城市人均综合能耗分类评估研究
|
摘要
提出了使用影响城市人均综合能耗的客观因素对城市进行分类评估的新方法,以解决城市间能效可比性及能效目标针对性的问题。运用单因素多阶段分类法及AdaBoost算法将全国地级以上城市分为采暖-高产值、采暖-低产值、非采暖-高工业-高产值、非采暖-高工业-低产值、非采暖-低工业-高产值、非采暖-低工业-低产值6类。2005—2015年,人均综合能耗全国平均值呈逐年稳中有升趋势,其中"采暖-高产值"城市人均综合能耗水平高、增长快,"非采暖-低工业-低产值"城市人均综合能耗始终居6类城市中最低水平。
A new classification evaluation method of city per total energy consumption was proposed based on objective factors,in order to solve the area comparability and pertinence.The prefecture level above cities of China was divided into 6kinds of"heating-high per capita GDP","heating-low per capita GDP","non-heating-developed industry-high per capita GDP","non-heating-developed industry-low per capita GDP","non-heating-undeveloped industry-high per capita GDP"and"non-heating-undeveloped industry-low per capita GDP"using single multistep classification and AdaBoost algorithm.During 2005-2015,the average per capita total energy consumption in China increased gradually.The per capita total energy consumption of the cities with heating-high per capita GDP was the highest and increased fastest while the cities with non-heating-undeveloped industry-low per capita GDP always ranked the last.
A new classification evaluation method of city per total energy consumption was proposed based on objective factors,in order to solve the area comparability and pertinence.The prefecture level above cities of China was divided into 6kinds of"heating-high per capita GDP","heating-low per capita GDP","non-heating-developed industry-high per capita GDP","non-heating-developed industry-low per capita GDP","non-heating-undeveloped industry-high per capita GDP"and"non-heating-undeveloped industry-low per capita GDP"using single multistep classification and AdaBoost algorithm.During 2005-2015,the average per capita total energy consumption in China increased gradually.The per capita total energy consumption of the cities with heating-high per capita GDP was the highest and increased fastest while the cities with non-heating-undeveloped industry-low per capita GDP always ranked the last.
引文
[1]方国斌,马慧敏,宋国君.基于气候区划的城市能源效率分类研究[J].统计与决策,2016(18):125-130.
[2]赵先超,宋丽美,朱翔.湖南省城乡居民生活能耗测算及节能思路研究[J].科技与经济,2016,29(1):77-81.
[3]宋国君,傅毅明,马本,等.中国地区能源利用效率评估指数体系设计及实证探讨[J].环境污染与防治,2010,32(10):91-96.
[4]宋国君,马本.中国城市能源效率评估研究[M].北京:化学工业出版社,2013.
[5] HAO Y,PENG H.On the convergence in China’s provincial per capita energy consumption:new evidence from a spatial econometric analysis[J].Energy Economics,2017,68:31-43.
[6] BURCU O,ILHAN O.A new approach to energy consumption per capita stationarity:evidence from OECD countries[J].Renewable and Sustainable Energy Reviews,2016,65:332-344.
[7] HASSAN M,RATI R.Convergence in energy consumption per capita across the US states,1970-2013:an exploration through selected parametric and non-parametric methods[J].Energy Economics,2017,62:404-410.
[8]史丹,马翠萍.我国能源需求的驱动因素与节能减排政策效果分析[J].当代财经,2014(10).
[9]孙欣.省际节能减排效率变动及收敛性研究——基于Malmquist指数[J].统计与信息论坛,2010,25(6):101-107.
[10]宋一弘.环境约束下城市能源效率及其影响因素分析——基于三阶段DEA-malmquist指数的实证分析[J].暨南学报(哲学社会科学版),2012(11):99-105,163.
[11]王效华,胡晓燕.农村家庭能源消费的影响因素[J].农业工程学报,2010,26(3):294-297.
[12]王菲,董锁成,毛琦梁.基于工业结构特征的中国地区能源消费强度差异分析[J].地理科学进展,2013,32(4):522-531.
[13]陈泽军,马本.浙江省城市能源效率评估研究[J].环境污染与防治,2011,33(6).
[14]曾雪兰,徐伟嘉,郭绍德,等.广东省“十二五”节能减碳下降潜力分析及对策研究[J].环境污染与防治,2014,36(3):99-102,109.
[15]沈镭,刘立涛,王礼茂,等.2050年中国能源消费的情景预测[J].自然资源,2015,30(3):361-373.
[16]傅春,巫锡金.中部地区能源效率影响因素的分析模型与案例研究[J].长江流域资源与环境,2010,19(10):1107-1110.
[17] HOSSEIN E.A structural equation model of energy consumption in the United States:untangling the complexity of per-capita residential energy use[J].Energy Research&Social Science,2015,6:109-120.
[18]刘满芝,刘贤贤.中国城镇居民生活能源消费影响因素及其效应分析——基于八区域的静态面板数据模型[J].资源科学,2016,38(12):2295-2306.
[19]杨冰,王继龙,左晓利,等.北京市居民节能意识调查及潜力分析[J].中外能源,2017,22(10):92-97.
[20]刘满芝,刘贤贤,陈梦.中国城镇生活能源消费:影响因素分解及空间差异分析[J].首都经济贸易大学学报,2017,19(5):13-20.
[21]方国斌,宋国君.城市能源效率的PS-kNN分类综合评价[J].统计与信息论坛,2014,29(9):34-43.
[2]赵先超,宋丽美,朱翔.湖南省城乡居民生活能耗测算及节能思路研究[J].科技与经济,2016,29(1):77-81.
[3]宋国君,傅毅明,马本,等.中国地区能源利用效率评估指数体系设计及实证探讨[J].环境污染与防治,2010,32(10):91-96.
[4]宋国君,马本.中国城市能源效率评估研究[M].北京:化学工业出版社,2013.
[5] HAO Y,PENG H.On the convergence in China’s provincial per capita energy consumption:new evidence from a spatial econometric analysis[J].Energy Economics,2017,68:31-43.
[6] BURCU O,ILHAN O.A new approach to energy consumption per capita stationarity:evidence from OECD countries[J].Renewable and Sustainable Energy Reviews,2016,65:332-344.
[7] HASSAN M,RATI R.Convergence in energy consumption per capita across the US states,1970-2013:an exploration through selected parametric and non-parametric methods[J].Energy Economics,2017,62:404-410.
[8]史丹,马翠萍.我国能源需求的驱动因素与节能减排政策效果分析[J].当代财经,2014(10).
[9]孙欣.省际节能减排效率变动及收敛性研究——基于Malmquist指数[J].统计与信息论坛,2010,25(6):101-107.
[10]宋一弘.环境约束下城市能源效率及其影响因素分析——基于三阶段DEA-malmquist指数的实证分析[J].暨南学报(哲学社会科学版),2012(11):99-105,163.
[11]王效华,胡晓燕.农村家庭能源消费的影响因素[J].农业工程学报,2010,26(3):294-297.
[12]王菲,董锁成,毛琦梁.基于工业结构特征的中国地区能源消费强度差异分析[J].地理科学进展,2013,32(4):522-531.
[13]陈泽军,马本.浙江省城市能源效率评估研究[J].环境污染与防治,2011,33(6).
[14]曾雪兰,徐伟嘉,郭绍德,等.广东省“十二五”节能减碳下降潜力分析及对策研究[J].环境污染与防治,2014,36(3):99-102,109.
[15]沈镭,刘立涛,王礼茂,等.2050年中国能源消费的情景预测[J].自然资源,2015,30(3):361-373.
[16]傅春,巫锡金.中部地区能源效率影响因素的分析模型与案例研究[J].长江流域资源与环境,2010,19(10):1107-1110.
[17] HOSSEIN E.A structural equation model of energy consumption in the United States:untangling the complexity of per-capita residential energy use[J].Energy Research&Social Science,2015,6:109-120.
[18]刘满芝,刘贤贤.中国城镇居民生活能源消费影响因素及其效应分析——基于八区域的静态面板数据模型[J].资源科学,2016,38(12):2295-2306.
[19]杨冰,王继龙,左晓利,等.北京市居民节能意识调查及潜力分析[J].中外能源,2017,22(10):92-97.
[20]刘满芝,刘贤贤,陈梦.中国城镇生活能源消费:影响因素分解及空间差异分析[J].首都经济贸易大学学报,2017,19(5):13-20.
[21]方国斌,宋国君.城市能源效率的PS-kNN分类综合评价[J].统计与信息论坛,2014,29(9):34-43.