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[Life Cycle Carbon Emission Accounting and Emission Reduction Potential Assessment of Steel Industry].
Song, Xiao-Cong; Du, Shuai; Deng, Chen-Ning; Xie, Ming-Hui; Shen, Peng; Zhao, Ci; Chen, Chen; Liu, Xiao-Yu.
Affiliation
  • Song XC; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
  • Du S; Beijing Guo Dian Fu Tong Science and Technology Development Co., Ltd., Beijing 100070, China.
  • Deng CN; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
  • Xie MH; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
  • Shen P; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
  • Zhao C; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
  • Chen C; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
  • Liu XY; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
Huan Jing Ke Xue ; 44(12): 6630-6642, 2023 Dec 08.
Article in Zh | MEDLINE | ID: mdl-38098390
ABSTRACT
The steel industry is one of the most carbon-intensive industries in China. To analyze the carbon emission and carbon reduction potential of the steel industry in the life cycle, a carbon emission accounting model was built from the perspective of the life cycle. Taking the year 2020 as an example, an empirical analysis was carried out to predict and evaluate the carbon reduction potential of the steel industry in the life cycle by optimizing four variables, namely, scrap usage, fossil fuel combustion, electric power carbon footprint factor, and clean transportation proportion. At the same time, sensitivity analysis was used to determine the key degree of factors affecting carbon emission reduction in the life cycle of steel. The results showed that in 2020, the total life cycle CO2 emissions of the steel industry in China was approximately 2.404 billion tons, of which the acquisition and processing of raw materials were the key links in the carbon emissions of the steel industry, accounting for more than 98% of the total life cycle CO2 emissions of the steel industry. From the analysis of CO2 emission source categories, fossil fuel savings and outsourcing power cleaning were the top priorities of carbon reduction in the steel industry. By 2025, the steel industry could achieve 20%, 6%, 5%, and 1% carbon emission reduction potential by respectively promoting low-carbon technology, optimizing the power structure, increasing the number of steel scraps, and increasing the proportion of clean transportation. The fossil fuel combustion had the most significant impact on the life cycle CO2 emissions of the steel industry, followed by the electric power carbon footprint factor and scrap steelmaking usage. With regard to low-carbon technologies in the steel industry, in the short term, the promotion of low-carbon technologies in the steel rolling process and blast furnace ironmaking process should be the main focus. Later, with the gradual increase in the proportion of electric furnace steelmaking, the promotion of low-carbon technologies in the electric furnace steelmaking process will significantly improve the carbon emission reduction potential of the steel industry throughout its life cycle.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Language: Zh Journal: Huan Jing Ke Xue Year: 2023 Document type: Article Affiliation country: Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: Zh Journal: Huan Jing Ke Xue Year: 2023 Document type: Article Affiliation country: Country of publication: