Increasing co-occurrence of fine particulate matter and ground-level ozone extremes in the western United States.
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ABSTRACT:
SUBMITTER: Kalashnikov DA
PROVIDER: S-EPMC8730618 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Heat waves and air pollution episodes pose a serious threat to human health and may worsen under future climate change. In this paper, we use 15 years (1999-2013) of commensurately gridded (1° x 1°) surface observations of extended summer (April-September) surface ozone (O3), fine particulate matter (PM2.5), and maximum temperature (TX) over the eastern United States and Canada to construct a climatology of the coincidence, overlap, and lag in space and time of their extremes. Extremes of each quantity are defined climatologically at each grid cell as the 50 d with the highest values in three 5-y windows (∼95th percentile). Any two extremes occur on the same day in the same grid cell more than 50% of the time in the northeastern United States, but on a domain average, co-occurrence is approximately 30%. Although not exactly co-occurring, many of these extremes show connectedness with consistent offsets in space and in time, which often defy traditional mechanistic explanations. All three extremes occur primarily in large-scale, multiday, spatially connected episodes with scales of >1,000 km and clearly coincide with large-scale meteorological features. The largest, longest-lived episodes have the highest incidence of co-occurrence and contain extreme values well above their local 95th percentile threshold, by +7 ppb for O3, +6 µg m-3 for PM2.5, and +1.7 °C for TX. Our results demonstrate the need to evaluate these extremes as synergistic costressors to accurately quantify their impacts on human health.
| S-EPMC5358352 | biostudies-literature
Project description:Short-term effects of air pollution exposure on respiratory disease mortality are well established. However, few studies have examined the effects of long-term exposure, and among those that have, results are inconsistent.To evaluate long-term association between ambient ozone, fine particulate matter (PM2.5, particles with an aerodynamic diameter of 2.5 ?m or less), and chronic lower respiratory disease (CLRD) mortality in the contiguous United States.We fit Bayesian hierarchical spatial Poisson models, adjusting for five county-level covariates (percentage of adults aged ?65 years, poverty, lifetime smoking, obesity, and temperature), with random effects at state and county levels to account for spatial heterogeneity and spatial dependence.We derived county-level average daily concentration levels for ambient ozone and PM2.5 for 2001-2008 from the U.S. Environmental Protection Agency's down-scaled estimates and obtained 2007-2008 CLRD deaths from the National Center for Health Statistics. Exposure to ambient ozone was associated with an increased rate of CLRD deaths, with a rate ratio of 1.05 (95% credible interval, 1.01-1.09) per 5-ppb increase in ozone; the association between ambient PM2.5 and CLRD mortality was positive but statistically insignificant (rate ratio, 1.07; 95% credible interval, 0.99-1.14).This study links air pollution exposure data with CLRD mortality for all 3,109 contiguous U.S. counties. Ambient ozone may be associated with an increased rate of death from CLRD in the contiguous United States. Although we adjusted for selected county-level covariates and unobserved influences through Bayesian hierarchical spatial modeling, the possibility of ecologic bias remains.
| S-EPMC4937454 | biostudies-literature
Project description:Exposures to ambient particulate matter (PM) are associated with increased morbidity and mortality. PM2.5 (<2.5 μm) and ozone exposures have been shown to associate with carotid intima media thickness in humans. Animal studies support a causal relationship between air pollution and atherosclerosis and identified adverse PM effects on HDL functionality. We aimed to determine whether brief exposures to PM2.5 and/or ozone could induce effects on HDL anti-oxidant and anti-inflammatory capacity in humans.Subjects were exposed to fine concentrated ambient fine particles (CAP) with PM2.5 targeted at 150 μg/m(3), ozone targeted at 240 μg/m(3) (120 ppb), PM2.5 plus ozone targeted at similar concentrations, and filtered air (FA) for 2 h, on 4 different occasions, at least two weeks apart, in a randomized, crossover study. Blood was obtained before exposures (baseline), 1 h after and 20 h after exposures. Plasma HDL anti-oxidant/anti-inflammatory capacity and paraoxonase activity were determined. HDL anti-oxidant/anti-inflammatory capacity was assessed by a cell-free fluorescent assay and expressed in units of a HDL oxidant index (HOI). Changes in HOI (ΔHOI) were calculated as the difference in HOI from baseline to 1 h after or 20 h after exposures.There was a trend towards bigger ΔHOI between PM2.5 and FA 1 h after exposures (p = 0.18) but not 20 h after. This trend became significant (p <0.05) when baseline HOI was lower (<1.5 or <2.0), indicating decreased HDL anti-oxidant/anti-inflammatory capacity shortly after the exposures. There were no significant effects of ozone alone or in combination with PM2.5 on the change in HOI at both time points. The change in HOI due to PM2.5 showed a positive trend with particle mass concentration (p = 0.078) and significantly associated with the slope of systolic blood pressure during exposures (p = 0.005).Brief exposures to concentrated PM2.5 elicited swift effects on HDL anti-oxidant/anti-inflammatory functionality, which could indicate a potential mechanism for how particulate air pollution induces harmful cardiovascular effects.
| S-EPMC4879751 | biostudies-other
Project description:We developed daily maps of surface fine particulate matter (PM2.5) for the western United States. We used geographically weighted regression fit to air quality station observations with Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) data, and meteorological data to produce daily 1-kilometer resolution PM2.5 concentration estimates from 2003-2020. To account for impacts of stagnant air and inversions, we included estimates of inversion strength based on meteorological conditions, and inversion potential based on human activities and local topography. Model accuracy based on cross-validation was R2 = 0.66. AOD data improve the model in summer and fall during periods of high wildfire activity while the stagnation terms capture the spatial and temporal dynamics of PM2.5 in mountain valleys, particularly during winter. These data can be used to explore exposure and health outcome impacts of PM2.5 across spatiotemporal domains particularly in the intermountain western United States where measurements from monitoring station data are sparse. Furthermore, these data may facilitate analyses of inversion impacts and local topography on exposure and health outcome studies.
| S-EPMC9345996 | biostudies-literature
Project description:BackgroundEpidemiological studies report fairly consistent associations between various air pollution metrics and autism spectrum disorder (ASD), with some elevated risks reported for different prenatal and postnatal periods.ObjectivesTo examine associations between ASD and ambient fine particulate matter (PM2.5) and ozone concentrations during the prenatal period through the second year of life in a case-control study.MethodsASD cases (n = 428) diagnosed at Cincinnati Children's Hospital Medical Center were frequency matched (15:1) to 6420 controls from Ohio birth records. We assigned daily PM2.5 and ozone estimates for 2005-2012 from US EPA's Fused Air Quality Surface Using Downscaling model to each participant for each day based on the mother's census tract of residence at birth. We calculated adjusted odds ratios (aORs) using logistic regression across continuous and categorical exposure window averages (trimesters, first and second postnatal years, and cumulative measure), adjusting for maternal- and birth-related confounders, both air pollutants, and multiple temporal exposure windows.ResultsWe detected elevated aORs for PM2.5 during the 2nd trimester, 1st year of life, and a cumulative period from pregnancy through the 2nd year (aOR ranges across categories: 1.41-1.44, 1.54-1.84, and 1.41-1.52 respectively), and for ozone in the 2nd year of life (aOR range across categories: 1.29-1.42). Per each change in IQR, we observed elevated aORs for ozone in the 3rd trimester, 1st and 2nd years of life, and the cumulative period (aOR range: 1.19-1.27) and for PM2.5 in the 2nd trimester, 1st year of life, and the cumulative period (aOR range: 1.11-1.17).DiscussionWe saw limited evidence of linear exposure-response relationships for ASD with increasing air pollution, but the elevated aORs detected for PM2.5 in upper exposure categories and per IQR unit increases were similar in magnitude to those reported in previous studies, especially for postnatal exposures.
| S-EPMC7232936 | biostudies-literature
Project description:The Community Multi-Scale Air Quality (CMAQ) model was applied to evaluate the air quality in the coastal city of Kannur, India, during the 2020 COVID-19 lockdown. From the Pre1 (March 1-24, 2020) period to the Lock (March 25-April 19, 2020) and Tri (April 20-May 9, 2020) periods, the Kerala state government gradually imposed a strict lockdown policy. Both the simulations and observations showed a decline in the PM2.5 concentrations and an enhancement in the O3 concentrations during the Lock and Tri periods compared with that in the Pre1 period. Integrated process rate (IPR) analysis was employed to isolate the contributions of the individual atmospheric processes. The results revealed that the vertical transport from the upper layers dominated the surface O3 formation, comprising 89.4%, 83.1%, and 88.9% of the O3 sources during the Pre1, Lock, and Tri periods, respectively. Photochemistry contributed negatively to the O3 concentrations at the surface layer. Compared with the Pre1 period, the O3 enhancement during the Lock period was primarily attributable to the lower negative contribution of photochemistry and the lower O3 removal rate by horizontal transport. During the Tri period, a slower consumption of O3 by gas-phase chemistry and a stronger vertical import from the upper layers to the surface accounted for the increase in O3. Emission and aerosol processes constituted the major positive contributions to the net surface PM2.5, accounting for a total of 48.7%, 38.4%, and 42.5% of PM2.5 sources during the Pre1, Lock, and Tri periods, respectively. The decreases in the PM2.5 concentrations during the Lock and Tri periods were primarily explained by the weaker PM2.5 production from emission and aerosol processes. The increased vertical transport rate of PM2.5 from the surface layer to the upper layers was also a reason for the decrease in the PM2.5 during the Lock periods.
| S-EPMC9109815 | biostudies-literature
Project description:Urban air pollution is a complex problem, which requires a multi-pronged approach to understand its dynamics. In the current study, various aspects of air pollution over Bengaluru city were studied utilizing simultaneous reference-grade measurements (during the period July 2019 to June 2020) of fine particulate matter mass concentration (PM2.5), aerosol black carbon mass concentrations (BC), and surface ozone (O3) concentrations. The study period mean PM2.5, BC, and O3 were observed to be 26.8 ± 11.5 µg m-3, 5.6 ± 2.8 µg m-3, and 25.5 ± 12.4 ppb, respectively. Statistical methods such as principal component analysis, moving average subtraction method, conditional bivariate probability function, and concentration weighted trajectory analysis were performed to understand the dynamics of air pollution over Bengaluru and its long-range transportation pathways. Some of the major findings from the statistical analyses include (i) contrasting association in BC versus O3 and PM2.5 versus O3; (ii) around one-fourth of the observed receptor site BC was contributed by local sources/emissions; and (iii) the source locations potentially contributing to BC and PM2.5 were spatially different. In Bengaluru, long-term exposure to PM2.5 resulted in around 3413, 3393, 1016, and 147 attributable deaths for the health endpoints chronic obstructive pulmonary disorder, ischemic heart disease, stroke, and lung cancer, respectively. Long-term exposure to O3 resulted in around 155 attributable deaths for respiratory diseases, as estimated by the AirQ + model. Finally, the limitations of the study in terms of data availability and analysis have been detailed.
| S-EPMC8863905 | biostudies-literature
Project description:Future fine particulate matter (PM2.5) concentrations and resulting health impacts will be largely determined by factors such as energy use, fuel choices, emission controls, state and national policies, and demographcs. In this study, a human-earth system model is used to estimate PM2.5 mortality costs (PMMC) due to air pollutant emissions from each US state over the period 2015 to 2050, considering current major air quality and energy regulations. Contributions of various socioeconomic and energy factors to PMMC are quantified using the Logarithmic Mean Divisia Index. National PMMC are estimated to decrease 25% from 2015 to 2050, driven by decreases in energy intensity and PMMC per unit consumption of electric sector coal and transportation liquids. These factors together contribute 68% of the decrease, primarily from technology improvements and air quality regulations. States with greater population and economic growth, but with fewer clean energy resources, are more likely to face significant challenges in reducing future PMMC from their emissions. In contrast, states with larger projected decreases in PMMC have smaller increases in population and per capita GDP, and greater decreases in electric sector coal share and PMMC per unit fuel consumption.
| S-EPMC7055525 | biostudies-literature
Project description:People of color disproportionately bear the health impacts of air pollution, making air quality a critical environmental justice issue. However, quantitative analysis of the disproportionate impacts of emissions is rarely done due to a lack of suitable models. Our work develops a high-resolution reduced-complexity model (EASIUR-HR) to evaluate the disproportionate impacts of ground-level primary PM2.5 emissions. Our approach combines a Gaussian plume model for near-source impacts of primary PM2.5 with a previously developed reduced-complexity model, EASIUR, to predict primary PM2.5 concentrations at a spatial resolution of 300 m across the contiguous United States. We find that low-resolution models underpredict important local spatial variation of air pollution exposure to primary PM2.5 emissions, potentially underestimating the contribution of these emissions to national inequality in PM2.5 exposure by more than a factor of 2. We apply EASIUR-HR to analyze the impacts of vehicle electrification on exposure disparities. While such a policy has small aggregate air quality impacts nationally, it reduces exposure disparity for race/ethnic minorities. Our high-resolution RCM for primary PM2.5 emissions (EASIUR-HR) is a new, publicly available tool to assess inequality in air pollution exposure across the United States.
| S-EPMC9996819 | biostudies-literature
Project description:BackgroundPolycystic ovary morphology (PCOM) is an ultrasonographic finding that can be present in women with ovulatory disorder and oligomenorrhea due to hypothalamic, pituitary, and ovarian dysfunction. While air pollution has emerged as a possible disrupter of hormone homeostasis, limited research has been conducted on the association between air pollution and PCOM.MethodsWe conducted a longitudinal cohort study using electronic medical records data of 5,492 women with normal ovaries at the first ultrasound that underwent a repeated pelvic ultrasound examination during the study period (2004-2016) at Boston Medical Center. Machine learning text algorithms classified PCOM by ultrasound. We used geocoded home address to determine the ambient annual average PM2.5 exposures and categorized into tertiles of exposure. We used Cox Proportional Hazards models on complete data (n = 3,994), adjusting for covariates, and additionally stratified by race/ethnicity and body mass index (BMI).ResultsCumulative exposure to PM2.5 during the study ranged from 4.9 to 17.5 µg/m3 (mean = 10.0 μg/m3). On average, women were 31 years old and 58% were Black/African American. Hazard ratios and 95% confidence intervals (CI) comparing the second and third PM2.5 exposure tertile vs. the reference tertile were 1.12 (0.88, 1.43) and 0.89 (0.62, 1.28), respectively. No appreciable differences were observed across race/ethnicity. Among women with BMI ≥ 30 kg/m2, we observed weak inverse associations with PCOM for the second (HR: 0.93, 95% CI: 0.66, 1.33) and third tertiles (HR: 0.89, 95% CI: 0.50, 1.57).ConclusionsIn this study of reproductive-aged women, we observed little association between PM2.5 concentrations and PCOM incidence. No dose response relationships were observed nor were estimates appreciably different across race/ethnicity within this clinically sourced cohort.
| S-EPMC8855564 | biostudies-literature