中国建筑能耗影响因素分析模型与实证研究
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摘要
随着城镇化化进程加速、人们生活水平提高,中国建筑能耗呈现刚性增长趋势。而工业化的推动下,工业行业能效水平提升较快,工业领域节能潜力下降,因此建筑领域将承担越来越大的节能减排任务。中国提出到2020年单位GDP碳排放下降40-45%的减排目标,建筑节能成为能否完成此目标的关键所在。目前我国正开展规模巨大的城乡建设,建筑面积增长迅猛,当前阶段是推进建筑节能的关键时机。如果错失当前机遇,城镇化进程结束后,大量高耗能建筑将长期、持续消耗大量能源,中国将面临“碳锁定”风险,届时将付出巨大的减排成本。
识别影响建筑能耗的关键因素,确定各因素对建筑能耗的影响程度,有助于政府找到推动建筑节能的着力点,出台有针对性的政策措施。目前,国内对建筑能耗影响因素的研究还主要停留在以描述性为主的定性分析上,定量研究较少。在此背景下,本文选择建筑能耗影响因素作为研究对象,尝试运用定性与定量相结合的方法,对建筑能耗影响因素的作用机理及影响程度进行研究,在此基础上,分析在各类因素不同的变化趋势下的情况下中国建筑能耗未来增长情景,为制定建筑节能战略规划提供依据。
论文核心的研究内容包括:建筑能耗的计算与分析,建筑能耗增长驱动因素定性与定量研究,缓解建筑能耗增长的影响因素定性分析及节能贡献量研究,建筑能耗情景分析与政策研究。主要结论如下:
①建筑相关能耗是全国能源消费的最大部门。从LCA理论出发,计算分析了宏观建筑全寿命周期能耗。2009年建筑相关能耗为12亿吨标准煤,占全社会终端能源消费的41.4%,成为国民经济中能源消费最大的部门。
②人口、城镇化、建筑面积、消费水平、第三产业发展对建筑能耗增长的发挥了关键驱动作用。利用STIRPAT模型,对驱动建筑能耗增长的因素进行了定量研究,运用岭回归方法建立了回归分析模型,研究发现以上五个因素对建筑能耗增长具有重要的推动作用。
③技术进步、政策的推进有效缓解了建筑能耗增长。利用LMDI方法对缓解建筑能耗增长的因素进行定量研究。研究发现,2005-2009年技术和政策因素促使建筑能耗增速缓解23%,累计实现节能量1.21亿吨标准煤。
④要完成2020年中国碳减排目标,需进一步加大建筑节能政策力度。根据各影响因素不同的发展趋势,对2020年中国建筑能耗进行了情景分析。根据2020年我国碳减排目标,对建筑节能目标进行了测定,与建筑能耗情景相比较发现:按照目前政策力度推进,建筑节能将无法实现2020年的节能目标,如果政策力度进一步加强,且政策执行顺利的话,将有机会超过2020年的目标。
综观全文,论文在以下方面取得了创新:
①建立了宏观建筑能耗全寿命周期分析模型。将宏观建筑生命周期能耗分为建筑材料生产能耗、新建建筑建造能耗和既有建筑运行能耗,通过对1980-2009年建筑能耗的计算与分析发现,利用全寿命周期分析方法,能够全面客观的反映全社会建筑领域能源消费现状。
②首次利用STIRPAT模型对建筑能耗增长的驱动因素进行了研究。STIRPAT模型被广泛用于能源环境问题研究,国内对该方法应用主要集中对全国能源消费总量或工业消费及碳排放研究上,尚未找到利用IPAT模型或者STIRPAT模型研究建筑能耗驱动因素的相关文献。本文首次利用STIRPAT模型建筑能耗增长的驱动因素进行了研究,得到了较为合理的分析结果。
③提出了从宏观层面测度建筑节能量的一种可行方法。与一般用能产品不同,建筑产品难以可以用明确的、可度量的单一指标(如家用电器单位使用时间能源消费量)衡量其能效水平,建筑节能量的计算存在较大争议。本文在LMDI方法的基础上,提出了从宏观层面计算建筑节能量的一种可行方法。
④提出了建筑能耗情景分析一种简单有效方法。本文提出了基于关键影响因素分析模型的建筑能耗情景分析方法,该方法具备以下几个特点:1)合理实用。影响建筑能耗的因素众多,模型考虑了人口、城镇化、建筑面积、生活水平、建筑能效等关键影响因素,剔除众多的次要因素。2)形式简单,模型将建筑能耗表示为几个因素的乘积的形式,容易理解。3)计算简便,运用EXCEL表格即可进行情景预测与计算。
With the accelerated urbanization process and the improving of people’s living standard, China's building energy consumption shows rigid growth trend. Under the promotion of industrialization, the level of energy efficiency of industrial sector goes up fast, while the energy conservation potential in industrial field declines. Therefore, the construction sector will bear increasingly important energy conservation and emission reduction tasks. Since China has put forward the task of emission reduction to decrease unit of GDP carbon emission by 40-45% till 2020, building energy efficiency turns out to be the key to accomplish this goal. Since huge scale city and country development are carried on in China recently and the fast increasing number of building area, it is time to push on the energy conservation in building. If we missed this chance, a lot of highly energy-consuming buildings will constantly consume big amount of energy for a long time after the urbanizing process, and China will have to spend huge money on the emission reduction because of the danger of“Carbon Lock-In”.
Realizing the key factor of building energy consumption is good for government to find the fulcrum of developing energy conservation in building and define every impact degree on the building energy consumption caused by each elements. Currently, the main researches about factors of building energy consumption are focusing on the descriptive qualitative analysis, while quantitative researches are less. Under such background, this paper takes the factors of building energy consumption as the research object, trying to research the mechanism of action and influence degree of these factors effect on buildings by combining the qualitative and quantitative research method. On this basis, this paper will analyze the future increase of Chinese building energy consumption under different variation trend of each factor to provide references for the strategy of building energy conservation.
The core of this paper include: calculation and analysis of building energy consumption, qualitative and quantitative research about the increase of building energy consumption, analysis of driving elements of building energy conservation and energy conservation contribution research, analysis of the situation of building energy consumption and policy research. Main conclusions are:
①Building related energy consumption is the biggest consuming department in China. Basing from LCA method, the paper calculated and analyzed the macroscopic buildings life cycle energy consumption(MBEC). In 2009, MBEC is 1.2 billion tce, which is 41.4 percent of the amount of end energy consumption of China, and building has become the largest sector of energy consumption.
②Five factors, population, urbanization, building area, consumption level and the development of tertiary-industry, play the key role in driving the increase of building energy consumption. Using STIRPAT model, the paper researched the driving factors of the building energy consumption(BEC) increase quantitatively and built the regression model for elements of BEC increase by ridge regression method. The research shows that the above five factors have driving effect on the increase of building energy consumption.
③Technical and policy factors has played an important role in inhibiting BEC growing. Using LMDI approach, the paper researched the factors of the building energy efficiency quantitatively. The research shows that technical and policy factors have contributed to 23% of BEC growth rate of remission, the cumulative energy savings achieved 121 million tce.
④It is required further policy efforts to increase building energy efficiency, to complete the 2020 carbon reduction targets. According to different trends of all factors, the paper launched a scenario analysis of BEC in 2020. According to China's carbon emission reduction targets in 2020, building energy efficiency targets were determined. Compared with BEC scenes and the targets, the paper found: if according to current policy efforts to promote energy efficiency in buildings will not be able to achieve energy saving targets by 2020; If the policy efforts to further strengthen and policy implementation goes well, will have opportunities over the target.
Looking full text of the paper,there are several innovations.
①A life cycle analysis of macroscopic building energy consumption model is been established. MBEC was divided into energy consumption of the building materials production, new buildings construction and existing buildings operation. By calculating and analyzing BEC in 1980-2009, the paper found: it is could reflect the status of all social BEC fully and objectively, by using LCA.
②This paper use STIRPAT model firstly in reaserch on the driving factors of BEC. STIRPAT models are widely used in research on energy and environmental issues, domestic research is focus on energy consumption and carbon emissions of total national or industrial, on application of the method, there is few relevant literature on research driving factors of BEC, using IPAT model or STIRPAT model. This study obtained reasonable results.
③This paper proposes a feasible way to measure the building energy conservation from the macroscopical level. Different from ordinary energy-using products, it is hard to judge the energy efficiency level of a building by using a definite and measurable single variable (such as the number of electricity consumed by a household appliance when it is working). Therefore, there is debate in the calculation of building energy conservation. Based on the LMDI method, this paper gives a feasible way to measure the building energy conservation from the macroscopical level and initially proposes concepts of comparable energy consumed by every building area and the building energy consumption index. Author also researches the influence degree caused by the behavior of residents using energy in a quantitative way.
④A simple and valid way of scenario analyzing building energy consumption is been proposed. Based on factors model of buildings energy consuming, the scenario analysis proposed in this paper has follow characteristics: 1) Reasonable and feasible. Since there are many elements which can influence buildings energy consuming, the model considers key factors, population, urbanization, building area, life level and building energy consuming, etc, and eliminated many unimportant factors. 2) Simple form. The model shows the energy consumed by building as the product of few factors, which is easy to be understood. 3) Easy to calculate. Using EXCEL sheet can people forecast and calculate the scenario.
识别影响建筑能耗的关键因素,确定各因素对建筑能耗的影响程度,有助于政府找到推动建筑节能的着力点,出台有针对性的政策措施。目前,国内对建筑能耗影响因素的研究还主要停留在以描述性为主的定性分析上,定量研究较少。在此背景下,本文选择建筑能耗影响因素作为研究对象,尝试运用定性与定量相结合的方法,对建筑能耗影响因素的作用机理及影响程度进行研究,在此基础上,分析在各类因素不同的变化趋势下的情况下中国建筑能耗未来增长情景,为制定建筑节能战略规划提供依据。
论文核心的研究内容包括:建筑能耗的计算与分析,建筑能耗增长驱动因素定性与定量研究,缓解建筑能耗增长的影响因素定性分析及节能贡献量研究,建筑能耗情景分析与政策研究。主要结论如下:
①建筑相关能耗是全国能源消费的最大部门。从LCA理论出发,计算分析了宏观建筑全寿命周期能耗。2009年建筑相关能耗为12亿吨标准煤,占全社会终端能源消费的41.4%,成为国民经济中能源消费最大的部门。
②人口、城镇化、建筑面积、消费水平、第三产业发展对建筑能耗增长的发挥了关键驱动作用。利用STIRPAT模型,对驱动建筑能耗增长的因素进行了定量研究,运用岭回归方法建立了回归分析模型,研究发现以上五个因素对建筑能耗增长具有重要的推动作用。
③技术进步、政策的推进有效缓解了建筑能耗增长。利用LMDI方法对缓解建筑能耗增长的因素进行定量研究。研究发现,2005-2009年技术和政策因素促使建筑能耗增速缓解23%,累计实现节能量1.21亿吨标准煤。
④要完成2020年中国碳减排目标,需进一步加大建筑节能政策力度。根据各影响因素不同的发展趋势,对2020年中国建筑能耗进行了情景分析。根据2020年我国碳减排目标,对建筑节能目标进行了测定,与建筑能耗情景相比较发现:按照目前政策力度推进,建筑节能将无法实现2020年的节能目标,如果政策力度进一步加强,且政策执行顺利的话,将有机会超过2020年的目标。
综观全文,论文在以下方面取得了创新:
①建立了宏观建筑能耗全寿命周期分析模型。将宏观建筑生命周期能耗分为建筑材料生产能耗、新建建筑建造能耗和既有建筑运行能耗,通过对1980-2009年建筑能耗的计算与分析发现,利用全寿命周期分析方法,能够全面客观的反映全社会建筑领域能源消费现状。
②首次利用STIRPAT模型对建筑能耗增长的驱动因素进行了研究。STIRPAT模型被广泛用于能源环境问题研究,国内对该方法应用主要集中对全国能源消费总量或工业消费及碳排放研究上,尚未找到利用IPAT模型或者STIRPAT模型研究建筑能耗驱动因素的相关文献。本文首次利用STIRPAT模型建筑能耗增长的驱动因素进行了研究,得到了较为合理的分析结果。
③提出了从宏观层面测度建筑节能量的一种可行方法。与一般用能产品不同,建筑产品难以可以用明确的、可度量的单一指标(如家用电器单位使用时间能源消费量)衡量其能效水平,建筑节能量的计算存在较大争议。本文在LMDI方法的基础上,提出了从宏观层面计算建筑节能量的一种可行方法。
④提出了建筑能耗情景分析一种简单有效方法。本文提出了基于关键影响因素分析模型的建筑能耗情景分析方法,该方法具备以下几个特点:1)合理实用。影响建筑能耗的因素众多,模型考虑了人口、城镇化、建筑面积、生活水平、建筑能效等关键影响因素,剔除众多的次要因素。2)形式简单,模型将建筑能耗表示为几个因素的乘积的形式,容易理解。3)计算简便,运用EXCEL表格即可进行情景预测与计算。
With the accelerated urbanization process and the improving of people’s living standard, China's building energy consumption shows rigid growth trend. Under the promotion of industrialization, the level of energy efficiency of industrial sector goes up fast, while the energy conservation potential in industrial field declines. Therefore, the construction sector will bear increasingly important energy conservation and emission reduction tasks. Since China has put forward the task of emission reduction to decrease unit of GDP carbon emission by 40-45% till 2020, building energy efficiency turns out to be the key to accomplish this goal. Since huge scale city and country development are carried on in China recently and the fast increasing number of building area, it is time to push on the energy conservation in building. If we missed this chance, a lot of highly energy-consuming buildings will constantly consume big amount of energy for a long time after the urbanizing process, and China will have to spend huge money on the emission reduction because of the danger of“Carbon Lock-In”.
Realizing the key factor of building energy consumption is good for government to find the fulcrum of developing energy conservation in building and define every impact degree on the building energy consumption caused by each elements. Currently, the main researches about factors of building energy consumption are focusing on the descriptive qualitative analysis, while quantitative researches are less. Under such background, this paper takes the factors of building energy consumption as the research object, trying to research the mechanism of action and influence degree of these factors effect on buildings by combining the qualitative and quantitative research method. On this basis, this paper will analyze the future increase of Chinese building energy consumption under different variation trend of each factor to provide references for the strategy of building energy conservation.
The core of this paper include: calculation and analysis of building energy consumption, qualitative and quantitative research about the increase of building energy consumption, analysis of driving elements of building energy conservation and energy conservation contribution research, analysis of the situation of building energy consumption and policy research. Main conclusions are:
①Building related energy consumption is the biggest consuming department in China. Basing from LCA method, the paper calculated and analyzed the macroscopic buildings life cycle energy consumption(MBEC). In 2009, MBEC is 1.2 billion tce, which is 41.4 percent of the amount of end energy consumption of China, and building has become the largest sector of energy consumption.
②Five factors, population, urbanization, building area, consumption level and the development of tertiary-industry, play the key role in driving the increase of building energy consumption. Using STIRPAT model, the paper researched the driving factors of the building energy consumption(BEC) increase quantitatively and built the regression model for elements of BEC increase by ridge regression method. The research shows that the above five factors have driving effect on the increase of building energy consumption.
③Technical and policy factors has played an important role in inhibiting BEC growing. Using LMDI approach, the paper researched the factors of the building energy efficiency quantitatively. The research shows that technical and policy factors have contributed to 23% of BEC growth rate of remission, the cumulative energy savings achieved 121 million tce.
④It is required further policy efforts to increase building energy efficiency, to complete the 2020 carbon reduction targets. According to different trends of all factors, the paper launched a scenario analysis of BEC in 2020. According to China's carbon emission reduction targets in 2020, building energy efficiency targets were determined. Compared with BEC scenes and the targets, the paper found: if according to current policy efforts to promote energy efficiency in buildings will not be able to achieve energy saving targets by 2020; If the policy efforts to further strengthen and policy implementation goes well, will have opportunities over the target.
Looking full text of the paper,there are several innovations.
①A life cycle analysis of macroscopic building energy consumption model is been established. MBEC was divided into energy consumption of the building materials production, new buildings construction and existing buildings operation. By calculating and analyzing BEC in 1980-2009, the paper found: it is could reflect the status of all social BEC fully and objectively, by using LCA.
②This paper use STIRPAT model firstly in reaserch on the driving factors of BEC. STIRPAT models are widely used in research on energy and environmental issues, domestic research is focus on energy consumption and carbon emissions of total national or industrial, on application of the method, there is few relevant literature on research driving factors of BEC, using IPAT model or STIRPAT model. This study obtained reasonable results.
③This paper proposes a feasible way to measure the building energy conservation from the macroscopical level. Different from ordinary energy-using products, it is hard to judge the energy efficiency level of a building by using a definite and measurable single variable (such as the number of electricity consumed by a household appliance when it is working). Therefore, there is debate in the calculation of building energy conservation. Based on the LMDI method, this paper gives a feasible way to measure the building energy conservation from the macroscopical level and initially proposes concepts of comparable energy consumed by every building area and the building energy consumption index. Author also researches the influence degree caused by the behavior of residents using energy in a quantitative way.
④A simple and valid way of scenario analyzing building energy consumption is been proposed. Based on factors model of buildings energy consuming, the scenario analysis proposed in this paper has follow characteristics: 1) Reasonable and feasible. Since there are many elements which can influence buildings energy consuming, the model considers key factors, population, urbanization, building area, life level and building energy consuming, etc, and eliminated many unimportant factors. 2) Simple form. The model shows the energy consumed by building as the product of few factors, which is easy to be understood. 3) Easy to calculate. Using EXCEL sheet can people forecast and calculate the scenario.
引文
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