西部地区工业碳排放达峰预测与减排潜力分析

邹艳; 李佳佳; 王淑平

doi:10.13205/j.hjgc.202505022

西部地区工业碳排放达峰预测与减排潜力分析

doi: 10.13205/j.hjgc.202505022

重庆师范大学经济与管理学院, 重庆 401331

基金项目:

教育部人文社会科学研究项目“西部地区工业碳达峰情景预测及达峰路径研究”（23XJA630006）；重庆市自然科学基金项目“非线性多变量动态灰色预测建模理论与方法研究”（CSTB2023NSCQ-MSX0380）；重庆师范大学研究生科研创新项目“融合多源信息的中国碳市场碳价时滞组合预测研究”（YKC24016）

详细信息

作者简介:
邹艳（1974—），女，教授，主要研究方向为预测与决策、智能计算、技术创新管理。zouyan@cqnu.edu.cn

通讯作者:
王淑平（1999—），女，硕士研究生，主要研究方向为预测与决策。wsp17755698041@163.com

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出版历程
- 收稿日期: 2024-06-17
- 录用日期: 2024-08-15
- 修回日期: 2024-07-23
- 网络出版日期: 2025-09-11

Peak prediction and emission-reduction potential analysis for industrial carbon emissions in Western China

School of Economics and Management, Chongqing Normal University, Chongqing 401331, China

摘要

摘要: 西部地区作为中国工业发展的重点区域，科学预测其工业碳达峰情况有利于制定符合区域特点的减排政策。提出一种符合中国实际的碳排放核算体系，对西部11个省级行政区工业碳排放量进行合理测算；在此基础上构建粒子群-小波神经网络模型，以预测西部地区2020—2030年工业碳排放总量；结合最终预测结果分析西部地区工业碳达峰情况及减排潜力。结果显示：1）自然达峰情景下，广西、云南、陕西、甘肃、新疆、重庆、青海、宁夏有望2030年前实现达峰，内蒙古、四川、贵州在实现碳达峰目标方面可能存在一定困难；2）碳排放强度方面，除内蒙古外，西部其余省级行政区的工业行业均能实现碳排放强度较2005年下降60%~65%的目标，且广西、重庆、陕西、贵州、云南的碳排放下降幅度可达到90%以上；3）碳减排潜力方面，西部地区整体减排潜力较大，其中内蒙古、青海、宁夏是西部地区中减排潜力最大的3个省级行政区。最后结合西部地区工业行业特点，提出合理调整减排重点区域、优化能源结构、制定动态达峰控制策略等建议。
- 工业碳排放 /
- 小波神经网络 /
- 西部地区 /
- 碳达峰预测 /
- 减排潜力分析
Abstract: As a critical region for China's industrial development， accurately predicting the industrial carbon peak in Western China is essential for formulating effective emission reduction policies tailored to local characteristics. This paper proposes a carbon emission accounting system aligned with China's specific conditions to reasonably estimate industrial carbon emissions in 11 major western regions. Based on this， a combined forecasting model was established using particle swarm optimization （PSO） to optimize wavelet neural networks （WNN） for predicting the total industrial carbon emissions in the western region from 2020 to 2030. Furthermore， the final prediction results were analyzed to assess the western region's industrial carbon peak situation and reduction potential. The findings indicated that：1） under the natural peak scenario， eight administrative regions of Guangxi， Yunnan， Shaanxi， Gansu， Xinjiang， Chongqing， Qinghai， and Ningxia were expected to reach their peak before 2030， while three administrative regions of Inner Mongolia， Sichuan， and Guizhou might have some difficulties in achieving this carbon peak target. 2） in terms of carbon emission intensity reduction， the industrial sectors in the western region， except Inner Mongolia， were capable of reaching a reduction in carbon emission intensity by 60% to 65% compared to their 2005 levels. Notably， the carbon emissions in Guangxi， Chongqing， Shaanxi， Guizhou， and Yunnan were projected to decrease by more than 90%. 3） regarding emission reduction potential， the western region showed substantial overall potential， with Inner Mongolia， Qinghai， and Ningxia identified as the three regions with the highest emission reduction potential. Based on the characteristics of the industrial sectors in the western region， this paper proposed recommendations for adjusting the focus of emission reduction efforts， optimizing the energy structure， and developing dynamic peak control strategies. The primary recommendations are as follows： 1） classified regulation based on carbon emission trends across western administrative regions： administrative regions with a relatively strong foundation in carbon reduction may warrant a moderate relaxation of regulatory measures， provided that industrial carbon emissions continue to decline without rebounding. For regions that have transitioned from the growth phase to the reduction phase of carbon emissions， sustained regulation of industrial carbon reduction is essential to further decrease emissions and ensure the achievement of carbon peak targets. Conversely， regions with a weaker foundation in carbon reduction require prioritized monitoring of industrial carbon emissions. Regulatory efforts in these areas should be continuously adjusted according to their specific carbon emission levels to enhance the effectiveness of reduction measures. 2） focus on regions with high carbon reduction potential： regions with significant carbon reduction potential should be prioritized for increased policy interventions， and this can be achieved by advancing technological capabilities， promoting clean energy development， and optimizing industrial structures.
- industrial carbon emissions /
- wavelet neural network /
- the western region /
- prediction of carbon peaking /
- emission reduction potential analysis

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