The impacts of regional transport on anthropogenic source contributions of PM2.5 in a basin China

被引:5
|
作者
Liu, Huikun [1 ]
Wang, Qiyuan [1 ,2 ,3 ]
Wei, Peng [4 ]
Zhang, Qian [5 ]
Qu, Yao [1 ]
Zhang, Yong [1 ]
Tian, Jie [1 ]
Xu, Hongmei [6 ]
Zhang, Ningning [1 ]
Shen, Zhenxing [6 ]
Su, Hui [1 ]
Han, Yongming [1 ,2 ,3 ]
Cao, Junji [7 ,8 ]
机构
[1] Chinese Acad Sci, Inst Earth Environm, State Key Lab Loess & Quaternary Geol, Xian 710061, Peoples R China
[2] CAS Ctr Excellence Quaternary Sci & Global Change, Xian 710061, Peoples R China
[3] Guanzhong Plain Ecol Environm Change & Comprehens, Xian 710061, Peoples R China
[4] Chinese Res Inst Environm Sci, Beijing 100012, Peoples R China
[5] Xian Univ Architecture & Technol, Key Lab Northwest Resource Environm & Ecol, MOE, Xian 710055, Peoples R China
[6] Xi An Jiao Tong Univ, Dept Environm Sci & Engn, Xian 710049, Peoples R China
[7] Shaanxi Key Lab Atmospher & Haze fog Pollut Preven, Xian 710061, Peoples R China
[8] Chinese Acad Sci, Inst Atmospher & Phys, Beijing 100029, Peoples R China
关键词
PM2.5 source apportionment; Regional transport; Guanzhong basin; RIVER DELTA REGION; SOURCE APPORTIONMENT; PARTICULATE MATTER; CHEMICAL-COMPOSITION; AIR-POLLUTION; BLACK CARBON; WINTER HAZE; MODEL; URBAN; EMISSIONS;
D O I
10.1016/j.scitotenv.2024.170038
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
PM2.5 pollution events are often happened in urban agglomeration locates in mountain-basin regions due to the complex terra and intensive emissions. Source apportionment is essential for identifying the pollution sources and important for developing local mitigation strategies, however, it is influenced by regional transport. To understand how the regional transport influences the atmospheric environment of a basin, we connected the PM2.5 source contributions estimated by observation-based receptor source apportionment and the regional contributions estimated by a tagging technology in the comprehensive air quality model with extensions (CAMx) via an artificial neural network (ANNs). The result shows that the PM2.5 in Xi'an was from biomass burning, coal combustion, traffic related emissions, mineral dust, industrial emissions, secondary nitrate and sulfate. 48.8 % of the PM2.5 in study period was from Xi'an, then followed by the outside area of Guanzhong basin (28.2 %), Xianyang (14.6 %) and Weinan (5.8 %). Baoji and Tongchuan contributed trivial amount. The sensitivity analysis showed that the transported PM2.5 would lead to divergent results of source contributions at Xi'an. The transported PM2.5 from the outside has great a potential to alter the source contributions implying a large uncertainty of the source apportionment introduced when long-range transported pollutants arrived. It suggests that a full comprehension on the impacts of regional transport can lower the uncertainty of the local PM2.5 source apportionment and reginal collaborative actions can be of great use for pollution mitigation.
引用
收藏
页数:11
相关论文
共 50 条
  • [1] Source regional contributions to PM2.5 in a megacity in China using an advanced source regional apportionment method
    Tian, Ying-Ze
    Chen, Gang
    Wang, Hai-Ting
    Huang-Fu, Yan-Qi
    Shi, Guo-Liang
    Han, Bo
    Feng, Yin-Chang
    CHEMOSPHERE, 2016, 147 : 256 - 263
  • [2] Characterization of winter PM2.5 source contributions and impacts of meteorological conditions and anthropogenic emission changes in the Sichuan Basin, 2002-2020
    Xian, Yaohan
    Zhang, Yang
    Liu, Zhihong
    Wang, Haofan
    Xiong, Tianxin
    SCIENCE OF THE TOTAL ENVIRONMENT, 2024, 947
  • [3] Seasonal trends in PM2.5 source contributions in Beijing, China
    Zheng, M
    Salmon, LG
    Schauer, JJ
    Zeng, LM
    Kiang, CS
    Zhang, YH
    Cass, GR
    ATMOSPHERIC ENVIRONMENT, 2005, 39 (22) : 3967 - 3976
  • [4] Modeling Studies of Source Contributions to PM2.5 in Chengdu, China
    Xu Y.-L.
    Yi A.-H.
    Xue W.-B.
    Huanjing Kexue/Environmental Science, 2020, 41 (01): : 50 - 56
  • [5] Source regions and transport pathways of PM2.5 at a regional background site in East China
    Zhang, Yanru
    Zhang, Hongliang
    Deng, Junjun
    Du, Wenjiao
    Hong, Youwei
    Xu, Lingling
    Qiu, Yuqing
    Hong, Zhenyu
    Wu, Xin
    Ma, Qianli
    Yao, Jie
    Chen, Jinsheng
    ATMOSPHERIC ENVIRONMENT, 2017, 167 : 202 - 211
  • [6] Source apportionment and a novel approach of estimating regional contributions to ambient PM2.5 in Haikou, China
    Liu, Baoshuang
    Li, Tingkun
    Yang, Jiamei
    Wu, Jianhui
    Wang, Jiao
    Gao, Jixin
    Bi, Xiaohui
    Feng, Yinchang
    Zhang, Yufen
    Yang, Haihang
    ENVIRONMENTAL POLLUTION, 2017, 223 : 334 - 345
  • [7] Assessment of the regional source contributions to PM2.5 mass concentration in Beijing
    Han Xiao
    Zhang Mei-Gen
    ATMOSPHERIC AND OCEANIC SCIENCE LETTERS, 2018, 11 (02) : 143 - 149
  • [8] Assessment of the regional source contributions to PM2.5 mass concentration in Beijing
    HAN Xiao
    ZHANG Mei-Gen
    AtmosphericandOceanicScienceLetters, 2018, 11 (02) : 143 - 149
  • [9] Impacts of regional transport and boundary layer structure on the PM2.5 pollution in Wuhan, Central China
    Xiao, Zhisheng
    Miao, Yucong
    Du, Xiaohui
    Tang, Wei
    Yu, Yang
    Zhang, Xin
    Che, Huizheng
    ATMOSPHERIC ENVIRONMENT, 2020, 230
  • [10] Numerical study on the characteristics of regional transport of PM2.5 in China
    Xue, Wen-Bo
    Fu, Fei
    Wang, Jin-Nan
    Tang, Gui-Qian
    Lei, Yu
    Yang, Jin-Tian
    Wang, Yue-Si
    Zhongguo Huanjing Kexue/China Environmental Science, 2014, 34 (06): : 1361 - 1368