基于LSTM神经网络的中国省级碳达峰路径分析
摘要
作为世界最大的碳排放国家和第二大经济体，中国承诺二氧化碳排放量将于2030年左右达到峰值，届时二氧化碳排放强度较2005年下降60%～65%。然而，中国各省份之间存在较大的异质性，其碳达峰路径不能“一刀切”。基于各省份的“十四五”规划，本文设计了基准、绿色发展、高碳发展三种情境，采用LSTM神经网络动态预测2020-2040年中国及各省份的碳达峰路径，并根据各省份碳排放强度、累积碳排放量和达峰时间三因素分析了其适合的达峰路径。结果表明：在不同的情境下中国都将在2030年之前实现碳达峰目标，峰值水平在10884-11792百万吨；24个省份能够在至少一种情境下实现2030年之前碳达峰目标，且大部分省份都呈现绿色发展情境下达峰时间早、峰值低，高碳情境达峰时间晚、峰值高的特点；北京、上海、福建、浙江等省份有望在2035年之后实现负碳。研究结果对中国合理制定2030年碳达峰路径措施，统筹分配减排任务具有重要参考价值。<br/>As the world's largest carbon emitter and second largest economy, China has pledged that its carbon emissions will peak before 2030. Meanwhile, the intensity of carbon emissions will drop by 60%～65%compared to that of 2005. However, due to the varying carbon emissions trajectories of individual provinces, their carbon emissions paths cannot be one-size-fits-all. Three scenarios, i. e., benchmark, green development, and high-carbon, are designed based on the “14th Five-Year Plan” of each province. Based on LSTM, the carbon emissions of each province from 2020—2040 are predicted under different scenarios. Finally, the appropriate peak paths for individual provinces are analyzed based simultaneously on carbon emission intensity, cumulative carbon emissions and peak time. The results show that the higher the growths rate is, the later the peak time will arrive; China will achieve its carbon emissions peak before 2030, with a peak level of 11884～11792Mt; 24 provinces can achieve the carbon emissions peak before 2030 under at least one scenario; Beijing, Shanghai, Zhejiang, etc. can achieve negative carbon emissions after 2035; An important reference is provided for national policy makers to allocate emission reduction tasks and optimize emission reduction policies.