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Unveiling key drivers of urban embodied and controlled carbon footprints

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  • Chen, Shaoqing
  • Zhu, Feiyao

Abstract

Fast-growing urban demand drives increase of production at a global scale. A full understanding of how carbon footprint is driven by socioeconomic factors in local, domestic and international economies is essential. Herein, we develop a cross-boundary carbon tracking approach based on input-output analysis, network control analysis and structural decomposition analysis. Using Beijing as a case study, we quantify both urban embodied and controlled carbon footprints over 1985–2012, and look into how they are impacted by socio-economic factors in local, domestic and foreign regions. We find that the carbon controlled by urban economy from inside accounts for 60% of the total footprint over 1985–2000, while this proportion decreased to 45% in 2012 due to externalization of production supply chains. Carbon intensity and urban consumption strongly compete with each other and together determine the variation trend of the city’s consumption-based and controlled carbon footprint. Compared to a consumption-based perspective, this control approach reveals a higher impact of production structure transition on urban carbon footprint, and clearly tracks how carbon emissions are increasingly manipulated by other regions. The local-production-related carbon footprint have decreased by 15–22% over 2000–2012, while meanwhile that from domestic and foreign imports has increased dramatically by 700–960%. Network control approach is able to unveil drivers of carbon emission that are actually regulated by a city as a consequence of its interactions with the rest of global economy.

Suggested Citation

  • Chen, Shaoqing & Zhu, Feiyao, 2019. "Unveiling key drivers of urban embodied and controlled carbon footprints," Applied Energy, Elsevier, vol. 235(C), pages 835-845.
    • Handle: RePEc:eee:appene:v:235:y:2019:i:c:p:835-845
    DOI: 10.1016/j.apenergy.2018.11.018
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    Cited by:

    1. Tan, Ling Min & Arbabi, Hadi & Brockway, Paul E. & Densley Tingley, Danielle & Mayfield, Martin, 2019. "An ecological-thermodynamic approach to urban metabolism: Measuring resource utilization with open system network effectiveness analysis," Applied Energy, Elsevier, vol. 254(C).
    2. Han Sun & Chao Huang & Shan Ni, 2022. "Driving factors of consumption-based PM2.5 emissions in China: an application of the generalized Divisia index," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(8), pages 10209-10231, August.
    3. Chen, Shaoqing & Long, Huihui & Chen, Bin & Feng, Kuishuang & Hubacek, Klaus, 2020. "Urban carbon footprints across scale: Important considerations for choosing system boundaries," Applied Energy, Elsevier, vol. 259(C).
    4. Sun, Chen & Song, Junnian & Zhang, Dongqi & Wang, Xiaofan & Yang, Wei & Qi, Zhimin & Chen, Shaoqing, 2023. "Tracing urban carbon footprints differentiating supply chain complexity: A metropolis case," Energy, Elsevier, vol. 282(C).
    5. Haoran Wang & Toshiyuki Fujita, 2023. "A Review of Research on Embodied Carbon in International Trade," Sustainability, MDPI, vol. 15(10), pages 1-15, May.
    6. Xu, Chao & Haase, Dagmar & Su, Meirong & Yang, Zhifeng, 2019. "The impact of urban compactness on energy-related greenhouse gas emissions across EU member states: Population density vs physical compactness," Applied Energy, Elsevier, vol. 254(C).
    7. Tu, Chuang & Mu, Xianzhong & Chen, Jian & Kong, Li & Zhang, Zheng & Lu, Yutong & Hu, Guangwen, 2021. "Study on the interactive relationship between urban residents’ expenditure and energy consumption of production sectors," Energy Policy, Elsevier, vol. 157(C).
    8. Chen, Shaoqing & Zhu, Feiyao & Long, Huihui & Yang, Jin, 2019. "Energy footprint controlled by urban demands: How much does supply chain complexity contribute?," Energy, Elsevier, vol. 183(C), pages 561-572.

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