长三角地区碳排放效率时空特征及影响因素分析

长三角区域一体化发展战略上升为国家战略,要求建立区域间协调机制,引导低碳产业,弥补绿色发展的短板。掌握长三角地区碳排放效率时空特征及其影响因素,对长三角地区低碳高效发展及顺利实现碳减排目标具有重要的现实意义。基于考虑非期望产出的SBM-DEA模型与窗口分析相结合的方法,测算碳排放效率,利用传统统计分析与空间分析相结合的方法,分析了1995～2017年长三角地区碳排放效率时空特征,并考虑空间因素,构建空间杜宾面板模型分析其影响因素。结果表明:(1)1995～2017年碳排放效率总体呈波动变化趋势。2017年,上海、苏州和无锡的碳排放效率为1。碳排放效率绝对差异与相对差异呈波动变化,且变化趋势基本一致。碳排放效率存在不均衡现象。(2)碳排放效率区域差异明显,2005年后,空间格局变化不大,上海、苏州和无锡形成了碳排放效率高值区。碳排放效率重心主要分布在南京市,总体向西北移动。(3)空间杜宾面板模型结果表明:提高技术水平是改变碳排放效率的重要途径。城镇化和空间因素对碳排放效率具有明显的正向作用;外商投资、单位GDP能耗和生态环境对碳排放效率具有明显的负向作用。     

中国省级CO2排放影响因素的空间计量分析

提出面板数据空间误差分量模型,采用基于广义矩1估计的可行广义最小二乘法估计方法,研究1997-2007年间,我国省级CO2排放的影响因素.实证结果表明,我国省级CO2排放量存在显著的正向空间相关性,CO2排放较多的省份往往会影响邻近地区的CO2排放；CO2排放量与人均GDP呈倒N型环境库兹涅兹曲线.未考虑空间相关性时,CO2排放转折点为人均GDP 51 73O元,我国目前仍处于CO2排放量上升期；采用面板数据空间误差分量模型修正后,CO2排放下降转折点为人均GDP约53 237元,较未考虑空间因素时有所提高,省际间的空间相互影响,对CO2排放下降转折点的人均GDP提出更高的要求；实证研究结果同时显示,煤炭消费比重提高及人口数量增大,都将显著增加我国CO2排放量,体现优化能源结构和控制人口增长对抑制CO2排放增长的重要性.     

中国省域物流作业的CO2排放量测评及低碳化对策研究

物流活动是主要碳排放源之一,是温室气体减排、缓解气候变化的重要领域,从省域层面对我国物流作业的碳排放量进行核算和比较分析,对于从宏观上掌控各省域物流作业碳排放量及省域物流作业节能减排目标确定具有重要的意义.本文首先给出了省域物流作业CO2排放量测量模型,测算了不同能源的CO2排放因子及排放系数.然后,以物流作业直接能耗法核算我国各省域2008年物流作业的CO2排放指标,包括各省域的CO2排放量和单位货物周转CO2排放置,对比分析发现:我国省域之间物流活动产生的CO2排放量存在着地域不平衡性,CO2排放量中东部大部分省域要高于西部省域,而单位货物周转CO2排放置西部大部分省域要高于中东部省域.最后,根据物流作业的特点,分别从发展低碳运输、探索物流作业的技术性减碳方法、实行精细化物流作业管理、建立完善的节能减排考核与激励约束机制、制定低碳物流作业标准与打造低碳物流示范企业等五个主要的方面,阐述了我国物流作业的低碳化对策,以期促进我国低碳物流的发展.     

Characteristics of oxidant precursor emissions from anthropogenic sources in the United States

Hydrocarbons (HC) and nitrogen oxides (NO_x) have been identified as the most important precursor pollutants for oxidant formation in the atmosphere. These pollutants are emitted both from natural and anthropogenic sources; however, these two types of sources are generally geographically separated. Anthropogenic emissions are dominant in and around urban centers, where the majority of severe oxidant problems occur. Based on data gathered by the MAP3S/RAINE emissions inventory project, anthropogenic emissions of HC in the conterminous United States were 24.8 million metric tons in 1979. HC emissions were predominantly from area sources, the transportation sector being the largest contributor with 39.8% of the total. State-by-state breakdowns are also included. Based on analyses by other emissions inventory projects, the nonreactive fraction of the emissions from the transportation sector is less than 20% by weight. The highest proportion of HC emissions occur at low altitudes (0–50 m range) in high population density areas. Anthropogenic emissions of NO_x were 23.7 million metric tons in 1979; 50.8% were from point sources. The transportation sector and the electric utilities sector account for 37.1% and 30.9% of the NO_x emissions, respectively. The NO₂ fraction of the emissions from the transportation and electric utilities sectors is less than 10% by weight, based on NO/NO₂ speciation data from two other emissions inventories. Highest rates of NO_x emissions occur in high population density areas and are released at low altitude (0–50 m); three areas of high electric generating capacity were found to have high release altitudes.     

Predicting CO2 and SO2 emissions in the Baltic States through reorganization of energy infrastructure

The paper deals with predicting carbon dioxide and sulphur dioxide emissions generated by power production sector in the Baltic States in period up to year 2020. The economies of Lithuania, Latvia and Estonia are rapidly growing therefore forecast of emissions related with this occurrence becomes very important. The Ignalina Nuclear Power Plant (INPP), one of the largest in the world, is situated in the region. Two power production scenarios are modelled to investigate changes in power sector's emissions expected as the consequences of the coming closure of Ignalina NPP. Power market was assumed to be common for all three Baltic countries and was modelled by applying the Balmorel model. The planned closure of Ignalina NPP will bring restructuring of Lithuania power production sector and will change also power transmission between countries. Predictive identified the potential of investments for new modern power generation technologies. At the same time, modelling results show in both scenarios that CO(2) and SO(2) emissions from power production in the Baltic region will increase. The increment of emissions is discussed in the context of meeting requirements of UNFCCC Kyoto protocol and EC Directives. Despite of CO(2) emissions increase the Kyoto protocol's requirements may be expected. At the same time, SO(2) formation in Lithuania power sector may exceed the limits of the EU Council Directive 2001/80/EB therefore the additional measures to control SO(2) emissions have to be investigated.     

江苏省人口规模、结构对碳排放的影响分析

将人口结构因素纳入STIRPAT模型,利用江苏省1982~2010年的相关数据运用统计和计量方法对影响碳排放的人口总量、人口城市化、老龄人口比重、家庭规模、人均消费额、碳排放强度等相关因素进行实证分析。结果表明：家庭规模具有显著的负效应;在显著的正向影响因素中,老龄人口比重弹性最大,其它依次为人均消费额、人口总量、人口城市化水平、碳排放强度。在考虑人口结构情况下,碳排放的人口规模弹性小于1,缺乏弹性,说明人口总量对江苏碳排放的影响开始放缓;人口年龄结构对碳排放的影响逐渐显现,特别是老龄人口比重已经超过人口规模,成为促进碳排放的第一驱动因素;人口城市化进程和人均消费额直接加剧了碳排放,以碳排放强度表示技术进步对抑制碳排放有一定的作用,但不显著。针对分析结果,探讨了江苏省未来低碳发展的应对之策     

上海市居民消费碳排放的实证分析

居民消费碳排放是国内外温室气体排放研究的重要问题。利用1997～2010年上海市统计数据,分别采用改进的投入产出模型法、碳排放系数法核算了上海市居民间接和直接能源消费产生的碳排放,分析了上海市居民消费的碳排放变化、居民消费碳排放的城乡差异、各部门对居民间接能源消费碳排放的贡献。结果表明:(1)1997～2010年上海市居民消费产生的碳排放呈逐年上升趋势,间接能源消费是居民消费的碳排放的主要来源,在居民消费碳排放总量中占有较大比重;(2)1997～2010年上海市城镇居民消费碳排放呈逐年上升,农村居民消费碳排放呈下降趋势,居民消费碳排放存在着显著的城乡差异;(3)14个部门对居民消费碳排放的贡献大小不同,其中文教卫生商务及其他服务、交通运输仓储及信息服务、食品制造及烟草加工业3个部门对城乡居民消费碳排放的贡献最大;(4)提高各部门能源利用效率、降低部门单位产出的碳排放、引导居民向低碳产品消费的转变是居民消费碳减排的有效措施。研究结果可为上海市居民生存碳排放的评估提供数据支持,为政府部门制定碳减排措施、引导居民低碳消费提供理论指导。     

长江经济带旅游业碳排放效率的综合测度与时空分异

以长江经济带为研究对象，运用DEA-SBM模型和Malmquist-Luenberger指数法，对2001～2016年长江经济带旅游业碳排放效率进行综合测度，从静态和动态的视角考察其旅游业碳排放效率的时空分异特征，并进一步探讨了效率变化的影响因素。结果显示:（1）2001~2016年间长江经济带旅游业碳排放效率的平均值为0.672，距离最佳生产前沿面还存在32.8%的提升空间。研究期内其旅游业碳排放效率ML指数均值为1.092，年均增长9.2%。不同时期的效率变化值表现出较大的波动性；（2）长江经济带旅游业碳排放效率的时空分异特征明显，上游地区呈现出低效率、低增长的特征，中游地区表现为中效率、高增长的特点，下游地区则呈现出高效率、中增长的特征；（3）长江经济带旅游业碳排放效率的增长主要源于技术水平的进步，技术效率对旅游业碳排放效率的贡献相对较小。不同区域旅游业碳排放效率变化的影响因素差异较大。     

中国碳排放的因素分解模型及实证分析:1995-2004

能源消费是碳排放的主要来源。随着中国经济的快速发展,能源消费的急剧增长以及以煤为主的能源结构在短期内很难改变,因此,碳排放不可避免地会出现一定幅度的增加。本文基于碳排放量的基本等式,采用对数平均权重Divisia分解法（Logarithmic mean weight Divisia method,LMD）,建立中国人均碳排放的因素分解模型,定量分析了1995-2004年间,能源结构、能源效率和经济发展等因素的变化对中国人均碳排放的影响,结果显示经济发展对拉动中国人均碳排放的贡献率呈指数增长,而能源效率和能源结构对抑制中国人均碳排放的贡献率都呈倒“U”。这说明能源效率对抑制中国碳排放的作用在减弱,以煤为主的能源结构未发生根本性变化,能源效率和能源结构的抑制作用难以抵销由经济发展拉动的中国碳排放量增长。     

中国西北寒旱区农牧民生活碳排放评估

围绕碳排放权开展的气候谈判愈来愈关注贫困人口与弱势群体的生存权与发展权,一方面由于受制于其薄弱的社会经济水平,贫困人口与弱势群体在气候变化实践中表现出更高的脆弱性,另一方面则因气候变化减缓与适应行动而造成的贫困人口生活成本的增加以及生活水平的下降。然而,对这些地区和人口的排放权判断主要基于国家层面和地区层面宏观数据的分析,其结果掩盖了国家和地区内部不同社会经济水平下的人口排放差异,不能准确揭示贫困人口和脆弱群体的低碳排放事实。本文基于国际碳排放评估对人口生活排放的需求,结合IPCC参考方法,利用投入产出分析模型构建了人口生活碳排放评价指标体系,并用于对甘肃、青海和宁夏干旱-高寒地区农牧民生活碳排放的样本调查和分析。评估表明,中国西北干旱—高寒区人口生活碳排放仅为1.85tCO2/人,其中用于满足基本生活需要的碳排放量达到87.25%。研究发现,生活在更冷(海拔更高)区域内的人口生活排放量更高;随着家庭收入的增长,人口生活排放量也随之上升;家庭成员数量越多,家庭的人均碳排放量就会越低。     

中国城市化进程中的城市道路交通碳排放研究

探讨了中国城市化、经济发展、技术进步等与城市道路交通碳排放之间的长期均衡关系与动态作用机制,并对中国城市道路交通碳排放进行了预测和情景分析。结果表明:①城市化率、交通能源强度、城市居民消费水平和人均GDP对城市道路交通碳排放的长期均衡弹性分别为0.93、0.73、0.68、0.44;②城市道路交通碳排放的最大贡献者在中短期内是交通能源强度,长期内是城市化率;③人均GDP增长率的提高,短期内会促使城市道路交通碳排放增长率提高,而长期又有助于使之降低;④中国城市道路交通碳排放持续增长的趋势在相当长时期内不可避免;⑤不同的发展理念和政策与技术的组合,可以使城市道路交通碳排放发生重大变化。基于研究,提出了中国城市道路交通碳减排的政策取向。     

中国城市CO_2排放数据集研究——基于中国高空间分辨率网格数据

城市CO_2排放数据的可获取性和质量直接影响了城市碳排放的科学研究、低碳战略制定及公众对于城市低碳发展的监督和参与。数据缺乏和多源数据的不确定性大是中国城市CO_2排放核算和低碳城市规划面临的重要问题和挑战,而这些问题同时也导致中国低碳城市研究水平参差不齐。本研究使用自下而上建立的中国高空间分辨率网格数据(空间分辨率为1km),采用统一数据源和规范化、标准化数据处理方法,建立中国城市CO_2排放数据集,供研究者和决策者参考。城市CO_2排放计算借鉴国际上较为成熟和应用广泛的核算方法,包括范围1和范围2排放。以北京、上海、天津、重庆和广州5个典型城市的能源统计数据自上而下计算其CO_2排放作为参考水平,检验数据集的数值质量,结果显示5个城市的数据差异均不超过10%。中国城市CO_2排放整体呈现北方大于南方,东部高于中部和西部的空间格局。CO_2排放量较高的城市大多处于华北、东北以及华东沿海地区,西部地区城市CO_2排放量则较低。城市CO_2排放8个部门(工业能源、工业过程、农业、服务业、城镇生活、农村生活、交通、范围2排放)之间的相关性中,城镇生活和交通排放的相关性最高,并且呈现显著性(p0.001),工业过程排放和服务业排放的相关性最弱且没有显著性。基于中国高空间分辨率网格数据的中国城市CO_2排放数据集的不断完善和发展,为中国城市CO_2排放研究奠定了重要的数据基础,为城市CO_2排放横向比较和对标工作提供了重要依据。     

Impact of demographic dynamics on CO_2 emissions in Sichuan,China

Global climate change is one of the major environmental issues faced by humans.Existing evidence indicates that the anthropogenic push for a rise in the atmospheric concentration of greenhouse gases(GHGs)(particularly CO_2)has been a primary cause for global warming.Aside from economic and teclinological factors,demographic dynamics(including human consumption in a broad demographic sense)has been a major driver for CO_2 emissions.In this paper,we performed both nonlinear regression analysis(based on the STIRPAT model)and gray correlation degree analysis(based on gray system theory)on the impact of demographic dynamics on CO_2 emissions.Our results reveal that CO_2 emissions are positively correlated with population size and GDP per capita and negatively correlated with energy intensity.We also show that gray correlation degree with CO_2 emissions for five variables(i.e.,household consumption,urbanization rate,household size,population aging rate,population size)varies substantially:household consumptionurbanization ratehousehold sizepopulation aging ratepopulation size,with household consumption being the highest,and population size the lowest.To mitigate the impact of demographic dynamics on CO_2 emissions,it is of vital significance to nurture people's awareness of sustainable consumption and to adhere to current population control policies.     

CO2 emissions in German, Swedish and Colombian manufacturing industries

This study evaluates and compares the trends in CO₂ emissions for the manufacturing industries of three countries: two developed countries (Germany and Sweden) that have applied several measures to promote a shift towards a low-carbon economy and one developing country (Colombia) that has shown substantial improvements in the reduction of CO₂ emissions. This analysis is conducted using panel data cointegration techniques to infer causality between CO₂ emissions, production factors and energy sources. The results indicate a trend of producing more output with less pollution. The trends for these countries’ CO₂ emissions depend on investment levels, energy sources and economic factors. Furthermore, the trends in CO₂ emissions indicate that there are emission level differences between the two developed countries and the developing country. Moreover, the study confirms that it is possible to achieve economic growth and sustainable development while reducing greenhouse gas emissions, as Germany and Sweden demonstrate. In the case of Colombia, it is important to encourage a reduction in CO₂ emissions through policies that combine technical and economic instruments and incentivise the application of new technologies that promote clean and environmentally friendly processes.     

Primary energy-related carbon dioxide emissions in China

Climate change is one of the focuses to mitigate greenhouse effect and reduce carbon dioxide emissions.First,the paper summarizes on the carbon dioxide emission factors and methods suitable to the situation in China.Second,it analyzes the primary energy-related carbon dioxide emissions during the period between 1995 and 2005 from different fossil fuels and different zones.The trend of primary energy-related carbon dioxide emissions from 1995 to 2005 is"first decreasing and later increasing."Seven regions-Liaoning,Shanxi,Hebei,Shandong,Henan,and Jiangsu-and most of the provinces(cities or regions)were found to have similar trends regarding total carbon dioxide emissions in China.The annual carbon dioxide emissions and the growth ratio of these seven regions are much higher compared to those of the other 24 provinces(cities or regions).Finally,this paper puts forward some suggestions to reduce carbon dioxide.     

江苏省交通运输业能源消费碳排放及脱钩效应

通过自上而下的计算方法，测算了江苏省1995～2010年交通运输行业能源消费碳排放量和人均碳排放量，并结合行业自身发展特点，扩展了Kaya恒等式，运用LMDI分解法进行分解分析。同时，在上述基础上采用Tapio模型对江苏省交通碳排放与交通运输业经济发展的脱钩关系进行了探讨。研究发现:(1)江苏省交通碳排放量与人均碳排量均呈明显上升趋势，其中石油制品类能源消费碳排放表现突出;(2)正向驱动交通碳排放量增加的因素为经济产出、人口规模和产业结构，负向驱动因素为交通能源结构和交通能源强度。其中，拉动碳排放量增长的决定性因素是经济产出规模的扩大，而促使碳排放减少的主要因素是交通能源强度的降低，相对于正向驱动因素，负向驱动因素抑制交通碳排放增加作用有限;(3)交通碳排放量变化与运输业经济发展之间的脱钩状态以扩张负连接、扩张负脱钩和弱脱钩为主，脱钩关系总体呈先恶化后改善的趋势，但要完全实现两者的绝对脱钩，依然任重道远     

The significance of various factors for GHG emissions of buildings

The objective of the research was to create improved understanding of the significance of diverse factors for the total greenhouse gas (GHG) emissions of buildings. The specific focus of the study was on the assessment of the significance of building materials and embodied carbon. The scope of the study covers multi-storey residential buildings in Finland. This research was based on a literature survey and supported by a parametric case study. The parametric study assessed the building-material-related GHG emissions relative to total GHG emissions and the possible range of variation. The research assesses the minimum and maximum GHG emissions for production of buildings with similar spaces, to reveal the likely range of variation for the emissions. The calculations for the ‘minimum’ and ‘maximum’ scenarios assume a similar purpose of use, occupancy and spaces in the building, while the production methods, materials, site conditions and location are varied. The research also assesses the relative importance of various building components and other calculation parameters in terms of GHGs. Total material-related GHG emissions were compared with the GHG emissions caused by the operation of the building, at three distinct levels of energy performance. In addition, the material- and operation-related GHG emissions were compared with the location-related GHG emissions arising from people's mobility.     

Trends in food production and nitrous oxide emissions from the agriculture sector in India: environmental implications

We studied trends in food production and nitrous oxide emissions from India's agricultural sector between 1961 and 2000. Data from Food and Agricultural Statistics (FAO) have been gathered covering production, consumption, fertilizer use and livestock details. IPCC 1996 revised guidelines were followed in studying the variations in N₂O-N emissions. Results suggest that total N₂O-N emissions (direct, animal waste and indirect sources) increased ~6.1 times from ~0.048 to ~0.294 Tg N₂O-N, over 40 years. Source-wise breakdown of emissions from 1961–2000 indicated that during 1961 most of the N₂O-N inputs were from crop residues (61%) and biological nitrogen fixation (25%), while during 2000 the main sources were synthetic fertilizer (~48%) and crop residues (19%). Direct emissions increased from ~0.031 to ~0.183 Tg. It is estimated that ~3.1% of global N₂O-N emissions comes from India. Trends in food production, primarily cereals (rice, wheat and coarse grains) and pulses, and fertilizer consumption from 1961–2000 suggest that food production (cereals and pulses) increased only 3.7 times, while nitrogenous fertilizer consumption increased ~43 times over this period, leading to extensive release of nitrogen to the atmosphere. From this study, we infer that the challenge for Indian agriculture lies not only in increasing production but also in achieving production stability while minimizing the impact to the environment, through various management and mitigation options.     

碳排放权交易试点是否促进了对外直接投资?

环境规制与跨国投资之间的关系一直是学术界关注的焦点。作为重要的环境规制手段,碳排放权交易试点的推进标志着我国环境规制强度的增强。对外直接投资(OFDI)作为最典型的跨国经济活动之一,是中国"走出去"战略的重要组成部分。近年来,中国对外直接投资存量与净额都呈现稳定的上升趋势,与此同时,环境规制强度也在不断提升。中国对外直接投资是否受到国内环境规制加强的影响值得探讨,而2013年正式启动碳排放权交易试点为解决此问题提供了一个准自然实验场景。基于此,文章使用中国30个省级行政单位2010—2019年的面板数据,以北京、上海、广东、天津、湖北、重庆和福建开展的碳排放权交易试点作为准自然实验,运用双重差分法(DID)研究碳排放权交易试点的开展是否提升了对外直接投资水平。研究结论表明,碳排放权交易试点能够显著提升我国对外直接投资水平。且该结论在平行趋势检验、合成控制法(SCM)、安慰剂检验等检验后依旧稳健。此外,潜在机制的研究发现碳排放权交易试点满足"污染避难所假说"和"波特假说",进而促进了对外直接投资水平的提升。通过净效应的初步讨论,文章发现"污染避难所假说"仍旧在目前占据主导地位。研究结论意味着:(1)未来要继续推进全国统一的碳排放权交易市场建设;(2)持续探索激发碳排放权交易试点对创新产生的激励效应;(3)完善投资便利化的制度与措施,搭建国际技术交易或信息平台等。一方面促进我国生态环境的改善,另一方面促进对外投资水平的增质提量。     

Global Research Trends Related to CO2 Emissions and Their Enlightenment to China

Given the growing awareness of the likely catastrophic impacts of climate change and close association of climate change with global emissions of greenhouse gases (of which carbon dioxide is more prominent) , considerable research efforts have been devoted to the analysis of carbon dioxide (CO2) emissions and its relationship to sustainable development. Now GHG reduction programs have been coming into effect in many developed countries that have more responsibility for historical CO2 emissions, and the studies have become mature. First, the GHG emissions accounting system is more all-inclusive and the methods are more rational with the effort of IPCC from 1995 and all other researchers related. Second, the responsibility allocation is more rational and fair. Along with the clarity of "carbon transfer" and "carbon leakage", the perspective and methodology for allocating regional CO2 emissions responsibility is turning from production base to consumption base. Third, the decomposition method has become more mature and more complex. For example, the decomposition formulas are including KAYA expression and input-output expression and the decomposition techniques are developed from index analysis to simple average divisia and then adaptive-weighting divisia. Fourth, projection models have become more integrated and long-term. The top-down model and bottom-up model are both inter-embedded and synergetic. Trends above give some advice for the research on CO2 in China, such as emissions factors database construction, deeper-going research on emissions responsibility and structure analysis, promotion of modeling technology and technology-environment database.