Uncovering PM2.5 transport trajectories and sources at district within city scale

被引:17
作者
Shan, Mei [1 ]
Wang, Yuan [1 ]
Lu, Yaling [2 ]
Liang, Chen [1 ]
Wang, Tingyu [1 ]
Li, Linyan [3 ]
Li, Rita Yi- man [4 ]
机构
[1] Tianjin Univ, Sch Environm Sci & Engn, Tianjin 300350, Peoples R China
[2] Chinese Acad Environm Planning, Ctr Enterprise Green Governance, Beijing 100012, Peoples R China
[3] City Univ Hong Kong, Sch Data Sci, Hong Kong, Peoples R China
[4] Hong Kong Shue Yan Univ, Dept Econ & Finance, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Regional transport; Potential source areas; District scale; Tianjin; TRANSBOUNDARY TRANSPORT; AIR-POLLUTION; CHINA; REGION; VARIABILITY; EMISSIONS; TIANJIN; PATHWAYS; IMPACTS; MODEL;
D O I
10.1016/j.jclepro.2023.138608
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
To continuously improve air quality, it is necessary to carry out fine management of air pollution prevention and control. However, research into regional transport of PM2.5 at a smaller spatial scale such as district is limited. In this study, a novel combined method was constructed to simulate and identify the regional transport trajectories and potential sources of PM2.5 concentrations at district scale, based on a hybrid model that integrates the Bayesian maximum entropy (BME) model, Weather Research and Forecast (WRF) and backward trajectory model. Take Tianjin as an example, an analysis of the transport trajectories showed that the air masses from northwest and southwest were the dominant atmospheric transport pathway in all seasons except summer. The number of transport trajectories from northwest and southwest accounted for 42.41% and 40.75% of the total number of transport trajectories. Despite the dominant wind direction in winter was northwest, it can be beneficial to atmospheric transport. This was because northwest trajectories were the long-range pathways, corresponding to fast-moving air masses that facilitate the dispersion of pollutants. On contrast, it is noteworthy that the southwest trajectories were the short-range pathways, resulting in limited diffusion and unfavorable conditions. The major potential cities that were likely contributors of PM2.5 (Weighted Concentration-Weighted Trajectory (WCWT) values greater than 40 mu g m-3) were situated in the southwest. Furthermore, the interdistrict transport results indicated that the primary direction of PM2.5 transport in Tianjin was also from south to north. It is critical that the current layout of Tianjin is adjusted in a timely manner through relocating or phasing out, as the majority of industrial enterprises with severe air pollution in Tianjin are located in the southern districts. This method of combining BME, WRF and backward trajectory can be used for atmospheric environment planning in other similar city and district-scale around the world. It also provides useful insights to policy makers when they formulate pollutants prevention control policies.
引用
收藏
页数:11
相关论文
共 54 条
  • [1] 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
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2022, 808
  • [2] A Hybrid Approach to Estimating National Scale Spatiotemporal Variability of PM2.5 in the Contiguous United States
    Beckerman, Bernardo S.
    Jerrett, Michael
    Serre, Marc
    Martin, Randall V.
    Lee, Seung-Jae
    van Donkelaar, Aaron
    Ross, Zev
    Su, Jason
    Burnett, Richard T.
    [J]. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2013, 47 (13) : 7233 - 7241
  • [3] Impacts of sea-land and mountain-valley circulations on the air pollution in Beijing-Tianjin-Hebei (BTH): A case study
    Bei, Naifang
    Zhao, Linna
    Wu, Jiarui
    Li, Xia
    Feng, Tian
    Li, Guohui
    [J]. ENVIRONMENTAL POLLUTION, 2018, 234 : 429 - 438
  • [4] Estimation of the impact of biomass burning based on regional transport of PM2.5 in the Colombian Caribbean
    Bolano-Truyol, Jehison
    Schneider, Ismael L.
    Cano Cuadro, Heidis
    Bolano-Truyol, Jorge D.
    Oliveira, Marcos L. S.
    [J]. GEOSCIENCE FRONTIERS, 2022, 13 (01)
  • [5] Impacts of the differences in PM2.5 air quality improvement on regional transport and health risk in Beijing-Tianjin-Hebei region during 2013-2017
    Cao, Jingyuan
    Qiu, Xionghui
    Peng, Lin
    Gao, Jian
    Wang, Fangyuan
    Yan, Xiao
    [J]. CHEMOSPHERE, 2022, 297
  • [6] Multiscale assessment of the impact on air quality of an intense wildfire season in southern Italy
    Castagna, Jessica
    Senatore, Alfonso
    Bencardino, Mariantonia
    D'Amore, Francesco
    Sprovieri, Francesca
    Pirrone, Nicola
    Mendicino, Giuseppe
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2021, 761 (761)
  • [7] PM2.5 over North China based on MODIS AOD and effect of meteorological elements during 2003-2015
    Chen, Youfang
    Zhou, Yimin
    Zhao, Xinyi
    [J]. FRONTIERS OF ENVIRONMENTAL SCIENCE & ENGINEERING, 2019, 14 (02):
  • [8] A BAYESIAN MAXIMUM-ENTROPY VIEW TO THE SPATIAL ESTIMATION PROBLEM
    CHRISTAKOS, G
    [J]. MATHEMATICAL GEOLOGY, 1990, 22 (07): : 763 - 777
  • [9] Estimating Wildfire Smoke Concentrations during the October 2017 California Fires through BME Space/Time Data Fusion of Observed, Modeled, and Satellite-Derived PM2.5
    Cleland, Stephanie E.
    West, J. Jason
    Jia, Yiqin
    Reid, Stephen
    Raffuse, Sean
    O'Neill, Susan
    Serre, Marc L.
    [J]. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2020, 54 (21) : 13439 - 13447
  • [10] Atmospheric Dispersion of PM2.5 Precursor Gases from Two Major Thermal Power Plants in Andhra Pradesh, India
    Dodla, Venkata Bhaskar Rao
    Gubbala, China Satyanarayana
    Desamsetti, Srinivas
    [J]. AEROSOL AND AIR QUALITY RESEARCH, 2017, 17 (02) : 381 - 393