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Peaking Carbon Emissions in a Megacity through Economic Restructuring: A Case Study of Shenzhen, China

doi: 10.3390/en15196932
With the growing cost of carbon emissions reduction, the application of industrial restructuring to suppress carbon emissions is becoming more attractive. By constructing an input-output optimization model, this study explored how industrial restructuring helps megacities synergistically achieve carbon peak and high-quality development. The results showed that through contributing 164.4% of the reduction in emissions from 2020 to 2025, industrial structure optimization significantly inhibited the growth of carbon emissions; From 2020 to 2025, the manufacturing structure continued to be high-end, which resulted in a reduction in industrial carbon emissions by 10.3%; through vigorous development of the low-carbon service industry, the carbon emission of the service industry would continue to slow down at an average annual rate of 2.4%. Industrial premiumization and the low-carbonization of the modern service sector are the key driving forces for Shenzhen to achieve low-carbon transformation. The results also showed that the power and retail sectors are the most important for emissions reduction. This study can provide a roadmap for megacities on how to explore potential emission reduction via optimizing their economic structure to help them achieve their carbon emissions peak.
- Harbin Institute of Technology China (People's Republic of)
- Shenzhen University China (People's Republic of)
- University Town of Shenzhen China (People's Republic of)
- Shenzhen University China (People's Republic of)
- Harbin Institute of Technology China (People's Republic of)
Technology, I-O optimization model, emission reduction potential, T, industrial restructuring, I-O optimization model; industrial restructuring; emission reduction potential
Technology, I-O optimization model, emission reduction potential, T, industrial restructuring, I-O optimization model; industrial restructuring; emission reduction potential
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