Research on the Spatial Heterogeneity and Influencing Factors of Air Pollution: A Case Study in Shijiazhuang, China

被引:5
|
作者
Sun, Yuan [1 ]
Zeng, Jian [1 ]
Namaiti, Aihemaiti [1 ]
机构
[1] Tianjin Univ, Sch Architecture, Tianjin 300072, Peoples R China
基金
中国国家自然科学基金;
关键词
air pollution; spatial heterogeneity; Geodetector; influencing factors; Shijiazhuang City; URBAN FORM; PREMATURE MORTALITY; QUALITY; TIANJIN; HEBEI; REGION; PM2.5; URBANIZATION; POLLUTANTS; PROGRESS;
D O I
10.3390/atmos13050670
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Rapid urbanization causes serious air pollution and constrains the sustainable development of society. The influencing factors of urban air pollution are complex and diverse. Multiple factors act together to interact in influencing air pollution. However, most of the existing studies on the influencing factors of air pollution lack consideration of the interaction mechanisms between the factors. Using multisource data and geographical detectors, this study analyzed the spatial heterogeneity characteristics of air pollution in Shijiazhuang City, identified its main influencing factors, and analyzed the interaction effects among these factors. The results of spatial heterogeneity analysis indicate that the distribution of aerosol optical depth (AOD) has obvious agglomeration characteristics. High agglomeration areas are concentrated in the eastern plain areas, and low agglomeration areas are concentrated in the western mountainous areas. Forests (q = 0.620), slopes (q = 0.616), elevation (q = 0.579), grasslands (q = 0.534), and artificial surfaces (q = 0.506) are the main individual factors affecting AOD distribution. Among them, natural factors such as topography, ecological space, and wind speed are negatively correlated with AOD values, whereas the opposite is true for human factors such as roads, artificial surfaces, and population. Each factor can barely affect the air pollution status significantly alone, and the explanatory power of all influencing factors showed an improvement through the two-factor enhanced interaction. The associations of elevation boolean AND artificial surface (q = 0.625), elevation boolean AND NDVI (q = 0.622), and elevation boolean AND grassland (q = 0.620) exhibited a high explanatory power on AOD value distribution, suggesting that the combination of multiple factors such as low altitude, high building density, and sparse vegetation can lead to higher AOD values. These results are conducive to the understanding of the air pollution status and its influencing factors, and in future, decision makers should adopt different strategies, as follows: (1) high-density built-up areas should be considered as the key areas of pollution control, and (2) a single-factor pollution control strategy should be avoided, and a multi-factor synergistic optimization strategy should be adopted to take full advantage of the interaction among the factors to address the air pollution problem more effectively.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] Research on the changes and influencing factors of Air pollution Policy in China
    Liu, Chunfang
    [J]. 2020 ASIA CONFERENCE ON GEOLOGICAL RESEARCH AND ENVIRONMENTAL TECHNOLOGY, 2021, 632
  • [2] A spatial analysis of the causal factors influencing China's air pollution
    Kim Y.
    Tanaka K.
    Zhang X.
    [J]. Asian Journal of Atmospheric Environment, 2017, 11 (3) : 194 - 201
  • [3] Research on influencing factors of environmental pollution in China: A spatial econometric analysis
    Liu, Kui
    Lin, Boqiang
    [J]. JOURNAL OF CLEANER PRODUCTION, 2019, 206 : 356 - 364
  • [4] Spatial Patterns and Influencing Factors of Rural Land Commodification at Township Scale: A Case Study in Shijiazhuang City, North China
    Fu, Lin
    Sanada, Junko
    [J]. LAND, 2023, 12 (06)
  • [5] Fine particulate air pollution and hospitalization for pneumonia: a case-crossover study in Shijiazhuang, China
    Duan, Zheng
    Han, Xue
    Bai, Zina
    Yuan, Yadong
    [J]. AIR QUALITY ATMOSPHERE AND HEALTH, 2016, 9 (07): : 723 - 733
  • [6] Fine particulate air pollution and hospitalization for pneumonia: a case-crossover study in Shijiazhuang, China
    Zheng Duan
    Xue Han
    Zina Bai
    Yadong Yuan
    [J]. Air Quality, Atmosphere & Health, 2016, 9 : 723 - 733
  • [7] Correlation between biomass burning and air pollution in China: Spatial heterogeneity and corresponding factors
    Wang, Shu
    Feng, Huihui
    Zou, Bin
    Yang, Zhuolin
    Ding, Ying
    [J]. GLOBAL AND PLANETARY CHANGE, 2022, 213
  • [8] Evaluation of the spatial heterogeneity in marine organic pollution and land-based influencing factors: A case study of the marine area of Laizhou Bay, China
    Wang, Youxiao
    Liu, Gaohuan
    Yu, Ge
    Zhao, Zhonghe
    Hu, Guobin
    Liu, Dahai
    [J]. REGIONAL STUDIES IN MARINE SCIENCE, 2021, 45
  • [9] Spatial characteristics and influencing factors of river pollution in China
    Wang, Enru
    Li, Qian
    Hu, Hao
    Peng, Fuli
    Zhang, Peng
    Li, Jianjun
    [J]. WATER ENVIRONMENT RESEARCH, 2019, 91 (04) : 351 - 363
  • [10] Spatial correlation and influencing factors of industrial agglomeration and pollution discharges: a case study of 284 cities in China
    Chengzhen Song
    Yanbin Chen
    Guanwen Yin
    Yiming Hou
    [J]. Environmental Science and Pollution Research, 2023, 30 : 434 - 450