A Systematic Approach to Optimizing Regional Industrial Networks for High Eco-Efficiency Transformation

Industrial networks have become intricately interwoven, utilizing material resources to meet humanity's needs. Recently, sustainable technologies have been pursued to enhance industrial efficiency and reduce environmental and resource impacts. However, current research lacks a comprehensive methodology and typical cases for constructing efficient resource-based industrial networks. Hence, this study employs a comprehensive approach to identify and construct efficient industrial networks from a holistic perspective. Using the Qinghai Saline Lake industrial zone as an example, this research elaborates on establishing and evaluating highly efficient regional industrial networks. It evaluates the eco-efficiency of 184 technologies based on resource development and constructs an efficient resource industry network for the development of the Qinghai Salt Lake using natural resources such as coal, oil, natural gas, and various types of ores as the initial stage and analyzes the characteristics of the industry network with different efficiencies. The research findings emphasize that solely scrutinizing technological efficiency and focusing on either the upstream raw processing network or the downstream deep-processing network while neglecting interactions within the industrial network can constrain the network's overall efficiency and hinder synergy between resources and the environment throughout the entire network. The method applies to constructing, evaluating, and optimizing industrial zones with resource endowments.

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Publication Details

Journal
Environmental Science & Technology
Published
2024-12-27
DOI
https://doi.org/10.1021/acs.est.4c05408
Citations
1
Primary Topic
Sustainable Industrial Ecology
Type
article
Field-Weighted Citation Impact
0.35
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article

A Systematic Approach to Optimizing Regional Industrial Networks for High Eco-Efficiency Transformation

Dingjiang Chen, Yadong Yu, Hang Fu, Shanying Hu et al.
1 citations
Environmental Science & Technology
Sustainable Industrial Ecology
0.35
article

A Systematic Approach to Optimizing Regional Industrial Networks for High Eco-Efficiency Transformation

Dingjiang Chen, Yadong Yu, Hang Fu, Shanying Hu, Kai Zhao, Xin Xie
article en
1 citations

Abstract

Industrial networks have become intricately interwoven, utilizing material resources to meet humanity's needs. Recently, sustainable technologies have been pursued to enhance industrial efficiency and reduce environmental and resource impacts. However, current research lacks a comprehensive methodology and typical cases for constructing efficient resource-based industrial networks. Hence, this study employs a comprehensive approach to identify and construct efficient industrial networks from a holistic perspective. Using the Qinghai Saline Lake industrial zone as an example, this research elaborates on establishing and evaluating highly efficient regional industrial networks. It evaluates the eco-efficiency of 184 technologies based on resource development and constructs an efficient resource industry network for the development of the Qinghai Salt Lake using natural resources such as coal, oil, natural gas, and various types of ores as the initial stage and analyzes the characteristics of the industry network with different efficiencies. The research findings emphasize that solely scrutinizing technological efficiency and focusing on either the upstream raw processing network or the downstream deep-processing network while neglecting interactions within the industrial network can constrain the network's overall efficiency and hinder synergy between resources and the environment throughout the entire network. The method applies to constructing, evaluating, and optimizing industrial zones with resource endowments.

Environmental Science & TechnologyVol. 59(1)
Nanchang University (CN), East China University of Science and Technology (CN), Tsinghua University (CN)
Openalex Percentile: Top 32%
Sustainable Industrial Ecology
0.35
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