IDENTIFYING THE DRIVING FACTORS OF POPULATION EXPOSURE TO FINE PARTICULATE MATTER (PM2.5) IN WUHAN, CHINA

Yang, C.; Zhan, Q.; Xiao, Y.; Liu, H.

Characterizing the spatiotemporal dynamics of population exposure to fine particulate matter (PM2.5) and the underlying external forcing can provide proactive implication for public health precautions. In this study, satellite-derived surface-level PM2.5 concentration as well as landscape factors and socioeconomic data are collected to identify the inter-annual variations and potential driving forces of population exposure to fine particulate matter (PM2.5) in Wuhan, China from 2000 to 2015. The fine-scale PM2.5 exposures in 2000, 2005, 2010 and 2015 were first estimated. Then the contributions of landscape factors and socioeconomic forcing are quantified by a machine learning method (i.e. Random Forest). The results revealed that the population in Wuhan faced increasing and more clustering PM2.5 threats from 2000 to 2010. Then a weakened and dispersed health threat of PM2.5 was witnessed in 2015. In general, the Gross Domestic Product (GDP) contributed the most to high-level PM2.5 exposure in the period of 2000–2015, i.e. variable importance (VIM) equalled to xxx. Among all the biophysical and landscape characteristics, the percentage of urban landscape (PLAND_UA) and urban area fraction were attributed the most to the PM2.5 population exposure. In parallel, precipitation played a crucial part in the mitigation of PM2.5 exposure. The identification of inter-annual dynamics of population PM2.5 exposure and the underlying forcing can facilitate the decision making and epidemiological precautions in the evaluation and alleviation of population exposure risks.

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Yang, C. / Zhan, Q. / Xiao, Y. / et al: IDENTIFYING THE DRIVING FACTORS OF POPULATION EXPOSURE TO FINE PARTICULATE MATTER (PM2.5) IN WUHAN, CHINA. 2020. Copernicus Publications.

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