Affiliations: [a] Finance and Economics College, Chongqing Chemical Industry Vocational College, Chongqing, China
| [b] Research Centre for International Business and Economics, International Business School, Sichuan International Studies University, Chongqing, China
Correspondence:
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Corresponding author. Weixin Wang, Research Centre for International Business and Economics, International Business School, Sichuan International Studies University, 400031, Chongqing, China. E-mail: wangweixin_301@163.com.
Abstract: The research on carbon footprint of steel energy supply chain plays an important role in energy conservation and emission reduction. Therefore, this article puts forward a definition method of carbon footprint of iron and steel energy supply chain based on correlation dispersion degree. Firstly, the definition of carbon footprint was given, and the carbon emission of iron and steel industry was calculated. On this basis, the influencing factors were analyzed quantitatively. Meanwhile, the carbon footprint data was processed based on carbon footprint accounting standards, including the carbon footprint data preprocessing, transformation and reduction. According to the preprocessing results, the computation of carbon footprint was checked. Finally, the correlation dispersion degree of carbon footprints in the steel energy supply chain was analyzed, so as to achieve the definition of carbon footprints in the steel energy supply chain. In order to test the validity and feasibility of the proposed method, a simulation was carried out. Simulation results show that the result of the proposed method is close to the actual result, so that the proposed method can accurately get the influence of various factors on CO2 emissions of the steel industry, and thus to present some targeted measures to reduce the carbon emission of steel industry.
Keywords: Carbon footprint, supply chain, data preprocessing, accounting
