PM2.5, Population Exposure and Economic Effects in Urban Agglomerations of China Using Ground-Based Monitoring Data
文献类型：期刊论文
| 作者 | Shen, Yonglin1; Yao, Ling2,3 |
| 刊名 | INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
 |
| 出版日期 | 2017-07-01 |
| 卷号 | 14期号:7页码:15 |
| 关键词 | fine particulate matter population exposure population-weighted mean urban agglomeration |
| ISSN号 | 1660-4601 |
| DOI | 10.3390/ijerph14070716 |
| 通讯作者 | Yao, Ling(yaoling@lreis.ac.cn) |
| 英文摘要 | This paper adopts the PM2.5 concentration data obtained from 1497 station-based monitoring sites, population and gross domestic product (GDP) census data, revealing population exposure and economic effects of PM2.5 in four typical urban agglomerations of China, i.e., Beijing-Tianjin-Hebei (BTH), the Yangtze River delta (YRD), the Pearl River delta (PRD), and Chengdu-Chongqing (CC). The Cokriging interpolation method was used to estimate the PM2.5 concentration from station-level to grid-level. Next, an evaluation was conducted mainly at the grid-level with a cell size of 1 x 1 km, assisted by the urban agglomeration scale. Criteria including the population-weighted mean, the cumulative percent distribution and the correlation coefficient were applied in our evaluation. The results showed that the spatial pattern of population exposure in BTH was consistent with that of PM2.5 concentration, as well as changes in elevation. The topography was also an important factor in the accumulation of PM2.5 in CC. Moreover, the most polluted urban agglomeration based on the population-weighted mean was BTH, while the least was PRD. In terms of the cumulative percent distribution, only 0.51% of the population who lived in the four urban agglomerations, and 2.33% of the GDP that was produced in the four urban agglomerations, were associated with an annual PM2.5 concentration smaller than the Chinese National Ambient Air Quality Standard of 35 mu g/m(3). This indicates that the majority of people live in the high air polluted areas, and economic development contributes to air pollution. Our results are supported by the high correlation between population exposure and the corresponding GDP in each urban agglomeration. |
| WOS关键词 | FINE PARTICULATE MATTER ; YANGTZE-RIVER DELTA ; CHEMICAL-COMPOSITION ; SOURCE APPORTIONMENT ; AIR-POLLUTION ; SICHUAN BASIN ; TERM TRENDS ; MEGA-CITY ; AEROSOL ; CITIES |
| 资助项目 | National Natural Science Foundation of China[41501459] ; National Marine Hazard Mitigation Service of China[2016AA053] ; Young Talents Training Fund of State Key Laboratory of Resources and Environment Information System of China[O8R8B6E0YA] |
| WOS研究方向 | Environmental Sciences & Ecology ; Public, Environmental & Occupational Health |
| 语种 | 英语 |
| WOS记录号 | WOS:000407370700048 |
| 出版者 | MDPI AG |
| 资助机构 | National Natural Science Foundation of China ; National Marine Hazard Mitigation Service of China ; Young Talents Training Fund of State Key Laboratory of Resources and Environment Information System of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/61322]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Yao, Ling |
| 作者单位 | 1.China Univ Geosci, Coll Informat Engn, Wuhan 430074, Hubei, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 3.Nanjing Normal Univ, Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China |
| 推荐引用方式 GB/T 7714 | Shen, Yonglin,Yao, Ling. PM2.5, Population Exposure and Economic Effects in Urban Agglomerations of China Using Ground-Based Monitoring Data[J]. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH,2017,14(7):15. |
| APA | Shen, Yonglin,&Yao, Ling.(2017).PM2.5, Population Exposure and Economic Effects in Urban Agglomerations of China Using Ground-Based Monitoring Data.INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH,14(7),15. |
| MLA | Shen, Yonglin,et al."PM2.5, Population Exposure and Economic Effects in Urban Agglomerations of China Using Ground-Based Monitoring Data".INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 14.7(2017):15. |
入库方式： OAI收割
来源：地理科学与资源研究所
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