Research on Carbon Peak Prediction of Various Prefecture-Level Cities in Jiangsu Province Based on Factors Influencing Carbon Emissions
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References listed on IDEAS
- Fang, Kai & Tang, Yiqi & Zhang, Qifeng & Song, Junnian & Wen, Qi & Sun, Huaping & Ji, Chenyang & Xu, Anqi, 2019. "Will China peak its energy-related carbon emissions by 2030? Lessons from 30 Chinese provinces," Applied Energy, Elsevier, vol. 255(C).
- Xu, Xianshuo & Zhao, Tao & Liu, Nan & Kang, Jidong, 2014. "Changes of energy-related GHG emissions in China: An empirical analysis from sectoral perspective," Applied Energy, Elsevier, vol. 132(C), pages 298-307.
- Chen, Jiandong & Xu, Chong & Cui, Lianbiao & Huang, Shuo & Song, Malin, 2019. "Driving factors of CO2 emissions and inequality characteristics in China: A combined decomposition approach," Energy Economics, Elsevier, vol. 78(C), pages 589-597.
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- Siting Hong & Ting Fu & Ming Dai, 2025. "Machine Learning-Based Carbon Emission Predictions and Customized Reduction Strategies for 30 Chinese Provinces," Sustainability, MDPI, vol. 17(5), pages 1-29, February.
- Xuelian Zhu & Jianan Che & Xiaogeng Niu & Nannan Cao & Guofeng Zhang, 2025. "Optimization of Carbon Emission Reduction Path in the Beijing–Tianjin–Hebei Region Based on System Dynamics," Sustainability, MDPI, vol. 17(4), pages 1-24, February.
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Keywords
STIRPAT model; influencing factors; carbon peak; scenario analysis;All these keywords.
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