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The Evolution of the Spatial Association Effect of Carbon Emissions in Transportation: A Social Network Perspective

Author

Listed:
  • Fei Ma

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

  • Yixuan Wang

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

  • Kum Fai Yuen

    (Department of International Logistics, Chung-Ang University, Seoul 06974, Korea)

  • Wenlin Wang

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

  • Xiaodan Li

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

  • Yuan Liang

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

Abstract

The association effect between provincial transportation carbon emissions has become an important issue in regional carbon emission management. This study explored the relationship and development trends associated with regional transportation carbon emissions. A social network method was used to analyze the structural characteristics of the spatial association of transportation carbon emissions. Indicators for each of the structural characteristics were selected from three dimensions: The integral network, node network, and spatial clustering. Then, this study established an association network for transportation carbon emissions ( ANTCE ) using a gravity model with China’s provincial data during the period of 2007 to 2016. Further, a block model (a method of partitioning provinces based on the information of transportation carbon emission) was used to group the ANTCE network of inter-provincial transportation carbon emissions to examine the overall association structure. There were three key findings. First, the tightness of China’s ANTCE network is growing, and its complexity and robustness are gradually increasing. Second, China’s ANTCE network shows a structural characteristic of “dense east and thin west.” That is, the transportation carbon emissions of eastern provinces in China are highly correlated, while those of central and western provinces are less correlated. Third, the eastern provinces belong to the two-way spillover or net benefit block, the central regions belong to the broker block, and the western provinces belong to the net spillover block. This indicates that the transportation carbon emissions in the western regions are flowing to the eastern and central regions. Finally, a regression analysis using a quadratic assignment procedure (QAP) was used to explore the spatial association between provinces. We found that per capita gross domestic product (GDP) and fixed transportation investments significantly influence the association and spillover effects of the ANTCE network. The research findings provide a theoretical foundation for the development of policies that may better coordinate carbon emission mitigation in regional transportation.

Suggested Citation

  • Fei Ma & Yixuan Wang & Kum Fai Yuen & Wenlin Wang & Xiaodan Li & Yuan Liang, 2019. "The Evolution of the Spatial Association Effect of Carbon Emissions in Transportation: A Social Network Perspective," IJERPH, MDPI, vol. 16(12), pages 1-23, June.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:12:p:2154-:d:240829
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    References listed on IDEAS

    as
    1. D. S. Choi & P. J. Wolfe & E. M. Airoldi, 2012. "Stochastic blockmodels with a growing number of classes," Biometrika, Biometrika Trust, vol. 99(2), pages 273-284.
    2. Zhang, Chuanguo & Nian, Jiang, 2013. "Panel estimation for transport sector CO2 emissions and its affecting factors: A regional analysis in China," Energy Policy, Elsevier, vol. 63(C), pages 918-926.
    3. T. S. Breusch & A. R. Pagan, 1980. "The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 239-253.
    4. M. Hashem Pesaran, 2021. "General diagnostic tests for cross-sectional dependence in panels," Empirical Economics, Springer, vol. 60(1), pages 13-50, January.
    5. César Ducruet & Laurent Beauguitte, 2014. "Spatial Science and Network Science: Review and Outcomes of a Complex Relationship," Networks and Spatial Economics, Springer, vol. 14(3), pages 297-316, December.
    6. Ryan, Lisa & Ferreira, Susana & Convery, Frank, 2009. "The impact of fiscal and other measures on new passenger car sales and CO2 emissions intensity: Evidence from Europe," Energy Economics, Elsevier, vol. 31(3), pages 365-374, May.
    7. Xu, Helian & Cheng, Long, 2016. "The QAP weighted network analysis method and its application in international services trade," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 91-101.
    8. Hampf, Benjamin & Krüger, Jens, 2014. "Technical Efficiency of Automobiles - A Nonparametric Approach Incorporating Carbon Dioxide Emissions," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 69998, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    9. José Miguel Barrios & Willem W. Verstraeten & Piet Maes & Jean-Marie Aerts & Jamshid Farifteh & Pol Coppin, 2012. "Using the Gravity Model to Estimate the Spatial Spread of Vector-Borne Diseases," IJERPH, MDPI, vol. 9(12), pages 1-19, November.
    10. César Ducruet & Laurent Beauguitte, 2014. "Network science and spatial science : Review and outcomes of a complex relationship," Post-Print hal-03246947, HAL.
    11. Rafael E. De Hoyos & Vasilis Sarafidis, 2006. "Testing for cross-sectional dependence in panel-data models," Stata Journal, StataCorp LP, vol. 6(4), pages 482-496, December.
    12. Liao, Chun-Hsiung & Lu, Chin-Shan & Tseng, Po-Hsing, 2011. "Carbon dioxide emissions and inland container transport in Taiwan," Journal of Transport Geography, Elsevier, vol. 19(4), pages 722-728.
    13. Dieter Vanderelst, 2015. "Social Network Analysis As a Tool for Research Policy," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 9(12), pages 1-3, December.
    14. Bart Los & Bart Verspagen, 2009. "Localized innovation, localized diffusion and the environment: an analysis of reductions of CO 2 emissions by passenger cars," Journal of Evolutionary Economics, Springer, vol. 19(4), pages 507-526, August.
    15. Fei Ma & Wenlin Wang & Qipeng Sun & Fei Liu & Xiaodan Li, 2018. "Ecological Pressure of Carbon Footprint in Passenger Transport: Spatio-Temporal Changes and Regional Disparities," Sustainability, MDPI, vol. 10(2), pages 1-17, January.
    16. Ebohon, Obas John & Ikeme, Anthony Jekwu, 2006. "Decomposition analysis of CO2 emission intensity between oil-producing and non-oil-producing sub-Saharan African countries," Energy Policy, Elsevier, vol. 34(18), pages 3599-3611, December.
    17. Kiyong Keum, 2010. "Tourism flows and trade theory: a panel data analysis with the gravity model," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 44(3), pages 541-557, June.
    18. Hyun-Jin Kim & Jin-young Min & Yong-Seok Seo & Kyoung-bok Min, 2019. "Association of Ambient Air Pollution with Increased Liver Enzymes in Korean Adults," IJERPH, MDPI, vol. 16(7), pages 1-10, April.
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    2. Haidong Gao & Tiantian Li & Jing Yu & Yangrui Sun & Shijie Xie, 2023. "Spatial Correlation Network Structure of Carbon Emission Efficiency in China’s Construction Industry and Its Formation Mechanism," Sustainability, MDPI, vol. 15(6), pages 1-23, March.
    3. Yiyang Sun & Guolin Hou, 2021. "Analysis on the Spatial-Temporal Evolution Characteristics and Spatial Network Structure of Tourism Eco-Efficiency in the Yangtze River Delta Urban Agglomeration," IJERPH, MDPI, vol. 18(5), pages 1-29, March.
    4. Xiaoxuan Wei & Meng Ye & Liang Yuan & Wei Bi & Weisheng Lu, 2022. "Analyzing the Freight Characteristics and Carbon Emission of Construction Waste Hauling Trucks: Big Data Analytics of Hong Kong," IJERPH, MDPI, vol. 19(4), pages 1-21, February.
    5. Jiekun Song & Huisheng Xiao & Zhicheng Liu, 2024. "Analysis of the Driving Mechanism of Urban Carbon Emission Correlation Network in Shandong Province Based on TERGM," Sustainability, MDPI, vol. 16(10), pages 1-24, May.
    6. Yuhao Yang & Fengying Yan, 2023. "An Inquiry into the Characteristics of Carbon Emissions in Inter-Provincial Transportation in China: Aiming to Typological Strategies for Carbon Reduction in Regional Transportation," Land, MDPI, vol. 13(1), pages 1-24, December.
    7. Hailing Wu & Yuanjun Li & Kaihuai Liao & Qitao Wu & Kanhai Shen, 2024. "Structural Characteristics of Expressway Carbon Emission Correlation Network and Its Influencing Factors: A Case Study in Guangdong Province," Sustainability, MDPI, vol. 16(22), pages 1-20, November.
    8. Jia-Bao Liu & Xin-Bei Peng & Jing Zhao, 2023. "Analyzing the spatial association of household consumption carbon emission structure based on social network," Journal of Combinatorial Optimization, Springer, vol. 45(2), pages 1-34, March.

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