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Ecological network analysis for urban metabolism and carbon emissions based on input-output tables: A case study of Guangdong province

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  • Li, Jizhe
  • Huang, Guohe
  • Liu, Lirong

Abstract

Global warming has received more and more attention in recent years for its inevitable influence on population, species, soil, ocean, water and so on. It is essential to investigate the urban metabolism of carbon emissions which is a main cause of global warming and most of it occurs in the process of production and living in urban areas. In this paper, a carbon emission metabolic network is established to explore the emission reduction strategies by modeling carbon dioxide flows and identifying the mutual relationships based on the input-output analysis. Specifically, Eff-Lorenz curve derived from the painting of Lorenz curve is developed to compare the efficiency of carbon emissions from different sectors. The newly developed method has been applied to Guangdong province to demonstrate its availability and benefit. It is revealed that carbon emissions mainly concentrated in the secondary and tertiary industries with electric power generation, manufacturing industry, domestic consumption and transportation ranking at the top. The competition relationship reveals good interactions in terms of emission reduction while a mutualism relationship provides effective pathways to mitigate carbon emissions between pairwise sectors simultaneously. In Guangdong province, upgrading the clean combustion technology in electric power generation and energy extraction sectors would drive other sectors to cut emissions and adjusting the production structure of the construction sector also contribute to achieve this goal. The results are expected to provide corresponding and holistic reference for decision makers to develop the mitigation policies.

Suggested Citation

  • Li, Jizhe & Huang, Guohe & Liu, Lirong, 2018. "Ecological network analysis for urban metabolism and carbon emissions based on input-output tables: A case study of Guangdong province," Ecological Modelling, Elsevier, vol. 383(C), pages 118-126.
    • Handle: RePEc:eee:ecomod:v:383:y:2018:i:c:p:118-126
    DOI: 10.1016/j.ecolmodel.2018.05.009
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    Citations

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    Cited by:

    1. Xinhui Feng & Yan Li & Lu Zhang & Chuyu Xia & Er Yu & Jiayu Yang, 2022. "Carbon Metabolism in Urban “Production–Living–Ecological” Space Based on Ecological Network Analysis," Land, MDPI, vol. 11(9), pages 1-22, August.
    2. Linlin Xia & Jianfeng Wei & Ruwei Wang & Lei Chen & Yan Zhang & Zhifeng Yang, 2022. "Exploring Potential Ways to Reduce the Carbon Emission Gap in an Urban Metabolic System: A Network Perspective," IJERPH, MDPI, vol. 19(10), pages 1-23, May.
    3. Mohammad Aghapour Sabbaghi & Afsaneh Naeimifar, 2022. "Analysis of import substitution policy with an emphasis on environmental issues based on environmental input–output (EIO) model," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(12), pages 14130-14162, December.
    4. Jingyao Peng & Yidi Sun & Junnian Song & Wei Yang, 2020. "Exploring Potential Pathways toward Energy-Related Carbon Emission Reduction in Heavy Industrial Regions of China: An Input–Output Approach," Sustainability, MDPI, vol. 12(5), pages 1-20, March.
    5. Wang, P.P. & Huang, G.H. & Li, Y.P. & Liu, Y.Y. & Li, Y.F., 2024. "An ecological input-output CGE model for unveiling CO2 emission metabolism under China's dual carbon goals," Applied Energy, Elsevier, vol. 365(C).
    6. Chuang Tu & Xianzhong Mu & Yufeng Wu & Yifan Gu & Guangwen Hu, 2022. "Heterogenous impacts of components in urban energy metabolism: evidences from gravity model," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(8), pages 10089-10117, August.
    7. Li, Jizhe & Huang, Guohe & Liu, Lirong & Li, Yongping & Zhai, Mengyu & Xu, Xinli, 2021. "Projections of carbon metabolism in 2035 and implications for demand-side controls under various scenarios," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    8. Lingwei Li & Yongping Bai & Xuedi Yang & Zuqiao Gao & Fuwei Qiao & Jianshe Liang & Chunyue Zhang, 2022. "A Low-Carbon Land Use Management Framework Based on Urban Carbon Metabolism: A Case of a Typical Coal Resource-Based City in China," Sustainability, MDPI, vol. 14(21), pages 1-18, October.
    9. Liu, S. & Xiao, Q., 2021. "An empirical analysis on spatial correlation investigation of industrial carbon emissions using SNA-ICE model," Energy, Elsevier, vol. 224(C).
    10. Zhai, Mengyu & Huang, Guohe & Liu, Lirong & Zheng, Boyue & Guan, Yuru, 2020. "Inter-regional carbon flows embodied in electricity transmission: network simulation for energy-carbon nexus," Renewable and Sustainable Energy Reviews, Elsevier, vol. 118(C).
    11. Galychyn, Oleksandr, 2022. "Towards sustainable cities: A multi-criteria assessment framework for studying urban metabolism," MPRA Paper 121584, University Library of Munich, Germany, revised 11 May 2022.

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