Dataset Information

Comparison of Ground-Based PM2.5 and PM10 Concentrations in China, India, and the U.S.

ABSTRACT: Urbanization and industrialization have spurred air pollution, making it a global problem. An understanding of the spatiotemporal characteristics of PM2.5 and PM10 concentrations (particulate matter with an aerodynamic diameter of less than 2.5 ?m and 10 ?m, respectively) is necessary to mitigate air pollution. We compared the characteristics of PM2.5 and PM10 concentrations and their trends of China, India, and the U.S. from 2014 to 2017. Particulate matter levels were lowest in the U.S., while China showed higher concentrations, and India showed the highest. Interestingly, significant declines in PM2.5 and PM10 concentrations were found in some of the most polluted regions in China as well as the U.S. No comparable decline was observed in India. A strong seasonal trend was observed in China and India, with the highest values occurring in winter and the lowest in summer. The opposite trend was noted for the U.S. PM2.5 was highly correlated with PM10 for both China and India, but the correlation was poor for the U.S. With regard to reducing particulate matter pollutant concentrations, developing countries can learn from the experiences of developed nations and benefit by establishing and implementing joint regional air pollution control programs.

SUBMITTER: Yang X

PROVIDER: S-EPMC6068888 | biostudies-other | 2018 Jul

REPOSITORIES: biostudies-other

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Comparison of Ground-Based PM2.5 and PM10 Concentrations in China, India, and the U.S.

Yang Xingchuan X Jiang Lei L Zhao Wenji W Xiong Qiulin Q Zhao Wenhui W Yan Xing X

International journal of environmental research and public health 20180702 7

Urbanization and industrialization have spurred air pollution, making it a global problem. An understanding of the spatiotemporal characteristics of PM2.5 and PM10 concentrations (particulate matter with an aerodynamic diameter of less than 2.5 μm and 10 μm, respectively) is necessary to mitigate air pollution. We compared the characteristics of PM2.5 and PM10 concentrations and their trends of China, India, and the U.S. from 2014 to 2017. Particulate ...[more]

PMID: 30004395

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Project description:Predicting long-term spatiotemporal characteristics of fine particulate matter (PM2.5) is important in China to understand historical levels of PM2.5, to support health effects research of both long-term and short-term exposures to PM2.5, and to evaluate the efficacy of air pollution control policies. Satellite-retrieved aerosol optical depth (AOD) provides a unique opportunity to characterize the long-term trends of ground-level PM2.5 at high spatial resolution. However, the missing rate of AOD in Northeastern China (NEC) is very high, especially in winter, and challenges the accuracy of long-term predictions of PM2.5 if left unresolved. Using random forest algorithms, this study developed a gap-filling approach combing satellite AOD, meteorological data, land use parameters, population and visibility in the NEC during 2005-2016. The model, including all predictors, combined with a model without AOD was able to fill the gap of PM2.5 predictions caused by missing AOD at 1-km resolution. The R2 (RMSE) of the full-coverage predictions was 0.81 (18.5 μg/m3) at the daily level. Gap-filled PM2.5 predictions on days with missing AOD reduced the relative prediction error from 28% to 2.5% in winter. The leave-one-year-out-cross-validation R2 (RMSE) of the full-coverage predictions was 0.65 (16.3 μg/m3) at the monthly level, indicating relatively high accuracy of predicted historical PM2.5 concentrations. Our results suggested that AOD helped increase the reliability of historical PM2.5 prediction when ground PM2.5 measurements were unavailable, even though predictions from the AOD model only accounted for approximate 37% of the whole dataset. Predicted PM2.5 level in NEC have increased since 2005, reached its peak during 2013-2015, then saw a major decline in 2016. Our high-resolution predictions also showed a south to north gradient and many pollution hot spots in the city clusters surrounding provincial capitals, as well as within large cities. Overall, by combining predictions from the AOD model with higher accuracy and predictions from the non-AOD model to achieve full coverage, our modeling approach could produce long-term, full-coverage historical PM2.5 levels in high-latitude areas in China, despite the widespread and persistent AOD missingness.

Project description:BackgroundAssociations between pediatric emergency department (ED) visits and ambient concentrations of particulate matter ? 2.5 ?m in diameter (PM2.5) have been reported in previous studies, although few were performed in nonmetropolitan areas.ObjectiveWe estimated associations between daily PM2.5 concentrations, using a two-stage model that included land use parameters and satellite aerosol optical depth measurements at 1-km resolution, and ED visits for six pediatric conditions in the U.S. state of Georgia by urbanicity classification.MethodsWe obtained pediatric ED visits geocoded to residential ZIP codes for visits with nonmissing PM2.5 estimates and admission dates during 1 January 2002-30 June 2010 for 2- to 18-year-olds for asthma or wheeze (n = 189,816), and for 0- to 18-year-olds for bronchitis (n = 76,243), chronic sinusitis (n = 15,745), otitis media (n = 237,833), pneumonia (n = 52,946), and upper respiratory infections (n = 414,556). Daily ZIP code-level estimates of 24-hr average PM2.5 were calculated by averaging concentrations within ZIP code boundaries. We used time-stratified case-crossover models stratified on ZIP code, year, and month to estimate odds ratios (ORs) between ED visits and same-day and previous-day PM2.5 concentrations at the ZIP code level, and we investigated effect modification by county-level urbanicity.ResultsA 10-?g/m3 increase in same-day PM2.5 concentrations was associated with ED visits for asthma or wheeze (OR = 1.013; 95% CI: 1.003, 1.023) and upper respiratory infections (OR = 1.015; 95% CI: 1.008, 1.022); associations with previous-day PM2.5 concentrations were lower. Differences in the association estimates across levels of urbanicity were not statistically significant.ConclusionPediatric ED visits for asthma or wheeze and for upper respiratory infections were associated with PM2.5 concentrations in Georgia.CitationStrickland MJ, Hao H, Hu X, Chang HH, Darrow LA, Liu Y. 2016. Pediatric emergency visits and short-term changes in PM2.5 concentrations in the U.S. state of Georgia. Environ Health Perspect 124:690-696;?http://dx.doi.org/10.1289/ehp.1509856.

Dataset Information

Comparison of Ground-Based PM2.5 and PM10 Concentrations in China, India, and the U.S.

Publications

Comparison of Ground-Based PM<sub>2.5</sub> and PM<sub>10</sub> Concentrations in China, India, and the U.S.

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