Virtual water analysis for the Jing-Jin-Ji region based on multiregional input-output model

Tao, 曹涛 Cao; Saige, 王赛鸽 Wang; Bin, 陈彬 Chen

doi:10.5846/stxb201612122549

Cited by 5 publications

(4 citation statements)

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“…In this paper, we use three main types of datasets: the IO table, CO2 emissi value added, and demographic data. (1) The YEB-MRIO in this paper is based MRIO table for China [47]. We obtained the MRIO table for 31 provinces of China Taiwan Province, Hong Kong Special Administrative Region, and Macao Special istrative Region) with 42 industrial sectors (Table A1…”

Section: Data Sourcementioning

confidence: 99%

“…In this paper, we use three main types of datasets: the IO table, CO 2 emissions and value added, and demographic data. (1) The YEB-MRIO in this paper is based on the MRIO table for China [47]. We obtained the MRIO table for 31 provinces of China (except Taiwan Province, Hong Kong Special Administrative Region, and Macao Special Administrative Region) with 42 industrial sectors (Table A1 A4, Appendix C) were obtained based on the China Statistical Yearbook-2018 (http://www.stats.gov.cn/sj/ndsj/2018/indexch.htm, accessed on 17 June 2023).…”

Section: Data Sourcementioning

confidence: 99%

See 1 more Smart Citation

Carbon Inequality Embodied in Inter-Provincial Trade of China’s Yangtze River Economic Belt

Ban,

Li,

Tian

et al. 2023

Energies

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Regional trade leads to carbon transfer, which in turn raises the issue of carbon inequality. However, less existing research has focused on carbon inequality within megaregions. Combining multi-regional input-output analysis, carbon Gini coefficients and carbon deviation coefficients, this paper presents a comprehensive analysis of carbon equity in inter-provincial trade in the Yangtze River Economic Belt (YEB) from the perspective of economic benefits and environmental pressure. The results show that: (1) Carbon emissions from the production and consumption sides of the 11 provinces in the YEB vary considerably. (2) Significant carbon inequality exists in the YEB region. This is manifested in the unequal relationship between the transfer of embodied carbon emissions and economic benefits, as well as the difference in carbon deviation coefficients. Based on the results of our research, this paper can help provide theoretical support and decision-making reference for implementing a differentiated carbon emission reduction responsibility mechanism and establishing a coordinated carbon emission reduction responsibility system.

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Section: Data Sourcementioning

confidence: 99%

Section: Data Sourcementioning

confidence: 99%

Carbon Inequality Embodied in Inter-Provincial Trade of China’s Yangtze River Economic Belt

Ban,

Li,

Tian

et al. 2023

Energies

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show abstract

“…The two parts of water resource constitute TWCC, which refers to the total water resource consumed by the whole economic system to increase one unit of products in a sector. TWCC has become an important tool to account for the virtual water and optimize the industrial structure [15][16][17][18]. It is worth emphasizing that the characteristics of TWCC mentioned above make it a more objective indicator for measuring AWUE.…”

Section: Introductionmentioning

confidence: 99%

Agricultural Total Water Consumption Coefficient and Its Spatial Correlation Network in Yangtze River Economic Belt

Yang

Gao

Zhang

et al. 2023

Water

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Agriculture contributes extensively to the economic development of countries; however, it is one of the main water-consuming industries. Revealing the characteristics and network structure of agricultural water use efficiency (AWUE) is conducive to green and coordinated development of agriculture. Considering that analyzing the variation of AWUE is helpful to calculating the AWUE, this study aims to calculate the total water consumption coefficient of the agricultural sector in the Yangtze River Economic Belt (YEB) by using the China interregional input-output tables in 2012 and 2017. The gravity model was modified to deduce the spatial correlation network of agricultural total water consumption coefficient (ATWCC), and the social network analysis method was used to analyze the network structural characteristics. The results show that: (1) compared to 2012, the AWUE of YEB in 2017 improved, with a decrease of ATWCC from 532.5 to 387.5 m3/10,000-yuan, account for 27.2%; (2) The network relevance of ATWCC of YEB’s 11 provinces (cities) enhanced, the rank relationship within the network and the network structure was relatively stable; (3) The spatial correlation network formed several network centers, Zhejiang and Jiangsu in the eastern coastal area were the main destinations of the spatial spillover of the spatial correlation network.

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“…Zhang et al conducted a multi-regional input-output (MRIO) analysis of China's regional energy utilization as reflected in the final demand and inter-regional trade 2007 and pointed out that the energy flow has largely shifted from the central and western regions to the eastern regions [17]. Cao et al calculated the virtual water flow in the Beijing-Tianjin-Hebei region based on I-O table in 2012, and pointed out that the virtual water showed a net outflow as a whole [18]. Yan and Sun calculated the water footprint transfer of 30 regions in China based on interregional I-O Tables in 2007 and 2012 [19].…”

Section: Introductionmentioning

confidence: 99%

Interprovincial Virtual Water-Energy Flow and Its Network Structure Resilience in Yangtze River Economic Belt

Yang,

Zhou,

Zhang

et al. 2023

Water

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Water and energy are essential resources that flow between different regions in economic activities, forming a complex network that profoundly impacts sustainable development. Revealing network structural resilience allows for the identification of weak links, thus enhancing the capacity for sustainable development. This study employs a resilience-based method to examine changes in virtual water-energy transfers, combining input–output tables and total resource consumption coefficients (TRCC) to investigate the structural resilience of the virtual water-energy network. Case studies were conducted in the Yangtze River Economic Belt (YEB) in 2012 and 2017. The results show that the virtual water flow rate decreased by 28.66%, while that of virtual energy increased by 4.88% in YEB. The virtual energy network’s structural resilience is better than that of the virtual water network and shows significant improvement in later periods. The virtual water network structure has a clear hierarchical structure, while the virtual energy network structure is relatively flat. The transmission and connectivity of the two networks do not differ significantly, but the virtual energy network’s transmission is superior to that of the virtual water network. There is a significant improvement in the virtual energy network’s agglomeration in the later stages, while there is no significant change in the virtual water contact network.

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Virtual water analysis for the Jing-Jin-Ji region based on multiregional input-output model

Cited by 5 publications

References 0 publications

Carbon Inequality Embodied in Inter-Provincial Trade of China’s Yangtze River Economic Belt

Carbon Inequality Embodied in Inter-Provincial Trade of China’s Yangtze River Economic Belt

Agricultural Total Water Consumption Coefficient and Its Spatial Correlation Network in Yangtze River Economic Belt

Interprovincial Virtual Water-Energy Flow and Its Network Structure Resilience in Yangtze River Economic Belt

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