Abstract
Air pollution measurements from monitoring stations are widely used in health assessment, and it is important to take into account the spatial representativeness (SR) of stations when quantifying population exposure to air pollution measured in these stations. Using high-quality satellite-derived PM2.5 data with 1-km spatial resolution over Yangtze River Delta (YRD) from 2016 to 2020, this study estimates SR of 213 PM2.5 monitoring stations, and these SR estimates are further used to calculate annual population-weighted mean (PWM) PM2.5 and deaths attributable to PM2.5 exposure for each city in YRD. Our results show that SR areas of 213 stations totally account for 32.33% of the area of YRD, and the SR size varies greatly with stations. Additionally, we find that the city-level PWM PM2.5 based on SR is nearly always larger than that using full coverage satellite-derived data. The difference tends to decrease as the population ratio of SR area increases. For the entire YRD, attributable deaths using PWM PM2.5 based on SR are 182,009 (95% CI: 136,632–225,081), and are comparable to the ones derived using full-coverage satellite-derived data. Nevertheless, the relative change in attributable deaths is more than 6% in some cities due to the low population ratio of SR (less than 20%), which suggests that more monitoring stations should be deployed in these cities for human assessment.
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Data availability
Satellite-derived PM2.5 data are available from the China-High-Air-Pollutants (CHAP) data set (https://weijing-rs.github.io/product.html). Population data were obtained from the Gridded Population of the World, Version 4 (available at https://sedac.ciesin.columbia.edu/data/collection/gpw-v4). Data on the age structure as well as the age specific and disease-specific mortality were obtained from the Global Burden of Disease Study 2019 dataset (https://vizhub.healthdata.org/gbd-compare).
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Funding
This work was supported by the National Key Research and Development Program of China (No. 2018YFC1507701), Jiangsu Provincial Double-Innovation Doctor Program (No. JSSCBS20211072), and Nantong University Scientific Research Foundation for the Introduced Talents (No. 135419629079).
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Bai, H., Yan, R., Gao, W. et al. Spatial representativeness of PM2.5 monitoring stations and its implication for health assessment. Air Qual Atmos Health 15, 1571–1581 (2022). https://doi.org/10.1007/s11869-022-01202-2
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DOI: https://doi.org/10.1007/s11869-022-01202-2