Global Carbon Dioxide Emissions Scenarios: Sensitivity to Social and Technological Factors in Three Regions

Carbon dioxide emissions from 1990 to 2100 AD are decomposed into the product of four factors: population size, affluence (measured here as GDP per capita), energy intensity (energy use per unit GDP) and carbon intensity (carbon dioxide emissions per unit energy). These emissions factors are further subdivided into three regions: more developed countries (MDCs), China, and the remaining less developed countries (LDCs). Departures from a baseline scenario (based on IPCC, 1992a — the so-called ‘business-as-usual’ scenario) are calculated for a variety of alternative assumptions concerning the four emissions factors in the three regions. Although the IPCC scenario is called a ‘non-intervention’ scenario, it is shown, for example, that large decreases in energy intensity in China or carbon intensity in MDCs are built into the ‘business as usual’ case — and such large changes vary considerably from region to region. We show what CO₂ emissions would look like if each of these four emissions factors projected in the baseline case somehow remained constant at 1990 levels. Certain factors like energy intensity improvements and long-term population growth in LDCs, or GDP growth and carbon intensity improvements in MDCs, are shown to have a big contribution to cumulative global emissions to 2100 AD, and consequently, changes in these projected factors will lead to significant deviations from baseline emissions. None of the scenarios examined in this analysis seems to indicate that any one global factor is clearly dominant, but cultural, economic, and political costs or opportunities of altering each factor may differ greatly from country to country.     

2009年全球二氧化碳排放量下降,过去十年二氧化碳排放仍然快速增长

<正>2009年,中国二氧化碳排放量居世界第一,增长近9%。同时,大多数工业化国家的二氧化碳排放有所下降,这使全球因化石燃料而排放的二氧化碳总量从2008年的8.5亿吨碳     

碳排放现状及驱动因素分解实证分析研究——以东莞市为例

根据IPCC碳排放计算指南核算东莞市2005年-2011年期间能源消费的碳排放量,并进行现状分析和采用对数平均权重分解法（LMDI）因素分解分析.研究结果表明：碳排放总量以5.8％速度增长,而碳排放强度以5.8％速度递减;煤是碳排放主源,但所占比重逐年下降;工业碳排放量比重最大,但是增速减慢;交通业、服务业和居民生活碳排放量及所占比重逐年增加;经济规模的扩大是拉动东莞市人均碳排放的决定因素,累计效应远高于能源效率和能源结构对碳减排影响.     

水泥行业二氧化碳排放统计——以贵阳市为例

本文从水泥行业二氧化碳的排放统计出发,研究二氧化碳排放的重要影响因素、二氧化碳排放的指标体系,从而得出一套水泥行业二氧化碳排放统计的核算方法.以贵阳市为例,从三种不同活动水平的统计数据对水泥行业生产工艺过程中产生的CO2排放量进行估算比较,验证统计核算方法的有效性,为贵阳市乃至全国水泥行业CO2的减排提供一个可行的科学依据.     

Carbon Dioxide Emission Reduction Scenarios in Mexico for Year 2005: Industrial Cogeneration and Efficient Lighting

An analysis of the impacts on Mexican energy demand and associated carbon dioxide (CO₂) emissions in the year 2005 due to efficient lighting in the commercial and residential sectors and cogeneration in the industrial sector is presented. Estimation of CO₂ abatement costs and an incremental cost curve for CO₂ mitigation options are considered. These technologies are cost effective opportunities, and together are projected to reduce CO₂ emissions in 2005 by nearly 13 percent. Implementation of efficient lighting is already part of the demand side management (DSM) programs of the Mexican state-owned utility. However, there are important barriers that may hinder the implementation of large scale cogeneration plants.     

Carbon Dioxide Emission Reduction Scenarios in Mexico for Year 2005: Industrial Cogeneration and Efficient Lighting

An analysis of the impacts on Mexican energy demand and associated carbon dioxide (CO₂) emissions in the year 2005 due to efficient lighting in the commercial and residential sectors and cogeneration in the industrial sector is presented. Estimation of CO₂ abatement costs and an incremental cost curve for CO₂ mitigation options are considered. These technologies are cost effective opportunities, and together are projected to reduce CO₂ emissions in 2005 by nearly 13 percent. Implementation of efficient lighting is already part of the demand side management (DSM) programs of the Mexican state-owned utility. However, there are important barriers that may hinder the implementation of large scale cogeneration plants.     

昆明市能源活动CO2排放量调查研究

通过对国内外二氧化碳排放估算相关成果分析研究,在2008年昆明市能源消耗调查基础上,根据联合国政府间气候变化专门委员会(IPCC)2006年碳排放计算指南中的计算公式和碳排放系数缺省值,完成昆明市能源活动二氧化碳排放总量估算,为昆明的低碳城市建设摸清家底,为省会城市能源活动二氧化碳排放估算提供了方法验证和实践.     

后京都议定书时代的二氧化碳排放格局与中国面临的发展挑战

阐述了近期世界主要国家的温室气体排放状况,以及2012年<京都议定书>第一承诺期到期后,全球二氧化碳可能的排放格局.分析了气候变化对中国发展带来的挑战.指出气候变化是人类共同面临的挑战,世界各国都在采取各种措施努力减少额外的二氧化碳排放量;作为发展中的温室气体排放大国,中国面临巨大的减排压力,为此,中国必须尽快做出调整,向低碳经济转型.     

中国能源消费和碳排放特征研究

基于中国能源消费数据,采用IPCC报告中碳排放估算方法,对我国1978～2010年的能源消费和碳排放特征进行研究。结果显示:中国能源消费和碳排放总量增幅较大,2010年中国能源消费量和二氧化碳排放量分别达到32.5亿t和76.13亿t,但是能源强度和碳强度总体上呈下降趋势;不论是总量上还是强度上,能源消费和碳排放的地区差异均较大。     

2005～2009年南京市二氧化碳排放特征研究

采用IPCC报告(2006版)提供的计量方法与碳含量缺省值,对南京市能源消费碳排放进行了计量研究.结果表明:从2005～2009年,CO2排放总量从8.05×107t增加到1.02×108t,人均CO2排放量从11.7 t/a增加到13.2 t/a,但CO2排放强度持续降低,从3.34 t/万元下降到2.41 t/万元...     

Economic and Technological Development in Climate Scenarios

Recent years have seen continuing debate about the factors underlying the process of economic development, but increasing consensus that technology and innovation play a key role. Increasing energy supplies are seen by some observers as fundamentally necessary for economic development, while others believe that a process of dematerialisation is underway in a shift to a "knowledge-based" economy. Energy futures will depend heavily on the process of technology innovation and transfer, which is affected by investment in research and development (R&D) and education, management styles and culture, market and regulatory incentives, perceived human needs, and many other factors. The primary energy carbon dioxide (CO2) emission intensity of the world economy has fallen by only about 1.1% per year in the last 20 years. However, circumstances are imaginable where energy intensity could decline by 2-3% per year in the long term. It is also possible that energy intensity could increase.     

重庆市工业耗能相关碳排放变化驱动因素研究

在构建重庆市工业耗能相关碳排放影响因素分解模型的基础上,采用因素分解方法分析了过去十余年间(1999²011)4种驱动因素对重庆市工业碳排放变化的影响,并识别出关键驱动因素。结果显示:能耗增长的主要原因是工业经济发展;工业能源强度是促进重庆市工业耗能相关碳减排的主要影响因素;产业结构因素对重庆市工业耗能相关碳排放变化的影响存在波动,但其累积效果表现为减排;能源结构因素对重庆市工业耗能相关碳排放变化没有显著影响。最后,结合各关键因素的未来发展趋势,提出重庆市工业未来低碳发展的可行途径为技术进步和产业升级。     

中国工业二氧化碳排放的影响因素分析

以气候变暖为特征的全球气候变化问题日益严峻的情况下,二氧化碳排放研究已经受到各方关注.采用LMDI方法,利用中国1995-2007年工业能源消耗数据,分析了影响中国工业二氧化碳排放总量、人均工业二氧化碳排放量和工业二氧化碳排放强度的因素,结果表明:人口因素是拉动中国工业二氧化碳排放总量增加的主要因素,经济发展是拉动中国...     

上海能源消费碳排放分解研究

能源利用不仅为经济活动提供动力还大量排放二氧化碳.为分解上海市能源消费CO2排放的影响因素,明晰上海市能源消费CO2排放变化特征,采用指数分解分析方法建立了上海市能源消费碳排放的LMDI分解模型,从经济规模、产业结构、能源强度和产业碳排放系数4个影响因素着手,实证研究了1995-2005年上海分三次产业的能源消费碳排放变化机理.结果表明:经济快速增长是上海碳排放增加的主导因素,能源强度下降是抑制碳排放增长的重要因素.产业结构,能源结构优化有利于控制碳排放,而重工业化、能源结构高碳化会增加碳排放.基于实证分析结果和上海市情,提出了上海市未来控制碳排放的相关政策建议.     

State-By-State Carbon Dioxide Emissions from Fossil Fuel Use in the United States 1960–2000

Time series of fossil fuel carbon emissions from 1960–2000 for each of the U.S. states and the District of Columbia are presented and discussed. Comparison of the nationally summarized results with other national datasets shows generally good agreement, usually within 2%, and gives insight into the quality of all the data series. Our extension of the state-by-state emissions estimates back to 1960 reveals patterns of change that are coherent across states and can be related to historic events such as energy crises and federal legislation. Most notable is the changing pattern of coal usage, as coal-producing states produce increasingly more energy (mostly for electricity) for other states so that per capita CO₂ emissions diverge for states that import as opposed to those that export electricity. The decline in carbon emissions from petroleum products following the 1970s is also evident. Per capita emissions range over an order of magnitude for the different states. The data suggest that differences in per capita emissions arise from differences in many technological, physical, resource, social, and economic factors. The data presented here and the few correlations briefly noted pose a challenge for trying to use per capita emissions as a measure of equity or to provide mitigation targets.     

On the Effects of Social and Economic Policies on Future Carbon Emissions

Published scenarios of carbon emissions vary over a 40:1 range, and vary greatly even when the possible effects of future climate change policies are ignored. Differences in assumptions about how social and economic policies will affect the rates of economic growth throughout the world, population growth, international trade and investment, the rate of improvement in energy efficiency, and innovations and developments in non-carbon technologies are among the main reasons for such huge differences - alongside the considerable uncertainties that remain about the structural forms and parameters of the economic models used for making projections. The following analysis shows that a low carbon emissions scenario is fully consistent with developing countries achieving economic prosperity and the rich countries increasing theirs. It would depend on the emergence of non-carbon options, such as renewable energy, and this is indeed more likely to happen with favourable conditions for economic growth and innovation.     

中国碳排放轨迹特征、驱动因素及减排策略

采用1979-2017年数据,对中国中长期碳排放规律和减排对策进行了综合讨论,研究结果显示:(1)中国存在碳库兹涅茨倒U型曲线,2012年开始进入"碳拐点"前期阶段,"碳拐点"预计在2026年左右达到,碳排放峰值约为120亿tCO₂e。(2)HP滤波分析发现,改革开放以来中国碳排放存在1979-1996年、1997-2011年2个长周期和2012年启动的不完整周期。(3)Tapio脱钩弹性分析表明,中国碳排放与经济增长间经历了"弱脱钩-扩张连结-弱脱钩"的变化历程,目前正处于弱脱钩向强脱钩过渡的转变期。(4)LMDI分解分析表明,当前碳排放增长的主要助长性因素是经济增长效应,其次是人口规模效应;主要抑制性因素是能源强度效应;能源结构效应影响相对较小,但其负贡献增长速度较快。(5)"碳拐点"前期减排机制优化方向应着眼于促进能源效率提升、清洁能源使用、工业过程碳排放控制、进出口贸易优化以及更好地运用市场化减排机制方面。     

云南省碳排放历史变化特征及影响因素分析

基于1980—2011年云南省经济发展和能源消费数据,计算了云南省碳排放量和碳排放强度,并分析了历史变化特征。采用LMDI法定量分析了能源结构、能源效率和经济发展因素对云南省人均碳排放的影响效应。结果表明,1980—2011年,云南省一次能源消费产生的碳排放总量呈指数型递增。碳排放量中平均有88.55%来自煤炭的消费,9.53%来自石油的消费,1.92%来自天然气的消费。32年来云南省人均碳排放增长的主要原因是经济发展的拉动作用,经济发展对人均碳排放的贡献率呈指数增长;抑制因素主要是能源效率的提高;能源结构的调整对人均碳排放的抑制效应不显著。     

浙江省碳排放与经济增长的脱钩关系及驱动因素研究

运用IPCC参考方法、Tapio脱钩模型、协整分析和Granger因果检验,研究了浙江碳排放特征及其驱动因素.结果表明:碳排放量呈增长趋势,碳排放强度呈下降趋势,多数年份碳排放与经济增长之间呈"弱脱钩"状态;经济增长、外贸和人口增长对碳排放正向驱动,能源效率和城市化对碳排放负向驱动;经济增长、外贸、城市化和人口增长是引起碳排放增长的单向Granger原因,能源效率与碳排放互为Granger原因.     

河北省碳排放及其影响因素变化趋势研究

在国家十三五规划政策的指引下,减少碳排放是当今社会的大势所趋。以产业结构调整优化为目的,就河北省碳排放及其影响因素变化趋势进行研究,旨在生态文明建设中促进京津冀产业协同发展。在研究碳排放时,运用STIRPAT模型,根据河北省实际情况,将影响碳排放的因素分为城市化水平、人口数量、富裕度和能源强度,并选取了河北省2003-2014年碳排放及其相关数据作为研究样本,经过对能源消耗量的转换计算得到比较精确的碳排放数据。在此基础上分别建立碳排放灰色GM(1,1)预测模型和碳排放影响因素灰色GM(1,1)预测模型来预测2015-2020年对应的数据变化。并分析各个影响因素的变化趋势及其对碳排放的影响。经过分析发现,富裕度对碳排放影响最大,所以政府等相关部门应加大对该方面的监督与管理,从而从整体上达到低碳的目标。