居民生活能源消费碳排放驱动因素分解——以天津市为例
|
摘要
气候变化是当前全球面临的重大挑战之一。研究居民生活能源消费碳排放变化趋势以及影响因素,对提出科学的碳减排策略,减缓气候变化具有重要的指导意义。以天津市为研究案例,对其居民生活能源消费产生的CO_2排放量进行计算,并运用LMDI模型对天津市居民生活能源消费产生的CO_2变动量进行因素分解,从能源碳排放强度、能源消费结构、能源消费强度、经济发展、人口等方面对居民生活能源消费碳排放因素进行分解分析,确定导致碳排放量变化的驱动因素。分析结果表明,经济发展、人口效应为正向效应,能源碳排放强度、能源消费结构、能源消费强度总体上为负向效应,其中经济发展因素是天津市居民生活能源消费碳排放的主要拉动因素,而能源消费强度因素是抑制碳排放的主要减量因素。
Climate change is one of the major challenges facing the world today. The research on the change trend and the influencing factors of carbon emissions about residential energy consumption has an important guiding significance to put forward the scientific carbon emission reduction strategy to mitigate climate change. This paper takes Tianjin as a case study. Based on the data of the residential energy consumption of Tianjin, the CO_2 emissions generated by the energy consumption are calculated. The paper analyzes the factors of carbon emissions about residential energy consumption and examines the influence with LMDI, including energy consumption structure, energy consumption intensity, economic development and population, and then determines the driving factors leading to changes in carbon emission. The results show that economic development and population effect are the positive effect; energy consumption structure and energy consumption intensity are the negative effect. Economic development is the main factor to increase the carbon emission of Tianjin residential living energy consumption, and the energy consumption intensity is the main factor to reduce the carbon emission.
Climate change is one of the major challenges facing the world today. The research on the change trend and the influencing factors of carbon emissions about residential energy consumption has an important guiding significance to put forward the scientific carbon emission reduction strategy to mitigate climate change. This paper takes Tianjin as a case study. Based on the data of the residential energy consumption of Tianjin, the CO_2 emissions generated by the energy consumption are calculated. The paper analyzes the factors of carbon emissions about residential energy consumption and examines the influence with LMDI, including energy consumption structure, energy consumption intensity, economic development and population, and then determines the driving factors leading to changes in carbon emission. The results show that economic development and population effect are the positive effect; energy consumption structure and energy consumption intensity are the negative effect. Economic development is the main factor to increase the carbon emission of Tianjin residential living energy consumption, and the energy consumption intensity is the main factor to reduce the carbon emission.
引文
[1]IPCC.Summary for Policymakers.Climate Change 2013:The Physical Science Basis.Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change[R].Cambridge,United Kingdom and New York,NY,USA:Cambridge University Press,2013.
[2]国家统计局能源统计局.中国能源统计年鉴—2014[M].北京:中国统计出版社,2015.
[3]王宁.基于LMDI的居民生活用能碳排放的区域差异研究[D].北京:首都经济贸易大学,2015.
[4]秦翊.中国居民生活能源消费研究[D].太原:山西财经大学,2013.
[5]李铁.污染物排放量的基本计算方法解析[J].考试周刊,2013(36):196.
[6]IPCC.《2006年IPCC国家温室气体清单指南》[M].日本:日本全球环境战略研究所,2006.
[7]徐军委.基于LMDI的我国二氧化碳排放影响因素研究[D].北京:中国矿业大学(北京),2013.
[8]Dai Y,Gao H O.Energy consumption in China’s logistics industry:A decomposition analysis using the LMDI approach[J].Transportation Research Part D Transport&Environment,2016,46:69-80.
[9]宋杰鲲.基于LMDI的山东省能源消费碳排放因素分解[J].资源科学,2012(1):35-41.
[10]王倩.基于LMDI的广东省碳排放驱动因子研究[D].广州:广东省社会科学院,2014.
[2]国家统计局能源统计局.中国能源统计年鉴—2014[M].北京:中国统计出版社,2015.
[3]王宁.基于LMDI的居民生活用能碳排放的区域差异研究[D].北京:首都经济贸易大学,2015.
[4]秦翊.中国居民生活能源消费研究[D].太原:山西财经大学,2013.
[5]李铁.污染物排放量的基本计算方法解析[J].考试周刊,2013(36):196.
[6]IPCC.《2006年IPCC国家温室气体清单指南》[M].日本:日本全球环境战略研究所,2006.
[7]徐军委.基于LMDI的我国二氧化碳排放影响因素研究[D].北京:中国矿业大学(北京),2013.
[8]Dai Y,Gao H O.Energy consumption in China’s logistics industry:A decomposition analysis using the LMDI approach[J].Transportation Research Part D Transport&Environment,2016,46:69-80.
[9]宋杰鲲.基于LMDI的山东省能源消费碳排放因素分解[J].资源科学,2012(1):35-41.
[10]王倩.基于LMDI的广东省碳排放驱动因子研究[D].广州:广东省社会科学院,2014.