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.     

2005-2009年我国省域CO2排放特征研究

利用IPCC的参考方法测算并比较分析了2005-2009年我国30个省(市、自治区)的CO₂排放总量、人均排放量、排放强度、综合能源排放系数等重要指标,并在此基础上,依据人均GDP、第二产业比重和能源利用结构与碳排放强度的关系,将各省(市、自治区)划分为不同的CO₂排放类型。研究结果表明,省域间各指标差异较大,影响碳排放的因素也不尽相同。省域减排的政策、途径和措施须充分考虑各自的经济发展水平、产业结构和能源利用结构等因素。     

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。     

2020年中国发电行业碳减排目标规划相符性分析

基于发电行业节能减排技术的现有应用规划,预测3种不同的GDP增长情景,即减速发展,基准情景和高速发展情景下,若能实现我国现有关于发电行业节能减排技术的规划目标,2020年发电行业的CO2排放量将达到35.32,39.15,43.20亿t.同时基于中国2020年碳强度减排承诺,计算得国家2020年CO2排放目标在不同发展情景下将达到97.30~127.96亿t不等.结合上述结果讨论,发电行业规划目标相符要求2020年的CO2排放比例为33.27%~36.82%.结果表明,若能实现我国现有关于发电行业节能减排技术的规划目标,则对应于不同的GDP增长速度,发电行业总碳排放量能够完成国家承诺碳强度减排的分解目标.     

产业转移视角下京津冀石化产业碳排放因素分解与减排潜力分析

石化产业是我国经济的支柱性产业,但其大量的碳排放却给环境造成严重负担,因此提倡石化产业低碳发展能有效推动京津冀区域经济与环境绿色均衡发展.基于产业转移视角,分析2007-2016年京津冀区域石化产业碳排放量现状;运用对数平均迪式分解（Logarithmic Mean Divisia Index,LMDI）法分解并分析京津冀区域石化产业碳排放量影响因素在三地的作用效果,进而借助产业竞争力系数佐证碳排放量影响因素作用效果在区域间的关联性;最后通过合理调整京津冀区域石化产业能源结构,将未调整和调整后的能源结构类型分别设置为基准情境和低碳情境,利用SPSS拟合最优曲线来预测2017-2030年京津冀区域石化产业减排潜力.结果表明:①2007-2016年京津冀区域石化产业碳排放量增加386.79×104 t,碳排放强度由0.77 t/（104元）降至0.31 t/（104元）.②2007-2016年,能源强度因素使京津冀区域石化产业碳排放量减少13 663.77×104 t,其贡献率高达148.38%;人均GDP因素促使石化产业碳排放量增加12 327.10×104 t,贡献率达110.69%.③对于石化产业竞争力系数,北京市由0.03降至-0.02,为三地石化产业转出地;河北省由-0.14增至0.16,为转入地.④在低碳情境下,2020年、2030年京津冀区域石化产业碳排放量分别比基准情境减少502.84×104、528.95×104 t,碳排放强度分别降至0.19、0.17 t/（104元）,均达到发展目标的要求.研究显示,2007-2016年京津冀区域石化产业碳排放量逐年上升,承受巨大减排压力,该区域可以通过调整石化产业能源结构来挖掘碳减排潜力,推动石化产业绿色发展.      

城市碳排放达峰和低碳发展研究:以上海市为例

在2015年巴黎气候变化大会上,中国政府提出"2030年前后碳排放达到峰值并加快实现"等一系列新阶段目标。城市是能源资源消耗和碳排放的集聚区域,推动城市低碳发展成为各国面临的共同挑战。采用STIRPAT模型,探究上海市过去20年发展总体形势,分析碳排放影响因素,判断上海在2025年是否可以达峰。结果表明:无论基准情景还是超低碳情景,上海市在2025年之前达峰的目标均可以实现。在对上海市碳排放各影响因素中,城市化率对其影响最大,其次是人均GDP水平。     

基于化石能源消耗的重庆市二氧化碳排放峰值预测

首先利用重庆市能源平衡表,采用IPCC方法 1对重庆市1997—2012年的碳排放进行核算;其次依据重庆市经济社会发展状况,通过LMDI因素分解法将影响碳排放的因素分解为:人口、人均GDP、产业结构、能源结构、能源强度和碳排放系数;然后利用扩展的重庆市STIRPAT碳排放模型,在9个情景模式下对2013—2050年重庆市碳排放进行预测;最后对比分析了各情景下的峰值大小及出现时间.研究发现:基准模式下的重庆市碳排放在2035年出现32135.38万t的峰值;提高能源利用技术、增加清洁能源使用比例和大力发展第三产业,能在不降低经济发展的情况下有效降低碳排放;消极因素中的第二产业占比下降比碳排放强度下降对碳排放的抑制作用更加明显;积极因素对碳排放峰值的影响比消极因素更有效.     

2000-2009年安徽省能源消费与碳排放分析

根据联合国政府气候变化专门委员会(IPCC)2006年版碳排放指南中的计算公式和碳排放系数缺省值,计算了安徽省2000年-2009年能源消费和碳排放情况。结果表明:安徽省能源消费由2000年的4878.82万t标准煤增长到2009年的8895.90万t标准煤,平均年增长率为6.9%,其中第二产业部门能源消费量均占能源消费总量的79%以上;能源消费产生的二氧化碳由2000年的4107.48万t增长到2009年的8536.12万t,其中在各种能源消费碳排放量中原煤的碳排放量最大,占总碳排放量的77%82%;碳排放强度总体上呈现下降的趋势,低于全国平均碳排放强度,但高于全球和美国;碳排放的因素分析得出碳排放量与人口、人均GDP、能源强度呈现高度相关性。     

山西省CO2排放影响因素研究及情景分析

山西作为我国的能源大省,其碳排放强度更是持续位于全国最高水平,分析山西省CO₂排放影响因素,探究其发展模式,对于山西省的低碳发展意义重大.基于STIRPAT模型,将山西省能源CO₂排放的影响因素确定为人口、城镇化率、人均GDP、第二产业占GDP比重、能源强度.在岭回归拟合分析的基础上,利用灰色GM（1,1）模型对山西省CO₂排放驱动因素值进行预测,以提高能源CO₂排放预测的准确性,并结合情景分析方法,为山西省的CO₂减排设计了10种不同的发展情景.结果表明:①人口对山西省CO₂排放影响最大,其次是城镇化率和第二产业占GDP比重.②在当前经济发展阶段,能源强度和人均GDP等因素对山西省的CO₂排放影响不大,但能源强度对CO₂排放的抑制作用不可忽略.③山西省CO₂减排最佳的情景方案为适当控制人口数量和城镇化进程、加快产业结构的转型和技术的革新、降低第二产业占GDP比重和能源强度,并且大力推广新能源和清洁可再生能源的开发使用以优化能源消费结构.在该情景下,山西省2020年的CO₂排放量可以控制在5.16×108 t.      

Emissions Scenarios Database and Review of Scenarios

This paper reviews and analyzes more than 400 scenarios of global and regional greenhouse gas emissions and their main driving forces - population, economy, energy intensity, and carbon intensity - drawn from an extensive literature survey and summarized in a database. This new and growing database is available online, which makes summary statistics on these scenarios widely available. The scenarios in the database were collected from almost 200 different literature sources and other scenario evaluation activities. The ultimate objective of the database is to include all relevant global and regional emissions scenarios. This paper shows how the database can be utilized for the analysis of greenhouse gas emissions ranges across the scenarios in the literature and for the analysis of their main driving forces. The scenarios in the database display a large range of future greenhouse gas emissions. Part of the range can be attributed to the different methods and models used to formulate the scenarios, which include simple spreadsheet models, macroeconomic models and systems-engineering models. However, most of the range is due to differences in the input assumptions for the scenarios, in particular of the main scenario driving forces. Special emphasis is given to an analysis of medians and ranges of scenario distributions and the distributions of the main scenario driving forces in the database. The analysis shows that the range for projected population increase in the world, across the scenarios in the database, is the smallest of all main driving forces (about a factor of 3 in 2100). The range of economic growth, measured by the gross world product, and the range of primary energy consumption vary by a factor of 10 in 2100. Carbon intensity of energy, an indicator of the degree of technological change, varies by nearly two orders of magnitude in the year 2100. In addition, this paper presents the first attempt to analyze the relationships among the main scenario driving forces. Subsequent papers in this special issue give further analyses of the relationships among the main scenario driving forces and their other relevant characteristics.     

2006—2015年中国电力碳足迹及其生态压力分析

电力行业是我国节能减排的主力军.本文根据电力来源多样性特征,采用IPCC计算方法,结合净初级生产力模型,定量分析了中国2006-2015年电力消费碳足迹及其生态压力的变化,并将电力碳足迹生态压力与人均GDP进行脱钩分析.结果表明,2006-2015年,电力消费碳排放量经历了先升后降两个阶段,其中,2006-2013年,碳排放量稳步上升,2013年后开始逐渐下降,电力碳足迹生态压力与人均GDP之间主要呈弱脱钩关系,但在2013-2015年,开始出现强脱钩状态.可见在国家″十二五″政策引导下,推动经济结构转型调整,促进电力产业节能减排,已获得显著成效,但仍需继续努力,缓解电力消费过程给生态环境带来的压力.     

Can Advances in Science and Technology Prevent Global Warming?

The most stringent emission scenarios published by the Intergovernmental Panel on Climate Change (IPCC) would result in the stabilization of atmospheric carbon dioxide (CO₂) at concentrations of approximately 550 ppm which would produce a global temperature increase of at least 2 ^{^}C by 2100. Given the large uncertainties regarding the potential risks associated with this degree of global warming, it would be more prudent to stabilize atmospheric CO₂ concentrations at or below current levels which, in turn, would require more than 20-fold reduction (i.e., ≥95%) in per capita carbon emissions in industrialized nations within the next 50–100 years. Using the Kaya equation as a conceptual framework, this paper examines whether CO₂ mitigation approaches such as energy efficiency improvements, carbon sequestration, and the development of carbon-free energy sources would be sufficient to bring about the required reduction in per capita carbon emissions without creating unforeseen negative impacts elsewhere. In terms of energy efficiency, large improvements (≥5-fold) are in principle possible through aggressive investments in R&D and the removal of market imperfections such as corporate subsidies. However, energy efficiency improvements per se will not result in a reduction in carbon emissions if, as predicted by the IPCC, the size of the global economy expands 12–26-fold by 2100. Terrestrial carbon sequestration via reforestation and improved agricultural soil management has many environmental advantages, but has only limited CO₂ mitigation potential because the global terrestrial carbon sink (ca. 200 Gt C) is small relative to the size of fossil fuel deposits (≥4000 Gt C). By contrast, very large amounts of CO₂ can potentially be removed from the atmosphere via sequestration in geologic formations and oceans, but carbon storage is not permanent and is likely to create many unpredictable environmental consequences. Renewable energy can in theory provide large amounts of carbon-free power. However, biomass and hydroelectric energy can only be marginally expanded, and large-scale solar energy installations (i.e., wind, photovoltaics, and direct thermal) are likely to have significant negative environmental impacts. Expansion of nuclear energy is highly unlikely due to concerns over reactor safety, radioactive waste management, weapons proliferation, and cost. In view of the serious limitations and liabilities of many proposed CO₂ mitigation approaches, it appears that there remain only few no-regrets options such as drastic energy efficiency improvements, extensive terrestrial carbon sequestration, and cautious expansion of renewable energy generation. These promising CO₂ mitigation technologies have the potential to bring about the required 20-fold reduction in per capita carbon emission only if population and economic growth are halted without delay. Therefore, addressing the problem of global warming requires not only technological research and development but also a reexamination of core values that equate material consumption and economic growth with happiness and well- being.     

基于发热量的中国煤炭碳含量研究

煤炭基于发热量的碳含量数据,是计算煤炭的二氧化碳排放因子的基础。本研究对全国范围内采集的煤炭样品进行工业分析、元素分析及发热量分析,统计分析得出我国基于发热量的煤炭碳含量。对所得结果按地区分煤种分别阐述,并与国外煤炭碳含量数据进行了对比。结果表明,我国褐煤、次烟煤、烟煤、无烟煤的碳含量平均值分别为27.21±0.35 kg/GJ、26.57±0.14 kg/GJ、25.50±0.03 kg/GJ、26.77±0.13 kg/GJ。我国无烟煤的碳含量与IPCC缺省值相当,烟煤、褐煤的碳含量比IPCC缺省碳含量分别低1.16%和1.41%,次烟煤碳含量比IPCC缺省碳含量高1.41%。     

人均GDP、能源强度与碳排放的面板数据分析

利用2000年-2009年中国各省市的面板数据,考察了人均GDP与能源强度对碳排放的影响。在单位根检验的基础上,对这三个变量进行了协整关系检验,实证结果显示,三个变量间存在长期的均衡关系,并以碳排放为被解释变量,能源强度和人均GDP分别作为解释变量进行回归分析。能源强度和人均财富的提高都会增加二氧化碳的排放量。     

基于STIRPAT模型的重庆市能源消费碳排放影响因素研究

定量分析人类活动对环境的影响,对减少碳排放和建设环境友好型社会具有重要的指导意义.因此,本文采用重庆市1980-2010年能源消费碳排放时间序列数据,基于STIRPAT模型,通过岭回归拟合得到能源消费碳排放与人口数量、人均GDP及其二次项、能源强度、第三产业比重、城镇化水平的多元线性模型.结果表明,人口数量、人均GDP、能源强度、城市化水平每增加1％,将引起重庆市能源消费碳排放相应增加0.963％、(0.398 +0.463lnA)％、0.059％、0.266％,其中,A为人均GDP.可以看出,人口数量对重庆市能源消费碳排放量影响最大.第三产业比重每增加1％,能源消费碳排放将会减少0.093％.     

The value of energy efficiency programs for US residential and commercial buildings in a warmer world

US residential and commercial buildings were responsible for about 41 exajoules (EJ) of primary energy use per year in 2002, accounting for approximately 9% of the world fossil-fuel related anthropogenic carbon (C) emissions of 6.7 Gt that contribute to climate change. US Government-sponsored building energy efficiency research and implementation programs are focused on reducing energy consumption in US residential and commercial buildings and reducing these carbon (C) emissions. Although not specifically intended for adaptation to a warmer climate and less effective than under today’s cooler climate, these programs also could help reduce energy demand in a future warmer world. Warming scenarios projected by the United Nations Intergovernmental Panel on Climate Change (IPCC) in 2001 imply net overall decreases in both site energy and primary energy consumption in US residential and commercial buildings, largely because of the reduced need for heating. However, there would be as much as a 25% increase in building space cooling demand and a significant part of the increase could be offset by energy-efficiency improvements in buildings. Overall, in the US, buildings-related energy efficiency programs would reduce site energy consumption in buildings in the US by more than 2 EJ in 2020 and primary energy by more than 3.5 EJ, more than enough to offset the projected growth in cooling energy consumption due to climate change and growth in the US building stock. The savings would have an estimated annual net value at 2005 energy prices of between $45.0 and $47.3 billion to consumers.

IPCC第一工作组评估报告分析及建议

2021年8月6日,政府间气候变化专门委员会(IPCC)第一工作组第六次评估报告(AR6)发布,针对气候系统变化科学领域最新研究进展和成果进行了全面、系统的评估. AR6以更强有力的证据进一步确定了近百年全球气候变暖的客观事实,人类活动对气候变暖影响的信号更为清晰. 本文总结了历次IPCC评估报告,并从气候现状、未来可能的气候状态、风险评估和区域适应气候变化信息以及减缓未来气候变化4个方面对AR6进行系统梳理. 结果表明:人类活动产生的温室气体对大气、海洋、冰冻圈和生物圈的影响前所未有,引发了全球许多地区的极端天气和气候极端事件. 未来若温室气体排放没有显著减少,到2100年全球地表温度将至少升高2.1 ℃;如若人类影响得到有效改善,在最低排放情景(SSP1-1.9)中,2055年将变为负碳,到21世纪末气温开始再次下降. 减少CH₄等其他污染物可以为全球气候治理争取时间,并改善空气质量. 建议中国应对气候变化应加强基础科学研究,聚焦模式开发和应用及与各工作组之间的衔接,加快短寿命气候强迫(SLCFs)与温室气体协同控制研究,强化应对气候变化政策措施的科技支撑等.      

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.     

中国省域能源消费碳排放时空异质性的EOF和GWR分析

利用自然正交函数(EOF)揭示中国各省份能源消费碳排放量变动的时空特征,借助地理加权回归模型(GWR)分析了碳排放量驱动因素的空间分布状况.研究结果表明:中国省域能源消费碳排放量整体处于增长状态,但其增长速度有减缓趋势;EOF第一模态结果显示,碳排放量以四川省为中心向南北方向扩散,低值区集中分布在西北地区和珠三角地区;第二模态结果显示,碳排放量增长速度表现出西南地区和东南沿海地区较快,而中部省份碳排放量增长速度较慢的态势.碳排放量影响因素的重要程度由大到小依次为:总人口变化量、人均GDP变化量、城镇化率变化量、二产比重变化量、贸易开放程度变化量和能源消耗强度变化量,其中,总人口变化量的影响程度最为剧烈,每当总人口变化1%时,碳排放量相应地会变化0.5358%.     

中国能源消费导致的CO_2排放量的时空演变分析

利用《IPCC2006国家温室气体清单指南》推荐的基准方法,结合能源消费统计数据,在省级尺度上对中国1997～2007年由于能源消费产生的CO2排放总量、CO2排放的分布、人均排放量、CO2排放强度等进行计算和对比分析。研究结果表明:(1)1997～2007年山东、河北、江苏、广东、辽宁、河南、山西等省的CO2排放总量一直居于前列。(2)中国能源消费产生的CO2排放主要集中在第二产业,而且第一、第二产业的CO2排放比重近年来有加大的趋势。(3)从CO2排放强度来看,中西部省区的CO2排放强度明显高于东部沿海省份。