IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i14p5065-d384287.html
   My bibliography  Save this article

Spatiotemporal Evolution of Global Greenhouse Gas Emissions Transferring via Trade: Influencing Factors and Policy Implications

Author

Listed:
  • Zhangqi Zhong

    (School of Economics, Zhejiang University of Finance & Economics, Hangzhou 310018, China
    Center for Regional Economy & Integrated Development, Zhejiang University of Finance & Economics, Hangzhou 310018, China)

  • Xu Zhang

    (School of Economics, Zhejiang University of Finance & Economics, Hangzhou 310018, China)

  • Weina Gao

    (The New Types Key Think Tank of Zhejiang Province, China Research Institute of Regulation and Public Policy, Zhejiang University of Finance & Economics, Hangzhou 310018, China
    China Institute of Regulation Research, Zhejiang University of Finance & Economics, Hangzhou 310018, China)

Abstract

Global climate change caused by greenhouse gas emissions (GHGs) from anthropogenic activities have already become the focus of the world. A more systematic and comprehensive analysis on the factors influencing the changes of global GHGs transferring via trade have not been fully discussed. To this end, employing spatial econometric regression models and multi-regional input-output models, this paper reveals factors influencing the GHGs transferring via trade changes in 39 major economies, so as to develop the relevant GHGs reduction policies. The results indicate that regions with the highest net outflow of GHGs transferring via trade are primarily Russia and Canada, and the adverse effects of promoting GHGs reduction on the national economy could be avoided by these regions owing to trade relations. Additionally, factors influencing the changes in GHGs transferring via trade have significant spatial autocorrelation, and population size and energy structure exert significant spatial spillover effects on the changes in the GHGs transferring via trade. On this basis, this paper suggests that one more effective way to prevent trade from the rigorous demands of environmental governance measures while preserving the economic benefits of international trade may be to facilitate cooperation between countries on GHGs mitigation. Further, we articulate more balanced environment governance policies, including conducting the sharing of advanced energy technologies and developing clearer production technologies.

Suggested Citation

  • Zhangqi Zhong & Xu Zhang & Weina Gao, 2020. "Spatiotemporal Evolution of Global Greenhouse Gas Emissions Transferring via Trade: Influencing Factors and Policy Implications," IJERPH, MDPI, vol. 17(14), pages 1-24, July.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:14:p:5065-:d:384287
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/14/5065/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/17/14/5065/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shahbaz, Muhammad & Nasreen, Samia & Ahmed, Khalid & Hammoudeh, Shawkat, 2017. "Trade openness–carbon emissions nexus: The importance of turning points of trade openness for country panels," Energy Economics, Elsevier, vol. 61(C), pages 221-232.
    2. Cohen, Gail & Jalles, Joao Tovar & Loungani, Prakash & Marto, Ricardo & Wang, Gewei, 2019. "Decoupling of emissions and GDP: Evidence from aggregate and provincial Chinese data," Energy Economics, Elsevier, vol. 77(C), pages 105-118.
    3. Cox, Adam & Collins, Alan & Woods, Lee & Ferguson, Neil, 2012. "A household level environmental Kuznets curve? Some recent evidence on transport emissions and income," Economics Letters, Elsevier, vol. 115(2), pages 187-189.
    4. Sanchez, Luis F. & Stern, David I., 2016. "Drivers of industrial and non-industrial greenhouse gas emissions," Ecological Economics, Elsevier, vol. 124(C), pages 17-24.
    5. Zhong, Zhangqi & Jiang, Lei & Zhou, Peng, 2018. "Transnational transfer of carbon emissions embodied in trade: Characteristics and determinants from a spatial perspective," Energy, Elsevier, vol. 147(C), pages 858-875.
    6. Chen, G.Q. & Chen, Z.M., 2011. "Greenhouse gas emissions and natural resources use by the world economy: Ecological input–output modeling," Ecological Modelling, Elsevier, vol. 222(14), pages 2362-2376.
    7. Pablo-Romero, María del P. & Sánchez-Braza, Antonio, 2017. "The changing of the relationships between carbon footprints and final demand: Panel data evidence for 40 major countries," Energy Economics, Elsevier, vol. 61(C), pages 8-20.
    8. Ji, Ling & Liang, Sai & Qu, Shen & Zhang, Yanxia & Xu, Ming & Jia, Xiaoping & Jia, Yingtao & Niu, Dongxiao & Yuan, Jiahai & Hou, Yong & Wang, Haikun & Chiu, Anthony S.F. & Hu, Xiaojun, 2016. "Greenhouse gas emission factors of purchased electricity from interconnected grids," Applied Energy, Elsevier, vol. 184(C), pages 751-758.
    9. Jiang, Lei & He, Shixiong & Zhong, Zhangqi & Zhou, Haifeng & He, Lingyun, 2019. "Revisiting environmental kuznets curve for carbon dioxide emissions: The role of trade," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 245-257.
    10. Robert W. R. Parker & Julia L. Blanchard & Caleb Gardner & Bridget S. Green & Klaas Hartmann & Peter H. Tyedmers & Reg A. Watson, 2018. "Fuel use and greenhouse gas emissions of world fisheries," Nature Climate Change, Nature, vol. 8(4), pages 333-337, April.
    11. Liu, Zhu & Geng, Yong & Lindner, Soeren & Guan, Dabo, 2012. "Uncovering China’s greenhouse gas emission from regional and sectoral perspectives," Energy, Elsevier, vol. 45(1), pages 1059-1068.
    12. Davis, Matthew & Ahiduzzaman, Md. & Kumar, Amit, 2018. "How will Canada’s greenhouse gas emissions change by 2050? A disaggregated analysis of past and future greenhouse gas emissions using bottom-up energy modelling and Sankey diagrams," Applied Energy, Elsevier, vol. 220(C), pages 754-786.
    13. Griffin, Paul W. & Hammond, Geoffrey P., 2019. "Industrial energy use and carbon emissions reduction in the iron and steel sector: A UK perspective," Applied Energy, Elsevier, vol. 249(C), pages 109-125.
    14. Li, Xin & Chalvatzis, Konstantinos J. & Pappas, Dimitrios, 2018. "Life cycle greenhouse gas emissions from power generation in China’s provinces in 2020," Applied Energy, Elsevier, vol. 223(C), pages 93-102.
    15. Wen-Wen Zhang & Basil Sharp & Shi-Chun Xu, 2019. "Does economic growth and energy consumption drive environmental degradation in China’s 31 provinces? New evidence from a spatial econometric perspective," Applied Economics, Taylor & Francis Journals, vol. 51(42), pages 4658-4671, September.
    16. Chen, G.Q. & Zhang, Bo, 2010. "Greenhouse gas emissions in China 2007: Inventory and input-output analysis," Energy Policy, Elsevier, vol. 38(10), pages 6180-6193, October.
    17. Mi, Zhifu & Zhang, Yunkun & Guan, Dabo & Shan, Yuli & Liu, Zhu & Cong, Ronggang & Yuan, Xiao-Chen & Wei, Yi-Ming, 2016. "Consumption-based emission accounting for Chinese cities," Applied Energy, Elsevier, vol. 184(C), pages 1073-1081.
    18. Mi, Zhifu & Zheng, Jiali & Meng, Jing & Zheng, Heran & Li, Xian & Coffman, D'Maris & Woltjer, Johan & Wang, Shouyang & Guan, Dabo, 2019. "Carbon emissions of cities from a consumption-based perspective," Applied Energy, Elsevier, vol. 235(C), pages 509-518.
    19. Chen, B. & Li, J.S. & Zhou, S.L. & Yang, Q. & Chen, G.Q., 2018. "GHG emissions embodied in Macao's internal energy consumption and external trade: Driving forces via decomposition analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 4100-4106.
    20. Maenpaa, Ilmo & Siikavirta, Hanne, 2007. "Greenhouse gases embodied in the international trade and final consumption of Finland: An input-output analysis," Energy Policy, Elsevier, vol. 35(1), pages 128-143, January.
    21. Geniaux, Ghislain & Martinetti, Davide, 2018. "A new method for dealing simultaneously with spatial autocorrelation and spatial heterogeneity in regression models," Regional Science and Urban Economics, Elsevier, vol. 72(C), pages 74-85.
    22. Jiang, Xuemei & Green, Christopher, 2017. "The Impact on Global Greenhouse Gas Emissions of Geographic Shifts in Global Supply Chains," Ecological Economics, Elsevier, vol. 139(C), pages 102-114.
    23. Xu, Ning & Ding, Song & Gong, Yande & Bai, Ju, 2019. "Forecasting Chinese greenhouse gas emissions from energy consumption using a novel grey rolling model," Energy, Elsevier, vol. 175(C), pages 218-227.
    24. Berghout, Niels & Meerman, Hans & van den Broek, Machteld & Faaij, André, 2019. "Assessing deployment pathways for greenhouse gas emissions reductions in an industrial plant – A case study for a complex oil refinery," Applied Energy, Elsevier, vol. 236(C), pages 354-378.
    25. Wang, H. & Ang, B.W., 2018. "Assessing the role of international trade in global CO2 emissions: An index decomposition analysis approach," Applied Energy, Elsevier, vol. 218(C), pages 146-158.
    26. James P. LeSage & R. Kelley Pace, 2018. "Spatial econometric Monte Carlo studies: raising the bar," Empirical Economics, Springer, vol. 55(1), pages 17-34, August.
    27. P Burridge, 1981. "Testing for a Common Factor in a Spatial Autoregression Model," Environment and Planning A, , vol. 13(7), pages 795-800, July.
    28. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
    29. Lawrence D. LaPlue & Christopher A. Erickson, 2020. "Outsourcing, trade, technology, and greenhouse gas emissions," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 22(2), pages 217-245, April.
    30. Zhang, Youguo, 2017. "Interregional carbon emission spillover–feedback effects in China," Energy Policy, Elsevier, vol. 100(C), pages 138-148.
    31. Zhang, Bo & Yang, T.R. & Chen, B. & Sun, X.D., 2016. "China’s regional CH4 emissions: Characteristics, interregional transfer and mitigation policies," Applied Energy, Elsevier, vol. 184(C), pages 1184-1195.
    32. Chen, B. & Yang, Q. & Li, J.S. & Chen, G.Q., 2017. "Decoupling analysis on energy consumption, embodied GHG emissions and economic growth — The case study of Macao," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 662-672.
    33. Vinicius A. Vale & Fernando S. Perobelli & Ariaster B. Chimeli, 2018. "International trade, pollution, and economic structure: evidence on CO2 emissions for the North and the South," Economic Systems Research, Taylor & Francis Journals, vol. 30(1), pages 1-17, January.
    34. Liu, Lirong & Huang, Guohe & Baetz, Brian & Zhang, Kaiqiang, 2018. "Environmentally-extended input-output simulation for analyzing production-based and consumption-based industrial greenhouse gas mitigation policies," Applied Energy, Elsevier, vol. 232(C), pages 69-78.
    35. Zhang, Dongyu & Liu, Gengyuan & Chen, Caocao & Zhang, Yan & Hao, Yan & Casazza, Marco, 2019. "Medium-to-long-term coupled strategies for energy efficiency and greenhouse gas emissions reduction in Beijing (China)," Energy Policy, Elsevier, vol. 127(C), pages 350-360.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Valeria Ferreira & Laia Pié & Antonio Terceño, 2020. "The Role of the Foreign Sector in the Spanish Bioeconomy: Two Approaches Based on SAM Linear Models," IJERPH, MDPI, vol. 17(24), pages 1-25, December.
    2. Nejati, Mehdi & Shah, Muhammad Ibrahim, 2023. "How does ICT trade shape environmental impacts across the north-south regions? Intra-regional and Inter-regional perspective from dynamic CGE model," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    3. Tingzhu Li & Debin Du & Xueli Wang & Xionghe Qin, 2022. "Can Nuclear Power Products Mitigate Greenhouse Gas Emissions? Evidence from Global Trade Network," IJERPH, MDPI, vol. 19(13), pages 1-25, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhong, Zhangqi & Guo, Zhifang & Zhang, Jianwu, 2021. "Does the participation in global value chains promote interregional carbon emissions transferring via trade? Evidence from 39 major economies," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    2. Zhong, Zhangqi & Jiang, Lei & Zhou, Peng, 2018. "Transnational transfer of carbon emissions embodied in trade: Characteristics and determinants from a spatial perspective," Energy, Elsevier, vol. 147(C), pages 858-875.
    3. Zhangqi, Zhong & Zhuli, Chen & Lingyun, He, 2022. "Technological innovation, industrial structural change and carbon emission transferring via trade-------An agent-based modeling approach," Technovation, Elsevier, vol. 110(C).
    4. Hong, Jingke & Shen, Qiping & Xue, Fan, 2016. "A multi-regional structural path analysis of the energy supply chain in China's construction industry," Energy Policy, Elsevier, vol. 92(C), pages 56-68.
    5. Li, Jia Shuo & Zhou, H.W. & Meng, Jing & Yang, Q. & Chen, B. & Zhang, Y.Y., 2018. "Carbon emissions and their drivers for a typical urban economy from multiple perspectives: A case analysis for Beijing city," Applied Energy, Elsevier, vol. 226(C), pages 1076-1086.
    6. Ghazala Aziz & Zouheir Mighri, 2022. "Carbon Dioxide Emissions and Forestry in China: A Spatial Panel Data Approach," Sustainability, MDPI, vol. 14(19), pages 1-40, October.
    7. Zhang, Yu & Tian, Kailan & Li, Xiaomeng & Jiang, Xuemei & Yang, Cuihong, 2022. "From globalization to regionalization? Assessing its potential environmental and economic effects," Applied Energy, Elsevier, vol. 310(C).
    8. Jiang, Lei & He, Shixiong & Zhong, Zhangqi & Zhou, Haifeng & He, Lingyun, 2019. "Revisiting environmental kuznets curve for carbon dioxide emissions: The role of trade," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 245-257.
    9. Haider Mahmood & Maham Furqan & Muhammad Shahid Hassan & Soumen Rej, 2023. "The Environmental Kuznets Curve (EKC) Hypothesis in China: A Review," Sustainability, MDPI, vol. 15(7), pages 1-32, April.
    10. Li, Y.L. & Chen, B. & Chen, G.Q., 2020. "Carbon network embodied in international trade: Global structural evolution and its policy implications," Energy Policy, Elsevier, vol. 139(C).
    11. Hongguang Liu & Xiaomei Fan, 2017. "Value-Added-Based Accounting of CO 2 Emissions: A Multi-Regional Input-Output Approach," Sustainability, MDPI, vol. 9(12), pages 1-18, December.
    12. Zhang, Jianhua & Ballas, Dimitris & Liu, Xiaolong, 2023. "Neighbourhood-level spatial determinants of residential solar photovoltaic adoption in the Netherlands," Renewable Energy, Elsevier, vol. 206(C), pages 1239-1248.
    13. Ridwan Lanre Ibrahim & Kazeem Bello Ajide, 2022. "Trade facilitation and environmental quality: empirical evidence from some selected African countries," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(1), pages 1282-1312, January.
    14. Hanen Ragoubi & Zouheir Mighri, 2021. "Spillover effects of trade openness on CO2 emissions in middle‐income countries: A spatial panel data approach," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(3), pages 835-877, June.
    15. Zhou, Zhanhang & Zeng, Chen & Li, Keke & Yang, Yuemin & Zhao, Kuokuo & Wang, Zhen, 2024. "Decomposition of the decoupling between electricity CO2 emissions and economic growth: A production and consumption perspective," Energy, Elsevier, vol. 293(C).
    16. Fan, Xiaojia & Wu, Sanmang & Li, Shantong, 2019. "Spatial-temporal analysis of carbon emissions embodied in interprovincial trade and optimization strategies: A case study of Hebei, China," Energy, Elsevier, vol. 185(C), pages 1235-1249.
    17. Hong, Jingke & Shen, Geoffrey Qiping & Guo, Shan & Xue, Fan & Zheng, Wei, 2016. "Energy use embodied in China׳s construction industry: A multi-regional input–output analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1303-1312.
    18. Zhen, Wei & Qin, Quande & Wei, Yi-Ming, 2017. "Spatio-temporal patterns of energy consumption-related GHG emissions in China's crop production systems," Energy Policy, Elsevier, vol. 104(C), pages 274-284.
    19. Tang, Miaohan & Hong, Jingke & Liu, Guiwen & Shen, Geoffrey Qiping, 2019. "Exploring energy flows embodied in China's economy from the regional and sectoral perspectives via combination of multi-regional input–output analysis and a complex network approach," Energy, Elsevier, vol. 170(C), pages 1191-1201.
    20. Zheng Meng & Jinling Guo & Kejia Yan & Zhuan Yang & Bozi Li & Bo Zhang & Bin Chen, 2022. "China’s Trade of Agricultural Products Drives Substantial Greenhouse Gas Emissions," IJERPH, MDPI, vol. 19(23), pages 1-16, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:17:y:2020:i:14:p:5065-:d:384287. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.