Spatial-temporal patterns of PM2.5 concentrations for 338 Chinese cities

被引:159
作者
Ye, Wei-Feng [1 ]
Ma, Zhong-Yu [1 ,2 ]
Ha, Xiu-Zhen [3 ]
机构
[1] Renmin Univ China, Sch Environm & Nat Resources, Beijing 100872, Peoples R China
[2] State Informat Ctr, Beijing 100045, Peoples R China
[3] Renmin Univ China, Sch Econ, Beijing 100872, Peoples R China
基金
国家重点研发计划;
关键词
PM(2.5 )concentrations; Spatial-temporal patterns; Spatial autocorrelation; China; PARTICULATE MATTER PM2.5; AIR-POLLUTION; CHEMICAL-COMPOSITION; SOURCE APPORTIONMENT; URBAN; PM10; HAZE; ASSOCIATION; EXPOSURE; EPISODES;
D O I
10.1016/j.scitotenv.2018.03.057
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 has become a major concern in cities worldwide. The present study explores the spatial-temporal patterns of PM2.5 (partides with an aerodynamic diameters <= 2.5 mu m) and the variation in the attainment rate (the number of cities attaining the national PM2.5 standard each day) at different time-scales based on PM(2.5 )concentrations. One-year of monitoring was conducted in 338 cities at or above the prefectural level in China. Spatial hot spots of PM2.5 were analyzed using exploratory spatial data analysis. Meteorological factors affecting PM2.5 distributions were analyzed. The results indicate the following: (1) Diurnal variations of PM2.5 exhibited a Wshaped trend, with the lowest value observed in the afternoon. The peak concentrations occurred after the ends of the morning and evening rush hours. (2) Out of 338 cities, 235 exceeded the national annual PM2.5 standards (535 mu g/m(3)), with slightly polluted (75-115 mu g/m(3)) cities occupying the greatest proportion. (3) The attainment rate showed an inverted U-shape, while there was a U-shaped pattern observed for daily and monthly mean PM2.5. (4) The spatial distribution of PM2.5 concentrations varied greatly, PM2.5 has significant spatial autocorrelation and clustering characteristics. Hot spots for pollution were mainly concentrated in the Beijing-Tianjin-Hebei area and neighboring regions, in part because of the large amount of smoke and dust emissions in this region. However, weather factors (temperature, humidity, and wind speed) also had an effect. In addition, southwest Xinjiang experienced heavy PM2.5 pollution that was mainly caused by the frequent occurrence of sandstorms, although no significant relationship was observed between PM2.5 and meteorological elements in this region. (C) 2018 Elsevier B.V. All tights reserved.
引用
收藏
页码:524 / 533
页数:10
相关论文
共 54 条
  • [11] THE ANALYSIS OF SPATIAL ASSOCIATION BY USE OF DISTANCE STATISTICS
    GETIS, A
    ORD, JK
    [J]. GEOGRAPHICAL ANALYSIS, 1992, 24 (03) : 189 - 206
  • [12] The association between fine particulate air pollution and hospital emergency room visits for cardiovascular diseases in Beijing, China
    Guo, Yuming
    Jia, Yuping
    Pan, Xiaochuan
    Liu, Liqun
    Wichmann, H. -Erich
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2009, 407 (17) : 4826 - 4830
  • [13] Haining R., 1990, SPATIAL DATA ANAL SO
  • [14] Prospective evaluation of respiratory health benefits from reduced exposure to airborne particulate matter
    Hao, Yanhui
    Zhang, Guanghui
    Han, Bin
    Xu, Xiaowen
    Feng, Nannan
    Li, Yong
    Wang, Wei
    Kan, Haidong
    Bai, Zhipeng
    Zhu, Yiliang
    Au, William
    Xia, Zhao-lin
    [J]. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH, 2017, 27 (02) : 126 - 135
  • [15] Spatial and temporal variability of PM2.5 and PM10 over the North China Plain and the Yangtze River Delta, China
    Hu, Jianlin
    Wang, Yungang
    Ying, Qi
    Zhang, Hongliang
    [J]. ATMOSPHERIC ENVIRONMENT, 2014, 95 : 598 - 609
  • [16] Spatial and temporal characteristics of particulate matter in Beijing, China using the Empirical Mode Decomposition method
    Hu, Maogui
    Jia, Lin
    Wang, Jinfeng
    Pan, Yuepeng
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2013, 458 : 70 - 80
  • [17] High secondary aerosol contribution to particulate pollution during haze events in China
    Huang, Ru-Jin
    Zhang, Yanlin
    Bozzetti, Carlo
    Ho, Kin-Fai
    Cao, Jun-Ji
    Han, Yongming
    Daellenbach, Kaspar R.
    Slowik, Jay G.
    Platt, Stephen M.
    Canonaco, Francesco
    Zotter, Peter
    Wolf, Robert
    Pieber, Simone M.
    Bruns, Emily A.
    Crippa, Monica
    Ciarelli, Giancarlo
    Piazzalunga, Andrea
    Schwikowski, Margit
    Abbaszade, Guelcin
    Schnelle-Kreis, Juergen
    Zimmermann, Ralf
    An, Zhisheng
    Szidat, Soenke
    Baltensperger, Urs
    El Haddad, Imad
    Prevot, Andre S. H.
    [J]. NATURE, 2014, 514 (7521) : 218 - 222
  • [18] Analysis of heavy pollution episodes in selected cities of northern China
    Ji, Dongsheng
    Wang, Yuesi
    Wang, Lili
    Chen, Liangfu
    Hu, Bo
    Tang, Guiqian
    Xin, Jinyuan
    Song, Tao
    Wen, Tianxue
    Sun, Yang
    Pan, Yuepeng
    Liu, Zirui
    [J]. ATMOSPHERIC ENVIRONMENT, 2012, 50 : 338 - 348
  • [19] Spatio-temporal variations of PM2.5 emission in China from 2005 to 2014
    Jin, Qiang
    Fang, Xinyue
    Wen, Bo
    Shan, Aidang
    [J]. CHEMOSPHERE, 2017, 183 : 429 - 436
  • [20] Trends of PM2.5 and Chemical Composition in Beijing, 2000-2015
    Lang, Jianlei
    Zhang, Yanyun
    Zhou, Ying
    Cheng, Shuiyuan
    Chen, Dongsheng
    Guo, Xiurui
    Chen, Sha
    Li, Xiaoxin
    Xing, Xiaofan
    Wang, Haiyan
    [J]. AEROSOL AND AIR QUALITY RESEARCH, 2017, 17 (02) : 412 - 425