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Sector aggregation effect on embodied carbon emission based on city-centric global multi-region input-output (CCG-MRIO) model

Author

Listed:
  • Xu, Duo
  • Liu, Gengyuan
  • Meng, Fanxin
  • Yan, Ningyu
  • Li, Hui
  • Agostinho, Feni
  • Almeida, Cecilia MVB
  • Giannetti, Biagio F

Abstract

Sector aggregation under the input-output framework may lead to deviation in results and the lack of detailed sectoral information, which hinder the targeted implementation of accurate sectoral adjustment policies. This paper explores the effects of sector aggregation on the embodied carbon emission of the residential consumptions of Beijing and Shanghai based on the city-centric global multi-region input-output (CCG-MRIO) model. Integrating with structural path analysis and structural decomposition analysis, the impacts of sector aggregation on the identifying of critical emission transmission paths and driving forces are also revealed. Three sector aggregation datasets are discussed to track the sector aggregation effect in 2012 and 2017. The findings show that the carbon emission results at 8 sector level better align with the results at the 22 sector level than those at 32 sector level. Moreover, sector aggregation will lead to the absence of some critical carbon transmission paths, some factor contributions on carbon emission also changed their directions at different sector levels. On the basis of clarifying the sector aggregation effect on embodied carbon emission, the research results provide a reference for similar studies to select the appropriate level of sector aggregation, to realize the goal of simplifying the calculation or gaining more detailed sectoral emission information.

Suggested Citation

  • Xu, Duo & Liu, Gengyuan & Meng, Fanxin & Yan, Ningyu & Li, Hui & Agostinho, Feni & Almeida, Cecilia MVB & Giannetti, Biagio F, 2023. "Sector aggregation effect on embodied carbon emission based on city-centric global multi-region input-output (CCG-MRIO) model," Ecological Modelling, Elsevier, vol. 484(C).
    • Handle: RePEc:eee:ecomod:v:484:y:2023:i:c:s030438002300217x
    DOI: 10.1016/j.ecolmodel.2023.110487
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    1. Su, Bin & Huang, H.C. & Ang, B.W. & Zhou, P., 2010. "Input-output analysis of CO2 emissions embodied in trade: The effects of sector aggregation," Energy Economics, Elsevier, vol. 32(1), pages 166-175, January.
    2. Su, Bin & Ang, B.W., 2017. "Multiplicative structural decomposition analysis of aggregate embodied energy and emission intensities," Energy Economics, Elsevier, vol. 65(C), pages 137-147.
    3. Maaike Bouwmeester & Jan Oosterhaven, 2013. "Specification and Aggregation Errors in Environmentally Extended Input–Output Models," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 56(3), pages 307-335, November.
    4. Zhou, Dequn & Zhou, Xiaoyong & Xu, Qing & Wu, Fei & Wang, Qunwei & Zha, Donglan, 2018. "Regional embodied carbon emissions and their transfer characteristics in China," Structural Change and Economic Dynamics, Elsevier, vol. 46(C), pages 180-193.
    5. Manfred Lenzen, 2011. "Aggregation Versus Disaggregation In Input-Output Analysis Of The Environment," Economic Systems Research, Taylor & Francis Journals, vol. 23(1), pages 73-89.
    6. de Koning, Arjan & Bruckner, Martin & Lutter, Stephan & Wood, Richard & Stadler, Konstantin & Tukker, Arnold, 2015. "Effect of aggregation and disaggregation on embodied material use of products in input–output analysis," Ecological Economics, Elsevier, vol. 116(C), pages 289-299.
    7. Erik Dietzenbacher & Bart Los, 1998. "Structural Decomposition Techniques: Sense and Sensitivity," Economic Systems Research, Taylor & Francis Journals, vol. 10(4), pages 307-324.
    8. Lin, Jianyi & Hu, Yuanchao & Zhao, Xiaofeng & Shi, Longyu & Kang, Jiefeng, 2017. "Developing a city-centric global multiregional input-output model (CCG-MRIO) to evaluate urban carbon footprints," Energy Policy, Elsevier, vol. 108(C), pages 460-466.
    9. Kjartan Steen-Olsen & Anne Owen & Edgar G. Hertwich & Manfred Lenzen, 2014. "Effects Of Sector Aggregation On Co 2 Multipliers In Multiregional Input-Output Analyses," Economic Systems Research, Taylor & Francis Journals, vol. 26(3), pages 284-302, September.
    10. Bin Su & B. W. Ang, 2012. "Structural Decomposition Analysis Applied To Energy And Emissions: Aggregation Issues," Economic Systems Research, Taylor & Francis Journals, vol. 24(3), pages 299-317, March.
    11. Liu, Hongguang & Liu, Weidong & Fan, Xiaomei & Zou, Wei, 2015. "Carbon emissions embodied in demand–supply chains in China," Energy Economics, Elsevier, vol. 50(C), pages 294-305.
    12. Su, Bin & Ang, B.W. & Li, Yingzhu, 2019. "Structural path and decomposition analysis of aggregate embodied energy and emission intensities," Energy Economics, Elsevier, vol. 83(C), pages 345-360.
    13. Yan, Yunfeng & Wang, Ran & Zheng, Xiuxiu & Zhao, Zhongxiu, 2020. "Carbon endowment and trade-embodied carbon emissions in global value chains: Evidence from China," Applied Energy, Elsevier, vol. 277(C).
    14. Su, Bin & Ang, B.W., 2012. "Structural decomposition analysis applied to energy and emissions: Some methodological developments," Energy Economics, Elsevier, vol. 34(1), pages 177-188.
    15. 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.
    16. Da Zhang & Justin Caron & Niven Winchester, 2019. "Sectoral Aggregation Error in the Accounting of Energy and Emissions Embodied in Trade and Consumption," Journal of Industrial Ecology, Yale University, vol. 23(2), pages 402-411, April.
    17. Rui Xie & Linyuan Huang & Boshi Tian & Jiayu Fang, 2019. "Differences in Changes in Carbon Dioxide Emissions among China’s Transportation Subsectors: A Structural Decomposition Analysis," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(6), pages 1294-1311, May.
    18. Wang, H. & Ang, B.W. & Su, Bin, 2017. "Assessing drivers of economy-wide energy use and emissions: IDA versus SDA," Energy Policy, Elsevier, vol. 107(C), pages 585-599.
    19. Wang, Saige & Chen, Bin, 2021. "Unraveling energy–water nexus paths in urban agglomeration: A case study of Beijing–Tianjin–Hebei," Applied Energy, Elsevier, vol. 304(C).
    20. Cansino, José M. & Román, Rocío & Ordóñez, Manuel, 2016. "Main drivers of changes in CO2 emissions in the Spanish economy: A structural decomposition analysis," Energy Policy, Elsevier, vol. 89(C), pages 150-159.
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