4.7 Article

Uncovering the structure of virtual multi-regional grey water network in China

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出版社

ELSEVIER
DOI: 10.1016/j.resconrec.2021.105668

关键词

Grey water; Complex networks; Input-output analysis; Network analysis; Supply chain; Trade

资金

  1. Program for Guangdong Introducing Innovative and Enterpreneurial Teams [2019ZT08L213]
  2. Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) [GML2019ZD0403]
  3. National Natural Science Foundation of China [72004035]

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This study identifies critical transmission sectors and supply chain paths in China's virtual multi-regional grey water network, and suggests that improving the production efficiency of critical sectors can help reduce the economy-wide grey water footprint indirectly. Identifying supply chain paths provides explicit hotspots for production efficiency improvement measures.
Grey water footprint (GWF) is a useful indicator to describe inadequate water quality from the viewpoint of freshwater volume. The exchange of commodities prompts the flows of virtual grey water (i.e., grey water embodied in commodities) among economic sectors, which constitute a virtual grey water network. Conventional production-based and consumption-based GWF methods cannot identify intermediate sectors acting as transmission centres and major supply chain paths in the network. This study identifies critical transmission sectors and supply chain paths in China's virtual multi-regional grey water (VMGW) network, based on the betweenness concept, multi-regional input-output analysis, and structural path analysis. The top three important transmission sectors in the VMGW network are the food manufacturing in Shandong, the food manufacturing in Henan, and the chemical industry in Henan. These sectors transmit 117, 90, and 58 billion m(3) of virtual grey water, respectively. Improving the production efficiency of critical transmission sectors can indirectly help reduce the economy-wide GWF. Critical supply chain paths further provide explicit hotspots for production efficiency improvement measures. For instance, Heilongjiang-cattle. Liaoning-food manufacturing is the most important interregional supply chain path in the VMGW network, transmitting 316 million m(3) of virtual grey water. Improving the use efficiency of cattle products during food manufacturing in Liaoning can facilitate GWF reduction in Heilongjiang. This study provides additional hotspots and more explicit directions for formulating sector-oriented policies to reduce the GWF in China.

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