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Modeling Air Pollutant Emissions in the Provincial Level Road Transportation Sector in Korea: A Case Study of the Zero-Emission Vehicle Subsidy

Author

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  • Minyoung Roh

    (Department of Energy Systems Research, Ajou University, Suwon 16449, Korea)

  • Seungho Jeon

    (Department of Energy Systems Research, Ajou University, Suwon 16449, Korea)

  • Soontae Kim

    (Department of Environmental Engineering, Ajou University, Suwon 16449, Korea)

  • Sha Yu

    (Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD 20740, USA)

  • Almas Heshmati

    (Jönköping International Business School (JIBS), Jönköping University, P.O. Box 1026, SE-551 11 Jönköping, Sweden)

  • Suduk Kim

    (Department of Energy Systems Research, Ajou University, Suwon 16449, Korea)

Abstract

South Korea has been suffering from high PM 2.5 pollution. Previous studies have contributed to establishing PM 2.5 mitigation policies but have not considered provincial features and sector-interactions. In that sense, the integrated assessment model (IAM) could complement the shortcomings of previous studies. IAM, capable of analyzing PM 2.5 pollution levels at the provincial level in Korea, however, has not been developed yet. Hence, this study (i) expands on IAM which can represent provincial-level spatial resolution in Korea (GCAM-Korea) with air pollutant emissions modeling which focuses on the road transportation sector and (ii) examines the zero-emission vehicles (ZEVs) subsidy policy’s effects on PM 2.5 mitigation using the expanded GCAM-Korea. Simulation results show that PM 2.5 emissions decrease by 0.6–4.1% compared to the baseline, and the Seoul metropolitan area contributes 38–44% to the overall PM 2.5 emission reductions. As the ZEVs subsidy is weighted towards the light-duty vehicle 4-wheels (LDV4W) sector, various spillover effects are found: ZEVs’ share rises intensively in the LDV4W sector leading to an increase in its service costs, and at the same time, driving bus service costs to become relatively cheaper. This, in turn, drives an increase in bus service demand and emissions discharge. Furthermore, this type of impact of the ZEVs subsidy policy does not reduce internal combustion engine vehicles (ICEVs) in freight trucks, although diesel freight trucks are a major contributor to PM 2.5 emissions and also to NO x .

Suggested Citation

  • Minyoung Roh & Seungho Jeon & Soontae Kim & Sha Yu & Almas Heshmati & Suduk Kim, 2020. "Modeling Air Pollutant Emissions in the Provincial Level Road Transportation Sector in Korea: A Case Study of the Zero-Emission Vehicle Subsidy," Energies, MDPI, vol. 13(15), pages 1-22, August.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:15:p:3999-:d:393851
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    References listed on IDEAS

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    1. Seungho Jeon & Minyoung Roh & Jaeick Oh & Suduk Kim, 2020. "Development of an Integrated Assessment Model at Provincial Level: GCAM-Korea," Energies, MDPI, vol. 13(10), pages 1-15, May.
    2. Daniel Trnka, 2020. "Policies, regulatory framework and enforcement for air quality management: The case of Korea," OECD Environment Working Papers 158, OECD Publishing.
    3. Jae Edmonds & Marshall Wise & Hugh Pitcher & Richard Richels & Tom Wigley & Chris Maccracken, 1997. "An integrated assessment of climate change and the accelerated introduction of advanced energy technologies," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 1(4), pages 311-339, December.
    4. Yang Ou & J. Jason West & Steven J. Smith & Christopher G. Nolte & Daniel H. Loughlin, 2020. "Air pollution control strategies directly limiting national health damages in the US," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
    5. Kriegler, Elmar & Petermann, Nils & Krey, Volker & Schwanitz, Valeria Jana & Luderer, Gunnar & Ashina, Shuichi & Bosetti, Valentina & Eom, Jiyong & Kitous, Alban & Méjean, Aurélie & Paroussos, Leonida, 2015. "Diagnostic indicators for integrated assessment models of climate policy," Technological Forecasting and Social Change, Elsevier, vol. 90(PA), pages 45-61.
    6. Son H. Kim, Jae Edmonds, Josh Lurz, Steven J. Smith, and Marshall Wise, 2006. "The objECTS Framework for integrated Assessment: Hybrid Modeling of Transportation," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 63-92.
    7. Yu, Sha & Yarlagadda, Brinda & Siegel, Jonas Elliott & Zhou, Sheng & Kim, Sonny, 2020. "The role of nuclear in China's energy future: Insights from integrated assessment," Energy Policy, Elsevier, vol. 139(C).
    8. Yu, Sha & Tan, Qing & Evans, Meredydd & Kyle, Page & Vu, Linh & Patel, Pralit L., 2017. "Improving building energy efficiency in India: State-level analysis of building energy efficiency policies," Energy Policy, Elsevier, vol. 110(C), pages 331-341.
    9. Zulfikar Yurnaidi & Suduk Kim, 2018. "Reducing Biomass Utilization in the Ethiopia Energy System: A National Modeling Analysis," Energies, MDPI, vol. 11(7), pages 1-17, July.
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    Cited by:

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    2. Jeseok Ryu & Jinho Kim, 2020. "Demand Response Program Expansion in Korea through Particulate Matter Forecasting Based on Deep Learning and Fuzzy Inference," Energies, MDPI, vol. 13(23), pages 1-14, December.
    3. Thomas M. T. Lei & Martin F. C. Ma, 2023. "The Relationship between Roadside PM Concentration and Traffic Characterization: A Case Study in Macao," Sustainability, MDPI, vol. 15(14), pages 1-14, July.

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