Spatiotemporal Patterns and Regional Transport of Ground-Level Ozone in Major Urban Agglomerations in China

被引:11
作者
Liu, Xiaoyong [1 ,2 ]
Zhao, Chengmei [1 ,2 ]
Niu, Jiqiang [1 ,2 ]
Su, Fangcheng [3 ]
Yao, Dan [4 ]
Xu, Feng [1 ,2 ]
Yan, Junhui [1 ,2 ]
Shen, Xinzhi [5 ]
Jin, Tao [5 ]
机构
[1] Xinyang Normal Univ, Sch Geog Sci, Xinyang 464000, Peoples R China
[2] Xinyang Normal Univ, Henan Key Lab Synergist Prevent Water & Soil Envi, Xinyang 464000, Peoples R China
[3] Zhengzhou Univ, Coll Chem & Mol Engn, Zhengzhou 450001, Peoples R China
[4] Henan Normal Univ, Key Lab Yellow River & Huai River Water Environm, Minist Educ, Sch Environm, Xinxiang 453007, Henan, Peoples R China
[5] Xinyang Ecol Environm Monitoring Ctr, Xinyang 464000, Peoples R China
基金
中国国家自然科学基金;
关键词
ozone; spatiotemporal patterns; potential sources; Chinese major urban agglomeration; RIVER DELTA REGION; SOURCE APPORTIONMENT; PARTICULATE MATTER; CHEMICAL CHARACTERISTICS; TEMPORAL DISTRIBUTION; PREMATURE MORTALITY; POLLUTION EPISODES; POTENTIAL SOURCES; SURFACE OZONE; PM2.5;
D O I
10.3390/atmos13020301
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Ground-level ozone (O-3) pollution has become a serious environmental issue in major urban agglomerations in China. To investigate the spatiotemporal patterns and regional transports of O-3 in Beijing-Tianjin-Hebei (BTH-UA), the Yangtze River Delta (YRD-UA), the Triangle of Central China (TC-UA), Chengdu-Chongqing (CY-UA), and the Pearl River Delta urban agglomeration (PRD-UA), multiple transdisciplinary methods were employed to analyze the O-3-concentration data that were collected from national air quality monitoring networks operated by the China National Environmental Monitoring Center (CNEMC). It was found that although ozone concentrations have decreased in recent years, ozone pollution is still a serious issue in China. O-3 exhibited different spatiotemporal patterns in the five urban agglomerations. In terms of monthly variations, O-3 had a unimodal structure in BTH-UA but a bimodal structure in the other urban agglomerations. The maximum O-3 concentration was in autumn in PRD-UA, but in summer in the other urban agglomerations. In spatial distribution, the main distribution of O-3 concentration was aligned in northeast-southwest direction for BTH-UA and CY-UA, but in northwest-southeast direction for YRD-UA, TC-UA, and PRD-UA. O-3 concentrations exhibited positive spatial autocorrelations in BTH-UA, YRD-UA, and TC-UA, but negative spatial autocorrelations in CY-UA and PRD-UA. Variations in O-3 concentration were more affected by weather fluctuations in coastal cities while the variations were more affected by seasonal changes in inland cities. O-3 transport in the center cities of the five urban agglomerations was examined by backward trajectory and potential source analyses. Local areas mainly contributed to the O-3 concentrations in the five cities, but regional transport also played a significant role. Our findings suggest joint efforts across cities and regions will be necessary to reduce O-3 pollution in major urban agglomerations in China.
引用
收藏
页数:20
相关论文
共 56 条
  • [11] Ozone source apportionment over the Yangtze River Delta region, China: Investigation of regional transport, sectoral contributions and seasonal differences
    Li, Li
    An, Jingyu
    Huang, Ling
    Yan, Rusha
    Huang, Cheng
    Yarwood, Greg
    [J]. ATMOSPHERIC ENVIRONMENT, 2019, 202 : 269 - 280
  • [12] The analysis and application of a new hybrid pollutants forecasting model using modified Kolmogorov-Zurbenko filter
    Li, Peizhi
    Wang, Yong
    Dong, Qingli
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2017, 583 : 228 - 240
  • [13] Air pollution characteristics in China during 2015-2016: Spatiotemporal variations and key meteorological factors
    Li, Rui
    Wang, Zhenzhen
    Cui, Lulu
    Fu, Hongbo
    Zhang, Liwu
    Kong, Lingdong
    Chen, Weidong
    Chen, Jianmin
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2019, 648 (902-915) : 902 - 915
  • [14] Liao TT, 2017, SCI TOTAL ENVIRON, V584, P1056, DOI [10.1016/j.scitotenv2017.01.160, 10.1016/j.scitotenv.2017.01.160]
  • [15] Transition in air pollution, disease burden and health cost in China: A comparative study of long-term and short-term exposure
    Liu, Jun
    Yin, Hao
    Tang, Xiao
    Zhu, Tong
    Zhang, Qiang
    Liu, Zhu
    Tang, XiaoLong
    Yi, HongHong
    [J]. ENVIRONMENTAL POLLUTION, 2021, 277
  • [16] Chemical formation and source apportionment of PM2.5 at an urban site at the southern foot of the Taihang mountains
    Liu, Xiaoyong
    Wang, Mingshi
    Pan, Xiaole
    Wang, Xiyue
    Yue, Xiaolong
    Zhang, Donghui
    Ma, Zhigang
    Tian, Yu
    Liu, Hang
    Lei, Shandong
    Zhang, Yuting
    Liao, Qi
    Ge, Baozhu
    Wang, Dawei
    Li, Jie
    Sun, Yele
    Fu, Pingqing
    Wang, Zifa
    He, Hong
    [J]. JOURNAL OF ENVIRONMENTAL SCIENCES, 2021, 103 : 20 - 32
  • [17] Chemical Characteristics and Potential Sources of PM2.5 in Shahe City during Severe Haze Pollution Episodes in the Winter
    Liu, Xiaoyong
    Pan, Xiaole
    Wang, Zifa
    He, Hong
    Wang, Dawei
    Liu, Hang
    Tian, Yu
    Xiang, Weiling
    Li, Jie
    [J]. AEROSOL AND AIR QUALITY RESEARCH, 2020, 20 (12) : 2741 - 2753
  • [18] Characteristics of PM2.5 spatial distribution and influencing meteorological conditions in Sichuan Basin, southwestern China
    Liu, Yuelin
    Shi, Guangming
    Zhan, Yu
    Zhou, Li
    Yang, Fumo
    [J]. ATMOSPHERIC ENVIRONMENT, 2021, 253
  • [19] Overview on the spatial-temporal characteristics of the ozone formation regime in China
    Lu, Haoxian
    Lyu, Xiaopu
    Cheng, Hairong
    Ling, Zhenhao
    Guo, Hai
    [J]. ENVIRONMENTAL SCIENCE-PROCESSES & IMPACTS, 2019, 21 (06) : 916 - 929
  • [20] Air pollution characteristics and their relationship with emissions and meteorology in the Yangtze River Delta region during 2014-2016
    Ma, Tao
    Duan, Fengkui
    He, Kebin
    Qin, Yu
    Tong, Dan
    Geng, Guannan
    Liu, Xuyan
    Li, Hui
    Yang, Shuo
    Ye, Siqi
    Xu, Beiyao
    Zhang, Qiang
    Ma, Yongliang
    [J]. JOURNAL OF ENVIRONMENTAL SCIENCES, 2019, 83 : 8 - 20