Seasonal quantification of the inter-city transport of PM2.5 in the Yangtze River Delta region of China based on a source-oriented chemical transport model and the Michaelis-Menten equation

被引:0
|
作者
Gong K. [1 ]
Xie X. [1 ]
Ying Q. [2 ]
Hu J. [1 ]
机构
[1] Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing
[2] Zachry Department of Civil Engineering, Texas A&M University, College Station, 77843, TX
基金
中国国家自然科学基金;
关键词
Inter-city transport; Michaelis-Menten; PM[!sub]2.5[!/sub; Source-oriented model; Yangtze River Delta;
D O I
10.1016/j.scitotenv.2024.173856
中图分类号
学科分类号
摘要
Regional transport plays a crucial role in the pollution of fine particulate matter (PM2.5) over the Yangtze River Delta region (YRD). A practical joint regional emission control strategy requires quantitative assessment of the contribution of regional transport. In this study, the contribution of inter-city transport to PM2.5 among the 41 cities in the YRD region were quantitatively estimated using a source-oriented chemical transport model, and then the relationship between the cumulative contribution of regional transport and the distance was examined using the Michaelis-Menten equation. The results show that the Michaelis-Menten equation is suitable to represent the relationship between the cumulative contribution and transport distance. The coefficient of determination (r2) of the fittings is greater than 0.9 in 71 % of the cases in the six subregions and four seasons in YRD. Two key parameters in the Michaelis-Menten eq. K1, indicating the maximum contribution of regional transport, and K2, indicating the distance to which the regional transport contribution reach half the maximum contribution, show substantial regional and seasonal variations. The average K1 is 73.6 %, with lower values observed in the northern part of the YRD and higher values in central Jiangsu. K2 is larger in northern Jiangsu, as well as central and southern Zhejiang. The local contribution in autumn and winter is lower than that in spring and summer in the northern part of the YRD. Particularly in northern Jiangsu, the local contribution reaches 90.4 % in summer but drops to 53.0 % in autumn and winter, illustrating significant impacts of regional transport to PM2.5 in autumn and winter in this area. K2 is larger on polluted days, compared to clean days, indicating greater contributions from regional transport to PM2.5 in YRD. The results can serve as a scientific foundation for implementing regional joint prevention and control measures in the YRD region. © 2024 Elsevier B.V.
引用
收藏
相关论文
共 10 条
  • [1] Source apportionment of PM2.5 nitrate and sulfate in China using a source-oriented chemical transport model
    Zhang, Hongliang
    Li, Jingyi
    Ying, Qi
    Yu, Jian Zhen
    Wu, Dui
    Cheng, Yuan
    He, Kebin
    Jiang, Jingkun
    ATMOSPHERIC ENVIRONMENT, 2012, 62 : 228 - 242
  • [2] Complex network analysis of PM2.5 transport in the Yangtze River Delta Region, China
    Wang, Xiaohao
    Wang, Qian
    Duan, Yusen
    Huang, Kan
    STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2021, 35 (12) : 2645 - 2658
  • [3] Complex network analysis of PM2.5 transport in the Yangtze River Delta Region, China
    Xiaohao Wang
    Qian Wang
    Yusen Duan
    Kan Huang
    Stochastic Environmental Research and Risk Assessment, 2021, 35 : 2645 - 2658
  • [4] Regional Transport of PM2.5 and O3 Based on Complex Network Method and Chemical Transport Model in the Yangtze River Delta, China
    Wang, Qian
    Wang, Xiaohao
    Huang, Ruizhu
    Wu, Jianbin
    Xiao, Yu
    Hu, Ming
    Fu, Qingyan
    Duan, Yusen
    Chen, Jianmin
    JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2022, 127 (05)
  • [5] Quantifying the seasonal variations in and regional transport of PM2.5 in the Yangtze River Delta region, China: characteristics, sources, and health risks
    Zhan, Yangzhihao
    Xie, Min
    Zhao, Wei
    Wang, Tijian
    Gao, Da
    Chen, Pulong
    Tian, Jun
    Zhu, Kuanguang
    Li, Shu
    Zhuang, Bingliang
    Li, Mengmeng
    Luo, Yi
    Zhao, Runqi
    ATMOSPHERIC CHEMISTRY AND PHYSICS, 2023, 23 (17) : 9837 - 9852
  • [6] Quantifying the impacts of inter-city transport on air quality in the Yangtze River Delta urban agglomeration, China: Implications for regional cooperative controls of PM2.5 and O3
    Gong, Kangjia
    Li, Lin
    Li, Jingyi
    Qin, Momei
    Wang, Xueying
    Ying, Qi
    Liao, Hong
    Guo, Song
    Hu, Min
    Zhang, Yuanhang
    Hu, Jianlin
    SCIENCE OF THE TOTAL ENVIRONMENT, 2021, 779
  • [7] Source Apportionment of PM2.5 in Handan City, China Using a Combined Method of Receptor Model and Chemical Transport Model
    Wei, Zhe
    Wang, Litao
    Hou, Liquan
    Zhang, Hongmei
    Yue, Liang
    Wei, Wei
    Ma, Simeng
    Zhang, Chengyu
    Ma, Xiao
    SUSTAINABLE DEVELOPMENT OF WATER RESOURCES AND HYDRAULIC ENGINEERING IN CHINA, 2019, : 151 - 173
  • [8] Predictions and mitigation strategies of PM2.5 concentration in the Yangtze River Delta of China based on a novel nonlinear seasonal grey model
    Zhou, Weijie
    Wu, Xiaoli
    Ding, Song
    Ji, Xiaoli
    Pan, Weiqiang
    ENVIRONMENTAL POLLUTION, 2021, 276
  • [9] An eigenvector spatial filtering based spatially varying coefficient model for PM2.5 concentration estimation: A case study in Yangtze River Delta region of China
    Tan, Huangyuan
    Chen, Yumin
    Wilson, John P.
    Zhang, Jingyi
    Cao, Jiping
    Chu, Tianyou
    ATMOSPHERIC ENVIRONMENT, 2020, 223
  • [10] Underestimation of biomass burning contribution to PM2.5 due to its chemical degradation based on hourly measurements of organic tracers: A case study in the Yangtze River Delta (YRD) region, China
    Li, Qing
    Zhang, Kun
    Li, Rui
    Yang, Liumei
    Yi, Yanan
    Liu, Zhiqiang
    Zhang, Xiaojuan
    Feng, Jialiang
    Wang, Qiongqiong
    Wang, Wu
    Huang, Ling
    Wang, Yangjun
    Wang, Shunyao
    Chen, Hui
    Chan, Andy
    Latif, Mohd Talib
    Ooi, Maggie Chel Gee
    Manomaiphiboon, Kasemsan
    Yu, Jianzhen
    Li, Li
    SCIENCE OF THE TOTAL ENVIRONMENT, 2023, 872