山东理工大学学报（自然科学版）2025，Vol.39Issue(5)：21-28,8.
基于聚类分析的中国省域建筑业碳排放影响因素研究和情景预测
Research on influencing factors and scenario prediction of carbon emissions in China's provincial construction industry based on clustering analysis
摘要
Abstract
Taking the influencing factors of carbon emissions in the construction industry as the clustering index,the provinces with similar characteristics were divided into three clusters.The random forest algo-rithm was used to identify the key factors affecting the carbon emissions of each type of construction in-dustry.The STIRPAT model was constructed to predict carbon emissions under three different scenarios(baseline,extensive and low-carbon)by adjusting the relevant influencing factors.The results show that there are large differences in carbon emissions among different types of provinces.Category 1 and Catego-ry 2 have great potential for carbon emission reduction.It is necessary not only to accelerate the upgra-ding of industrial structure and energy structure transformation,but also to pay attention to the impact of economy and technology on carbon emissions in the construction industry.The peak time varies.The provinces in Category 1 will reach peaks around 2032,2032 and 2030 under the baseline,extensive and low-carbon scenarios respectively.Provinces in Category 2 can only reach the peak in 2032 under the low-carbon scenario.Provinces in Category 3 can peak their carbon emissions around 2030 under any scenario.关键词
建筑业碳排放/K-means/随机森林算法/STIRPAT/影响因素/情景预测Key words
carbon emissions from the construction industry/K-means/random forest algorithm/STIR-PAT/influencing factors/scenario prediction分类
建筑与水利引用本文复制引用
韩硕,王志强,刘馨月,任金哥,闫庆雨..基于聚类分析的中国省域建筑业碳排放影响因素研究和情景预测[J].山东理工大学学报（自然科学版）,2025,39(5):21-28,8.基金项目
山东省自然科学基金项目(ZR2024ME173) （ZR2024ME173）
