Collaborative management of the energy-water-carbon footprint: analysing the spatial network characteristics

Abstract

AbstractWater and energy consumption and carbon emissions caused by humans have vital impacts on the natural environment. Due to the dramatic global environmental pollution problem, understanding the relationship between these factors is emerging as an important approach to realising sustainable development. However, with the strengthening of interregional trade links, it is difficult to manage and evaluate their relationship. Therefore, from the perspective of regional and industrial sectors, using the multiregional input-output (MRIO) model and social network analysis (SNA), our research explores an innovative analytical methodology to evaluate the characteristics of the energy-water-carbon spatial network, and a scheme is proposed to improve it. The results demonstrate that the characteristics of water scarcity and energy enrichment could lead to a net inflow of the water footprint and a net outflow of the energy and carbon footprints. Moreover, traditional high-energy-consumption industrial sectors contribute significantly to the energy and carbon footprints. The energy-water-carbon spatial network correlation is low and unstable, and it lacks rationalisation and balance in resource-based areas. Network-based energy-water-carbon research provides more insights toward understanding the carbon emission reduction responsibilities of industrial supply chains. Our findings provide a reference for reducing the energy-water-carbon footprint and achieving the carbon reduction goal of China.KEYWORDS: Collaborative managementenergy-water-carbon footprintmultiregional input–output analysissocial network analysisspatial network AcknowledgmentsWe also thank anonymous commentators and editors for their helpful suggestions.Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe authors confirm that the data supporting the findings of this study are available within the article.Additional informationFundingThis research was supported by the National Natural Science Foundation of China (Grant No. 42001257 and 71874119), the Research on Philosophy and Social Sciences in Shanxi Province's Colleges and Universities (Grant No. 20210115), and the Major decision-making consulting projects in Shanxi Province in 2022 (Grant No. 2005).Notes on contributorsXiuli LiuXiuli Liu is a Professor in the Research Institute of Resource-based Economics at Shanxi University of Finance and Economics (Taiyuan, China). She received her Ph.D. in Natural Geography from Northwest Normal University (Gansu, China) in June 2013. Her research interests include regional economic management, energy ecology, and resource-based economic transformation. In this paper, she is mainly responsible for conceptualization, writing – review, and editing.Rui XiongRui Xiong is a graduate student in the Research Institute of Resource-based Economics at Shanxi University of Finance and Economics (Taiyuan, China). Her research interests include resource environment and regional sustainable development, energy ecology, and resource-based economic transformation. In this paper, she is mainly responsible for writing – reviewing, and editing.Sandun C. PereraSandun C. Perera is an Associate Professor of Business Analytics and Operations at the College of Business, University of Nevada, Reno. His research focuses on Disruptive Technologies in Operations Management, Supply Chain Management, Healthcare Operations Management, and interfaces between Operations and other functional areas in business. In this paper, he is mainly responsible for supervision, writing – review, and editing.Pibin GuoPibin Guo is a Professor at the Shanxi Institute of Economics Management. He is mainly committed to research on scientific and technological innovation, regional development, and energy technology innovation. He is a provincial famous teacher and a provincial academic and technical leader in Shanxi, China. In this paper, his contribution is to propose methods.