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Carbon Peak Prediction and Carbon Reduction Path Simulation under the “Dual Carbon” Target: A Case Study of Jiangsu Province
- 1 Guangdong Ocean University (Yangjiang Campus)
- 2 Guangdong Ocean University (Yangjiang Campus)
- 3 Guangdong Ocean University (Yangjiang Campus)
- 4 Guangdong Ocean University (Yangjiang Campus)
- 5 Guangdong Ocean University (Yangjiang Campus)
* Author to whom correspondence should be addressed.
Abstract
To build a low-carbon and harmonious society that supports sustainable development, China has set forth the significant strategic goal of achieving carbon peaking by 2030 and carbon neutrality by 2060, commonly referred to as the “dual carbon” target. The key to achieving this target lies in scientifically and accurately predicting the timeline for carbon peaking, followed by developing effective carbon reduction paths. Using Jiangsu Province as an example, this study utilizes energy and economic data from 2010 to 2020 and introduces a penalized Lasso-Kaya model to forecast carbon emissions. The applicability of deep learning models, such as LSTM, in carbon peak prediction is also validated. Based on this, three levels of carbon reduction targets were established: baseline, steady progress, and ambitious. Through parameter simulation, the study derives an optimal carbon reduction path for Jiangsu Province through 2060. Consequently, this paper proposes a quantitative assurance mechanism for carbon reduction that maximizes economic growth, providing a valuable reference for future policy intervention.
Keywords
carbon peak, carbon neutrality, reduction path, numerical simulation, Kaya model
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Cite this article
Tian,T.;Qiu,F.;Zhao,G.;Li,Q.;Zeng,S. (2024). Carbon Peak Prediction and Carbon Reduction Path Simulation under the “Dual Carbon” Target: A Case Study of Jiangsu Province. Journal of Applied Economics and Policy Studies,12,43-52.
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