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.     

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.     

Twenty five years of industrial development: a study of resource use rates and macro-efficiency indicators for five Asian countries

Economic and population growth in Asia over the last three decades has been unprecedented. While conventional economic indicators have been increasing consistently, indicators of resource and environmental quality have been deteriorating, raising questions about the implications of future growth. Economic growth in the future is considered to be contingent on ensuring a more efficient use of natural resources, while simultaneously striving to reduce environmental impacts. We examine time trends of three efficiency indicators; agricultural efficiency, energy efficiency of economic production and carbon efficiency of energy use, for the five most populous countries in Asia in order to assess whether industrial development has lead to increased resource use efficiency and an associated reduction in total resource use and environmental impacts. Our results indicate that agricultural efficiency has decreased in all five countries. Results are mixed for energy and carbon efficiencies. Where increases in energy and carbon efficiency have occurred, they have been completely overwhelmed by absolute increases in energy use and carbon emissions caused by increases in the scale of economic activity. Based on this analysis, we study the potential for further improvements and policy implications for future food supply, energy consumption and carbon emissions in the region.     

碳排放与能源消费和经济增长的灰色关联分析

中国碳排放问题成为世界关注的焦点问题。研究碳排放与经济增长、能源消费关系有助于实现2020年碳减排目标。选取2001～2009年碳排放与能源消费、经济增长数据,运用灰色关联分析模型,分别计算碳排放与能源消费、经济增长的灰色关联度。研究结果表明,无论是从折线的相似程度还是相对于始点变化速率的接近程度来看,碳排放曲线与能源消费曲线、经济增长曲线十分相似,说明碳排放与能源消费、经济增长之间存在紧密联系。     

The impacts of information and communication technology,energy consumption,financial development,and economic growth on carbon dioxide emissions in 12 Asian countries

This study aims to investigate the effects of information and communication technology (ICT), energy consumption, economic growth, and financial development on carbon dioxide emissions using 1993–2013 panel data from 12 Asian countries. The study employs a panel unit root test accounting for the presence of cross-sectional dependence and found that Internet usage is stationary and carbon dioxide emissions, energy consumption, gross domestic production (GDP), and financial development are first-difference stationary. The results form Pedroni panel cointegration test confirms that the variables are cointegrated. The results of the cointegration test indicate that the ICT-energy-GDP-carbon dioxide emissions nexus has long-run equilibrium. Both energy consumption and GDP have significant, positive impacts on carbon dioxide emissions; energy consumption and GDP have an effect on carbon dioxide emissions growth. ICT has a significantly negative effect on carbon dioxide emissions; the promotion of ICT becomes one of the important strategies introduced to mitigate carbon dioxide emissions for various countries. Causality results show that energy consumption, GDP, and financial development cause more carbon dioxide emissions. Energy consumption, GDP, and carbon dioxide emissions cause ICT. GDP causes financial development, whereas energy consumption and GDP are interdetermined. The feedback hypothesis exists in the region; those countries need to develop alternative energy to replace fossil fuels. ICT does not threaten the environment and ICT policy can be seen as a part of carbon dioxide emissions reduction policy.     

中国化石能源消费碳排放与经济增长关系研究

化石能源过度消费导致的气候变化问题引发了全世界对经济发展模式的关注,论文运用计量经济学方法研究了中国化石能源消费碳排放与经济增长的关系,测算了中国1953-2010年化石能源消费引起的碳排放总量,建立了碳排放总量和国内生产总值的时序计量经济模型,通过协整检验、误差修正模型、基于VAR模型的脉冲响应函数、因果关系检验,分析了二者之间的长短期关系,结果表明:1953-2010年,我国的化石能源消费碳排放总量和国内生产总值之间存在长期均衡的协整关系和短期动态调整机制,通过短期调节,可以自动实现二者之间的长期均衡。当期GDP对碳排放总量的当期波动有显著性影响,每增加1%的GDP便会增加0.719%的碳排放量,上期误差对碳排放总量的当期波动调整幅度较大,单位调整比例为-0.102。利用脉冲响应函数波形图对碳排放量与经济增长之间的影响及响应进行了20期的详细刻画,揭示了二者之间复杂的短期动态关系。1953-2010年,存在从碳排放总量到GDP的单向Granger因果关系,碳排放是经济增长的Granger原因,而经济增长不是碳排放的Granger原因,说明从过去58 a的整体状况来看,高碳排放推动了经济增长,而经济增长并未导致明显的碳排放增加。研究结果将对中国制定节能减排和碳减排政策提供依据和支撑。     

基于IPAT扩展模型分析人口因素对碳排放的影响

以5个典型国家(中国、日本、印度、德国和美国)为研究对象,利用IPAT模型比较分析了人口总量、能源强度和人均财富对碳排放的影响程度.结果表明:中国和印度的人口总量是影响其碳排放变化的主要因素;而美国和日本财富的积累刺激碳排放增加的作用明显.基于1978─2007年中国人口和能源相关数据,以STIRPAT模型为框架,分别构建了总人口模型及家庭户模型,用于分析我国人口数量、人口结构、能源强度及消费变化对碳排放产生的影响.经模型验证发现,家庭户模型的解释力度总体优于总人口模型.碳排放量的各解释因素按其影响程度的大小依次为平均家庭户规模、人均居民消费额、人口结构、能源强度和家庭户数.针对适应低碳发展的人口政策提出了相关建议.      

碳交易政策如何影响工业碳生产率:来自中国省级数据的准自然实验

当前,在中国奋力实现"碳达峰"碳中和"目标的背景下,不仅给碳排放量相对较高的工业企业带来较大环境治理压力,同时也给其在经济增长方面带来较大冲击.对其随着碳交易政策的提出,是否能够产生"减碳促经"效果展开深入研究.基于2005~2019年30个省市数据,通过双重差分等方法和多重中介效应模型对碳交易政策与工业碳生产率的影响效果和作用路径展开深入分析.结果表明,碳交易政策能够明显提升工业碳生产率水平;同时该种作用效果会随着试点区域的不同存在明显差异;该政策能够产生显著的环境规制、结构优化、技术和能源结构优化效应.建议通过加速完善环境规制层面法律制度、加快构建环保产业发展新体系、加强绿色技术创新研发力度和加速优化能源结构方面促进中国工业经济向低碳化发展转型.     

基于城市化的浙江省湾区经济带碳排放时空分布特征及影响因素分析

基于STIRPAT扩展模型与2003-2017年浙江省湾区经济带面板数据,分析碳排放时空分布特征并应用时空地理加权回归模型（GTWR）实证考察城市化视角下碳排放的驱动机制及其时空异质性。结果表明：（1）浙江省湾区经济带各地市碳排放规模逐年增加但增幅不大,增速放缓,碳排放量差异明显,碳排放强度逐年下降,空间上呈现自西南向东北逐渐加大的趋势;（2）经济发展水平和对外开放程度是碳排放的主导因素,其他依次为能源消费结构、技术进步和城市化;（3）各影响因素呈现较强的时空异质性,不同时间、地区各驱动要素的波动方向和强度并不相同。在此基础上具体分析各地区碳排放驱动因素影响情况,为实现区域差异化碳减排策略提供指导。     

我国碳排放增长的驱动因素及贡献度分析

结合我国实际,对Kaya 等式进行扩展,引入经济效应影响因子、能源强度影响因子、行业贡献影响因子和碳排放强度影响因子,构建了行业CO₂排放增长驱动力模型。论文应用该模型测算和分析了1990 年至2010 年我国6 个经济部门CO₂排放的驱动因素。结果显示:①1990—2010 年,影响我国各行业CO₂排放的正向驱动因素主要是经济效应,负向驱动因素主要是能源强度效应和碳排放强度效应;②碳减排政策的制定要权衡经济发展和碳减排的政策协同;③1997—2000 年和2005—2010 年CO₂排放量减少或增速减缓的主要驱动力是能源强度效应和行业贡献效应;④基于国情,产业结构调整在短时间内对CO₂减排效力不大,而是一个长期的减排战略。     

基于系统动力学的中国碳减排路径模拟

通过分析二氧化碳排放影响因素之间作用关系与碳减排的主要路径,构建二氧化碳排放系统动力学模型。在此基础上,通过调控供给侧经济增长速度、能源结构和产业结构要素,预测四种不同情景方案对二氧化碳排放的影响,以进一步探讨二氧化碳排放主要部门减排贡献。结果表明：四种方案的二氧化碳净排放量增长趋势逐年变缓,在二氧化碳净排放量达到峰值后,调整经济增速、改善能源结构和优化产业结构继续为碳减排发挥积极作用,相比于经济增速和产业结构调整,能源结构改善的减排贡献度更高。在综合调控经济增速、能源结构和产业结构的方案下,中国二氧化碳净排放量2024年将达到高峰值104.45亿t,2058年实现碳中和,这与现实情况更加吻合。未来若能抓住经济、能源、产业低碳转型的良好机遇,并进一步加强各部门的减排努力,中国二氧化碳净排放量有望2025年前达峰,2060年前实现碳中和。     

基于LMDI的长江经济带交通碳排放变化分析

基于LMDI分解模型,探究了2000~2019年长江经济带交通运输业碳密度、运输结构、能源效率、能源强度、经济结构、经济水平以及人口规模等因素对交通碳排放的贡献程度及时空特性,并使用泰尔指数测算了碳排放的区域差异性.结果表明,经济规模持续扩张是长江经济带交通运输业碳排放增长的第一主导因素,对碳排放的正向驱动效应为116.33%,其次是人口规模（6.19%）;运输结构和经济结构的转变则是抑制碳排放增长的关键因素,其负向驱动率分别为-26.18%和-16.25%;而技术水平（能源效率和能源强度）的提升有助于抑制碳排放增加.此外,基于人均碳排放和碳排放强度的泰尔指数均显示长江经济交通碳排放量的区域差异性明显,其中区域内差异大于区域间差异,且基于碳排放强度的区域差异呈现出“俱乐部趋同”现象.最后,对长江经济带交通绿色发展提出了政策建议.     

基于IPAT模型的江苏省能源消费与碳排放情景研究

利用环境负荷模型与"脱钩"理论,对江苏未来中长期的经济发展、能源需求与CO2排放进行了情景分析,并结合当前的环境政策,对三种情景下主要指标的参数和结果进行了设计与分析。研究表明,资源节约型与环境友好型社会的构建,低碳情景是江苏能源-经济-社会的协调发展最合适、也是最现实的方案;通过不同情景的比较,认为低碳情景的实现一定程度上是以减缓经济增长来实现节能减排目标的;低碳情景下能源需求与CO2排放也将明显快速增加,与2007年相比,2030年能源需求总量将增加1.431倍,碳排放总量将达到15 655×104t,未来20 a能源资源的有效供应与合理利用成为制约低碳经济发展的瓶颈因素。最后给出了实现节能减排、促进低碳经济发展的相关建议。     

二氧化碳排放与经济增长关系的实证分析

在全球范围内为应对气候变化而达成二氧化碳减排共识的背景下,探求“经济增长”与“二氧化碳排放”间相互关系.运用协整,向量自回归模型,脉冲响应函数以及格兰杰因果检验等方法,对处在经济发展不同阶段区域的人均二氧化碳排放量与经济增长间关系进行因果检验.研究结果表明：区域经济发展与人均二氧化碳排放量存在长期均衡关系,但是由于区域间经济发展水平及发展方式的不同,人均二氧化碳排放量与经济增长间相互影响程度存在差异,且二氧化碳排放量的减少并不是经济增长的必然结果,必须通过产业结构调整,扶持第三产业,使用清洁能源,发展低碳经济的方式来实现,本文对我国碳减排政策的制定具有一定借鉴意义.     

碳达峰国家达峰特征与启示

基于世界银行数据库1960～2020年数据,采用Mann-Kendall(MK)检验和Spearman's Rho(SR)检验,对全球219个国家及地区的CO2排放及社会经济数据进行趋势分析.结果表明:MK检验和SR检验得出一致结论,共有42个国家和1个经济体联盟实现碳达峰,46个国家处于碳达峰平台期.多数国家碳达峰时...     

Determinants of CO2 emissions in Brazil and Russia between 1992 and 2011: A decomposition analysis

This paper deals with the decomposition analysis of energy-related CO₂ emissions in Brazil and Russia from 1992 to 2011. The refined Laspeyres index (RLI) method applied and both aggregated and sectoral changes in CO₂ emissions decomposed. Brazil’s and Russia’s economies divided into three economic sectors including agriculture, industry and services. Impact of four main factors, such as economic activity, employment, energy intensity, and carbon intensity in CO₂ emissions changes were analyzed. The aggregated decomposition analysis revealed that Brazil is still far from a decoupling between economic growth and carbon dioxide emissions where Russia achieved a substantial decline in carbon emissions mainly due to the improved energy intensity. The empirical findings of sectoral decomposition analysis emphasized that the economic activity was the major CO₂ increasing factor in Brazil’s economic sectors. On the other hand the economic activity effect followed a reducing impact in Russia’s sectoral emissions until 2000. The structural changes between sectors and their impacts on CO₂ emissions were captured by employment effect. Energy intensity and carbon intensity effects underlined that environmental sustainability widely neglected in Brazil and Russia during the study period. The results yield important hints for energy planning and sustainable environment.     

基于函数极值条件下的中国碳达峰碳中和情景分析

基于函数极值条件提出了碳达峰出现时间和需要满足的理论条件,并对主要发达国家作了验证,同时对中国现状做了分析,最后采用了基准和强化两种情景分析了中国实现2030年碳达峰后进入2060年碳中和时期的二氧化碳排放量。研究结果显示：（1）根据IPAT恒等式将碳排放函数分解成人口、人均GDP和碳强度三个因素时,碳峰值出现时间为三个因素年增长率之和由正转负的正数值年度,发达国家的历史数据证实了这一条件。（2）中国三个因素年增长率之和自2003年起已经开始降低,最近几年一直在0.01~0.02徘徊,表明总体上朝着有利于碳达峰的方向发展,同时按照三个因素的预期发展目标计算得出中国2030年碳排放峰值的上限为112.2亿t,若2021—2035年保持相同的人均GDP年均复合增长率,碳强度年均复合增长率的绝对值需要比人均GDP年均复合增长率高0.14个百分点。（3）在能源消费总量逐渐回落的前提条件下,2060年基准情景下非化石能源占比约为65%,产生的二氧化碳量约为31.4亿t,强化情景下非化石能源占比约为70%,二氧化碳排放约为26.6亿t,而碳汇和CCUS等固碳技术还存在不确定性,碳中和任务依然艰巨。实现碳达峰碳中和最终需要控制能源消费,践行低碳消费行为。     

闽三角地区碳排放时空差异及影响因素研究

以闽三角地区为研究对象,以2005~2017年为研究期,构建城市尺度的碳排放清单,应用对数平均迪氏指数分解方法从时间维度的纵向比较和典型年份城市横向比较两个维度开展了驱动因素的分解分析及评价,探讨了闽三角碳排放变化影响因素的时空差异.结果显示：研究期内闽三角CO₂排放增长较快,从2005年的74.08Mt增加到2017年169.48Mt,增幅为128.75%.其中,泉州贡献最大,占比为67.93%.碳排放变化趋势分析来看,产业结构和经济增长为导致闽三角地区碳排放量增长的主要因素,累计贡献度分别为30.38%和12.21%,能源结构为抑制碳排放的重要影响因素,累计贡献度为-45.76%.时空差异上看,能源结构效应在研究期内均表现为抑制效应,最大贡献率为52.95%;而产业结构效应均表现为促进效应,最大贡献率为33.85%.在研究期内,漳州市碳减排力度最大,最大净减排148.27Mt.而泉州市经济增长和产业结构效应贡献率较大,未来仍具有较大的减排空间.厦门市经济增长和产业结构效应贡献率均低于参考值,且在研究期内变动幅度较小,碳减排压力较低.研究结果深化了闽三角地区碳排放的时空格局及影响因素的科学认识,为闽三角地区及相似城市群的减排治理提供了有益借鉴.     

无锡市碳排放的因素分解模型及实证分析

在计算无锡市2000~2011年二氧化碳排放量的基础上,采用对数平均权重Divisia分解法,建立无锡市人均碳排放的因素分解模型,定量分析能源结构、能源效率、经济发展情况等因素对无锡市人均碳排放的影响。结果显示经济发展对拉动无锡人均碳排放的贡献率呈指数增长趋势,相比之下,能源效率及能源结构对碳排放的抑制作用并不明显。据此提出开发可再生能源,转变能源消费结构,发展清洁煤技术,提高能源利用率等对策。     

中国碳达峰路径的Meta回归分析

尽早实现碳达峰、碳中和是中国推动经济社会全面绿色低碳转型的内在需求,开展碳达峰路径研究对中国合理制定2030年碳达峰目标和措施具有重大现实意义.该文筛选发表于2015—2020年间的18篇文献,采用Meta回归分析方法研究中国碳达峰路径及主要影响因素.结果表明:①多数文献预测中国将于2030年或2030年前实现碳达峰,平均预测峰值水平约10.9 Gt CO₂;碳达峰时煤炭占比平均值为51.9%,非化石能源占比平均值为22.4%,经济年增长率平均值为5.4%,碳排放强度下降率平均值为54.0%.②该文筛选的样本对碳达峰路径预测结果与中国2030年前碳达峰目标一致,文献发表时间越晚预测的达峰时间越早且峰值越高.③除碳达峰时碳排放强度下降率（peakCEI）外,其余变量均对碳达峰峰值具有显著性;除文献类型（PTY）、影响因子（IF）、碳达峰时煤炭占比分类（yblcoal）、碳达峰时非化石能源占比（pnf）外,其余变量均对碳达峰时间具有显著性.未来中国应从基于成本效益的最优达峰路径、完善温室气体清单核算方法、大力推动清洁能源技术进步、提高经济发展质量等方面开展深入研究.