基于Urban-RAM模型的上海居民生活碳排放研究

随着全球对碳排放相关研究的不断深入,居民生活引起的能源消耗和碳排放问题引起了研究人员越来越多的关注,但目前鲜有对上海市居民生活整体碳排放的系统研究.本文以2010年为基准年,引入美国劳伦斯伯克利国家实验室开发的Urban-RAM模型,对上海市居民生活碳排放情况进行定量分析,旨在初步掌握上海市居民生活碳排放的总体规模和结构特征,为上海市低碳城市建设和相关决策提供科学依据.研究结果表明,上海市2010年居民生活碳排放总量(CO2e)为4985.7万t,主要以间接排放为主,间接碳排放和直接碳排放分别占居民生活碳排放总量的64.1%和35.9%;上海市居民生活碳排放在各个消费领域的分布不均,直接碳排放主要来自公共和居住建筑领域,该领域的直接碳排量为1065.0万t,占全市居民生活直接碳排放总量的59.5%;间接碳排放主要来自家庭消费领域,该领域的间接碳排量为1625.2万t,占全市居民生活间接碳排放总量的50.9%,其中以食品消费和衣装消费的贡献最大,分别占家庭消费领域碳排放总量的53.5%和29.5%;综合来看,公共和居住建筑领域的整体碳排量最大,为2231.6万t,占全市居民生活碳排放总量的44.8%.     

基于多区域投入产出(MRIO)的中国区域居民消费碳足迹分析

近年来,居民消费活动和环境的关系逐渐受到关注,而与温室气体排放相关的研究更是其中的热点.因此,本文采用“居民消费碳足迹”概念来定义特定居民消费活动所导致的直接和间接温室气体排放的总和,主要包括CO2、CH4、N2O3种温室气体;构建了基于环境扩展的多区域投入产出(Multiregional input-output,MRIO)模型的碳足迹核算方法,并以2007年中国8个区域为例对其居民消费碳足迹的数量、构成、分布及转移进行了分析.结果显示,2007年全国居民消费碳足迹总量达到31.74亿t(以CO2当量计).此外,碳足迹还呈现出区域差异明显、间接排放大于直接排放、城乡差距过大等特征.人均碳足迹方面,发展水平较高的京津、东部沿海地区明显高于相对滞后的西北、西南区域.研究还对碳足迹的区域分布和转移进行了深入探讨.结果发现,东北、京津、西北和西南区域转移收支为负,表示这些区域为其他区域承担的排放大于其他区域为其承担的排放;剩余的北部沿海、东部沿海、南部沿海和中部区域情况则正好相反.这些结果对现阶段中国制定具体区域消费政策或分配碳减排责任等具有参考价值;本研究的方法论也适用于研究其他环境因子及足迹因子与居民消费的关系.     

基于投入产出模型的居民消费品载能碳排放测算与分析

论文建立测算与分析居民消费品载能碳排放的投入产出模型,基于可比价投入产出序列表对中国居民消费品载能碳排放进行实证分析。研究表明,1992-2005年,我国居民消费品载能碳排放从33 876×10⁴ t C增长至67 940×10⁴ t C,增幅达1.0倍;其人均值从289.1 kg C增长至519.6 kg C,增幅为79.7%。居民消费碳排放的增幅远小于消费价值量增幅;居民消费碳排放占我国能源消费排放总量的比重波动下降。在排放结构方面,农业、 食品类消费品的排放比重大幅下降,居住、 交通、 信息等服务性消费的排放大幅上升。居民消费品载能碳排放的城乡差距不断扩大,人均排放的城乡比从2.4增至4.0;在排放结构的变动上则表现出一定的趋同特征。我国居民人均消费排放水平远低于欧美发达国家的同期水平,1990年代的人均排放水平仅为美国的1/14,在欧洲国家的1/5至1/2之间。研究认为,通过优化消费结构带动产业结构调整以及促进排放强度降低,未来我国有可能在持续提高居民消费水平的同时,有效减缓消费排放。     

城市汽车年检碳排放数据挖掘及其应用研究

基于城市汽车年检中CO₂的过程动态检测数据,对小型汽油客车CO₂的排放因子和排放水平信息进行了挖掘,并与文献研究结果进行了对比.结果表明,从城市汽车年检数据中挖掘的CO₂排放结果可以作为研究城市机动车碳排放的重要参考依据;合理有效地利用汽车年检数据可以为城市车辆尾气排放的精准分级管控、城市交通运输碳排放达峰的量化分析,以及城市交通源的污染物和CO₂协同减排提供重要的数据支撑;从国Ⅰ到国Ⅴ不同排放阶段汽油车的常规污染物CO、NO_x和HC的排放水平下降非常明显,而对应的CO₂排放水平差异不大;CO₂排放因子随累计行驶里程、车龄、基准质量和排量的变化关系反映出,如果需要削减城市汽车碳排放水平,应鼓励使用基准质量小或者排量小的车辆,淘汰高油耗高排放的老旧车辆,鼓励公共绿色出行而降低单车活动水平,增加纯电动车辆优化车队能源结构.     

基于LMDI模型和Q型聚类的中国城镇生活碳排放因素分解分析

为研究城镇居民生活碳排放特征及影响因素,基于LMDI模型从全国和省级层面研究了我国30个省、自治区、直辖市（不含港澳台及西藏自治区）2006-2015年的城镇生活碳排放,将城镇生活碳排放分解为生活能源消费结构效应、生活能源强度效应、消费倾向效应、人均可支配收入效应和城镇人口规模效应,分析各效应逐年和累积效应贡献度以及区域差异,并基于LMDI模型的计算结果对我国30个省、自治区、直辖市进行Q型聚类分析.结果表明:①从全国层面看,人均可支配收入、城镇人口规模是刺激因素,其中,人均可支配收入的影响效应最为显著,而消费倾向、生活能源消费结构、生活能源强度抑制了生活碳排放的增长.②从省级层面看,人均可支配收入、城镇人口规模的累积效应均为正,而消费倾向、生活能源消费结构、生活能源强度对各省、自治区、直辖市生活碳排放的影响效应有正有负,显示出显著差异.因此,政府应引导城镇人口合理增长,并积极制定相应政策优化居民生活能源消费结构.在制定碳减排战略时,要将省级生活碳排放的表面特征与其潜在驱动力相结合,根据不同区域有针对性地实施碳减排政策,同时应及时作出调整,以应对不同的发展阶段.      

中国平板玻璃生产碳排放研究

平板玻璃行业是典型的高能耗、高排放行业,目前关于中国平板玻璃行业的碳排放问题还没有得到深入的研究.因此,本文调查了中国300余条主要的平板玻璃生产线,并在此基础上从范围1(工艺过程和化石燃料燃烧引起的直接排放)和范围2(净购入电力和热力在生产阶段引起的间接排放)评估了中国平板玻璃行业从2005年到2014年的CO_2排放情况.结果发现,中国平板玻璃行业CO_2排放量逐年增加,由2005年的2626.9×10~4t逐步上升到2015年的4620.5×10~4t.研究表明:能源消耗是平板玻璃行业碳排放的最主要来源,占比在80%左右,节能降耗是促进平板玻璃行业CO_2减排的主要途径;平板玻璃生产原料中碳酸盐的热分解是CO_2的主要来源之一,占总排放量的20%左右,控制平板玻璃配合料的气体率,在减少平板玻璃生产过程中的CO_2排放有很大潜力;推荐平板玻璃新建项目使用天然气并配备大型熔窑(日熔化量650 t以上)的浮法玻璃生产线,以减少CO_2排放.     

中国服务业CO2排放的时空特征与EKC检验

采用IPCC温室气体排放清单中CO₂排放因子与估算方法,核算了1995—2012年中国30个省区(不含港澳台地区和西藏自治区数据,全文同)服务业的CO₂排放量,并对30个省区服务业人均CO₂排放量的时空特征进行分析;利用基于面板数据的EKC模型检验中国及其三大经济带服务业增长与CO₂排放之间的关系. 结果表明:在考察期内,中国服务业人均CO₂排放量从0.16 t升至0.77 t,服务业人均增加值从1 621.04元增至9 991.95元;服务业人均CO₂排放量排在前列的省区大都位于东部地区;东部和中部地区人均CO₂排放量与服务业人均增加值之间呈线性正相关,人均服务业增加值每增加1个单位,人均CO₂排放量将分别增加1.02和1.16个单位;西部地区人均CO₂排放量与服务业人均增加值之间呈单调递增关系. 在此基础上,提出差别化的碳减排对策:①东部地区应通过技术改进和优化产业结构、能源消费结构来降低CO₂排放,并成为中国服务业节能减排的“领头羊”;②中、西部地区应在保持服务业经济适当增速的前提下,将提高能源利用效率和降低能源强度作为减排重点.      

中国居民家庭消费碳足迹近20年增长情况及未来趋势研究

近年来,伴随着社会经济的快速发展,我国已成为全球温室气体排放量最大的经济体,而居民消费活动造成的碳排放始终是可持续消费领域的研究热点.本研究综合采用基于投入产出的生命周期评价、结构分解分析、截面分析等方法,并借助EORA数据库,系统研究了近20年中国居民消费碳足迹的总量与组成、驱动因素贡献及未来增长趋势.结果表明,居民消费碳足迹的快速上升通道已经形成,且内在结构演化也呈现规律性,即间接排放和城镇居民排放已占主导地位并且该趋势仍在加强.驱动因素方面,人口增长、城市化进程、消费水平提高是推动碳足迹增长的主要正向力量,同时另外三因素(排放强度、消费结构及经济结构)则构成了延缓碳足迹过快增长的减排力量.截面分析结果显示,未来中国居民消费跨越世界平均水平时其碳排放总量将达到2010年基数的1.45倍,当接近于美国人均消费水平时将达到5.45倍.可以预期,未来我国居民消费碳足迹将会加速增长.     

中国水泥工业CO2排放现状及减排对策

水泥工业是中国制造业中温室气体CO2的主要排放源,因此,根据水泥生产的基本原理和工艺特点,建立了CO2排放的数学模型并确定排放强度,计算了2001—2010年中国水泥工业CO2的排放量,分析了影响CO2排放量的主要因素及其发展趋势,并提出水泥工业CO2减排对策.结果表明,中国水泥工业CO2排放总量逐年增长,与水泥产量和单位产品原料、燃料消耗定额呈线性关系;在CO2排放总量中,原料煅烧和燃料燃烧阶段的排放量分别占49%和51%;"十一五"期间单位水泥产品CO2排放强度由0.69t.t-1下降到0.65t.t-1.万元GDPCO2排放量呈下降趋势,2008年达到最低值为0.3054t,平均每年万元GDPCO2排放量下降10.69%,说明水泥工业10年间实施节能降耗、资源循环利用、提高经济效益等措施对于减少CO2排放具有明显效果.     

人口迁移视角下城镇化对典型领域碳排放驱动效应研究——以辽宁省为例

城镇化的快速发展为我国带来了日新月异的变化,但城镇化进程中伴随着能源消费快速增长,使我国面临能源供应、节能减排等方面更加严峻的挑战.现有研究主要是从宏观角度研究城镇化对能源消费及碳排放的影响,较少探究人口从农村向城镇迁移过程中对典型领域产生的驱动效应.基于此,本研究以辽宁省为例,应用弹性系数模型,选取居民消费、住宅建筑、道路交通3个典型领域探讨城镇化对碳排放的驱动效应,并提出针对性的碳减排政策.结果表明,2006—2015年,城镇化对居民生活直接消费碳排放的驱动效应最为显著,弹性系数为9.91;对居民生活间接消费碳排放和道路交通领域的驱动效应次之,弹性系数分别为6.94和5.38;对住宅建筑等驱动效应最弱,弹性系数为2.71.研究表明,城乡生活方式差异导致居民直接生活消费碳排放显著增加,相较而言,城乡产品市场差异较小;辽宁省现阶段城镇住宅建筑存量与城镇新增人口的需求基本匹配,但人口城镇化带来的城市边界外扩、人口密度提高,导致道路交通碳排放增长.     

基于1 km网格的天津市二氧化碳排放研究

中国城市建制及地理边界特征使得国际城市CO2排放的关键问题在中国难以深入研究.例如,城市排放占比,城市与周边区域排放差异等.本文基于天津市CO2排放的1 km网格,分析天津市CO2排放的空间特征,探讨天津市不同城市范围的CO2排放水平,并与纽约市进行对比分析.结果显示,2007年天津市市域内CO2排放总量为12599万吨,人均排放11.30 t.天津市市域CO2排放的空间格局是从中心6个城区向外单位网格排放量逐渐降低.CO2排放在空间上具有显著的正空间自相关性,中心6个城区、滨海新区及郊区县中心镇的CO2排放对其周边区域CO2排放影响显著,天津市狭义城市人均CO2排放量为4.71 t,低于纽约市的6.33t;狭义城市范围1排放占总排放的比例为69.26％,略高于纽约市的59.70％.以狭义城市为城市范围时,天津城市及周边区域人均CO2排放的空间特征与发达国家城市的排放特征研究结论一致,都是从城区—郊区—周边区域,人均排放水平逐渐升高;在此范围下,天津城市CO2排放仅占全市域的14.00％.     

A decomposition analysis of carbon dioxide emissions in the Chinese nonferrous metal industry

The nonferrous metal industry (NMI) of China consumes large amounts of energy and associated emissions of carbon dioxide (CO ₂) are very high. Actions to reduce CO ₂ emissions and energy consumption are warranted. This study aims to analyze current China NMI trends of CO ₂ emissions and energy consumption including the underlying regional driver characteristics. We analyze the changes of CO ₂ emissions in the NMI based on the Logarithmic Mean Divisia Index (LMDI) method from 2000 to 2011. Then, a classification system is used to study the regional differences in emission changes from the NMI. The results show that the emissions of the Chinese NMI increased rapidly at an average annual growth rate of 31 million metric tons. The economic scale and energy intensity are the main driving factors responsible for the change in the emissions, while carbon emission coefficients make only a small contribution toward decreasing the emissions, and the energy structure has a volatile effect. Emissions and energy intensity of 29 China provinces were divided into five categories. The change in the trend of each region is indicated in this paper. Hebei is one of the provinces that achieved the best performance, and Chongqing achieved the worst performance among all of the regions. The analysis suggests that the main emphasis of CO ₂ emission mitigation should be focused on controlling the economic scale and improving the energy intensity. Developing the use of clean energy technologies and policies in both the NMI and power industries is important.     

农村居民生活碳达峰路径及对策

全国碳达峰目标已经明确,农村居民生活能源消费是碳排放增长的重要来源,亟待得到有效控制.为研究农村居民生活碳达峰路径,基于农村居民生活能源消费现状分析,采用碳排放系数法对2000—2018年农村居民生活的碳排放进行核算,基于情景分析法,从能源消费结构调整的角度,设定不同情景分析农村居民生活的碳达峰时间及峰值.结果表明:①2000—2018年,农村居民生活碳排放量、人均碳排放量均呈快速上升趋势,其中农村居民生活碳排放量占国家碳排放总量的3.0%~4.0%.②在2030年国家碳排放强度下降65%的目标下,农村居民生活同步碳达峰目标约为3.64×108 t;农村居民煤炭消费的碳排放已在2017年达峰,总量达峰则依托于能源结构调整情景实现目标.③基准情景下,2030年前无法实现碳达峰;政策情景下,将在2027—2028年达到峰值,峰值约为3.66×108 t;优化情景下,将在2024年达到峰值,峰值约为3.44×108 t.④基于能源结构调整的碳达峰路径主要表现为煤炭消费占比降至18.0%左右,天然气、电力、其他能源消费占比分别提至1.5%、35.0%、30.0%左右.研究显示,促进碳达峰的措施可重点从完善顶层设计、制定农村能源发展战略规划、推动分布式能源系统建设、加强节能减排技术保障、创新资金支持、普及绿色低碳生活方式等几个方面加强实施,从而推动农村的能源变革与节能减排.      

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.      

Low-carbon transition of iron and steel industry in China: Carbon intensity, economic growth and policy intervention

As the biggest iron and steel producer in the world and one of the highest CO₂ emission sectors, China's iron and steel industry is undergoing a low-carbon transition accompanied by remarkable technological progress and investment adjustment, in response to the macroeconomic climate and policy intervention. Many drivers of the CO₂ emissions of the iron and steel industry have been explored, but the relationships between CO₂ abatement, investment and technological expenditure, and their connections with the economic growth and governmental policies in China, have not been conjointly and empirically examined. We proposed a concise conceptual model and an econometric model to investigate this crucial question. The results of regression, Granger causality test and impulse response analysis indicated that technological expenditure can significantly reduce CO₂ emissions, and that investment expansion showed a negative impact on CO₂ emission reduction. It was also argued with empirical evidence that a good economic situation favored CO₂ abatement in China's iron and steel industry, while achieving CO₂ emission reduction in this industrial sector did not necessarily threaten economic growth. This shed light on the dispute over balancing emission cutting and economic growth. Regarding the policy aspects, the year 2000 was found to be an important turning point for policy evolution and the development of the iron and steel industry in China. The subsequent command and control policies had a significant, positive effect on CO₂ abatement.     

广东省CO2排放变化的社会经济影响因素

作为我国经济最为发达的省份之一,广东省社会经济可持续发展面临CO₂排放量增长的挑战.从多角度分析广东省CO₂排放变化的社会经济影响因素,有助于其实现低碳发展.基于投入产出模型,从生产、需求和供应角度分析1987—2015年广东省CO₂排放量的变化;此外,采用结构分解分析方法,从需求和供应角度量化广东省各种社会经济因素对CO₂排放变化的相对贡献.结果表明:①与生产端相比,需求侧和供给侧的研究有助于识别不同的关键行业,如建筑业（需求侧）、金融和保险业（供给侧）.②降低碳排放强度是减少广东省CO₂排放的主要因素,而人均最终需求水平和人均初始投入增加是推动广东省CO₂排放增加的主要因素.③生产结构、最终需求结构和初始投入结构变化导致CO₂排放量略有增加,表明广东省具有较大的通过调整结构性因素减排CO₂的潜力.综上,建议除了生产端CO₂减排措施外,广东省还应采取需求侧和供给侧相关措施,如优化消费行为、产品分配行为和初始投入结构等.      

基于LMDI分解方法的河北省PM2.5排放驱动因素分析

研究了河北省1990—2015年PM_(2.5)的排放总量及各个产业部门的排放量分布,并应用LMDI模型对五大部门PM_(2.5)排放变化的驱动因素进行了较全面的分解分析,以找出每个部门中PM_(2.5)排放变化的关键驱动因素.同时,通过对原始数据的整理分析和模型计算,结果发现:①工业、生活消费、农业部门是河北省PM_(2.5)排放的三大来源.其中,工业部门是PM_(2.5)排放的最主要贡献部门,占PM_(2.5)总排放量的70%;生活消费部门的贡献位居第二,占比约24%.②对于生产端,经济规模总量扩张是PM_(2.5)排放量增加的最主要原因;能源利用效率的提高和污染治理工艺水平的改进使得各部门的排放强度减弱,明显缓解了PM_(2.5)的排放增长,部门经济结构的优化也可带来明显的减排效应.③对于消费端,人均收入的提高促进了PM_(2.5)排放的增加,倡导绿色消费模式可以有效减缓PM_(2.5)排放.根据以上结论,本研究通过找到各部门存在的问题,为河北省大气污染治理提供参考和借鉴.     

Estimation of carbon dioxide flux and source partitioning over Beijing, China

The magnitude and partitioning of carbon dioxide emission from the urban area in Beijing, China was estimated based on a statistical approach. Results showed that the urban surface is a net source of CO2 to atmosphere. The main sources of CO2 are vehicles, which accounted for 75.5% and 38.9% of CO2 emission in summer and winter, respectively. At midday in summer, the CO2 uptake of-0.034 mg/（m^2.sec） indicated that vegetation is an important sink of CO2 in summer. Comparison between the annual emission rates of CO2 from the statistical approach and that directly measured by the eddy covariance technique implies that a bottom-up emission approach is a viable means to estimate CO2 emission in an urban area.     

Low-carbon transition of iron and steel industry in China: Carbon intensity,economic growth and policy intervention

As the biggest iron and steel producer in the world and one of the highest CO₂ emission sectors, China's iron and steel industry is undergoing a low-carbon transition accompanied by remarkable technological progress and investment adjustment, in response to the macroeconomic climate and policy intervention. Many drivers of the CO₂ emissions of the iron and steel industry have been explored, but the relationships between CO₂ abatement, investment and technological expenditure, and their connections with the economic growth and governmental policies in China, have not been conjointly and empirically examined. We proposed a concise conceptual model and an econometric model to investigate this crucial question. The results of regression, Granger causality test and impulse response analysis indicated that technological expenditure can significantly reduce CO₂ emissions, and that investment expansion showed a negative impact on CO₂ emission reduction. It was also argued with empirical evidence that a good economic situation favored CO₂ abatement in China's iron and steel industry, while achieving CO₂ emission reduction in this industrial sector did not necessarily threaten economic growth. This shed light on the dispute over balancing emission cutting and economic growth. Regarding the policy aspects, the year 2000 was found to be an important turning point for policy evolution and the development of the iron and steel industry in China. The subsequent command and control policies had a significant, positive effect on CO₂ abatement.     

Urban CO<Subscript>2</Subscript> emissions in Xi’an and Bangalore by commuters: implications for controlling urban transportation carbon dioxide emissions in developing countries

China and India together have more than one third of the world population and are two emerging economic giants of the developing world now experiencing rapid economic growth, urbanization, and motorization. The urban transportation sector is a major source of carbon dioxide (CO₂) emissions in China and India. The goal of this study is to analyze the characteristics and factors of CO₂ emissions produced by commuters in Chinese and Indian cities and thus to identify strategies for reducing transportation CO₂ emissions and mitigating global climate change. Xi’an in China and Bangalore in India were chosen as two case study cities for their representativeness of major cities in China and India. The trends of CO₂ emissions produced by major traffic modes (electric motors, buses, and cars) in major cities of China and India were predicted and analyzed. The spatial distributions of CO₂ emissions produced by commuters in both cities were assessed using spatial analysis module in ArcGIS (Geographic Information System) software. Tobit models were then developed to investigate the impact factors of the emissions. The study has several findings. Firstly, in both cities, the increase of vehicle occupancy could reduce commuting CO₂ emissions by 20 to 50 % or conversely, if vehicle occupancy reduces, an increase by 33.33 to 66.67 %. It is estimated that, with the current increasing speed of CO₂ emissions in Xi’an, the total CO₂ emissions from electric motors, buses, and cars in major cities of China and India will be increased from 135?×?10⁶ t in 2012 to 961?×?10⁶ t in 2030, accounting for 0.37 to 2.67 % of the total global CO₂ emissions of 2013, which is significant for global climate change. Secondly, households and individuals in the outer areas of both cities produce higher emissions than those in the inner areas. Thirdly, the lower emissions in Xi’an are due to the higher density and more compact urban pattern, shorter commuting distances, higher transit shares, and more clean energy vehicles. The more dispersed and extensive urban sprawl and the prevalence of two-wheeler motorbikes (two-wheeler motorbike is abbreviated as “two-wheeler” in the following sections) fueled by gasoline cause higher emissions in Bangalore. Fourthly, car availability, higher household income, living outside the 2nd or Outer Ring Road, distance from the bus stop, and working in the foreign companies in Bangalore are significant and positive factors of commuting CO₂ emissions. Fifthly, “70-20” and “50-20” (this means that generally, 20 % of commuters and households produce 70 % of total emissions in Xi’an and 20 % of commuters and households produce 50 % of total emissions in Bangalore) emission patterns exist in Xi’an and Bangalore, respectively. Several strategies have been proposed to reduce urban CO₂ emissions produced by commuters and further to mitigate global climate change. Firstly, in the early stage of fast urbanization, enough monetary and land investment should be ensured to develop rail transit or rapid bus routes from outer areas to inner areas in the cities to avoid high dependency on cars, thus to implement the transit-oriented development (TOD), which is the key for Chinese and Indian cities to mitigate the impact on global climate change caused by CO₂ emissions. Secondly, in Bangalore, it is necessary to improve public transit service and increase the bus stop coverage combined with car demand controls along the ring roads, in the outer areas, and in the industry areas where Indian foreign companies and the governments are located. Thirdly, Indian should put more efforts to provide alternative cleaner transport modes while China should put more efforts to reduce CO₂ emissions from high emitters.