基于STIRPAT模型的广州市建筑碳排放影响因素及减排措施分析
|
摘要
文章对影响建筑碳排放的因素进行了分析研究,找到了最有效的建筑减排措施。文章基于STIRPAT模型,在岭回归的基础上,分别对2006-2014年影响广州市公共和住宅建筑碳排放的因素进行了定量分析,并从微观角度定量评价了不同的减排措施。研究结果表明:公共建筑面积和第三产业增加值对公共建筑碳排放的影响最大,常住人口和公共建筑单耗的影响相对较小;常住人口和住宅建筑面积对住宅建筑碳排放的影响最大,其次为住宅单耗,而居民消费水平的影响较小。对广州市公共建筑进行外窗及外墙改造、普及LED灯和楼宇智能控制系统,2030年可减排512万tCO_2~e;对住宅建筑进行外窗贴膜及外墙改造、普及LED灯和太阳能热水器,2030年可减排127万t CO_2~e。
This paper aims to find the most effective measures on carbon emission reduction of buildings via analysis on contributing factors of it. Based on the STIRPAT model and ridge regression analysis, we quantitatively analyzed the factors that influenced the carbon emission of public and residential buildings in Guangzhou during the period from 2006 to 2014. We also quantitatively evaluated diverse measures on carbon emission reduction from the micro perspective.The results revealed that, for carbon emission of public buildings, public building area and the added value of the tertiary industry contributed the most, while permanent population and the unit consumption of public gross area affected relatively less. For carbon emission of residential buildings, the permanent population and residential construction area impacted the most, followed by residential unit consumption. However, the level of residential consumption contributed less. In2030, renewing of external windows and exterior wall, utilities of LED lights and building intelligent control systems for public buildings in Guangzhou will reduce emission of 5.12 million tCO2 e. External window filming, exterior wall renewing, utilities of LED lights and solar water heaters for residential buildings will reduce emission of 1.27 million tCO2 e.
This paper aims to find the most effective measures on carbon emission reduction of buildings via analysis on contributing factors of it. Based on the STIRPAT model and ridge regression analysis, we quantitatively analyzed the factors that influenced the carbon emission of public and residential buildings in Guangzhou during the period from 2006 to 2014. We also quantitatively evaluated diverse measures on carbon emission reduction from the micro perspective.The results revealed that, for carbon emission of public buildings, public building area and the added value of the tertiary industry contributed the most, while permanent population and the unit consumption of public gross area affected relatively less. For carbon emission of residential buildings, the permanent population and residential construction area impacted the most, followed by residential unit consumption. However, the level of residential consumption contributed less. In2030, renewing of external windows and exterior wall, utilities of LED lights and building intelligent control systems for public buildings in Guangzhou will reduce emission of 5.12 million tCO2 e. External window filming, exterior wall renewing, utilities of LED lights and solar water heaters for residential buildings will reduce emission of 1.27 million tCO2 e.
引文
[1]蔡伟光.中国建筑能耗影响因素分析模型与实证研究[D].重庆:重庆大学,2011.
[2]王霞,任宏,蔡伟光,等.中国建筑能耗时间序列变化趋势及其影响因素[J].暖通空调,2017(11):21-26.
[3]刘希雅,王宇飞,宋祺佼,等.城镇化过程中的碳排放来源[J].中国人口·资源与环境,2015,25:61-66.
[4] Zhu Y,Cai W.Applying STIRPAT model to identify driving factors of urban residential building energy consumption:A case study of Chongqing in China[A].Proceedings of the Seventh International Conference on Management Science and Engineering Management[C].Berlin Heidelberg:Springer-Verlag,2014.1299-1310.
[5] York R, Rosa Ea, Dietz T. STIRPAT, IPAT and ImPACT:Analytic tools for unpacking the driving forces of environmental impacts[J].Ecological Economics,2003,46:351-365.
[6]沈帆.窗户特性对建筑空调负荷的影响及经济性分析[D].武汉:华中科技大学,2014.
[7]兰勇,万朝均.建筑外墙传热系数对能耗的影响[J].重庆理工大学学报,2008,22(6):31-34.
[8] GB50034-2013建筑照明设计标准[M].北京:中国建筑工业出版社,2014.
[9]陈建峰,孙剑波.建筑节能玻璃膜的应用与建筑节能效果分析[J].住宅产业,2013(4):182-182.
[10]王克红,赵黛青,王伟.太阳能热水器和电热水器的环境和经济效益分析与评价[J].能源工程,2006(5):4-8.
[2]王霞,任宏,蔡伟光,等.中国建筑能耗时间序列变化趋势及其影响因素[J].暖通空调,2017(11):21-26.
[3]刘希雅,王宇飞,宋祺佼,等.城镇化过程中的碳排放来源[J].中国人口·资源与环境,2015,25:61-66.
[4] Zhu Y,Cai W.Applying STIRPAT model to identify driving factors of urban residential building energy consumption:A case study of Chongqing in China[A].Proceedings of the Seventh International Conference on Management Science and Engineering Management[C].Berlin Heidelberg:Springer-Verlag,2014.1299-1310.
[5] York R, Rosa Ea, Dietz T. STIRPAT, IPAT and ImPACT:Analytic tools for unpacking the driving forces of environmental impacts[J].Ecological Economics,2003,46:351-365.
[6]沈帆.窗户特性对建筑空调负荷的影响及经济性分析[D].武汉:华中科技大学,2014.
[7]兰勇,万朝均.建筑外墙传热系数对能耗的影响[J].重庆理工大学学报,2008,22(6):31-34.
[8] GB50034-2013建筑照明设计标准[M].北京:中国建筑工业出版社,2014.
[9]陈建峰,孙剑波.建筑节能玻璃膜的应用与建筑节能效果分析[J].住宅产业,2013(4):182-182.
[10]王克红,赵黛青,王伟.太阳能热水器和电热水器的环境和经济效益分析与评价[J].能源工程,2006(5):4-8.