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作 者:薛仲侠 王志强 XUE Zhongxia;WANG Zhiqiang(School of Management Engineering,Qingdao University of Technology,Qingdao 266520,China)
机构地区:[1]青岛理工大学管理工程学院,山东青岛266520
出 处:《山东理工大学学报(自然科学版)》2025年第1期60-64,共5页Journal of Shandong University of Technology:Natural Science Edition
基 金:山东省自然科学基金项目(ZR2024ME173)。
摘 要:随着我国碳市场的全面开启,低碳居住建筑增量成本过高、资金回笼期太长的现况或将被打破。以北京市一栋居住建筑为例,利用机器学习、工程经济学等相关理论方法,运用PKPM软件建模进行碳排放计算,以静态投资回收期作为评价指标,分析碳交易计划对低碳居住建筑全生命周期的经济影响。结果表明:碳交易计划可为新建低碳居住建筑整体带来10.92%的额外收益,其中运行阶段碳收益占比7.03%。本研究可为房地产开发商开发房屋类型选择提供参考。With the full opening of our country′s carbon market,the current situation of low carbon residential buildings with too high incremental costs and too long capital payback periods may be broken.Taking a residential building in Beijing as an example,we use machine learning,engineering economics and other relevant theoretical methods,calculate carbon emissions using PKPM software modeling,and take the investment payback period as an evaluation index to analyze the economic impact of carbon trading scheme on the full life cycle of low-carbon residential buildings.The results show that the carbon trading scheme can bring overall 10.92%additional benefits to new low-carbon residential buildings,and the carbon revenue in the operation stage accounts for 7.03%.The above research provides a reference for real estate developers to develop housing types.
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