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Using Grey Relational Analysis to Evaluate Energy Consumption, CO 2 Emissions and Growth Patterns in China’s Provincial Transportation Sectors

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Listed:
  • Changwei Yuan

    (School of Economics and Management, Chang’an University, Xi’an 710064, China)

  • Dayong Wu

    (Department of Civil, Environmental and Construction Engineering, Texas Tech University, Lubbock 79409, TX 79409, USA)

  • Hongchao Liu

    (Department of Civil, Environmental and Construction Engineering, Texas Tech University, Lubbock 79409, TX 79409, USA)

Abstract

The transportation sector is a complex system. Collecting transportation activity and the associated emissions data is extremely expensive and time-consuming. Grey Relational Analysis provides a viable alternative to overcome data insufficiency and gives insights for decision makers into such a complex system. In this paper, we achieved three major goals: (i) we explored the inter-relationships among transportation development, energy consumption and CO 2 emissions for 30 provincial units in China; (ii) we identified the transportation development mode for each individual province; and (iii) we revealed policy implications regarding the sustainable transportation development at the provincial level. We can classify the 30 provinces into eight development modes according to the calculated Grey Relational Grades. Results also indicated that energy consumption has the largest influence on CO 2 emission changes. Lastly, sustainable transportation policies were discussed at the province level according to the level of economy, urbanization and transportation energy structure.

Suggested Citation

  • Changwei Yuan & Dayong Wu & Hongchao Liu, 2017. "Using Grey Relational Analysis to Evaluate Energy Consumption, CO 2 Emissions and Growth Patterns in China’s Provincial Transportation Sectors," IJERPH, MDPI, vol. 14(12), pages 1-16, December.
    • Handle: RePEc:gam:jijerp:v:14:y:2017:i:12:p:1536-:d:122228
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    References listed on IDEAS

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    1. Yang, Yuan & Wang, Can & Liu, Wenling & Zhou, Peng, 2017. "Microsimulation of low carbon urban transport policies in Beijing," Energy Policy, Elsevier, vol. 107(C), pages 561-572.
    2. Yuan, Chaoqing & Liu, Sifeng & Fang, Zhigeng & Xie, Naiming, 2010. "The relation between Chinese economic development and energy consumption in the different periods," Energy Policy, Elsevier, vol. 38(9), pages 5189-5198, September.
    3. Yan Lu & Haikun Wang & Qin’geng Wang & Yanyan Zhang & Yiyong Yu & Yu Qian, 2017. "Global anthropogenic heat emissions from energy consumption, 1965–2100," Climatic Change, Springer, vol. 145(3), pages 459-468, December.
    4. Zhang, Ming & Li, Huanan & Zhou, Min & Mu, Hailin, 2011. "Decomposition analysis of energy consumption in Chinese transportation sector," Applied Energy, Elsevier, vol. 88(6), pages 2279-2285, June.
    5. Loo, Becky P.Y. & Li, Linna, 2012. "Carbon dioxide emissions from passenger transport in China since 1949: Implications for developing sustainable transport," Energy Policy, Elsevier, vol. 50(C), pages 464-476.
    6. Pao, Hsiao-Tien & Fu, Hsin-Chia & Tseng, Cheng-Lung, 2012. "Forecasting of CO2 emissions, energy consumption and economic growth in China using an improved grey model," Energy, Elsevier, vol. 40(1), pages 400-409.
    7. Lin, Sue J. & Lu, I.J. & Lewis, Charles, 2007. "Grey relation performance correlations among economics, energy use and carbon dioxide emission in Taiwan," Energy Policy, Elsevier, vol. 35(3), pages 1948-1955, March.
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    Cited by:

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    2. Mengqi Fu & Yanyan Yang & Yong Li & Huanqin Wang & Fajun Yu & Juan Liu, 2023. "Beijing Heavy-Duty Diesel Vehicle Battery Capacity Conversion and Emission Estimation in 2022," Sustainability, MDPI, vol. 15(14), pages 1-14, July.

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