Spatiotemporal patterns of remotely sensed PM2.5 concentration in China from 1999 to 2011

被引:260
|
作者
Peng, Jian [1 ]
Chen, Sha [2 ]
Lu, Huiling [2 ]
Liu, Yanxu [1 ]
Wu, Jiansheng [2 ]
机构
[1] Peking Univ, Coll Urban & Environm Sci, Minist Educ, Lab Earth Surface Proc, Beijing 100871, Peoples R China
[2] Peking Univ, Shenzhen Grad Sch, Sch Urban Planning & Design, Key Lab Environm & Urban Sci, Shenzhen 518055, Peoples R China
基金
中国国家自然科学基金;
关键词
PM2.5; concentration; Spatiotemporal patterns; Standard deviation ellipse analysis; Zoning control; Health risk exposure; FINE PARTICULATE MATTER; AEROSOL OPTICAL DEPTH; LONG-TERM EXPOSURE; CHEMICAL-COMPOSITIONS; SEASONAL-VARIATIONS; AIR-POLLUTION; EXTINCTION COEFFICIENTS; URBAN GUANGZHOU; PARTICLES PM2.5; ION CHEMISTRY;
D O I
10.1016/j.rse.2015.12.008
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Air pollution in the form of fine particulate matter, or PM2.5, can decrease human life expectancy and increase the overall mortality rate. Based on a time series of remotely sensed PM2.5 concentrations, this study analyzed the spatiotemporal patterns of this crucial pollutant in China from 1999 to 2011 using trend analysis and standard deviation ellipse analysis, and carried out a health risk assessment of human exposure to PM2.5. The results showed that PM2.5 concentrations increased significantly from 1999 to 2011 in China, especially in the central and eastern parts of the country. The proportion of areas with PM2.5 concentrations higher than 35 mu g/m(3) increased year by year, and the areas with PM2.5 concentrations lower than the annual primary standard of 15 mu g/m(3) decreased continuously. The areas most polluted by PM2.5 were south of Hebei, north of Henan and west of Shandong provinces, with changes in the overall spatial distribution of the pollutant occurring faster along a south-north axis than along an east-west axis, and also faster along an east-south axis than along a west-north axis. Based on the PM2.5 concentrations in China from 1999 to 2011, a two-tier standard (level-I and level-II) was proposed for delineated areas to assist in nationwide air pollution control. It was also found that the proportion of the population exposed to PM2.5 concentrations greater than 35 mu g/m(3) increased year by year, and increased faster than the proportion of population exposed to PM2.5 concentrations in the range 15-35 mu g/m(3). The health risk in the central and eastern areas of the country was the highest. Based on these results, PM2.5 pollution poses an increasingly serious risk to human health across China and there is an immediate need to implement its regional control. In addition, more attention should be paid at the national scale in terms of pollution risk, rather than focusing narrowly on a city scale. (C). 2015 Elsevier Inc. All rights reserved.
引用
收藏
页码:109 / 121
页数:13
相关论文
共 50 条
  • [41] Exploring spatiotemporal patterns of PM2.5 in China based on ground-level observations for 190 cities
    Zhang, Haifeng
    Wang, Zhaohai
    Zhang, Wenzhong
    [J]. ENVIRONMENTAL POLLUTION, 2016, 216 : 559 - 567
  • [42] Spatiotemporal variations and influencing factors of PM2.5 concentrations in Beijing, China
    Zhang, Licheng
    An, Ji
    Liu, Mengyang
    Li, Zhiwei
    Liu, Yue
    Tao, Lixin
    Liu, Xiangtong
    Zhang, Feng
    Zheng, Deqiang
    Gao, Qi
    Guo, Xiuhua
    Luo, Yanxia
    [J]. ENVIRONMENTAL POLLUTION, 2020, 262
  • [43] Spatiotemporal Characterization of Ambient PM2.5 Concentrations in Shandong Province (China)
    Yang, Yong
    Christakos, George
    [J]. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2015, 49 (22) : 13431 - 13438
  • [44] Eigenvector Spatial Filtering Regression Modeling of Ground PM2.5 Concentrations Using Remotely Sensed Data
    Zhang, Jingyi
    Li, Bin
    Chen, Yumin
    Chen, Meijie
    Fang, Tao
    Liu, Yongfeng
    [J]. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2018, 15 (06)
  • [45] The changing PM2.5 dynamics of global megacities based on long-term remotely sensed observations
    Zhang, Lili
    Wilson, John P.
    MacDonald, Beau
    Zhang, Wenhao
    Yu, Tao
    [J]. ENVIRONMENT INTERNATIONAL, 2020, 142
  • [46] Impact of environmental absorption capacity on PM2.5 concentration in China
    Lin Li
    Jinhua Cheng
    Beidi Diao
    [J]. Chinese Journal of Population,Resources and Environment, 2022, (02) : 190 - 198
  • [47] PM2.5 concentration declining saves health expenditure in China
    Xie, Yang
    Zhong, Hua
    Weng, Zhixiong
    Guo, Xinbiao
    Kim, Satbyul Estella
    Wu, Shaowei
    [J]. FRONTIERS OF ENVIRONMENTAL SCIENCE & ENGINEERING, 2023, 17 (07)
  • [48] Scenario Analysis of PM2.5 Concentration Targets and Milestones in China
    He, Jin-Yu
    Yan, Li
    Wang, Yan-Chao
    Lei, Yu
    Wang, Xu-Ying
    [J]. Huanjing Kexue/Environmental Science, 2019, 40 (05): : 2036 - 2042
  • [49] Predicting gridded winter PM2.5 concentration in the east of China
    Yin, Zhicong
    Duan, Mingkeng
    Li, Yuyan
    Xu, Tianbao
    Wang, Huijun
    [J]. ATMOSPHERIC CHEMISTRY AND PHYSICS, 2022, 22 (17) : 11173 - 11185
  • [50] Spatial Patterns, Drivers and Heterogeneous Effects of PM2.5: Experience from China
    Cui, Xufeng
    Huang, Weige
    Deng, Wei
    Jia, Chengye
    [J]. POLISH JOURNAL OF ENVIRONMENTAL STUDIES, 2022, 31 (06): : 5633 - 5647