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A multivariate statistical input–output model for analyzing water-carbon nexus system from multiple perspectives - Jing-Jin-Ji region

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  • Wang, P.P.
  • Li, Y.P.
  • Huang, G.H.
  • Wang, S.G.

Abstract

Water scarcity and carbon dioxide (CO2) emission continue to be challenges faced by decision makers in urban and regional scales. In this study, a multivariate statistical input–output (MSIO) model is developed for analyzing water-carbon nexus system, through incorporating techniques of input–output analysis (IOA) and multivariate statistical analysis (MSA) into a general framework. MSIO is able to: (i) recognize the complicated characteristics of multi-element, multi-sector and multi-factor in water-carbon nexus system from network and statistical perspectives; (ii) simulate different technology-upgrade policies on key transmission sectors that are the middle nodes of supply chain paths; (iii) quantify the individual and interactive effects of sectors on water-carbon variations. MSIO is applied to analyzing water-carbon nexus system in Jing-Jin-Ji region (China). Major findings are: (i) for the region in 2030, agriculture, service and food industries would be typical water consumers (accounting for 35.0%, 22.8% and 10.8%); metal, service, and electricity and heat industries would be typical CO2 emitters (accounting for 24.1%, 22.0% and 19.7%); (ii) CO2 reduction policy could aim at the sectors of cluster 1 (i.e. energy production, manufacturing, construction and service industries); policy oriented toward water resource could aim at the sectors of cluster 2 (i.e. agriculture, food and textile industries); (iii) technology-upgrade policy on Beijing’s electricity and heat industry would have significant performance in water-carbon reductions, indicating that this sector is highly dependent on upstream industry and intra-regional trade supply; (iv) the synergy of Hebei’s heavy industry and Beijing’s electricity and heat industry would perform best in water-carbon management (i.e. water-consumption intensity and CO2-emission intensity would decrease by 3.3% and 15.3%, respectively), suggesting that it is crucial to improve the production capacity and output efficiency of these sectors from the perspective of the middle of the supply chain.

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  • Wang, P.P. & Li, Y.P. & Huang, G.H. & Wang, S.G., 2022. "A multivariate statistical input–output model for analyzing water-carbon nexus system from multiple perspectives - Jing-Jin-Ji region," Applied Energy, Elsevier, vol. 310(C).
    • Handle: RePEc:eee:appene:v:310:y:2022:i:c:s0306261922000459
    DOI: 10.1016/j.apenergy.2022.118560
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    2. Ruihua Shen & Lei Yao, 2022. "Exploring the Regional Coordination Relationship between Water Utilization and Urbanization Based on Decoupling Analysis: A Case Study of the Beijing–Tianjin–Hebei Region," IJERPH, MDPI, vol. 19(11), pages 1-19, June.
    3. Liu, Dachuan & Wang, Pu & Sun, Yan & Zhang, Huawei & Xu, Shanqing, 2024. "Co-abatement of carbon and air pollutants emissions in China’s iron and steel industry under carbon neutrality scenarios," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).

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