安庆师范大学学报（自然科学版）2024，Vol.30Issue(2)：1-9,25,10.DOI:10.13757/j.cnki.cn34-1328/n.2024.02.001
安庆市工业能源消费碳排放影响因素分析与趋势预测
Analysis and Prediction of Carbon Emission from Industrial Energy Consumption in Anqing
摘要
Abstract
Carbon emissions from industrial energy consumption in Anqing from 2010 to 2021 were calculated using the emission factor method. The LMDI and STIRPAT models were employed to identify and analyze the contributing factors of carbon emissions and quantify the degree of their contribution to carbon emissions. Additionally, through scenario analysis, car-bon emissions from industrial energy consumption in Anqing for the period from 2022 to 2035 were projected under different development scenarios. The results reveal a general upward trend in carbon emissions, amounting to a total increase of 9.257 million tons over the 2010—2021 period, culminating in 21.02 million tons in 2021. Notably, the effects of per capita output and employment population emerged as the primary factors driving the increase in carbon emissions, while the impact of ener-gy intensity played a significant role in reducing emissions. The impact of energy structure on carbon emissions growth is limit-ed. Scenario analysis suggests that, under the benchmark scenario, Anqing's industry may encounter challenges in achieving its pre-2030 peak carbon dioxide emissions target. Reasonable regulation of per capita output, energy consumption intensity, or carbon emission intensity can effectively control carbon emissions and achieve carbon peaking on time. In the scenario charac-terized by a high rate of decline in carbon emission intensity and high energy consumption intensity decline rate, Anqing's in-dustrial sector has the potential to reach the peak carbon dioxide emissions target before 2030 without negatively impacting in-dustrial economic growth. The projected value for peak carbon emissions in this scenario is 23.41 million tons.关键词
工业碳排放/LMDI模型/STIRPAT模型/碳排放预测Key words
industrial carbon emission/LMDI model/STIRPAT model/carbon emission prediction分类
资源环境引用本文复制引用
李明,薛峰,张婧,戚乐乐,倪翔,赵宽,周葆华..安庆市工业能源消费碳排放影响因素分析与趋势预测[J].安庆师范大学学报（自然科学版）,2024,30(2):1-9,25,10.基金项目
国家自然科学基金青年项目(41907334)和安徽省自然科学基金青年项目(1908085QD163) （41907334）
