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Emission Variations of Primary Air Pollutants from Highway Vehicles and Implications during the COVID-19 Pandemic in Beijing, China

Author

Listed:
  • Xizi Cao

    (National Engineering Research Center of Urban Environmental Pollution Control, Beijing Municipal Research Institute of Environmental Protection, Beijing 100037, China)

  • Ye Tian

    (Beijing Municipal Ecology and Environment Bureau, Beijing 100048, China)

  • Yan Shen

    (National Engineering Research Center of Urban Environmental Pollution Control, Beijing Municipal Research Institute of Environmental Protection, Beijing 100037, China)

  • Tongran Wu

    (National Engineering Research Center of Urban Environmental Pollution Control, Beijing Municipal Research Institute of Environmental Protection, Beijing 100037, China)

  • Renfei Li

    (National Engineering Research Center of Urban Environmental Pollution Control, Beijing Municipal Research Institute of Environmental Protection, Beijing 100037, China)

  • Xinyu Liu

    (National Engineering Research Center of Urban Environmental Pollution Control, Beijing Municipal Research Institute of Environmental Protection, Beijing 100037, China)

  • Amanzheli Yeerken

    (National Engineering Research Center of Urban Environmental Pollution Control, Beijing Municipal Research Institute of Environmental Protection, Beijing 100037, China)

  • Yangyang Cui

    (National Engineering Research Center of Urban Environmental Pollution Control, Beijing Municipal Research Institute of Environmental Protection, Beijing 100037, China)

  • Yifeng Xue

    (National Engineering Research Center of Urban Environmental Pollution Control, Beijing Municipal Research Institute of Environmental Protection, Beijing 100037, China)

  • Aiping Lian

    (Beijing Municipal Ecology and Environment Bureau, Beijing 100048, China)

Abstract

According to the traffic flow variation from January 2019 to August 2020, emissions of primary air pollutants from highway vehicles were calculated based on the emission factor method, which integrated the actual structure of on-road vehicles. The characteristics of on-highway traffic flow and pollution emissions were compared during various progression stages of coronavirus disease (COVID-19). The results showed that the average daily traffic volume decreased by 38.2% in 2020, with a decrease of 62% during the strict lockdown due to the impact of COVID-19. The daily emissions of primary atmospheric pollutants decreased by 29.2% in 2020 compared to the same period in 2019. As for the structure of on-highway vehicle types, the small and medium-sized passenger vehicles predominated, which accounted for 76.3% of traffic, while trucks and large passenger vehicles accounted for 19.7% and 4.0%, but contributed 58.4% and 33.9% of nitrogen oxide (NO x ) emissions, respectively. According to the simulation results of the ADMS model, the average concentrations of NO x were reduced by 12.0 µg/m 3 compared with the same period in 2019. As for the implication for future pollution control, it is necessary to further optimize the structure of on-highway and the road traffic vehicle types and increase the proportions of new-energy vehicles and vehicles with high emission standards.

Suggested Citation

  • Xizi Cao & Ye Tian & Yan Shen & Tongran Wu & Renfei Li & Xinyu Liu & Amanzheli Yeerken & Yangyang Cui & Yifeng Xue & Aiping Lian, 2021. "Emission Variations of Primary Air Pollutants from Highway Vehicles and Implications during the COVID-19 Pandemic in Beijing, China," IJERPH, MDPI, vol. 18(8), pages 1-12, April.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:8:p:4019-:d:534236
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    References listed on IDEAS

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    1. Zeng, Jun-Wei & Qian, Yong-Sheng & Yu, Sen-Bin & Wei, Xu-Ting, 2019. "Research on critical characteristics of highway traffic flow based on three phase traffic theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 530(C).
    2. Ren, Lei & Zhou, Sheng & Ou, Xunmin, 2020. "Life-cycle energy consumption and greenhouse-gas emissions of hydrogen supply chains for fuel-cell vehicles in China," Energy, Elsevier, vol. 209(C).
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    Cited by:

    1. Ka-Ming Wai & Peter K. N. Yu, 2023. "Application of a Machine Learning Method for Prediction of Urban Neighborhood-Scale Air Pollution," IJERPH, MDPI, vol. 20(3), pages 1-10, January.

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