Study on the contribution of transport to PM2.5 in typical regions of China using the regional air quality model RAMS-CMAQ

被引:51
|
作者
Li, Rong [1 ,2 ]
Mei, Xin [1 ,2 ]
Wei, Lifei [1 ,2 ]
Han, Xiao [3 ]
Zhang, Meigen [3 ,4 ,5 ]
Jing, Yingying [6 ]
机构
[1] Hubei Univ, Hubei Key Lab Reg Dev & Environm Response, Wuhan 430062, Hubei, Peoples R China
[2] Hubei Univ, Fac Resources & Environm Sci, Wuhan 430062, Hubei, Peoples R China
[3] Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Atmospher Boundary Layer Phys & Atm, Beijing 100029, Peoples R China
[4] Chinese Acad Sci, Inst Urban Environm, Ctr Excellence Urban Atmospher Environm, Xiamen 361021, Fujian, Peoples R China
[5] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[6] Beijing Weather Modificat Off, Beijing Key Lab Cloud Precipitat & Atmospher Wate, Beijing 100089, Peoples R China
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
PM2.5; CMAQ-ISAM; Regional transport; Air quality; China; YANGTZE-RIVER DELTA; TIANJIN-HEBEI REGION; SOURCE APPORTIONMENT; PARTICULATE MATTER; PARTICLE POLLUTION; EMISSION INVENTORY; AMMONIA EMISSIONS; EASTERN CHINA; SURFACE OZONE; INTER-CITY;
D O I
10.1016/j.atmosenv.2019.116856
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Regional transport plays a significant role in the air pollution in China, which is characterized by diverse emission sources and distinct distributions. To improve the understanding of factors determining the PM2.5 level in China, a source apportionment tool coupled with the RAMS-CMAQ model (CMAQ-ISAM) was used to quantify the contribution of transport to PM2.5 and its major components during 2017 in the North China Plain (NCP), Yangtze River Delta (YRD), Pearl River Delta (PRD), and Chengyu area. It is found that transport accounts for a predominant fraction of the PM2.5 in Beijing, Tianjin, and Shanghai with relatively low PM2.5 levels. Transport in the NCP is mainly at intraregional scale and comparable to local emissions. In contrast, the contributions of interregional transport from the NCP to the YRD (similar to 10-25%) and from NCP and YRD to PRD and Chengyu (similar to 5-25%) is at similar level to those of intraregional transport and local emissions in winter and fall, but are lower in spring and summer. It is worth noting that particle components have very different transport capabilities. Nitrate exhibits much stronger intraregional transport than other components in the NCP, and much higher concentration than other components during winter. In contrast, the concentration of sulfate is higher than that of nitrate during spring and summer in most provinces. In addition, the transport potential of primary OC, EC, and ammonia are relatively weaker, but these compounds can still have considerable contributions. Our results reveal that the notable contributions of regional transport to PM2.5 should be addressed according to. targeted emission sources in order to improve air quality efficiently.
引用
收藏
页数:10
相关论文
共 50 条
  • [41] Temporal and spatial characteristics of PM2.5 transport fluxes of typical inland and coastal cities in China
    Guan, Panbo
    Wang, Xiaoqi
    Cheng, Shuiyuan
    Zhang, Hanyu
    JOURNAL OF ENVIRONMENTAL SCIENCES, 2021, 103 : 229 - 245
  • [42] Temporal and spatial characteristics of PM2.5 transport fluxes of typical inland and coastal cities in China
    Panbo Guan
    Xiaoqi Wang
    Shuiyuan Cheng
    Hanyu Zhang
    Journal of Environmental Sciences, 2021, 103 (05) : 229 - 245
  • [43] Meteorological mechanism of regional PM2.5 transport building a receptor region for heavy air pollution over Central China
    Bai, Yongqing
    Zhao, Tianliang
    Hu, Weiyang
    Zhou, Yue
    Xiong, Jie
    Wang, Ying
    Liu, Lin
    Shen, Lijuan
    Kong, Shaofei
    Meng, Kai
    Zheng, Huang
    SCIENCE OF THE TOTAL ENVIRONMENT, 2022, 808
  • [44] Spatial variations of PM2.5 during the Pittsburgh air quality study
    Tang, W
    Raymond, T
    Wittig, B
    Davidson, C
    Pandis, S
    Robinson, A
    Crist, K
    AEROSOL SCIENCE AND TECHNOLOGY, 2004, 38 : 80 - 90
  • [45] Synoptic meteorological modes of variability for fine particulate matter (PM2.5) air quality in major metropolitan regions of China
    Leung, Danny M.
    Tai, Amos P. K.
    Mickley, Loretta J.
    Moch, Jonathan M.
    van Donkelaar, Aaron
    Shen, Lu
    Martin, Randall V.
    ATMOSPHERIC CHEMISTRY AND PHYSICS, 2018, 18 (09) : 6733 - 6748
  • [46] Causes of PM2.5 pollution in an air pollution transport channel city of northern China
    Zhao, Xueyan
    Wang, Jing
    Xu, Bo
    Zhao, Ruojie
    Zhao, Guangjie
    Wang, Jian
    Ma, Yinhong
    Liang, Handong
    Li, Xianqing
    Yang, Wen
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2022, 29 (16) : 23994 - 24009
  • [47] A Monitoring and Modeling Study to Investigate Regional Transport and Characteristics of PM2.5 Pollution
    Lang, Jianlei
    Cheng, Shuiyuan
    Li, Jianbing
    Chen, Dongsheng
    Zhou, Ying
    Wei, Xiao
    Han, Lihui
    Wang, Haiyan
    AEROSOL AND AIR QUALITY RESEARCH, 2013, 13 (03) : 943 - 956
  • [48] Development of a source oriented version of the WRF/Chem model and its application to the California regional PM10/PM2.5 air quality study
    Zhang, H.
    DeNero, S. P.
    Joe, D. K.
    Lee, H. -H.
    Chen, S. -H.
    Michalakes, J.
    Kleeman, M. J.
    ATMOSPHERIC CHEMISTRY AND PHYSICS, 2014, 14 (01) : 485 - 503
  • [49] Modeling air quality during the California Regional PM10/PM2.5 Air Quality Study (CRPAQS) using the UCD/CIT source-oriented air quality model - Part I. Base case model results
    Ying, Qi
    Lu, Jin
    Allen, Paul
    Livingstone, Paul
    Kaduwela, Ajith
    Kleeman, Michael
    ATMOSPHERIC ENVIRONMENT, 2008, 42 (39) : 8954 - 8966
  • [50] Causes of PM2.5 pollution in an air pollution transport channel city of northern China
    Xueyan Zhao
    Jing Wang
    Bo Xu
    Ruojie Zhao
    Guangjie Zhao
    Jian Wang
    Yinhong Ma
    Handong Liang
    Xianqing Li
    Wen Yang
    Environmental Science and Pollution Research, 2022, 29 : 23994 - 24009