城市能源消费碳排放特征及其机理分析 ——以广州市为例

采用表观能源消费数据进行分能源品种和分行业类型的碳排放总量核算,利用基于IDA理论和Kaya恒等式的LMDI模型对碳排放总量变化进行多要素的分解分析,在解析人口规模效应、经济产出效应、能源强度效应对碳排放影响机理的同时,进一步纳入人口结构性因素、产业结构性因素和能源结构性因素对碳排放的影响。以广州市为例,对其2003—2013年产业活动和居民消费2个部门碳排放的主要驱动因素进行时间序列分析,并定量研究各个影响因子在2003—2005、2005—2010和2010—2013年3个不同发展阶段的作用机理,主要研究结论如下：1）广州市能源消费及其碳排放前期以煤炭为主,近年来以石油为主,同时外购电力对广州市的能源消费结构优化影响显著。2）各影响因子对广州市碳排放总量变化的作用机理与影响机制在3个发展阶段各不相同,不同发展阶段的发展措施和政策背景对于各个影响因子的碳排放效应影响显著。3）总体分析,经济产出效应和人口规模效应是产业部门碳排放增长的最主要贡献因子;工业能源消费强度效应、工业能源消费结构效应和经济结构效应是遏制产业部门碳排放增长的最主要贡献因子。城镇居民收入效应是居民消费碳排放增长的最主要贡献因子,城镇居民能源消费强度效应是遏制居民消费碳排放增长的最主要贡献因子。     

河南省能源消费碳排放的历史特征及趋势预测

根据联合国政府间气候变化专门委员会(IPCC)2006年版碳排放计算指南计算了河南省1995—2006年的能源消费碳排放量。预测了2007—2050年河南省平稳经济增长路径下的最优经济增长率和2007—2050年的河南省能源消费结构和产业结构。进一步,计算了河南省2007—2050年在经济平稳增长路径下的能源消费与碳排放总量以及人均量。结果表明:1995年以来,河南省的碳排放量逐年增加,碳排放强度先是逐年下降,到2003年发生转折,出现上升的趋势;同时,预测的2007—2050年的能源结构显示,河南省煤炭资源在能源消费总量中所占的比重有较大幅度的下降,石油与其他清洁能源的比重不断上升;另外,河南省分别在2036年和2034年达到能源消费和碳排放总量高峰;人均能源消费量和碳排放量的高峰则出现在2033年和2032年。另外,尝试预测了河南省森林碳汇潜力,发现2006—2050年累计森林碳汇量持续上升,到2050年,累计碳汇量达131.14M tc。     

基于经济模拟的中国能源消费与碳排放高峰预测

能源消费所产生的碳排放是经济发展过程中不可避免的副产品,而且碳排放在大气中的积累会使全球气候不断变暖,因此经济增长与碳排放之间的关系一直是学术界关注的焦点。传统的基于EKC曲线的经济计量学方法一般是对经济与排放历史数据的相关关系研究,不能很好地反映二者之间的动力学机制。为此本文在内生经济增长模型Moon-Sonn基础上进行改进,首先从理论上得到了最优经济增长率与能源强度之间存在倒U曲线关系的必要条件,即能源的产出弹性小于0.5;接着将投入产出分析得到的反映技术进步下的能源强度代入模型,对中国未来经济增长路径进行了预测,同时得到了最优增长路径下的能源消费走势,进而通过对能源消费结构和不同能源品种的碳排放系数的预测和估计,以及对分品种能源碳排放的汇总计算得到了中国未来能源消费所产生的总的碳排放走势。结果显示,在当前技术进步速率下,我国分别在2043年和2040年达到能源消费高峰和碳排放高峰。此外,本文对能源强度不同下降速率对能源消费高峰的影响进行模拟发现,当降速为4.5%~5%时,能源高峰将出现在2040年前,此时的人均GDP为10万元左右,与OECD国家的高峰时收入一致;而且分3种情景模拟了可再生能源替代政策对...     

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。     

资源型区域碳排放影响因素分析——以山西省为例

碳排放问题是应对气候变化的主要问题,更是困扰资源型区域改革与可持续发展的关键性问题。以山西省为例,采用LMDI分解方法,将碳排放分解为5种影响因素,对山西省碳排放趋势和变化、影响因素做了深入探讨。结果表明:1)山西省未来碳排放增速减缓,排放量将持续增加,生态环境压力进一步加大;2)能源结构效应为负向影响,虽效应值较小,但潜力巨大。而人口规模正向效应值缓慢变大需要关注;3)在产业结构效应方面,工业、交通运输仓储邮政业及批发零售住宿餐饮业部门产业效应为正效应,且有逐年增大的趋势。表明第二产业和第三产业内部结构不合理,产业结构优化有待提高。     

中国工业经济转型过程中能源消费与碳排放时空特征研究

就近30 a来中国工业经济转型过程中能源消费与碳排放的关联变化进行了分析,结果表明,工业部门能源消费的持续增长是中国能源消费总量增长与碳排放量增长的主要驱动因子;工业碳排放总量增长快速,但工业碳排放密集度持续降低;工业部门中制造业碳排放量最大,平均约占工业部门碳排放总量的60%,降低传统制造业能源消费、提高能源利用效率是推动节能减排政策实施和地方行动响应的关键环节;地区工业能源高消费地区集中分布于中国环渤海地区,能源较高消费地区主要集中于中国中部地区和东部经济发达地区,能源中等消费地区主要集中于中国西部地区,而能源低消费地区集中于西部经济落后地区;中国区域工业碳排放总量除受到本地工业能源消费量的直接影响外,还受到各地能源消费结构的影响,值得注意的是,较高碳排放地区空间布局趋于"孤岛"分布格局,低碳排放地区的数量也逐渐增加。     

县域尺度下能源产区能源消费碳排放强度空间分异——以陕西省榆林市为例

以能源产区陕西省榆林市的12个区县为研究单元,在Geo Da和Arc GIS等软件的支持下,结合趋势分析和空间统计方法,分析2005—2010年榆林县域尺度下的能源消费碳排放强度的空间格局特征与空间分异机制。榆林各区县能源消费碳排放强度水平差异明显,总体差异呈扩大趋势,两极分化加剧。县域碳排放强度南北走向上表现出逐渐减小趋势,东西走向上具有微弱的"U"型变化态势。总体上,东北部区县碳排放强度高于西南部。各区县碳排放强度具有正的空间关联分布特征,且处于低水平非均衡空间分布状态,空间依赖性明显。结合相关性分析,榆林区县碳排放强度具有极化区、扩散区、塌陷区和传染区4个特征。"热点"主要分布在东北部三县,"冷点"主要分布于南部六县。能源资源分布不均、经济总量以及产业结构差异是造成榆林碳排放强度空间分布不均的主要原因。     

环境规制对绿色经济效率的空间影响——以长江中游城市群为例

基于2005—2020年长江中游城市群面板数据,从环境规制对绿色经济效率的空间影响机理出发,运用空间杜宾模型探讨环境规制对长江中游城市群绿色经济效率的影响。结果表明：(1)长江中游城市群的正式、非正式环境规制和绿色经济效率在空间上均存在正相关关联性。(2)正式、非正式环境规制对长江中游城市群绿色经济效率具有显著促进作用,受正向空间溢出效应影响,环境规制能提升邻近城市绿色经济效率。区域上,正式、非正式环境规制对武汉城市圈、环长株潭城市群和环鄱阳湖城市群绿色经济效率均具有显著正向作用。(3)研发投入和经济发展对长江中游城市群绿色经济效率具有显著正相关影响,地区开放程度具有显著负相关影响,固定资产和产业结构的影响作用不明显。     

能源足迹核算的改进与预测——以吉林省为例

定量测度能源消费的生态环境影响是区域可持续发展评价的重要内容。以化石燃料燃烧-CO2排放-地表吸收的碳循环过程为研究对象,对现有模型的土地碳吸收能力测算等方面进行了修正,构建了基于净初级生产力的能源足迹改进模型,分析了1994～2008年的吉林省能源足迹及其各土地利用类型供给变化,并通过生态效应指数计算揭示了土地利用/...     

区域分部门贸易的隐含碳排放——以北京为例

碳排放增多带来的气候变化已成为各国政府共同面对的问题,碳减排责任的划分是各国争论的焦点,而国际贸易造成的"碳泄露"问题更是不可忽视。中国的碳减排责任最终要落实到省市区域尺度上,区域间贸易引起的"碳泄露"同样值得考虑。使用多区域投入产出分析法,分别从生产者和消费者的角度对北京各部门碳排放进行分析,并估算各部门进出口贸易中隐含的碳排放量。结果表明北京是一个碳排放净流入区域。基于生产者和消费者的角度,北京的碳排放总量分别是142.79 Mt和116.80 Mt。输出贸易中隐含的碳排放量为28.15 Mt,包括区域间调出和国际出口。输出贸易中隐含碳排放最大的部门是石油加工、炼焦及核燃料加工业。输入贸易中隐含的碳排放量为54.15 Mt,包括区域间调入和国际进口。输入贸易中隐含的碳排放最大的部门是建筑业。     

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。     

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.     

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.     

中小城市家庭生活用能碳排放空间分异——以开封市为例

利用2015年开封市居民家庭生活用能的大样本问卷调查数据,采用探索性空间数据分析（ESDA）和标准差椭圆（SDE）方法,探索城市居住区家庭生活用能碳排放空间分布特征。结果表明：① 家庭生活用能碳排放存在以热点区为主的空间正相关特性,碳排放高值集聚发生在城市新建开发区和建成区向外扩张较快区域,以2000年以后新建高档商品房小区和机关事业单位家属院为主,低值集聚区则发生在建成时间长、后续开发力度小的区域,以老商品房小区和胡同社区为主;② 开封市家庭电力消耗碳排放占生活用能总碳排放的67%,但人均生活用能碳排放空间格局由供暖碳排放决定,且人均供暖碳排放空间格局又由集中供暖碳排放空间格局决定,故降低集中供暖能耗、缩小居民供暖用能差异成为居民生活用能碳减排工作的重中之重;③ 家庭经济状况、集中供暖设施分布和城市发展的空间格局是家庭生活用能碳排放空间依赖性和空间异质性形成的主要驱动因素。     

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。     

青海高原西宁城镇社区家庭能耗直接碳排放研究

选取青海高原城市西宁为研究对象,开展家庭能源消费问卷入户调查,建立高原城市家庭能源消费数据库(N=500),采用探索性空间数据分析方法,总结分析家庭能耗碳排放的空间特征与驱动因素,得出以下结论：(1)西宁市家庭人均能源消费量与人均能耗碳排放平均值分别为10.57 kgce/d和6.11 kg/d,取暖、厨房设备及热水器设备是家庭能耗及碳排放的主要来源;(2)西宁市人均家庭能源消费碳排放总体呈现出高值区(HH)、低值区(LL)相对集聚,而局部地区也存在高低值区(HL)和低高值区(LH)集聚现象,其空间规律呈现明显的异质性;(3)家庭收入、地理环境以及建筑特征等因素是人均家庭能源消费碳排放空间异质性形成的主要因素。     

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.     

中国西北五省区水资源利用的协调性分析

水资源协调利用问题是中国西北五省区经济、社会和生态可持续发展的首要问题.采用协同性分析方法和耦合协调度模型,对中国西北陕西、甘肃、青海、宁夏、新疆五省区水资源利用率和生态用水率之间的区域协同性和耦合协调度进行分析.结果表明:(1)西北五省区的水资源利用率和生态用水率方差齐同,任意两省区之间不具有显著性区域差异,而在五省...     

Temporospatial changes of carbon footprint based on energy consumption in China

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 productive 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.     

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.