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Vehicular Emission Inventory and Reduction Scenario Analysis in the Yangtze River Delta, China

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  • Xiaowei Song

    (College of Resources and Environment, Shanxi University of Finance & Economics, Taiyuan 030006, China
    School of the Environment, Nanjing University, Nanjing 210046, China)

  • Yongpei Hao

    (College of Resources and Environment, Shanxi University of Finance & Economics, Taiyuan 030006, China
    Ministry of Education Key Laboratory for Coastal and Island Development, School of Geographic & Oceanographic Sciences, Nanjing University, Nanjing 210046, China)

Abstract

Vehicular emissions have become an important source of air pollution, and their effective reduction control is essential to protect the environment. The aim of this study was to establish multi-year vehicular emission inventories for ten important air pollutants and to analyze emission control policy scenarios based on these inventories. The inter-annual emission analysis results showed that the ten pollutant emissions had different change trends during the past decade. The emissions of CO, non-methane volatile organic compounds (NMVOC S ), NO x , PM 2.5 , PM 10 , and CH 4 tended to increase first and then decrease, but the years in which they began to decrease varied; the emissions of CO 2 and NH 3 showed the most significant growth trends, increasing by 567% and 4004% in 2015 compared with 1999, while the emissions of N 2 O and SO 2 showed a general increasing trend and decreased obviously in a certain year. Eight scenarios based on emission inventories were designed; compared with the BAU scenario, the ESV scenario was the most effective policy to control NO x , PM 2.5 , and CH 4 emissions; the radical AER scenario could decrease the vehicular emissions of CO, NMVOCs, PM 10 , CO 2 , N 2 O, and NH 3 ; and the RFS scenario could reduce vehicular SO 2 emissions significantly by 93.64%.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:23:p:4790-:d:292183
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    2. 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.

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