Integrated optimization modelling framework for low-carbon and green regional transitions through resource-based industrial symbiosis

Xin Xie, Hang Fu, Qisheng Zhu and Shanying Hu ()
Additional contact information
Xin Xie: Tsinghua University
Hang Fu: Tsinghua University
Qisheng Zhu: Tsinghua University
Shanying Hu: Tsinghua University

Nature Communications, 2024, vol. 15, issue 1, 1-13

Abstract: Abstract The development and utilization of bulk resources provide the basic material needs for industrial systems. However, most current resource utilization patterns are unsustainable, with low efficiencies and high carbon emissions. Here, we report a quantitative tool for resource-based industries to facilitate sustainable and low-carbon transitions within the regional economy. To evaluate the effectiveness of this tool, the saline Qinghai Lake region was chosen as a case study. After optimizing the industrial structure, the benefits of economic output, resource efficiency, energy consumption, solid waste reduction, and carbon emission reduction can be obtained. The scenario analyses exhibit disparities in different transition paths, where the carbon mitigation, economic output, and resource efficiency that benefit from optimal development paths are significantly better than those of the traditional path, indicating the urgency of adopting cleaner technology and industrial symbiosis for regional industries.

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-024-48249-6 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-48249-6

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-024-48249-6

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().