Abstract

To assess the health risk of PM2.5, it is necessary to accurately estimate the actual exposure level of the population to PM2.5. However, the spatial distribution of PM2.5 may be inconsistent with that of the population, making it necessary for a high-spatial-resolution and refined assessment of the population exposure to air pollution. This study takes the Yangtze River Delta (YRD) Region as an example since it has a high-density population and a high pollution level. The brightness reflectance of night-time light, and MODIS-based (Moderate Resolution Imaging Spectroradiometer) vegetation index, elevation, and slope information are used as independent variables to construct a random-forest (RF) model for the estimation of the population spatial distribution, before any combination with the PM2.5 data retrieved from MODIS. This enables assessment of the population exposure to PM2.5 (i.e., intensity of population exposure to PM2.5 and population-weighted PM2.5 concentration) at a 3-km resolution, using the year 2013 as an example. Results show that the variance explained for the RF-model-estimated population density reaches over 80%, while the estimated errors in half of counties are < 20%, indicating the high accuracy of the estimated population. The spatial distribution of population exposure to PM2.5 exhibits an obvious urban–suburban–rural difference consistent with the population distribution but inconsistent with the PM2.5 concentration. High and low PM2.5 concentrations are mainly distributed in the northern and southern YRD Region, respectively, with the mean proportions of the population exposed to PM2.5 concentrations > 35μg/m3 close to 100% in all four seasons. A high-level population exposure to PM2.5 is mainly found in Shanghai, most of the Jiangsu Province, the central Anhui Province, and some coastal cities of the Zhejiang Province. The highest risk of population exposure to PM2.5 occurs in winter, followed by spring and autumn, and the lowest in summer, consistent with the PM2.5 seasonal variation. Seasonal-averaged population-weighted PM2.5 concentrations are different from PM2.5 concentrations in the region, which are closely related to the urban-exposed population density and pollution levels. This work provides a novel assessment of the proposed population-density exposure to PM2.5 by using multi-satellite retrievals to determine the high-spatial-resolution risk of air pollution and detailed regional differences in the population exposure to PM2.5.

Highlights

  • Particulate matter of aerodynamic diameter ≤ 2.5 μm (PM2.5) is extremely harmful to public health due to the small particle size, and its physical properties and complex chemical composition [1,2,3,4]

  • Seasonal-averaged population-weighted PM2.5 concentrations are different from PM2.5 concentrations in the region, which are closely related to the urban-exposed population density and pollution levels

  • In January and December 2013, extensive and frequent haze events occurred in eastern China, where the daily-averaged PM2.5 exceeded 150 μg/m3 and reached > 500 μg/m3, resulting in significant economic losses and serious impacts on public health [15,16]

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Summary

Introduction

Particulate matter of aerodynamic diameter ≤ 2.5 μm (PM2.5) is extremely harmful to public health due to the small particle size, and its physical properties and complex chemical composition [1,2,3,4]. Seasonal-averaged population-weighted PM2.5 concentrations are different from PM2.5 concentrations in the region, which are closely related to the urban-exposed population density and pollution levels.

Results
Conclusion
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