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Data-driven low-carbon transformation management for manufacturing enterprises: an eco-efficiency perspective.

Authors :
Zhang, Cuixia
Liu, Fan
Liu, Conghu
Tian, Guangdong
Source :
Environmental Science & Pollution Research; Oct2023, Vol. 30 Issue 46, p102519-102530, 12p
Publication Year :
2023

Abstract

The low-carbon transformation of manufacturing enterprises is considered to be imperative to achieve carbon neutrality. Therefore, we propose a data-driven strategy to achieve a low-carbon transformation of manufacturing enterprises from an eco-efficiency perspective. Following the collection of input (energy, materials, equipment, R&D, and services) and output (waste and products) data from production systems of manufacturing enterprises, an ecological efficiency model of manufacturing enterprise production system was constructed from the perspective of carbon emissions, thus allowing the quantitative evaluation of the ecological efficiency of the production system. Furthermore, a "measurable, evaluable, and optimized" low-carbon transformation and upgrading method for manufacturing enterprise production system was established. Finally, through the production practice data of an enterprise from 2017 to 2021, the feasibility and effectiveness of this method were verified. The results show that this method can effectively improve the ecological efficiency of enterprises by 3.6% and reduce waste emissions by 12%. Our study provides new tools for improving the ecological efficiency of manufacturing systems, along with theoretical and methodological support to manufacturing enterprises for low-carbon transformation. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09441344
Volume :
30
Issue :
46
Database :
Complementary Index
Journal :
Environmental Science & Pollution Research
Publication Type :
Academic Journal
Accession number :
172915621
Full Text :
https://doi.org/10.1007/s11356-023-29573-8