Evaluation of Energy Saving and Emission Reduction in Steel Enterprises Using an Improved Dempster–Shafer Evidence Theory: A Case Study from China

Yongxia Chen (), Zhe Rao, Lin Yuan and Tianlong Meng
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Yongxia Chen: College of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China
Zhe Rao: College of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China
Lin Yuan: Magang (Group) Holding Co., Ltd., Maanshan 243003, China
Tianlong Meng: College of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China

Sustainability, 2025, vol. 17, issue 9, 1-26

Abstract: As global warming and environmental issues become increasingly prominent, steel enterprises, as a carbon-intensive industry, face urgent challenges in energy saving and emission reduction (ESER). This study develops a novel evaluation model integrating the WSR methodology, the cloud matter-element model, and an improved D-S evidence theory to address the fuzziness, randomness, and uncertainty in ESER assessments. A case study demonstrates that this approach can address the correlation between ESER indicators; quantify the evaluation process; and optimize issues related to fuzziness, randomness, and uncertainty. This finding provides a systematic evaluation framework for ESER in steel enterprises operating under the long-process production model (the blast furnace-converter model), offering valuable insights for formulating comprehensive ESER strategies throughout the entire production process.

Keywords: steel enterprises; ESER evaluation; WSR methodology; cloud matter-element model; improved D-S evidence theory (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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