4.7 Article

Identifying critical sectors and supply chain paths for the consumption of domestic resource extraction in China

期刊

JOURNAL OF CLEANER PRODUCTION
卷 208, 期 -, 页码 1577-1586

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2018.10.151

关键词

Domestic extraction; Natural resource consumption; Input-output analysis; Structural path analysis; Betweenness-based; China

资金

  1. National Natural Science Foundation of China [41871204, 41401636, 51474067, 71403175]
  2. Fundamental Research Funds for the Central Universities [N172504026]
  3. Fundamental Research Funds for the Central Universities
  4. Interdiscipline Research Funds of Beijing Normal University

向作者/读者索取更多资源

China is one of the largest consumers of natural resources worldwide and this has led to increasing pressure on scarce resources. An understanding of the use of natural resources in Chinese economy is thus important to mitigate resource scarcity at the global scale. This study investigates the natural resource flows within the economic system of China from the raw material extraction to the final production. We identify critical sectors using a variety of methods and consider the various roles of the sectors in the consumption of natural resources in the economy. We also identify critical supply chain paths using a structural path analysis (SPA). The results show that the intermediate-based approach complements the traditional direct and consumption-based approaches and highlights critical sectors for the consumption of domestic resource extraction in China such as Crop cultivation, Cotton and chemical fiber products, and Glass products. The most critical supply chain paths originate from the resource extraction sectors and ultimately end in the Construction sector (e.g., stone, lime, plaster, ceramic), given that more than half of the domestic resource extraction is driven by the Construction sector. To reduce the consumption of domestic resource extraction in China, the government should focus on the critical sectors and supply chain paths identified using our methods for targeted policy interventions. (C) 2018 Elsevier Ltd. All rights reserved.

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