View in EDS HTML Full Text PDF Full Text

Regional water-energy-carbon footprint in the context of sustainable development based on EE-MRIO: cases of Jiangsu, Zhejiang and Shanghai.

Saved in:
Bibliographic Details
Title: Regional water-energy-carbon footprint in the context of sustainable development based on EE-MRIO: cases of Jiangsu, Zhejiang and Shanghai.
Authors: Wang, Huanyu1,2,3 (AUTHOR), Yue, Qiang1,2 (AUTHOR) yueq@smm.neu.edu.cn, Liu, Rui3 (AUTHOR) liuruitsinghuazj@gmail.com, Zhang, Yujie1,2 (AUTHOR), Wang, Heming1,2 (AUTHOR), Wang, Qi1,2 (AUTHOR)
Source: Environment, Development & Sustainability. May2026, Vol. 28 Issue 5, p12705-12733. 29p.
Subject Terms: *Sustainable development, *Input-output analysis, *Ecological impact, *Economic sectors, *Mathematical decomposition, *Energy consumption
Geographic Terms: Shanghai (China), Zhejiang Sheng (China), Jiangsu Sheng (China)
Abstract: In the context of regional sustainable development, input–output analysis can provide a basis for interregional water-energy-carbon (W-E-C) footprint change strategies, and help solve regional resource and environmental problems from the perspective of trade and consumption. Based on the environmentally extended multi-regional input–output was used to construct a cross-regional W-E-C footprint accounting model. The regional trade and consumption of industry-wide W-E-C footprint, direct and total consumption coefficients, and transfer patterns are clarified. The water-energy (W-E) relationship is quantified as a water footprint driven by energy demand, and the Structural Decomposition Analysis is used to decompose the economic driving forces influencing the W-E relationship. The results show that the production and supply of electricity and heat industry (Eh) is the sector with the highest proportion of integrated W-E-C footprint consumption and the most active trade output, with a water-energy-carbon footprint of 38.2 billion m3, 328 Mtce, and 2576.5 MtCO2 respectively. While the equipment manufacturing (Em), construction (Co), services and transportation industries (St) are the input sectors of W-E-C footprint, with elevated inflow and multiple "source sectors". The regional mobility of energy footprint is the strongest. Eh in Jiangsu provides a large amount of energy footprint support for the production of various departments in Jiangsu, Zhejiang and Shanghai, with a total output of 352.78 Mtce energy footprint. The main suppliers are local Em (159.92 Mtce), Co (49.96 Mtce), St (76.83 Mtce) and Ch (35.21 Mtce). The water footprint intensity has the greatest impact on the W-E relationship during the study period, the contribution rate is above 50%, contributing 11.69 billion m3 of water footprint reduction. The change in industry structure impact is also a key factor in reducing the water footprint under energy requirement, contributing 2.23 billion m3 of water footprint reduction. While the impact of energy requirement structure, the impact of per capita energy requirement, and the impact of population lead to the increase of water footprint of 3.16, 5.77 and 2.06 billion m3 respectively. Based on the above findings, the government should improve the energy mix (electricity and heat as well as production and supply industries) and improve water efficiency (agriculture). Reduce water footprint intensity to reduce energy demand-driven water footprint. Therefore, the research results contribute to the policy formulation of the regional Sustainable Development Goals (SDGs). [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: enr
DbLabel: Energy & Power Source
An: 193283967
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Regional water-energy-carbon footprint in the context of sustainable development based on EE-MRIO: cases of Jiangsu, Zhejiang and Shanghai.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Wang%2C+Huanyu%22">Wang, Huanyu</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yue%2C+Qiang%22">Yue, Qiang</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> yueq@smm.neu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Liu%2C+Rui%22">Liu, Rui</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> liuruitsinghuazj@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Yujie%22">Zhang, Yujie</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Heming%22">Wang, Heming</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Qi%22">Wang, Qi</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Environment%2C+Development+%26+Sustainability%22">Environment, Development & Sustainability</searchLink>. May2026, Vol. 28 Issue 5, p12705-12733. 29p.
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: *<searchLink fieldCode="DE" term="%22Sustainable+development%22">Sustainable development</searchLink><br />*<searchLink fieldCode="DE" term="%22Input-output+analysis%22">Input-output analysis</searchLink><br />*<searchLink fieldCode="DE" term="%22Ecological+impact%22">Ecological impact</searchLink><br />*<searchLink fieldCode="DE" term="%22Economic+sectors%22">Economic sectors</searchLink><br />*<searchLink fieldCode="DE" term="%22Mathematical+decomposition%22">Mathematical decomposition</searchLink><br />*<searchLink fieldCode="DE" term="%22Energy+consumption%22">Energy consumption</searchLink>
– Name: SubjectGeographic
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Shanghai+%28China%29%22">Shanghai (China)</searchLink><br /><searchLink fieldCode="DE" term="%22Zhejiang+Sheng+%28China%29%22">Zhejiang Sheng (China)</searchLink><br /><searchLink fieldCode="DE" term="%22Jiangsu+Sheng+%28China%29%22">Jiangsu Sheng (China)</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: In the context of regional sustainable development, input–output analysis can provide a basis for interregional water-energy-carbon (W-E-C) footprint change strategies, and help solve regional resource and environmental problems from the perspective of trade and consumption. Based on the environmentally extended multi-regional input–output was used to construct a cross-regional W-E-C footprint accounting model. The regional trade and consumption of industry-wide W-E-C footprint, direct and total consumption coefficients, and transfer patterns are clarified. The water-energy (W-E) relationship is quantified as a water footprint driven by energy demand, and the Structural Decomposition Analysis is used to decompose the economic driving forces influencing the W-E relationship. The results show that the production and supply of electricity and heat industry (Eh) is the sector with the highest proportion of integrated W-E-C footprint consumption and the most active trade output, with a water-energy-carbon footprint of 38.2 billion m3, 328 Mtce, and 2576.5 MtCO2 respectively. While the equipment manufacturing (Em), construction (Co), services and transportation industries (St) are the input sectors of W-E-C footprint, with elevated inflow and multiple "source sectors". The regional mobility of energy footprint is the strongest. Eh in Jiangsu provides a large amount of energy footprint support for the production of various departments in Jiangsu, Zhejiang and Shanghai, with a total output of 352.78 Mtce energy footprint. The main suppliers are local Em (159.92 Mtce), Co (49.96 Mtce), St (76.83 Mtce) and Ch (35.21 Mtce). The water footprint intensity has the greatest impact on the W-E relationship during the study period, the contribution rate is above 50%, contributing 11.69 billion m3 of water footprint reduction. The change in industry structure impact is also a key factor in reducing the water footprint under energy requirement, contributing 2.23 billion m3 of water footprint reduction. While the impact of energy requirement structure, the impact of per capita energy requirement, and the impact of population lead to the increase of water footprint of 3.16, 5.77 and 2.06 billion m3 respectively. Based on the above findings, the government should improve the energy mix (electricity and heat as well as production and supply industries) and improve water efficiency (agriculture). Reduce water footprint intensity to reduce energy demand-driven water footprint. Therefore, the research results contribute to the policy formulation of the regional Sustainable Development Goals (SDGs). [ABSTRACT FROM AUTHOR]
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=193283967
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s10668-024-05168-2
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 29
        StartPage: 12705
    Subjects:
      – SubjectFull: Sustainable development
        Type: general
      – SubjectFull: Input-output analysis
        Type: general
      – SubjectFull: Ecological impact
        Type: general
      – SubjectFull: Economic sectors
        Type: general
      – SubjectFull: Mathematical decomposition
        Type: general
      – SubjectFull: Energy consumption
        Type: general
      – SubjectFull: Shanghai (China)
        Type: general
      – SubjectFull: Zhejiang Sheng (China)
        Type: general
      – SubjectFull: Jiangsu Sheng (China)
        Type: general
    Titles:
      – TitleFull: Regional water-energy-carbon footprint in the context of sustainable development based on EE-MRIO: cases of Jiangsu, Zhejiang and Shanghai.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Wang, Huanyu
      – PersonEntity:
          Name:
            NameFull: Yue, Qiang
      – PersonEntity:
          Name:
            NameFull: Liu, Rui
      – PersonEntity:
          Name:
            NameFull: Zhang, Yujie
      – PersonEntity:
          Name:
            NameFull: Wang, Heming
      – PersonEntity:
          Name:
            NameFull: Wang, Qi
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 05
              Text: May2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 1387585X
          Numbering:
            – Type: volume
              Value: 28
            – Type: issue
              Value: 5
          Titles:
            – TitleFull: Environment, Development & Sustainability
              Type: main
ResultId 1