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A Comprehensive 2018-Based Vehicle Emission Inventory and Its Spatial–Temporal Characteristics in the Central Liaoning Urban Agglomeration, China

Author

Listed:
  • Yingying Liu

    (State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
    These authors contributed equally to this work.)

  • Xueyan Zhao

    (State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
    These authors contributed equally to this work.)

  • Jing Wang

    (State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China)

  • Shengnan Zhu

    (Shenyang Academy of Environmental Sciences, Shenyang 110167, China)

  • Bin Han

    (State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China)

  • Di Zhao

    (Shenyang Academy of Environmental Sciences, Shenyang 110167, China)

  • Xinhua Wang

    (State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China)

  • Chunmei Geng

    (State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China)

Abstract

Rapid economic expansion and urbanisation have seriously affected the atmospheric environmental quality of the Central Liaoning Urban Agglomeration (CLUA). This study aimed to establish a detailed vehicle emission inventory of the CLUA with a 3 km × 3 km gridded spatiotemporal distribution. A top-down methodology using vehicle kilometres travelled annually, emission factors, and activity data of each city was established. Carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO 2 ), ammonia (NH 3 ), volatile organic compounds (VOCs), particulate matter with an aerodynamic diameter less than 2.5 μm (PM 2.5 ), particulate matter with an aerodynamic diameter less than 10 μm (PM 10 ), Black Carbon (BC), and organic carbon (OC) emissions were 291.0, 221.8, 3.6, 2.2, 42.8, 9.3, 10.3, 5.2, and 1.6 Gg in 2018, respectively. The contribution of diesel heavy-duty trucks to NOx, SO 2 , PM 2.5 , PM 10 , BC, and OC emissions was greater than 54.5%, the largest contribution of all vehicles. Gasoline small passenger vehicles were the primary contributor to CO, VOC, and NH 3 emissions, contributing 37.3%, 39.5%, and 75.3% of total emissions, respectively. For emission standards, Pre-China 1 vehicles were the largest contributor to CO and VOC emissions and China 3 vehicles contributed the largest amount of NOx, SO 2 , PM 2.5 , PM 10 , BC, and OC emissions. The spatial distribution of pollutants showed “obvious lines” and grids with high emissions were concentrated in expressways, national highways, and provincial highways. The temporal variation showed morning–evening peaks during diurnal variations, which was consistent with resident behaviour. This work can help us understand vehicular emission characteristics of the CLUA and provide basic data for air quality modelling. Future research should investigate traffic flow by vehicle types and emission factors at a local level, which will be helpful for transport management planning.

Suggested Citation

  • Yingying Liu & Xueyan Zhao & Jing Wang & Shengnan Zhu & Bin Han & Di Zhao & Xinhua Wang & Chunmei Geng, 2022. "A Comprehensive 2018-Based Vehicle Emission Inventory and Its Spatial–Temporal Characteristics in the Central Liaoning Urban Agglomeration, China," IJERPH, MDPI, vol. 19(4), pages 1-19, February.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:4:p:2033-:d:747185
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    References listed on IDEAS

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    1. Xiaowei Song & Yongpei Hao, 2019. "Vehicular Emission Inventory and Reduction Scenario Analysis in the Yangtze River Delta, China," IJERPH, MDPI, vol. 16(23), pages 1-21, November.
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    Cited by:

    1. Li, Xiang & Yan, Xiaoyu, 2024. "Fast penetration of electric vehicles in China cannot achieve steep cuts in air emissions from road transport without synchronized renewable electricity expansion," Energy, Elsevier, vol. 301(C).

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