 weeks of pregnancy). Prevalence ratios and 95% confidence intervals for each increasing quartile of ozone exposure level relative to the lowest quartile were: for overall CDH: 1.12 (0.92, 1.36), 0.99 (0.81, 1.22), and 1.12 (0.94, 1.40); for isolated CDH: 1.08 (0.86, 1.36), 1.01 (0.80, 1.28), and 1.15 (0.92, 1.44); and for complex CDH: 1.22 (0.91, 1.63), 0.92 (0.67, 1.25), and 1.12 (0.83, 1.52). ConclusionsOur results do not support a link between maternal exposure to ambient ozone and CDH. Studies with better exposure assessment and inclusion of spontaneous and planned abortions may be needed. Gene-environment interactions and the study of maternal vitamin A status as a mediator in the pathway between ambient ozone and CDH may provide further information on the potential role of ambient ozone in the etiology of CDH.

Uncertainty Characterization in PM2.5 Estimates Across the Contiguous US

BACKGROUND AND AIM: Accurate PM2.5 exposure assessment, often performed using statistical prediction models, is a critical component of health studies and regulatory action. Ensemble modeling is becoming increasingly popular as it improves accuracy by combining the unique strengths of different models. Identifying where prediction uncertainty is greatest can inform monitor deployment and model development. We fit an ensemble model integrating multiple existing PM2.5 prediction models, estimated location-specific uncertainty in predictions, and then identified factors contributing to uncertainty. METHODS: We predicted 2015 annual PM.5 concentrations at 0.01°×0.01° resolution across the contiguous US by combining three well-validated prediction models with the Bayesian Non-parametric Ensemble (BNE). Training data came from the US Environmental Protection Agency's Air Quality System database. We estimated model uncertainty, which captures disagreement between models, uncertainty of weights, and random error, as the standard deviations of predictions’ location-specific posterior predictive distribution. We analyzed how predicted PM2.5, AQS monitor count within a 50-km radius, summer- and winter-mean temperature, and population density vary with uncertainty via a generalized additive mixed model, with penalized splines and a random intercept for state. RESULTS:Mean (standard deviation; SD) predicted PM2.5 was 6.37 μg/m3 (1.78), with a spatial RMSE of 0.71 μg/m^3, and mean (SD) uncertainty was 0.47 (0.20) μg/m^3. We observed greater uncertainty in the Midwest and Great Lakes areas. Predicted concentration had a complex relationship with uncertainty, with a generally positive association above ~8 μg/m^3. Monitor density had a negative association. Winter temperature below 0°C was positively associated with uncertainty, and summer temperature was positively associated below 19°C and negatively above 19°C. Very high population density was associated with lower uncertainty. CONCLUSIONS:PM2.5 prediction uncertainty varied across space; uncertainty was greater in areas with more pollution, fewer monitors, colder winters, more moderate summers, and lower population density. Subsequent monitoring and prediction model development should consider prioritizing these areas. KEYWORDS: Exposure assessment, particulate matter, spatial statistics

Interstate transport of ozone in eastern United States: An analysis of the impact of southeastern states’ emissions in 2017

Abstract To meet the requirements of the Clean Air Act's “good neighbor” provision, it is necessary to quantify the interstate transport of air pollution and determine if upwind states significantly contribute to noncompliance with the National Ambient Air Quality Standards (NAAQS) at downwind states. This study aims to estimate the contributions of ten southeastern states (Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee, Virginia and West Virginia) to ozone (O3), and identify significant associations with nonattainment or maintenance at monitors across the eastern United States (US) in 2017. Two widely used air quality models, the Comprehensive Air quality Model with extensions (CAMx) and the Community Multiscale Air Quality model (CMAQ), using different versions of the Carbon Bond (CB) chemical mechanism, were applied to predict 2017 O3 design values (DVFs) from 2011 O3 design values (DVCs) at the US Environmental Protection Agency's (EPA) Air Quality System (AQS) sites throughout the eastern US. Since 2017 design values are already published, the accuracy of the EPA-recommended modeling methodology for projecting current design values into the future only by changing the emissions was evaluated. The assumption that good model performance in the base year would result in accurate future year ozone projections was tested. In general, CAMx/CB6r2 simulated higher DVFs than CMAQ/CB05, with an average difference of 0.5 ppb. As a result, this study identified 24 sites in the eastern US as nonattainment (DVF ≥ 76 ppb) with CAMx/CB6r2 compared to only 16 sites with CMAQ/CB05. Using monitor cell relative response factors (RRFs) instead of 3×3 cell matrix maximum RRFs (the approach used in EPA's proposed Cross-State Air Pollution Rule (CSAPR) modeling) (EPA, 2015a), led to higher DVFs at some monitors and lower DVFs at others. Source apportionment analysis with the CAMx Anthropogenic Precursor Culpability Assessment (APCA) probing tool revealed that NOx emissions dominated over VOC emissions in contributing to O3 in downwind states. Contributions of total anthropogenic NOx emissions and contributions of Electric Generating Unit (EGU) NOx emissions from the southeastern states to O3 at nonattainment and maintenance sites were quantified separately using CAMx/APCA as well as CMAQ/zero-out simulations. Contributions obtained from CAMx/APCA were typically larger than the contributions obtained from CMAQ/zero-out. Therefore, a “significant contribution” determined by CAMx/APCA may be insignificant according to CMAQ/zero-out. “Significant contribution” was defined as an impact larger than 1% of the 2008 O3 NAAQS (i.e., ≥ 0.76 ppb). Alabama, Kentucky, Mississippi, Tennessee, Virginia and West Virginia were linked to 2, 3, 1, 1, 6 and 5 nonattainment sites with CAMx/APCA, while only Kentucky, Virginia and West Virginia were linked to 2, 3 and 2 nonattainment sites with CMAQ/zero-out. Additionally, for significant linkages, EGU NOx contributions were 10–55% of the total anthropogenic NOx contributions. The information produced in this study can be used by southeastern states to help develop “good neighbor” State Implementation Plans (SIPs).

Respiratory illness, hospital visits, and health costs: Is it air pollution or pollen?

BackgroundBoth air pollution and airborne pollen can cause respiratory health problems. Since both are often jointly present in ambient air, it is important to control for one while estimating the effect of the other when considering pollution-abating policies. To date only a limited number of studies have considered the health effects of both irritants jointly for a general population, and for a sufficiently long time period to allow for variation in seasonal concentrations of both components. The primary goal of this study is to determine the causal impact of fine particulate matter (PM2.5) on hospital visits and related treatment costs, while controlling for potentially confounding pollen effects. Our study area is the metropolitan hub of Reno/Sparks in Northern Nevada. MethodsTaking advantage of a rare sample of daily pollen counts over a prolonged period of time (2009–2015), we model the effects of PM2.5 and pollen on respiratory-related hospital admissions for the population at large, plus specific age groups. Pollen data are provided by a local allergy clinic. Data on PM2.5 and other air pollutants are obtained from the U.S. Environmental Protection Agency's air quality data web site. We collect daily meteorological data from the National Centers for Environmental Information's data repository. Data on hospital admissions are given by the Nevada Center for Surveys, Evaluations, and Statistics. Our econometric approach centers on a fully robust count data (Poisson) model, estimated via Quasi-Maximum Likelihood. ResultsWe find that for our sample PM2.5 effects are largely robust to the inclusion of both pollen counts and temporal indicators. In contrast, pollen effects vanish when time fixed effects are added, pointing at their correlation with unobserved temporal confounders. At the same time, model fit improves with the inclusion of temporal indicators. Based on our preferred specification, we find a significant PM2.5 effect of approximately 0.5% additional hospital visits per day due to a one μg/m3 increase in PM2.5. This translates into expected augmented treatment costs of $2700 per day for the same unit-change in PM2.5. These figures can mount quickly when more pronounced and/or longer episodes of particulate matter pollution are considered, perhaps due to wildfire smoke. For instance, the expected increase in patients and costs due to a month-long 10-unit-jump of PM2.5 over the long-run annual average would amount to an extra 70 patients and approximately $680,000 in additional treatment costs.

Abstract 280: Ambient Air Quality And Cerebrovascular Disease Outcomes Among Older Adults

Introduction: Air quality is a major environmental determinant of health, especially among adults living in areas with high levels of air pollution. Given our world’s aging population and increasingly dynamic climate, better understanding the relationship between ambient air quality and cerebrovascular disease outcomes among older adult is increasingly important. Objective: To document the relationship between air quality, as measured by particulate matter (PM 2.5) and cerebrovascular disease outcomes, measured by stroke death rates among older adults in the United States. Methods: The CDC Wonder database was used to retrieve Environmental Protection Agency's Air Quality System annual average ambient concentrations of PM2.5 and National Center for Health Statistics (NCHS) stroke death and total cardiovascular death rates by county across the United States. Spearman correlation was used to analyze the relationship between these variables. Results: Nationally, average ambient concentration of PM2.5 ranged from 3 to 19.7 μg/m3 with a mean of 9 μg/m3 ± 1.9 μg/m3 among 3,108 counties reporting data. Particular matter concentrations had a moderately positive relationship with stroke death rates (0.44, p<0.01) and total cardiovascular death rates (0.45, p<0.01) among adults over age 65. Conclusions: Our analysis of ambient air quality and cerebrovascular as well as total cardiovascular death rates demonstrates a moderate correlation between fine particulate matter and poor outcomes. Our data further demonstrates a number of US counties exceed World Health Organization fine particulate matter guidelines. These findings provide compelling evidence for both increased efforts towards improvement of air quality and mitigation strategies to prevent associated negative health outcomes.

Quantifying source apportionment for ambient haze: An image haze extraction approach with air quality monitoring data

The annual average concentration of fine particles (PM2.5) in Taiwan has been decreasing yearly. However, ambient haze has not abated and visibility is still poor. This study proposes a method for quantifying the source apportionment of ambient haze from various constituents, namely measured PM2.5, moisture, and secondary organic aerosols (SOA, represented by the sum of measured O3 and NO2 levels). This study's model-based demisting technology integrated image haze extracting technology with air quality monitoring data. The images for haze extraction were from the instant cameras of the Taiwan Environmental Protection Agency's air quality monitoring stations (AQMSs). Results indicate that haze constituents with the product of light extinction and scene depth have very high correlation (R2 ≥ 0.8452), which demonstrate that this quantification approach was successful. The contributions of ambient haze from various constituents had quarterly and regional variations in the eastern, northern, central, and southern regions of Taiwan, which are slightly, lowly, moderately, and heavily contaminated areas, respectively. Each area was assigned a selected representative AQMS to represent its ambient haze characteristics. Cases where the dominant contributors to haze were PM2.5, moisture, and SOA were studied, in addition to the event days of PM2.5 and ozone. We detail the limits of this approach, especially with regard to the use of images. This approach can help administrators understand the composition of ambient haze to generate effective haze strategies and policies. Residents can use this method to determine the health effects of daily haze.

Air Quality Index and air quality awareness among adults in the United States

BackgroundInformation about local air quality is reported across the United States using air quality alerts such as the Environmental Protection Agency's Air Quality Index. However, the role of such alerts in raising awareness of air quality is unknown. We conducted this study to evaluate associations between days with Air Quality Index ≥101, corresponding to a categorization of air quality as unhealthy for sensitive groups, unhealthy, very unhealthy, or hazardous, and air quality awareness among adults in the United States. MethodsData from 12,396 respondents to the 2016–2018 ConsumerStyles surveys were linked by geographic location and survey year to daily Air Quality Index data. We evaluated associations between the number of days in the past year with Air Quality Index ≥101 and responses to survey questions about awareness of air quality alerts, perception of air quality, and changes in behavior to reduce air pollution exposure using logistic regression. ResultsAwareness of air quality alerts (prevalence ratio [PR] = 1.23; 95% confidence interval [CI] = 1.15, 1.31), thinking/being informed air quality was bad (PR = 2.02; 95% CI = 1.81, 2.24), and changing behavior (PR = 2.27; 95% CI = 1.94, 2.67) were higher among respondents living in counties with ≥15 days with Air Quality Index ≥101 than those in counties with zero days in the past year with Air Quality Index ≥101. Each aspect of air quality awareness was higher among adults with than without asthma, but no differences were observed by heart disease status. Across quintiles of the number of days with Air Quality Index ≥101, air quality awareness increased among those with and without selected respiratory and cardiovascular diseases. ConclusionsAmong U.S. adults, air quality awareness increases with increasing days with alerts of unhealthy air. These findings improve our understanding of the extent to which air quality alerts prompt people to take actions to protect their health amidst poor air quality.

A case-crossover analysis of the relationship of air pollution with out-of-hospital sudden unexpected death in Wake County, North Carolina (2013–2015)

Out-of-hospital sudden unexpected deaths are non-accidental deaths that occur without obvious underlying causes and may account for 10% of natural deaths before age 65. Short-term exposure to ambient air pollution is associated with all-cause (non-accidental) and cause-specific (e.g., cardiovascular) mortality, and with immediate exposures often yielding the highest magnitude risk estimates. Few studies have focused on short-term exposure to air pollution and sudden unexpected deaths. Using the University of North Carolina Sudden Unexpected Death in North Carolina population, we examine associations between short-term criteria air pollutant exposures with sudden unexpected deaths using a time-stratified case-crossover design, with data on criteria air pollutants from the Environmental Protection Agency's Air Quality System. Odds ratios (OR) and 95% confidence intervals (CI) were estimated using conditional logistic regression with air pollutant exposures scaled to roughly inter-quartile ranges; models were adjusted for average temperature and relative humidity on event day and preceding 3 days. Potential for confounding by co-pollutants were examined in two pollutant models. ORs for PM2.5 at lag day 1 were elevated (adjusted OR for 5 μg/m3 increase: 1.17 (0.98, 1.40)), and were robust to co-pollutant adjustment. Elevated odds were observed for SO2 at lag day 0, and reduced odds for O3 at lag day 0; however, these associations were somewhat attenuated toward the null (SO2) or were not robust (O3) to co-pollutant adjustment. This analysis in a racially and socioeconomically diverse cohort, with a more inclusive definition of sudden unexpected death than is typically employed offers evidence that PM2.5 may be a clinically relevant trigger of sudden unexpected deaths in susceptible individuals.

Trends in Excess Morbidity and Mortality Associated with Air Pollution above American Thoracic Society–Recommended Standards, 2008–2017

Rationale: Air quality improvements are increasingly difficult to come by as modern pollution control technologies and measures have been widely implemented in the United States. Although there have been dramatic improvements in air quality over the last several decades, it is important to evaluate changes in the health impacts of air pollution for a more recent time period to better understand the current trajectory of air quality improvements. Objectives: To provide county-level estimates of annual air pollution-related health outcomes across the United States and to evaluate these trends from 2008 to 2017, presented as part of the annual American Thoracic Society (ATS)/Marron Institute "Health of the Air" report. Methods: Daily air pollution values were obtained from the U.S. Environmental Protection Agency's Air Quality System for monitors in the United States from 2008 to 2017. Concentration-response functions used in the ATS/Marron Institute "Health of the Air" report were applied to the pollution increments corresponding to differences between the rolling 3-year design values (reported as the third year) and ATS-recommended levels for annual particulate matter less than or equal to 2.5 μm in aerodynamic diameter (PM2.5; 11 μg/m3), short-term PM2.5 (25 μg/m3), and ozone (O3; 60 ppb). Health impacts were estimated at the county level in locations with valid monitor data. Results: Annual excess mortality in the United States due to air pollution levels greater than recommended by the ATS decreased from approximately 12,600 (95% confidence interval [CI], 5,470-21,040) in 2010 to 7,140 (95% CI, 2,290-14,040) in 2017. This improvement can be attributed almost entirely to reductions in PM2.5-related mortality, which decreased by approximately 60% (reduced from 8,330 to 3,260 annual deaths), whereas O3-related mortality remained largely unchanged, other than year-to-year variability, over the same time period (reduced from 4,270 to 3,880 annual deaths). Conclusions: Improvements in health impacts attributable to ambient PM2.5 concentrations have been observed across most regions of the United States over the last decade, although the rate of these improvements has leveled off in recent years. Despite two revisions of the National Ambient Air Quality Standards strengthening the standard for O3 in 2008 and 2015, there has not yet been a substantial improvement in the health impacts attributable to O3 during this time period. In many U.S. cities, an increase in the exposed population over the last decade has outpaced the improvements in ambient O3 concentrations, resulting in a net increase in O3-related health impacts over time.

The San Diego 2007 wildfires and Medi-Cal emergency department presentations, inpatient hospitalizations, and outpatient visits: An observational study of smoke exposure periods and a bidirectional case-crossover analysis.

BackgroundThe frequency and intensity of wildfires is anticipated to increase as climate change creates longer, warmer, and drier seasons. Particulate matter (PM) from wildfire smoke has been linked to adverse respiratory and possibly cardiovascular outcomes. Children, older adults, and persons with underlying respiratory and cardiovascular conditions are thought to be particularly vulnerable. This study examines the healthcare utilization of Medi-Cal recipients during the fall 2007 San Diego wildfires, which exposed millions of persons to wildfire smoke.Methods and findingsRespiratory and cardiovascular International Classification of Diseases (ICD)-9 codes were identified from Medi-Cal fee-for-service claims for emergency department presentations, inpatient hospitalizations, and outpatient visits. For a respiratory index and a cardiovascular index of key diagnoses and individual diagnoses, we calculated rate ratios (RRs) for the study population and different age groups for 3 consecutive 5-day exposure periods (P1 [October 22–26], P2 [October 27–31], and P3 [November 1–5]) versus pre-fire comparison periods matched on day of week (5-day periods starting 3, 4, 5, 6, 8, and 9 weeks before each exposed period). We used a bidirectional symmetric case-crossover design to examine emergency department presentations with any respiratory diagnosis and asthma specifically, with exposure based on modeled wildfire-derived fine inhalable particles that are 2.5 micrometers and smaller (PM2.5). We used conditional logistic regression to estimate odds ratios (ORs), adjusting for temperature and relative humidity, to assess same-day and moving averages. We also evaluated the United States Environmental Protection Agency (EPA)’s Air Quality Index (AQI) with this conditional logistic regression method. We identified 21,353 inpatient hospitalizations, 25,922 emergency department presentations, and 297,698 outpatient visits between August 16 and December 15, 2007. During P1, total emergency department presentations were no different than the reference periods (1,071 versus 1,062.2; RR 1.01; 95% confidence interval [CI] 0.95–1.08), those for respiratory diagnoses increased by 34% (288 versus 215.3; RR 1.34; 95% CI 1.18–1.52), and those for asthma increased by 112% (58 versus 27.3; RR 2.12; 95% CI 1.57–2.86). Some visit types continued to be elevated in later time frames, e.g., a 72% increase in outpatient visits for acute bronchitis in P2. Among children aged 0–4, emergency department presentations for respiratory diagnoses increased by 70% in P1, and very young children (0–1) experienced a 243% increase for asthma diagnoses. Associated with a 10 μg/m3 increase in PM2.5 (72-hour moving average), we found 1.08 (95% CI 1.04–1.13) times greater odds of an emergency department presentation for asthma. The AQI level “unhealthy for sensitive groups” was associated with significantly elevated odds of an emergency department presentation for respiratory conditions the day following exposure, compared to the AQI level “good” (OR 1.73; 95% CI 1.18–2.53). Study limitations include the use of patient home address to estimate exposures and demographic differences between Medi-Cal beneficiaries and the general population.ConclusionsRespiratory diagnoses, especially asthma, were elevated during the wildfires in the vulnerable population of Medi-Cal beneficiaries. Wildfire-related healthcare utilization appeared to persist beyond the initial high-exposure period. Increased adverse health events were apparent even at mildly degraded AQI levels. Significant increases in health events, especially for respiratory conditions and among young children, are expected based on projected climate scenarios of wildfire frequency in California and globally.

Rural and Urban Differences in Air Quality, 2008-2012, and Community Drinking Water Quality, 2010-2015 - United States.

Problem/ConditionThe places in which persons live, work, and play can contribute to the development of adverse health outcomes. Understanding the differences in risk factors in various environments can help to explain differences in the occurrence of these outcomes and can be used to develop public health programs, interventions, and policies. Efforts to characterize urban and rural differences have largely focused on social and demographic characteristics. A paucity of national standardized environmental data has hindered efforts to characterize differences in the physical aspects of urban and rural areas, such as air and water quality.Reporting Period2008–2012 for air quality and 2010–2015 for water quality.Description of SystemSince 2002, CDC’s National Environmental Public Health Tracking Program has collaborated with federal, state, and local partners to gather standardized environmental data by creating national data standards, collecting available data, and disseminating data to be used in developing public health actions. The National Environmental Public Health Tracking Network (i.e., the tracking network) collects data provided by national, state, and local partners and includes 21 health outcomes, exposures, and environmental hazards. To assess environmental factors that affect health, CDC analyzed three air-quality measures from the tracking network for all counties in the contiguous United States during 2008–2012 and one water-quality measure for 26 states during 2010–2015. The three air-quality measures include 1) total number of days with fine particulate matter (PM2.5) levels greater than the U.S. Environmental Protection Agency’s (EPA’s) National Ambient Air Quality Standards (NAAQS) for 24-hour average PM2.5 (PM2.5 days); 2) mean annual average ambient concentrations of PM2.5 in micrograms per cubic meter (mean PM2.5); and 3) total number of days with maximum 8-hour average ozone concentrations greater than the NAAQS (ozone days). The water-quality measure compared the annual mean concentration for a community water system (CWS) to the maximum contaminant level (MCL) defined by EPA for 10 contaminants: arsenic, atrazine, di(2-ethylhexyl) phthalate (DEHP), haloacetic acids (HAA5), nitrate, perchloroethene (PCE), radium, trichloroethene (TCE), total trihalomethanes (TTHM), and uranium. Findings are presented by urban-rural classification scheme: four metropolitan (large central metropolitan, large fringe metropolitan, medium metropolitan, and small metropolitan) and two nonmetropolitan (micropolitan and noncore) categories. Regression modeling was used to determine whether differences in the measures by urban-rural categories were statistically significant.ResultsPatterns for all three air-quality measures suggest that air quality improves as areas become more rural (or less urban). The mean total number of ozone days decreased from 47.54 days in large central metropolitan counties to 3.81 days in noncore counties, whereas the mean total number of PM2.5 days decreased from 11.21 in large central metropolitan counties to 0.95 in noncore counties. The mean average annual PM2.5 concentration decreased from 11.15 μg/m3 in large central metropolitan counties to 8.87 μg/m3 in noncore counties. Patterns for the water-quality measure suggest that water quality improves as areas become more urban (or less rural). Overall, 7% of CWSs reported at least one annual mean concentration greater than the MCL for all 10 contaminants combined. The percentage increased from 5.4% in large central metropolitan counties to 10% in noncore counties, a difference that was significant, adjusting for U.S. region, CWS size, water source, and potential spatial correlation. Similar results were found for two disinfection by-products, HAA5 and TTHM. Arsenic was the only other contaminant with a significant result. Medium metropolitan counties had 3.1% of CWSs reporting at least one annual mean greater than the MCL, compared with 2.4% in large central counties.InterpretationNoncore (rural) counties experienced fewer unhealthy air-quality days than large central metropolitan counties, likely because of fewer air pollution sources in the noncore counties. All categories of counties had a mean annual average PM2.5 concentration lower than the EPA standard. Among all CWSs analyzed, the number reporting one or more annual mean contaminant concentrations greater the MCL was small. The water-quality measure suggests that water quality worsens as counties become more rural, in regards to all contaminants combined and for the two disinfection by-products individually. Although significant differences were found for the water-quality measure, the odds ratios were very small, making it difficult to determine whether these differences have a meaningful effect on public health. These differences might be a result of variations in water treatment practices in rural versus urban counties.Public Health ActionUnderstanding the differences between rural and urban areas in air and water quality can help public health departments to identify, monitor, and prioritize potential environmental public health concerns and opportunities for action. These findings suggest a continued need to develop more geographically targeted, evidence-based interventions to prevent morbidity and mortality associated with poor air and water quality.

Anemia prevalence and hemoglobin levels are associated with long-term exposure to air pollution in an older population

BackgroundAnemia, a highly prevalent disorder in elderly populations, is associated with numerous adverse health outcomes, including increased mortality, impaired functional status and cognitive disorders. Approximately two-thirds of anemia in American elderly is caused by chronic inflammation or is unexplained. A potential contributing factor may include air pollution exposures, which have been shown to increase systemic inflammation and affect erythropoiesis. Few studies, however, have investigated the associations of air pollution on hemoglobin levels and anemia. MethodsWe used linear regression models and modified Poisson regression with robust error variance to examine the associations of particulate matter (PM2.5) and nitrogen dioxide (NO2) on hemoglobin concentrations and prevalence of anemia, respectively, among 4121 older Americans enrolled in the National Social Life, Health, and Aging Project. We estimated participant-specific exposures to PM2.5 using spatio-temporal models, and to NO2 using nearest measurements from Environmental Protection Agency's Air Quality System. Hemoglobin levels were measured for participants in each of two data collection waves from dried blood spots. Anemia was defined using World Health Organization hemoglobin-based criteria of <13 and <12g/dL for men and women, respectively. Models were adjusted for age, sex, smoking status, race, income, education, neighborhood socioeconomic status, region, urbanicity and medication use. Mediation by C-reactive protein (CRP), a marker of systemic inflammation, was also investigated. ResultsAn inter-quartile range (IQR, 3.9μg/m3) increase in the one-year moving average PM2.5 was positively associated with anemia prevalence (prevalence ratio, or PR 1.33, 95% CI: 1.23, 1.45) and decreases in average hemoglobin of 0.81g/dL (p<0.001). Similarly, an IQR (9.6ppb) increase in NO2 was associated with anemia prevalence (PR 1.43, 95% CI: 1.25, 1.63) and a decrease in average hemoglobin of 0.81g/dL (p<0.001). Strong dose-response relationships were identified for both pollutants. Mediation of the effect of PM2.5 by CRP was also identified (p=0.007). Conclusions/interpretationsAir pollution exposures were significantly associated with increased prevalence of anemia and decreased hemoglobin levels in a cohort of older Americans. If causal, these associations could indicate that chronic air pollution exposure is an important risk factor for anemia in older adults.

Long-term trends (1990–2014), health risks, and sources of atmospheric polycyclic aromatic hydrocarbons (PAHs) in the U.S.

Polycyclic aromatic hydrocarbons (PAHs) are a category of over 100 various chemicals released from numerous combustion sources. The ubiquity and toxicity of PAHs have posed high health risks on human populations. This study aims to examine the long-term trends of atmospheric PAHs at the national-level in the U.S., and evaluate their cancer risks. Daily concentrations of PAHs measured at 169 monitoring stations between 1990 and 2014 were obtained from the U.S. Environmental Protection Agency's Air Quality System. Temporal trends were examined using generalized linear model with generalized estimating equations. Random-effects analysis of variance was performed to explore variance between regions, sites, years, and months with a hierarchical structure. Source categories were identified using diagnostic ratios. National population level cancer risks were estimated using the relative potency factors and inhalation unit risk method. Ambient PAH concentrations displayed an overall downward trend (6–9% annual reduction) in urban areas, but not in rural areas. Seasonal and weekday/weekend effects were significant. Urban concentrations were twice of the rural level. The between-site variation outweighed the temporal variation, indicating large spatial heterogeneity. The predominant PAH sources were from traffic and non-traffic related fuel combustions with a dominant contribution from diesel emissions. The average excess lifetime cancer risk was estimated to be 9.3 ± 30.1 × 10−6 (GM: 4.2 × 10−6) from exposure to ten carcinogenic PAHs. This is the first comprehensive study of the spatiotemporal trends of ambient PAHs at the U.S. national level. The results indicate that future efforts aimed to reduce PAH exposures should focus on diesel emission controls and extending the geographic coverage of air monitoring.

The Air Quality, Characterization of Polycyclic Aromatic Hydrocarbon, Organic Carbon, and Diurnal Variation of Particulate Matter over Riyadh City

Concentrations of airborne particulate matter (PM10 & PM2.5) were measured over a period extended from January 2012 to October 2013 at two sites: a suburban area, Riyadh airport (AP) and an urban area, King Fahd road district (KF) (densely trafficked site) in Riyadh city, Saudi Arabia. The quality of ambient air using the U.S. Environmental Protection Agency (USEPA) Air Quality Index (AQI) was evaluated during this period. The average AQI values exceeded 100 on 6 months out of 11 in AP district. At KF district the condition was worse, and AQI values exceeded 100 on all months. This emphasizes the fact that PM concentrations over Riyadh can be regarded as a real environmental problem that could be a severe risk to quality of life and threaten human health. A higher-volume air sampler at the two sites was used to collect particulate matter (PM10 and PM2.5) for chemical analysis of the PM for PAHs and total organic carbon. At KF station the mean concentrations’ values of total PAHs in PM2.5 and PM10 were 4.89 ng/m3 and 12.96 ng/m3 respectively. At the AP station the corresponding values of total PAHs in PM2.5 and PM10 were 8.07 ng/m3 and 11.91 ng/m3 respectively. The PAHs did not exceed the air criteria of World Health Organization indicating the air pollution of PAHs in Riyadh District was not serious. As for the total organic carbon the results demonstrated that the concentration ranged from 0.211 to 0.506 g/kg at KF station and from 0.054 to 0.342 g/kg at AP station. On an annual basis, OC concentrations were two times higher for the city center site (KF) compared to the rural AP site. This can most likely be explained by increased emissions from higher traffic at KF site. The diurnal variability of PM was mainly associated with the severity of pollution.

Rethinking Judicial Review of Expert Agencies

The role of generalist courts in reviewing the work of expert agencies is generally portrayed as either an institutional necessity on the one hand or a Pandora's Box on the other. Courts are expected to ensure the accountability of agency actions through their legal oversight role, yet on matters of science policy they do not have the expertise of the agencies nor can they allow themselves to become amateur policymakers in the course of their review. Given these challenges, we set out to better understand what courts are doing in their review of agency science. We conducted a qualitative examination of the courts' review of challenges to agency scientific choices in the entire set of the Environmental Protection Agency's (EPA's) National Ambient Air Quality Standards (NAAQS). Our study revealed an increasingly rigorous and substantive engagement in the courts' review of scientific challenges to the EPA's NAAQS over time that tracked the Agency's own progress in developing rigorous analytical approaches. Our findings, albeit preliminary, suggest the emergence of a constructive partnership between the courts and agencies in science policy in NAAQS cases. In overseeing scientific challenges, the courts appear to serve as a necessary irritant, encouraging the agency to develop much stronger administrative governance and deliberative decisions on complex science-policy issues. Conversely, in developing stronger decision-making processes, the resulting agency efforts have a reciprocal, positive impact on the courts' own standards for review. The courts and agencies thus appear to work symbiotically through their mutual efforts on the establishment of rigorous analytical yardsticks to guide the decision process. While our findings may be limited to the NAAQS, which likely present a best case in administrative process, the findings may still offer a grounded, normative model for imagining a constructive and even vital role for generalist courts in technically complex areas of social decision making.IntroductionThe role of generalist courts reviewing the work of expert agencies in the United States is generally portrayed as an institutional necessity on the one hand and a Pandora's Box on the other. Louis Jaffe once wrote that [t]he availability of judicial review is the necessary condition, psychologically if not logically, of a system of administrative power which purports to be legitimate, or legally valid.1 But courts do not have the expertise of the agencies they are reviewing; they are legal institutions. They are also not political and need to restrain from becoming amateur policy makers in the course of their review. By granting courts authority to review science-based regulatory decisions, there is a risk they will unravel layers of careful scientific work as a result of their combined ignorance and judicial second-guessing.The promise and perils of judicial review of agency science has been a longstanding puzzle, tantalizing scholars and commentators alike.2 Judges have openly admitted they are engaging in experimental strategies in reviewing challenges to agency science,3 while simultaneously posing the overarching question: What does and should a reviewing court do when it considers a challenge to technical administrative decision-making?4 On the other hand, it is well known that a variety of evils-ranging from agency incompetence to special-interest capture to illicit political manipulations-have been concealed from view by agency computational models and scientific terminology.5 Indeed, agency technical rules may be the new playground for beltway politics, a proclivity ripe for judicial oversight.Over the last several decades, scholars have pored through court opinions in search of the answer to this puzzle of judicial review of agency science. But in this work, they have come up empty-handed, concluding that courts essentially pass agency scientific judgments through without engaging in the substance. …

Evaluation of light-duty vehicle mobile source regulations on ozone concentration trends in 2018 and 2030 in the western and eastern United States

To improve U.S. air quality, there are many regulations on-the-way (OTW) and on-the-books (OTB), including mobile source California Low Emission Vehicle third generation (LEV III) and federal Tier 3 standards. This study explores the effects of those regulations by using the U.S. Environmental Protection Agency's (EPA) Community Multiscale Air Quality (CMAQ) model for 8-hr ozone concentrations in the western and eastern United States in the years 2018 and 2030 during a month with typical high ozone concentrations, July. Alterations in pollutant emissions can be due to technological improvements, regulatory amendments, and changes in growth. In order to project emission rates for future years, the impacts of all of these factors were estimated. This study emphasizes the potential light-duty vehicle emission changes by year to predict ozone levels. The results of this study show that most areas have decreases in 8-hr ozone concentrations in the year 2030, although there are some areas with increased concentrations. Additionally, there are areas with 8-hr ozone concentrations greater than the current U.S. National Ambient Air Quality Standard level, which is 75 ppb. Implications: To improve U.S. air quality, many regulations are on the way and on the books, including mobile source California LEV III and federal Tier 3 standards. This study explores the effects of those regulations for 8-hr ozone concentrations in the western and eastern United States in the years 2018 and 2030. The results of this study show that most areas have decreases in 8-hr ozone concentrations in 2030, although there are some areas with increased concentrations. Additionally, there are areas with 8-hr ozone concentrations greater than the current U.S. National Ambient Air Quality Standard level.

Early prenatal exposure to air pollution and its associations with birth defects in a state‐wide birth cohort from North Carolina

Few studies have examined the potential relationship between air pollution and birth defects. The objective of this study was to investigate whether maternal exposure to particulate matter (PM2.5 ) and ozone (O3 ) during pregnancy is associated with birth defects among women living throughout North Carolina. Information on maternal and infant characteristics was obtained from North Carolina birth certificates and health service data (2003-2005) and linked with information on birth defects from the North Carolina Birth Defects Monitoring Program. The 24-hr PM2.5 and O3 concentrations were estimated using a hierarchical Bayesian model of air pollution generated by combining modeled air pollution predictions from the U.S. Environmental Protection Agency's Community Multi-Scale Air Quality model with air monitor data from the Environmental Protection Agency's Air Quality System. Maternal residence was geocoded and assigned pollutant concentrations averaged over weeks 3 to 8 of gestation. Binomial regression was performed and adjusted for potential confounders. No association was observed between either PM2.5 or O3 concentrations and most birth defects. Positive effect estimates were observed between air pollution and microtia/anotia and lower limb deficiency defects, but the 95% confidence intervals were wide and included the null. Overall, this study suggested a possible relationship between air pollution concentration during early pregnancy and certain birth defects (e.g., microtia/anotia, lower limb deficiency defects), although this study did not have the power to detect such an association. The risk for most birth defects does not appear to be affected by ambient air pollution.