中国不同区域能源消费碳足迹的时空变化(英文)

Study on regional carbon emission is one of the hot topics under the background of global climate change and low-carbon economic development, and also help to establish different low-carbon strategies for different regions. On the basis of energy consumption and land use data of different regions in China from 1999 to 2008, this paper established carbon emission and carbon footprint models based on total energy consumption, and calculated the amount of carbon emissions and carbon footprint in different regions of China from 1999 to 2008. The author also analyzed carbon emission density and per unit area carbon footprint for each region. Finally, advices for decreasing carbon footprint were put forward. The main conclusions are as follows: (1) Carbon emissions from total energy consumption increased 129% from 1999 to 2008 in China, but its spatial distribution pattern among different regions just slightly changed, the sorting of carbon emission amount was: Eastern China > Northern China > Central and Southern China > Southwest China > Northwest China. (2) The sorting of carbon emission density was: Eastern China > Northeast China > Central and Southern China > Northern China > Southwest China > Northwest China from 1999 to 2003, but from 2004 Central and Southern China began to have higher carbon emission density than Northeast China, the order of other regions did not change. (3) Carbon footprint increased significantly since the rapid increasing of carbon emissions and less increasing area of pro-ductive land in different regions of China from 1999 to 2008. Northern China had the largest carbon footprint, and Northwest China, Eastern China, Northern China, Central and Southern China followed in turn, while Southwest China presented the lowest area of carbon footprint and the highest percentage of carbon absorption. (4) Mainly influenced by regional land area, Northern China presented the highest per unit area carbon footprint and followed by Eastern China, and Northeast China; Central and Southern China, and Northwest China had a similar medium per unit area carbon footprint; Southwest China always had the lowest per unit area carbon footprint. (5) China faced great ecological pressure brought by carbon emission. Some measures should be taken both from reducing carbon emission and increasing carbon absorption.     

基于能源消费的中国省级区域碳足迹时空演变分析

碳足迹作为衡量生产某一产品在其生命周期所直接或间接排放的CO₂量,其能够反应人类某项活动或某种产品对生态环境的压力程度。本文采用1997-2008年全国省级区域化石能源消费数据和土地利用结构数据,构建碳足迹计算模型,测算不同时间、不同区域的碳足迹、碳生态承载力和碳赤字,并引入物理学中重心的概念,测算1997-2008年全国各省级区域碳足迹的重心,进行碳足迹重心的时空演变趋势分析,掌握区域间能源消费碳排放的差异性;同时构建能源消费碳足迹压力指数模型,计算1997-2008年各省的碳足迹压力指数,对研究区域进行生态压力强度分级,并考察各省级区域碳足迹压力指数在两个相邻时间点之间的变化强度,进行生态压力变化强度的级别划分。     

中国能源消费碳排放的空间计量分析(英文)

Based on energy consumption data of each region in China from 1997 to 2009 and using ArcGIS9.3 and GeoDA9.5 as technical support,this paper made a preliminary study on the changing trend of spatial pattern at regional level of carbon emissions from energy con-sumption,spatial autocorrelation analysis of carbon emissions,spatial regression analysis between carbon emissions and their influencing factors.The analyzed results are shown as follows.(1) Carbon emissions from energy consumption increased more than 148% from 1997 to 2009 but the spatial pattern of high and low emission regions did not change greatly.(2) The global spatial autocorrelation of carbon emissions from energy consumption in-creased from 1997 to 2009,the spatial autocorrelation analysis showed that there exists a "polarization" phenomenon,the centre of "High-High" agglomeration did not change greatly but expanded currently,the centre of "Low-Low" agglomeration also did not change greatly but narrowed currently.(3) The spatial regression analysis showed that carbon emissions from energy consumption has a close relationship with GDP and population,R-squared rate of the spatial regression between carbon emissions and GDP is higher than that between carbon emissions and population.The contribution of population to carbon emissions in-creased but the contribution of GDP decreased from 1997 to 2009.The carbon emissions spillover effect was aggravated from 1997 to 2009 due to both the increase of GDP and population,so GDP and population were the two main factors which had strengthened the spatial autocorrelation of carbon emissions.     

基于能源消费的中国不同产业空间的碳足迹分析

Using energy consumption and land use data of each region of China in 2007,this paper established carbon emission and carbon footprint model based on energy consumption,and estimated the carbon emission amount of fossil energy and rural biomass energy of dif-ferent regions of China in 2007.Through matching the energy consumption items with indus-trial spaces,this paper divided industrial spaces into five types:agricultural space,living & industrial-commercial space,transportation industrial space,fishery and water conservancy space,and other industrial space.Then the author analyzed the carbon emission intensity and carbon footprint of each industrial space.Finally,advices of decreasing industrial carbon footprint and optimizing industrial space pattern were put forward.The main conclusions are as following:(1) Total amount of carbon emission from energy consumption of China in 2007 was about 1.65 GtC,in which the proportion of carbon emission from fossil energy was 89%.(2) Carbon emission intensity of industrial space of China in 2007 was 1.98 t/hm2,in which,carbon emission intensity of living & industrial-commercial space and of transportation in-dustrial space was 55.16 t/hm2 and 49.65 t/hm2 respectively,they were high-carbon-emission industrial spaces among others.(3) Carbon footprint caused by industrial activities of China in 2007 was 522.34 106 hm2,which brought about ecological deficit of 28.69 106 hm2,which means that the productive lands were not sufficient to compensate for carbon footprint of industrial activities,and the compensating rate was 94.5%.As to the regional carbon footprint,several regions have ecological profit while others have not.In general,the present ecologi-cal deficit caused by industrial activities was small in 2007.(4) Per unit area carbon footprint of industrial space in China was about 0.63 hm2/hm2 in 2007,in which that of living & indus-trial-commercial space was the highest (17.5 hm2/hm2).The per unit area carbon footprint of different industrial spaces all presented a declining trend from east to west of China.     

中国能源碳足迹时空格局演化及脱钩效应

利用DMSP-OLS夜间灯光数据和碳排放统计数据,构建碳排放面板数据模型,模拟了2000-2013年中国的碳排放量.运用探索性时空数据分析(ESTDA)框架体系,从时空交互视角分析2001-2013年碳足迹的空间格局和时空依赖动态演化;利用改进的Tapio脱钩模型对3个时间段336个地级单元环境碳负荷与经济增长之间的脱...     

基于能源消费的江苏省土地利用碳排放与碳足迹

采用2003~2007年江苏省能源消费和土地利用等数据,通过构建能源消费的碳排放模型,对江苏省5年来能源消费碳排放进行了核算,并通过土地利用类型和碳排放项目的对应,对不同土地利用方式的碳排放及碳足迹进行了定量分析。结论如下:(1)江苏省能源消费碳排放总量从2003年的8794.24万t上升到2007年的16329.85万t,涨幅达86%。其中,终端能源消费碳排放占53.6%。(2)江苏全省土地单位面积碳排放从2003年8.24t/hm²上升到2007年15.53 t/hm²,增幅为88.5%。其中,居民点及工矿用地单位面积碳排放最大,为95.62 t/hm²。(3)江苏全省能源消费碳足迹大于生产性土地的实际面积,由此造成的生态赤字达1351.285万hm²。(4)不同土地利用类型的碳足迹大小顺序为:居民点及工矿用地＞交通用地＞未利用地及特殊用地＞农用地和水利用地,其中居民点及工矿用地的碳足迹高达10.89 hm²/ hm²。(5)江苏全省单位面积碳足迹也呈明显的扩大趋势,从2003年的0.938 hm²/ hm²上升到2007年的1.769 hm²/ hm²。     

Spatial differences and multi-mechanism of carbon footprint based on GWR model in provincial China

Global warming has been one of the major concerns behind the world’s high-speed economic growth. How to implement the coordinated development of the carbon footprint and the economy will be the core issue of the world’s economic and social development, as well as the heated debate of the research at home and abroad in recent years. Based on the energy consumption, integrated with the “Top-Down” life cycle approach and geographically weighted regression (GWR) model, this paper analyzed the spatial differences and multi-mechanism of carbon footprint in provincial China in 2010. Firstly, this study calculated the amount of carbon footprint of each province using “Top-Down” life cycle approach and found that there were significant differences of carbon footprint and per capita carbon footprint in provincial China. The provinces with higher carbon footprint, mainly located in northern China, have large economic scales; the provinces with higher per capita carbon footprint are mainly distributed in central cities such as Beijing, Shanghai and energy-rich regions and heavy chemical bases. Secondly, with the aid of GIS and spatial analysis model (GWR model), this paper had unfolded that the expansion of economic scale is the main driver of the rapid growth of carbon footprint. The growth of population and urbanization also acted as promoting factors for the increase of the carbon footprint. Energy structure had no considerable promoting effect for the increase of the carbon footprint. Improving energy efficiency is the most important factor to inhibit the growing carbon footprint. Thirdly, developing low-carbon economies and low-carbon industries, as well as advocating low-carbon city construction and improving carbon efficiency would be the primary approaches to inhibit the rapid growth of carbon footprint. Moderately controlling the economic scale and population size would also be required to alleviate carbon footprint. Meanwhile, environmental protection and construction of low-carbon cities would evoke extensive attention in the process of urbanization.     

我国城市居民直接能耗的碳排放类型及影响因素

针对我国287个地级以上城市,在测算了近9年居民直接能耗导致的CO₂排放量的基础上,进行聚类、对比,并分析城市居民直接能耗的碳排放影响因素,得到以下结论:全国分为6类城市居民直接能耗碳排放类型;高碳排放型城市的地均碳排放强度、人均工资碳排放强度及居民直接能耗CO₂排放总量等方面均比低碳排放型城市高,人均地方生产总值碳排放强度低于低碳排放型城市,并多为经济发达城市和资源丰富城市,其碳排放构成上分别以电、交通能耗碳排放和气碳排放为主导,高碳排放型城市居民直接能耗CO₂排放量占全国地级以上城市的86.20%。我国大部分地级城市居民直接能耗的碳排放属于相对低碳排放型,其人均CO₂排放量低于全国平均水平。城市所在地的降温度日数(CDD)、采暖期、采暖强度、人均能源供给量、居民的人均工资、城市人均地方生产总值是影响城市居民直接能耗CO₂排放量的主要因素。     

环境规制、FDI与能源消费碳排放峰值预测——以西北五省为例

基于STIRPAT模型,运用情景分析法对西北地区2017—2030年能源消费碳排放进行预测,在高、中、低三种环境规制强度下设定出9种发展模式,以分析环境规制与FDI对能源碳排放峰值的影响。研究表明：（1） 在初始发展情境下,西北地区2030年碳排放总量为70 273.07×10⁴ t,无法实现碳排放达峰目标。（2） 低环境规制背景下,高、高中、高低三种发展模式2030年能源消费碳排放额为73 550.53×10⁴ t、64 881.98×10⁴ t、56 296.96×10⁴ t。（3） 中、高环境规制下,中低、低两种发展模式分别于2025年、2020年达到碳排放峰值,峰值额度为53 447.15×10⁴ t、51 022.68×10⁴ t。能源碳排放强度为0.86 t·（10⁴元）^-1、0.68 t·（10⁴元）^-1,相比较2005年碳排放强度下降48.38%、60.14%。9种发展模式中,仅中低、低两种发展模式能够如期实现碳排放峰值任务,表明严格的环境规制政策能够有效减缓西北地区能源消费碳排放,为促进西北地区碳排放峰值目标如期实现,针对西北地区碳减排工作提出了相应对策建议。     

Spatiotemporal dynamics of carbon intensity from energy consumption in China

The sustainable development has been seriously challenged by global climate change due to carbon emissions. As a developing country, China promised to reduce 40%-45% below the level of the year 2005 on its carbon intensity by 2020. The realization of this target depends on not only the substantive transition of society and economy at the national scale, but also the action and share of energy saving and emissions reduction at the provincial scale. Based on the method provided by the IPCC, this paper examines the spatiotemporal dynamics and dominating factors of China’s carbon intensity from energy consumption in 1997–2010. The aim is to provide scientific basis for policy making on energy conservation and carbon emission reduction in China. The results are shown as follows. Firstly, China’s carbon emissions increased from 4.16 Gt to 11.29 Gt from 1997 to 2010, with an annual growth rate of 7.15%, which was much lower than that of GDP (11.72%). Secondly, the trend of Moran’s I indicated that China’s carbon intensity has a growing spatial agglomeration at the provincial scale. The provinces with either high or low values appeared to be path-dependent or space-locked to some extent. Third, according to spatial panel econometric model, energy intensity, energy structure, industrial structure and urbanization rate were the dominating factors shaping the spatiotemporal patterns of China’s carbon intensity from energy consumption. Therefore, in order to realize the targets of energy conservation and emission reduction, China should improve the efficiency of energy utilization, optimize energy and industrial structure, choose the low-carbon urbanization approach and implement regional cooperation strategy of energy conservation and emissions reduction.     

近20年来中国能源消费碳排放时空格局动态

CO₂等温室气体引起的全球气候变暖是对人类社会可持续发展的严峻挑战。基于IPCC提供的参考方法,在对中国大陆30个省区(不含西藏)能源消费碳排放量估算的基础上,运用ESTDA框架,通过ESDA、LISA时间路径、时空跃迁和标准差椭圆等方法,从时空耦合的角度分析了1995-2014年中国能源消费碳排放时空格局动态性。结果表明：①近20年来中国省域碳排放具有显著的空间正相关性,碳排放空间差异呈先缩小后扩大的趋势;②LISA时间路径分析显示,中国大部分省区的局部空间结构具有较强的稳定性,1995-2001年和2002-2014年2个时段相对长度都小于平均长度的省区均为18个,大部分南方省区在空间依赖方向上的波动性呈增强趋势,而北方大多数省区则保持相对稳定;③出现协同运动的省区由1995-2001年的13个下降到2002-2014年的10个,表明中国碳排放空间格局具有一定的空间整合性,但呈减弱趋势;④中国省域碳排放的局部空间关联模式和集聚特征具有较强的稳定性,表现为一定的路径依赖或空间锁定特征;⑤碳排放重心在113.739°~114.324°E、34.475°~35.036°N之间变动,整体上有向西北方向移动的趋势。中国碳排放空间分布呈东北—西南格局,且有逐步向正北—正南转变的趋势。中国碳减排的重点是加快发展清洁能源与提高能效并重,优化能源结构和促进各省区产业结构转型,制定差异化的省域碳减排政策,建立碳交易制度。     

Urban carbon footprint and carbon cycle pressure: The case study of Nanjing简

Urban carbon footprint reflects the impact and pressure of human activities on ur- ban environment. Based on city level, this paper estimated carbon emissions and carbon footprint of Nanjing city, analyzed urban carbon footprint intensity and carbon cycle pressure and discussed the influencing factors of carbon footprint through LMDI decomposition model. The main conclusions are as follows： （1） The total carbon emissions of Nanjing increased rapidly since 2000, in which the carbon emission from the use of fossil energy was the largest Meanwhile, carbon sinks of Nanjing presented a declining trend since 2000, which caused the decrease of carbon compensation rate and the increase of urban carbon cycle pressure. （2） The total carbon footprint of Nanjing increased rapidly since 2000, and the carbon deficit was more than ten times of total land areas of Nanjing in 2009, which means Nanjing confronted high carbon cycle pressure. （3） Generally, carbon footprint intensity of Nanjing was on de- crease and the carbon footprint productivity was on increase. This indicated that energy utilization rate and carbon efficiency of Nanjing was improved since 2000, and the policy for energy conservation and emission reduction taken by Nanjing＇s government received better effects. （4） Economic development, population and industrial structure are promoting factors for the increase of carbon footprint of Nanjing, while the industrial carbon footprint intensity was inhibitory factor. （5） Several countermeasures should be taken to decrease urban carbon footprint and alleviate carbon cycle pressure, such as： improvement of the energy efficiency, industrial structure reconstruction, afforestation and environmental protection and land use control. Generally, transition to low-carbon economy is essential for Chinese cities to realize sustainable development in the future.     

Review on carbon emissions,energy consumption and low-carbon economy in China from a perspective of global climate change

Accompanying the rapid growth of China’s population and economy, energy consumption and carbon emission increased significantly from 1978 to 2012. China is now the largest energy consumer and CO₂ emitter of the world, leading to much interest in researches on the nexus between energy consumption, carbon emissions and low-carbon economy. This article presents the domestic Chinese studies on this hotpot issue, and we obtain the following findings. First, most research fields involve geography, ecology and resource economics, and research contents contained some analysis of current situation, factors decomposition, predictive analysis and the introduction of methods and models. Second, there exists an inverted “U-shaped” curve connection between carbon emission, energy consumption and economic development. Energy consumption in China will be in a low-speed growth after 2035 and it is expected to peak between 6.19–12.13 billion TCE in 2050. China’s carbon emissions are expected to peak in 2035, or during 2020 to 2045, and the optimal range of carbon emissions is between 2.4–3.3 PgC/year (1 PgC=1 billion tons C) in 2050. Third, future research should be focused on global carbon trading, regional carbon flows, reforming the current energy structure, reducing energy consumption and innovating the low-carbon economic theory, as well as establishing a comprehensive theoretical system of energy consumption, carbon emissions and low-carbon economy.     

Spatial-temporal characteristics and decoupling effects of China’s carbon footprint based on multi-source data

In 2007, China surpassed the USA to become the largest carbon emitter in the world. China has promised a 60%–65% reduction in carbon emissions per unit GDP by 2030, compared to the baseline of 2005. Therefore, it is important to obtain accurate dynamic information on the spatial and temporal patterns of carbon emissions and carbon footprints to support formulating effective national carbon emission reduction policies. This study attempts to build a carbon emission panel data model that simulates carbon emissions in China from 2000–2013 using nighttime lighting data and carbon emission statistics data. By applying the Exploratory Spatial-Temporal Data Analysis(ESTDA) framework, this study conducted an analysis on the spatial patterns and dynamic spatial-temporal interactions of carbon footprints from 2001–2013. The improved Tapio decoupling model was adopted to investigate the levels of coupling or decoupling between the carbon emission load and economic growth in 336 prefecture-level units. The results show that, firstly, high accuracy was achieved by the model in simulating carbon emissions. Secondly, the total carbon footprints and carbon deficits across China increased with average annual growth rates of 4.82% and 5.72%, respectively. The overall carbon footprints and carbon deficits were larger in the North than that in the South. There were extremely significant spatial autocorrelation features in the carbon footprints of prefecture-level units. Thirdly, the relative lengths of the Local Indicators of Spatial Association(LISA) time paths were longer in the North than that in the South, and they increased from the coastal to the central and western regions. Lastly, the overall decoupling index was mainly a weak decoupling type, but the number of cities with this weak decoupling continued to decrease. The unsustainable development trend of China's economic growth and carbon emission load will continue for some time.     

基于STIRPAT模型的江苏省能源消费碳排放影响因素分析及趋势预测

定量分析碳排放的影响因素,对降低区域碳排放具有重要的指导意义。利用STIRPAT模型,定量分析江苏省能源消费碳排放量与人口、富裕度（以人均GDP表示）、技术进步（以能源强度表示）和城镇化水平之间的关系,通过岭回归拟合后发现,人口数量、人均GDP、能源强度、城市化水平每变化1%,江苏省能源消费碳排放量将分别发生3.467%、(0.242+0.024 lnA)%、0.313%和0.151%的变化。在以上研究的基础上,设置8种不同的发展情景,分析了江苏省未来能源消费碳排放量的发展趋势。结果表明,当人口、经济保持低速增长,并保持高技术增长率时,有利于控制江苏省的能源消费碳排放量,2020年江苏省的能源消费碳排放量预测值为202.81 MtC。     

共享社会经济路径下中国碳中和路径预测

科学地预测和分析不同情景下中国碳中和路径有助于碳中和目标的合理推进,但当前研究仍缺少结合碳源—汇变化趋势的综合性分析与应用国际耦合模式情景的系统性分析。本文运用WITCH综合评估模型与IBIS植被动态模型模拟了各共享社会经济路径情景下21世纪中国碳源—汇路径,对中国碳中和时间及路径进行预测分析。研究发现：① 中国碳汇逐年值存在3~4 a的周期性波动。RCP6.0气候情景下中国碳汇总量均值稳定在约0.30 Gt C/a;RCP2.6气候情景下中国碳汇总量均值呈下降趋势,到2065—2100年下降至约0.18 Gt C/a。② 中国碳排放总量受到世界经济社会发展路径与政策强度的共同影响,在中高强度减排政策下中国碳排放均在2025—2030年达峰后呈下降趋势,其中SSP1/SSP4—高强度碳减排政策情景下碳排放在2060年降至约0.30 Gt C/a并实现碳中和目标。③ 基于典型碳中和情景的路径研究,实现碳中和目标应积极促进清洁能源技术进步与应用,推进非电力能源向电力能源转变,推广生物质能源及CCS技术,并积极倡导电动汽车的发展。     

基于GFI模型的西安市能源消费碳排放因素分解研究

基于2000-2015年西安市能源消费量数据,采用碳排放模型和GFI模型,分析区域能源消费碳排放量的变化趋势及影响因素,探讨西安市能源消费碳排放的拉动与抑制要素的互动关系及影响。结果表明：（1）西安市能源消费碳排放量总体呈现上升趋势,煤炭、原油消费为主要碳源。（2）能源利用结构正在发生转变,低能耗低碳排的能源消费量逐年上升,传统能源利用量正日趋减少。（3）经济发展要素和人口要素是西安市能源消费碳排放的主要拉动因素,能源结构要素拉动效应不显著,短期内不易改变;能源强度对能源消费碳排放具有抑制作用,且呈现增强态势,但效果不明显。最后提出西安市能源消费碳排放减排建议。     

长三角地区旅游业能源消耗的CO2排放测度研究

旅游业与气候环境变化息息相关,低碳旅游是旅游业对气候变化的积极响应,也是低碳经济的延伸,将会给全球旅游业带来深远影响。但目前国内大部分有关低碳旅游的研究仍停留在定性阶段,尤其是旅游业碳排放的测度研究仍比较薄弱。本文在深入分析和总结国内外已有研究的基础上,以能源消耗平衡表为依据,借鉴"旅游消费剥离系数"概念,构建出符合我国目前统计口径的旅游业碳排放测度方法。并以长江三角洲地区为研究范围,对江苏、浙江和上海三地旅游业碳排放进行测度和对比分析。研究表明:目前在长三角地区,旅游业碳排放总量持续攀升,并与旅游业总收入成正相关。其中旅游交通仓储和邮电业碳排放在旅游业碳排放总量中占主导地位,而旅游餐饮、住宿和购物过程中的碳排放也不容忽视。旅游收入增长与旅游低碳化发展的矛盾仍然十分突出,迫切需要转变旅游业发展方式。     

中国能源消费碳排放强度及其影响因素的空间计量

碳排放所引起的全球气候变化对人类经济社会发展带来了严峻的挑战。中国政府承诺到2020 年GDP碳排放强度较2005 年降低40%~45%,这一目标的实现有赖于全国层面社会经济和产业结构的实质性转型,更有赖于省区层面节能减排的具体行动。基于联合国政府间气候变化专门委员会(IPCC) 提供的方法,本文估算了全国30 个省区1997-2010 年碳排放强度,采用空间自相关分析方法和空间面板计量模型,探讨了中国省级尺度碳排放强度的时空格局特征及其主要影响因素,旨在为政府制定差异化节能减排的政策和发展低碳经济提供科学依据。研究结果表明:① 1997-2010 年,中国能能源消费CO₂排放总量从4.16 Gt 增加到11.29Gt,年均增长率为7.15%,而同期GDP年均增长率达11.72%,碳排放强度总体上呈逐年下降的态势;② 1997-2010 年,碳排放强度的Moran's I 指数呈波动型增长,说明中国能源消费碳排放强度在省区尺度上具有明显的空间集聚特征,且集聚程度有不断增强的态势,同时,碳排放强度高值集聚区和低值集聚区表现出一定程度的路径依赖或空间锁定;③ 空间面板计量模型分析结果表明,能源强度、能源结构、产业结构和城市化率对中国能源消费碳排放强度时空格局演变具有重要影响;④ 提高能源利用效率,优化能源结构和产业结构,走低碳城市化道路,以及实行节能减排省区联动策略是推动中国实现节能减排目标的重要途径。     

哈萨克斯坦能源消费的碳排放动态演进分析

能源消费是碳排放的主要来源。根据IPCC碳排放计算指南缺省值计算了哈萨克斯坦共和国1992-2010年的碳排放量,并对哈萨克斯坦近20 a来碳排放进行阶段划分,采用对数平均迪氏指数法（Logarithmic Mean Divisia Index）,对碳排放量进行因素分解,定量分析能源结构、能源效率和经济发展对不同阶段碳排放的影响。结果表明：（1）1992-2010年,哈萨克斯坦一次能源消费的碳排放量整体呈先下降后上升的“U”型曲线,拐点在1999年。煤炭消费仍然是碳排放的主要来源,这是受长期以煤为主能源供应政策影响的一种必然结果;（2）碳排放不同阶段各影响因素的作用程度不同。总体来看,经济增长是碳排放量增加的主要推动因素,能源强度降低是抑制碳排放量增长的主要贡献因子。并以此提出哈萨克斯坦未来能源战略的一些政策建议。