Co-occurrence of ozone and PM2.5 pollution in the Yangtze River Delta over 2013-2019: Spatiotemporal distribution and meteorological conditions

被引:72
|
作者
Dai, Huibin [1 ]
Zhu, Jia [1 ]
Liao, Hong [1 ]
Li, Jiandong [1 ]
Liang, Muxue [1 ]
Yang, Yang [1 ]
Yue, Xu [1 ]
机构
[1] Nanjing Univ Informat Sci & Technol, Jiangsu Key Lab Atmospher Environm Monitoring & P, Jiangsu Collaborat Innovat Ctr Atmospher Environm, Sch Environm Sci & Engn, Nanjing 210044, Peoples R China
基金
中国国家自然科学基金;
关键词
Co-occurrence; Ozone and PM2.5; Pollution; Typical weather patterns; NET PRIMARY PRODUCTIVITY; GROUND-LEVEL OZONE; SURFACE OZONE; REGIONAL TRANSPORT; WEATHER PATTERNS; AIR-POLLUTANTS; CHINA; IMPACTS; HAZE; EMISSION;
D O I
10.1016/j.atmosres.2020.105363
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
We examined the spatial-temporal variations of surface-layer ozone (O-3) and PM2.5 (particulate matter with an aerodynamic equivalent diameter of 2.5 mu m or less) observed from April 2013 to December 2019 in the Yangtze River Delta (YRD) region to identify the O3-PM2.5 relationship and to focus on the co-polluted days by O-3 and PM2.5. Averaged over the YRD, the observed annual mean concentration of maximum daily 8 h average ozone (MDA8 O-3) increased by 36.8 mu gm(3) (49.5%) whereas that of PM2.5 decreased by 13.3 mu gm(3) (22.1%) over 2014-2019. During warm months of April-October of 2013-2019, the observed regional mean daily concentrations of MDA8 O-3 and PM2.5 had a small positive correlation of 0.23, and this correlation coefficient became 0.44 when the long term trends were removed from the concentrations. The days with co-pollution of MDA8 O-3 and PM2.5 (MDA8 O-3 > 160 mu gm(3) and PM2.5 > 75 mu gm(3)) were observed frequently, which reached 54 days in Shanghai and 71 days in Jiangsu province during 2013-2019. Such co-polluted days in the YRD were found to occur mainly in the months of April, May, June, and October. The occurrence of co-pollution in the YRD is found to be mainly dependent on relative humidity, surface air temperature, and wind speed. The mean anomalous values of these three variables were, respectively,-7.3%, 0.46 degrees C,-0.17 m s(-1) for days with O-3 pollution alone while-6.2%, 1.84 degrees C, and-0.40 m s(-1) for days with co-pollution. Four typical weather patterns were identified to be associated with the co-polluted days. Our results provide better understanding of the complex air pollution and have implications for the control of such co-polluted events.
引用
收藏
页数:9
相关论文
共 50 条
  • [41] Exploring the impact of new particle formation events on PM2.5 pollution during winter in the Yangtze River Delta, China
    Jinping Ou
    Qihou Hu
    Haoran Liu
    Shiqi Xu
    Zhuang Wang
    Xiangguang Ji
    Xinqi Wang
    Zhouqing Xie
    Hui Kang
    [J]. Journal of Environmental Sciences, 2022, 111 (01) : 75 - 83
  • [42] Evaluation of regional transport of PM2.5 during severe atmospheric pollution episodes in the western Yangtze River Delta, China
    Sulaymon, Ishaq Dimeji
    Zhang, Yuanxun
    Hu, Jianlin
    Hopke, Philip K.
    Zhang, Yang
    Zhao, Bin
    Xing, Jia
    Li, Lin
    Mei, Xiaodong
    [J]. JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2021, 293 (293)
  • [43] Development and evaluation of a scheme system of joint prevention and control of PM2.5 pollution in the Yangtze River Delta region, China
    Wang, Yangjun
    Liu, Ziyi
    Huang, Ling
    Lu, Guibin
    Gong, Youguo
    Yaluk, Elly
    Li, Hongli
    Yi, Xin
    Yang, Liumei
    Feng, Jialiang
    Ivey, Cesunica
    Li, Li
    [J]. JOURNAL OF CLEANER PRODUCTION, 2020, 275 (275)
  • [44] Predicting spatio-temporal concentrations of PM2.5 using land use and meteorological data in Yangtze River Delta, China
    Yang, Dongyang
    Lu, Debin
    Xu, Jianhua
    Ye, Chao
    Zhao, Jianan
    Tian, Guanghui
    Wang, Xinge
    Zhu, Nina
    [J]. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2018, 32 (08) : 2445 - 2456
  • [45] Impact of urban space on PM2.5 distribution: A multiscale and seasonal study in the Yangtze River Delta urban agglomeration
    Zhang, Jing
    Chen, Jian
    Zhu, Wenjian
    Ren, Yuan
    Cui, Jiecan
    Jin, Xiaoai
    [J]. JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2024, 363
  • [46] Predicting spatio-temporal concentrations of PM2.5 using land use and meteorological data in Yangtze River Delta, China
    Dongyang Yang
    Debin Lu
    Jianhua Xu
    Chao Ye
    Jianan Zhao
    Guanghui Tian
    Xinge Wang
    Nina Zhu
    [J]. Stochastic Environmental Research and Risk Assessment, 2018, 32 : 2445 - 2456
  • [47] Spatiotemporal variations of PM2.5 pollution and its dynamic relationships with meteorological conditions in Beijing-Tianjin-Hebei region
    Deng, Chuxiong
    Qin, Chunyan
    Li, Zhongwu
    Li, Ke
    [J]. CHEMOSPHERE, 2022, 301
  • [48] PM2.5 Pollution in Six Major Chinese Urban Agglomerations: Spatiotemporal Variations, Health Impacts, and the Relationships with Meteorological Conditions
    Li, Zhuofan
    Zhang, Xiangmin
    Liu, Xiaoyong
    Yu, Bin
    [J]. ATMOSPHERE, 2022, 13 (10)
  • [49] PM2.5 and O3 pollution during 2015-2019 over 367 Chinese cities: Spatiotemporal variations, meteorological and topographical impacts
    Zhao, Suping
    Yin, Daiying
    Yu, Ye
    Kang, Shichang
    Qin, Dahe
    Dong, Longxiang
    [J]. ENVIRONMENTAL POLLUTION, 2020, 264
  • [50] Spatiotemporal characteristics of PM2.5 concentration in the Yangtze River Delta urban agglomeration, China on the application of big data and wavelet analysis
    Wang, Jiajia
    Lu, Xiaoman
    Yan, Yingting
    Zhou, Liguo
    Ma, Weichun
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2020, 724 (724)