High-Spatial-Resolution Population Exposure to PM2.5 Pollution Based on Multi-Satellite Retrievals: A Case Study of Seasonal Variation in the Yangtze River Delta, China in 2013
文献类型：期刊论文
| 作者 | Wang, Hong6; Li, Jiawen2,3; Gao, Zhiqiu6; Yim, Steve H. L.3,4; Shen, Huanfeng5; Ho, Hung Chak7; Li, Zhiyuan4; Zeng, Zhaoliang8; Liu, Chao6; Li, Yubin6 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2019-12-01 |
| 卷号 | 11期号:23页码:17 |
| 关键词 | population exposure PM2.5 satellite remote sensing random forest model population estimation Yangtze River Delta China |
| DOI | 10.3390/rs11232724 |
| 通讯作者 | Yang, Yuanjian(yyj1985@nuist.edu.cn) |
| 英文摘要 | 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 > 35 mu g/m(3) 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. |
| WOS关键词 | LONG-TERM EXPOSURE ; AMBIENT AIR-POLLUTION ; EASTERN CHINA ; SATELLITE-OBSERVATIONS ; PARTICULATE MATTER ; HAZE POLLUTION ; LUNG-CANCER ; HEALTH-RISK ; MORTALITY ; REGRESSION |
| 资助项目 | National Key Research and Development Program of China[2018YFC1506502] ; National Key Research and Development Program of China[2016YFC0203300] ; National Natural Science Foundation of China[41601550] ; State Key Laboratory of Loess and Quaternary Geology[SKLLQG1842] |
| WOS研究方向 | Remote Sensing |
| 语种 | 英语 |
| 出版者 | MDPI |
| WOS记录号 | WOS:000508382100005 |
| 资助机构 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; State Key Laboratory of Loess and Quaternary Geology |
| 源URL | [http://ir.ieecas.cn/handle/361006/13144]  |
| 专题 | 地球环境研究所_黄土与第四纪地质国家重点实验室（2010~） |
| 通讯作者 | Yang, Yuanjian |
| 作者单位 | 1.Chinese Acad Sci, Inst Earth Environm, State Key Lab Loess & Quaternary Geol, Xian 710061, Peoples R China 2.Nanjing Univ Informat Sci & Technol, Sch Geog, Nanjing 210044, Peoples R China 3.Chinese Univ Hong Kong, Dept Geog & Resource Management, Hong Kong 999077, Peoples R China 4.Chinese Univ Hong Kong, Inst Environm Energy & Sustainabil, Hong Kong 999077, Peoples R China 5.Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430072, Peoples R China 6.Nanjing Univ Informat Sci & Technol, Sch Atmospher Phys, Nanjing 210044, Peoples R China 7.Univ Hong Kong, Dept Urban Planning & Design, Hong Kong 999077, Peoples R China 8.Wuhan Univ, Chinese Antarct Ctr Surveying & Mapping, Wuhan 430072, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Hong,Li, Jiawen,Gao, Zhiqiu,et al. High-Spatial-Resolution Population Exposure to PM2.5 Pollution Based on Multi-Satellite Retrievals: A Case Study of Seasonal Variation in the Yangtze River Delta, China in 2013[J]. REMOTE SENSING,2019,11(23):17. |
| APA | Wang, Hong.,Li, Jiawen.,Gao, Zhiqiu.,Yim, Steve H. L..,Shen, Huanfeng.,...&Yang, Yuanjian.(2019).High-Spatial-Resolution Population Exposure to PM2.5 Pollution Based on Multi-Satellite Retrievals: A Case Study of Seasonal Variation in the Yangtze River Delta, China in 2013.REMOTE SENSING,11(23),17. |
| MLA | Wang, Hong,et al."High-Spatial-Resolution Population Exposure to PM2.5 Pollution Based on Multi-Satellite Retrievals: A Case Study of Seasonal Variation in the Yangtze River Delta, China in 2013".REMOTE SENSING 11.23(2019):17. |
入库方式： OAI收割
来源：地球环境研究所
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