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Developing a city-centric global multiregional input-output model (CCG-MRIO) to evaluate urban carbon footprints

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  • Lin, Jianyi
  • Hu, Yuanchao
  • Zhao, Xiaofeng
  • Shi, Longyu
  • Kang, Jiefeng

Abstract

The consumption-based carbon footprint (CBF) can facilitate the implementation of broader mitigation policies that concern final consumption. Here, a city-centric global multiregional input-output model (CCG-MRIO) was developed to assess the carbon footprints of urban consumption in the global supply chain. Beijing was selected as the studied case, and results were as follow. In 2010, Beijing's CBF was 338.26 Mt CO2e, which was 1.90 times amount of its purely geographic accounting (PGA). Manufacturing, services, and construction were the top three consumers, while Mainland China and other developing regions were the main net importing areas, and utilities, manufacturing, and agriculture were the top net importing sectors. These findings indicated that Beijing imports large amounts of energy, water, and raw materials to support its consumption, while it mainly exports services and industrial products. The study fills the gap of data and methods for urban CBF compiling and can replicate to other cities with an input-output table. The CBF can promote sustainable local consumption behaviors, local production efficiencies improvement, and cooperation with importing regions. However, the model uncertainties increase in coordinating sectors, estimating trade relationship, and ignoring traffic differences; and the availability of municipal input-output table and energy data hinder its application.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:enepol:v:108:y:2017:i:c:p:460-466
    DOI: 10.1016/j.enpol.2017.06.008
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    2. Meng, Fanxin & Liu, Gengyuan & Hu, Yuanchao & Su, Meirong & Yang, Zhifeng, 2018. "Urban carbon flow and structure analysis in a multi-scales economy," Energy Policy, Elsevier, vol. 121(C), pages 553-564.
    3. Xie, Bai-Chen & Zhao, Wei, 2018. "Willingness to pay for green electricity in Tianjin, China: Based on the contingent valuation method," Energy Policy, Elsevier, vol. 114(C), pages 98-107.
    4. Ye, Bin & Jiang, Jingjing & Liu, Junguo & Zheng, Yi & Zhou, Nan, 2021. "Research on quantitative assessment of climate change risk at an urban scale: Review of recent progress and outlook of future direction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    5. 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).
    6. Long, Yin & Yoshida, Yoshikuni, 2018. "Quantifying city-scale emission responsibility based on input-output analysis – Insight from Tokyo, Japan," Applied Energy, Elsevier, vol. 218(C), pages 349-360.
    7. Long, Yin & Yoshida, Yoshikuni & Fang, Kai & Zhang, Haoran & Dhondt, Maya, 2019. "City-level household carbon footprint from purchaser point of view by a modified input-output model," Applied Energy, Elsevier, vol. 236(C), pages 379-387.
    8. Meng, Fanxin & Wang, Dongfang & Meng, Xiaoyan & Li, Hui & Liu, Gengyuan & Yuan, Qiuling & Hu, Yuanchao & Zhang, Yi, 2022. "Mapping urban energy–water–land nexus within a multiscale economy: A case study of four megacities in China," Energy, Elsevier, vol. 239(PB).

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