Investigating the regional contributions to air pollution in Beijing: a dispersion modelling study using CO as a tracer

被引:18
|
作者
Panagi, Marios [1 ,7 ]
Fleming, Zoe L. [1 ,8 ]
Monks, Paul S. [2 ]
Ashfold, Matthew J. [3 ]
Wild, Oliver [4 ]
Hollaway, Michael [4 ,9 ]
Zhang, Qiang [5 ]
Squires, Freya A. [6 ]
Vande Hey, Joshua [7 ]
机构
[1] Univ Leicester, Natl Ctr Atmospher Sci, Dept Chem, Leicester, Leics, England
[2] Univ Leicester, Dept Chem, Leicester, Leics, England
[3] Univ Nottingham Malaysia, Sch Environm & Geog Sci, Semenyih 43500, Selangor, Malaysia
[4] Univ Lancaster, Lancaster Environm Ctr, Lancaster, England
[5] Tsinghua Univ, Dept Earth Syst Sci, Key Lab Earth Syst Modeling, Minist Educ, Beijing, Peoples R China
[6] Univ York, Dept Chem, York, N Yorkshire, England
[7] Univ Leicester, Sch Phys & Astron, Earth Observat Sci Grp, Leicester, Leics, England
[8] Univ Chile, Ctr Climate & Resilience Res CR2, Dept Geophys, Santiago, Chile
[9] Lancaster Environm Ctr, Ctr Ecol & Hydrol, Lib Ave, Lancaster, England
基金
英国自然环境研究理事会;
关键词
CHINA; HAZE; INVENTORY; EMISSIONS; QUALITY; WINTER; LAYER;
D O I
10.5194/acp-20-2825-2020
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The rapid urbanization and industrialization of northern China in recent decades has resulted in poor air quality in major cities like Beijing. Transport of air pollution plays a key role in determining the relative influence of local emissions and regional contributions to observed air pollution. In this paper, dispersion modelling (Numerical Atmospheric Modelling Environment, NAME model) is used with emission inventories and in situ ground measurement data to track the pathways of air masses arriving in Beijing. The percentage of time the air masses spent over specific regions during their travel to Beijing is used to assess the effects of regional meteorology on carbon monoxide (CO), a good tracer of anthropogenic emissions. The NAME model is used with the MEIC (Multi-resolution Emission Inventory for China) emission inventories to determine the amount of pollution that is transported to Beijing from the immediate surrounding areas and regions further away. This approach captures the magnitude and variability of CO over Beijing and reveals that CO is strongly driven by transport processes. This study provides a more detailed understanding of relative contributions to air pollution in Beijing under different regional airflow conditions. Approximately 45% over a 4-year average (2013-2016) of the total CO pollution that affects Beijing is transported from other regions, and about half of this contribution comes from beyond the Hebei and Tianjin regions that immediately surround Beijing. The industrial sector is the dominant emission source from the surrounding regions and contributes over 20% of the total CO in Beijing. Finally, using PM2.5 to determine high-pollution days, three pollution classification types of pollution were identified and used to analyse the APHH winter campaign and the 4-year period. The results can inform targeted control measures to be implemented by Beijing and the surrounding provinces to tackle air quality problems that affect Beijing and China.
引用
收藏
页码:2825 / 2838
页数:14
相关论文
共 50 条
  • [41] POLLUTANT VARIABILITY IN REGIONAL AIR-POLLUTION STUDY
    MCCLENNY, WA
    CHANEY, LW
    JOURNAL OF THE AIR POLLUTION CONTROL ASSOCIATION, 1978, 28 (07): : 693 - 696
  • [42] AN EMPIRICAL STUDY OF TRANSBOUNDARY AIR POLLUTION OF THE BEIJING-TIANJIN REGION
    Lu, Zuliang
    Huang, Fei
    Li, Lin
    Zuo, Xiaoxiao
    Li, Junhong
    ELECTRONIC TRANSACTIONS ON NUMERICAL ANALYSIS, 2020, 52 : 100 - 112
  • [43] Time-series study on the air pollution and daily mortality in Beijing
    Pan, XC
    Chang, GQ
    EPIDEMIOLOGY, 2004, 15 (04) : S59 - S59
  • [44] Modelling activity in the framework of the national project "transformation of air-pollution, modelling its transport and dispersion"
    Halenka, T
    Brechler, J
    Bednar, J
    AIR POLLUTION MODELING AND ITS APPLICATION XVI, 2004, 16 : 629 - 631
  • [45] Investigating air pollution in Northern Thailand using wavelet analysis
    Suwanarat, Suksan
    Anusasananan, Panatcha
    Thangprasert, Nipon
    19TH SIAM PHYSICS CONGRESS, 2025, 2934
  • [46] Urban compaction or dispersion? An air quality modelling study
    Martins, Helena
    ATMOSPHERIC ENVIRONMENT, 2012, 54 : 60 - 72
  • [47] Understand the local and regional contributions on air pollution from the view of human health impacts
    Jiang, Yueqi
    Xing, Jia
    Wang, Shuxiao
    Chang, Xing
    Liu, Shuchang
    Shi, Aijun
    Liu, Baoxian
    Sahu, Shovan Kumar
    FRONTIERS OF ENVIRONMENTAL SCIENCE & ENGINEERING, 2021, 15 (05)
  • [48] Understand the local and regional contributions on air pollution from the view of human health impacts
    Yueqi Jiang
    Jia Xing
    Shuxiao Wang
    Xing Chang
    Shuchang Liu
    Aijun Shi
    Baoxian Liu
    Shovan Kumar Sahu
    Frontiers of Environmental Science & Engineering, 2021, 15 (05) : 101 - 111
  • [49] Understand the local and regional contributions on air pollution from the view of human health impacts
    Yueqi Jiang
    Jia Xing
    Shuxiao Wang
    Xing Chang
    Shuchang Liu
    Aijun Shi
    Baoxian Liu
    Shovan Kumar Sahu
    Frontiers of Environmental Science & Engineering, 2021, 15
  • [50] Regional and global contributions of air pollution to risk of death from COVID-19
    Pozzer, Andrea
    Dominici, Francesca
    Haines, Andy
    Witt, Christian
    Munzel, Thomas
    Lelieveld, Jos
    CARDIOVASCULAR RESEARCH, 2020, 116 (14) : 2247 - 2253