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Spatial Characteristics and Factor Analysis of Pollution Emission from Heavy-Duty Diesel Trucks in the Beijing–Tianjin–Hebei Region, China

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  • Beibei Zhang

    (The Academy of Digital China, Fuzhou University, Fuzhou 350002, China
    State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Sheng Wu

    (The Academy of Digital China, Fuzhou University, Fuzhou 350002, China)

  • Shifen Cheng

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Feng Lu

    (The Academy of Digital China, Fuzhou University, Fuzhou 350002, China
    State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Peng Peng

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

Heavy-duty diesel trucks (HDDTs) contribute significantly to NO X and particulate matter (PM) pollution. Although existing studies have emphasized that HDDTs play a dominant role in vehicular pollution, the spatial distribution pattern of HDDT emissions and their related socioeconomic factors are unclear. To fill this research gap, this study investigates the spatial distribution pattern and spatial autocorrelation characteristics of NO X , PM, and SO 2 emissions from HDDTs in 200 districts and counties of the Beijing–Tianjin–Hebei (BTH) region. We used the spatial lag model to calculate the significances and directions of the pollutants from HDDTs and their related socioeconomic factors, namely, per capita GDP, population density, urbanization rate, and proportions of secondary and tertiary industries. Then, the geographical detector technique was applied to quantify the strengths of the significant socioeconomic factors of HDDT emissions. The results show that (1) NO X , PM, and SO 2 pollutants emitted by HDDTs in the BTH region have spatial heterogeneity, i.e., low in the north and high in the east and south. (2) The pollutants from HDDTs in the BTH region have significant spatial autocorrelation characteristics. The spatial dependence effect was obvious; for every 1% increase in the HDDT emissions in the surrounding districts and counties, the local HDDT emissions increased by 0.39%. (3) Related factors analysis showed that the proportion of tertiary industries had a significant negative correlation, whereas the proportion of secondary industries and urbanization rate had significant positive correlations with HDDT emissions. Population density and per capita GDP did not pass the significance test. (4) The order of effect intensities of the significant socioeconomic factors was proportion of tertiary industry > proportion of secondary industry > urbanization rate. This study guides scientific decision making for pollution control of HDDTs in the BTH region.

Suggested Citation

  • Beibei Zhang & Sheng Wu & Shifen Cheng & Feng Lu & Peng Peng, 2019. "Spatial Characteristics and Factor Analysis of Pollution Emission from Heavy-Duty Diesel Trucks in the Beijing–Tianjin–Hebei Region, China," IJERPH, MDPI, vol. 16(24), pages 1-16, December.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:24:p:4973-:d:295250
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    References listed on IDEAS

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    2. Xie, Rui & Wei, Dihan & Han, Feng & Lu, Yue & Fang, Jiayu & Liu, Yu & Wang, Junfeng, 2019. "The effect of traffic density on smog pollution: Evidence from Chinese cities," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 421-427.
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