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。     

International inequality in CO2 emissions: A new factorial decomposition based on Kaya factors

In this paper, we analyze the determinants of inequality in the global distribution of CO₂ emissions across the regions considered by the International Energy Agency during the period 1990–2010. The inequality analysis is carried out using a factorial decomposition of the second Theil index of inequality. Specifically, based on Kaya factors, CO₂ emissions by active population are decomposed into four factors: carbon intensity of electricity production, electricity intensity of GDP, economic growth in terms of labour productivity and employment rate. The results show that global inequality in CO₂ emissions by active population declined by 22 percent between 1990 and 2010, where the economic growth in terms of labour productivity is the main item responsible for the whole inequality value. Then, a second decomposition by multiplying factors for analyzing the within- and the between-group inequality components is described. In relation to the study of inequality by population groups, it was found that the within-group inequality component had been the main contributor to the whole inequality during all the period. Finally, some economic policy implications are discussed.     

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.     

Sectoral Trends and Driving Forces of Global Energy Use and Greenhouse Gas Emissions

Disaggregation of sectoral energy use and greenhouse gas emissions trends reveals striking differences between sectors and regions of the world. Understanding key driving forces in the energy end-use sectors provides insights for development of projections of future greenhouse gas emissions. This paper examines global and regional historical trends in energy use and carbon emissions in the industrial, buildings, transport, and agriculture sectors. Activity and economic drivers as well as trends in energy and carbon intensity are evaluated. We show that macro-economic indicators, such as GDP, are insufficient for comprehending trends and driving forces at the sectoral level. These indicators need to be supplemented with sector-specific information for a more complete understanding of future energy use and greenhouse gas emissions.     

Structural Change of the Manufacturing Sector in Korea: Measurement of Real Energy Intensity and CO2 Emissions

In terms of energy use, it is wellknown that energy intensity in the manufacturingsector is higher than any other sector. In Korea, theenergy intensity of the manufacturing sector hasdeteriorated since the late 1980s. This phenomenonis quite unique compared with the trend of energyintensity in other countries. In this study, weclosely examine the structural composition of Korea'smanufacturing sector from 1981 to 1996, its energyintensity, and its implications for carbon dioxide(CO₂) emissions by introducing the measurement ofreal energy intensity.The conventional index of energy intensity is notappropriate for aggregate industries. Since theaggregation of industries in the manufacturing sectorincludes structural change, it would be better toseparate the effect of structural change. Hence, inthis study, we apply a decomposition methodology forenergy intensity based on the `Divisia Index'. Ateach industry level, energy intensity is a mixedmeasurement of pure energy efficiency improvement andfuel substitution. We also calculate real energyintensity at each industry level. Based on ouranalysis, we derive carbon dioxide (CO₂) intensity and analyze the factors that affect CO₂ emission in this sector.During 1988–1993, the energy intensity of themanufacturing sector in Korea deteriorated. Industrial structural change,the real energy intensity in this sector became evenworse during this period. The primary reason for thisphenomenon was that the share of energy intensiveindustries, such as steel, cement, and petro-chemicalindustries increased. Second, during the sameperiod, liquefied natural gas (LNG) rapidlypenetrated this sector, so that theCO₂ intensity improved. We find thatharmonization of economic development strategies andenvironmental consideration is crucial for sustainabledevelopment. Based on our study, we derived somepolicy implications. Integration of industrialpolicies and energy efficiency improving programs isquite important, as well as the acceleration of fuelsubstitution to less carbon (C) intensive ones. Integration of local and global environmental policiesplays an important role for mitigatingCO₂ emissions.     

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.     

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.      

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STIRPAT模型的中国旅游业碳排放影响因素分析

采用"自下而上"的CO_2排放计算方法,对1995—2014年中国各区域旅游业CO_2排放量进行测算,从动态视角分析各区域旅游业CO_2排放总量及旅游接待人次、人均旅游收入、旅游业CO_2排放强度和旅游交通CO_2排放占比等影响因素的变化趋势特征,并基于STIRPAT模型对旅游业CO_2排放的主要影响因素进行定量分析.结果显示:各区域旅游业CO_2排放总量均呈逐年上升的趋势,且不同区域各影响因素的作用存在显著差异;其中,人均旅游收入对中国旅游业碳减排压力的弹性变化区间最小,仅从0.156变化到0.287,旅游交通CO_2排放占比的弹性变化区间最大,其CO_2排放占比每提高1%,东部地区旅游业CO_2排放总量将提高0.239%,而中部地区仅提高0.013%;旅游业CO_2排放强度是抑制碳排放的关键因素;研究期内,分析结果不支持倒"U"型环境Kuznets曲线的观点.最后,根据上述结论提出差异化的区域碳减排调控对策.     

Economic structural change,renewable energy development,and carbon dioxide emissions in China

As the world’s largest emitter, China’s reduction of carbon dioxide (CO2) emissions is crucial for the achievement of global temperature rise goals. In this paper, we employed input-output structural decomposition analysis and index decomposition analysis to assess the factors driving changes in China’s CO2 emissions from 2000 to 2018, with particular attention to the role of renewable energy development. Our results indicate that the slowdown of economic growth and rapid structural change, rather than the shifting fuel mix, were the major forces driving China’s recent slowdown of CO2 emissions ever since 2011. Despite the great importance attached to renewable energy development, non-hydro renewable has played negligible role in reducing China’s CO2 emissions. This suggests that China cannot simply rely on the large-scale development of renewable energies to achieve its Paris 2015 target and must make further drastic cuts that will help keep global temperature rise well below 2 °C above pre-industrial level. Major breakthroughs in scalable low carbon energy sources and technologies will be required, especially in the developing world.

     

China’s carbon emissions from urban and rural households during 1992-2007

In China, Rapid economic growth has stimulated fast urban expansion and rural household income and consumption expenditure. In current paper, an input-output method is used to determine the impact of China’s increased urban and rural household consumption on carbon emissions. The results shows that the direct and indirect CO₂ emission from household consumption accounted for more than 40% of total carbon emissions from primary energy utilization in China in 1992-2007. The population increase, expansion of urbanization and the increase of household consumption per capita all contribute to an increase of indirect carbon emissions, while carbon intensity decline mitigates the growth of carbon emissions. Therefore, at the domestic level, household consumption is of great significance for CO₂ emission, which could be mitigated through changing the composition of goods and services consumed by households, and switching to consumption pattern of less carbon-intensive products. The government must consider the substantial contribution of household consumption to carbon emissions when China is encouraging consumption in order to address the current global financial crisis.     

广东省能源消费碳排放分析及碳排放强度影响因素研究

根据省级能源统计和温室气体核算规则,计算分析了2005~2012年广东省能源消费碳排放和碳排放强度变化,并应用对数平均迪氏指数法对计算期的碳排放强度变化进行因素分解,定量分析了各产业(部门)能耗强度、产业结构、能源消费结构和能源碳排放系数对广东省碳排放强度变动的影响.结果表明:2005~2012年,广东省能源消费CO2排放年均增长6.28%,单位GDP碳排放累计下降27%,各产业(部门)能耗强度下降是推动碳排放强度下降的主要原因;净外购电力的碳排放系数下降及用作原材料石油消费比重上升也有利于单位GDP碳排放下降;产业结构和能源消费结构总体上朝着不利于碳排放强度下降的趋势发展;生活能源消费年均增速低于GDP年均增速,有利于地区碳排放强度下降.     

CO<Subscript>2</Subscript> emission and economic growth of Iran

This research investigates the relationship between CO₂ emission and economic growth of Iran over 14 years from 1994 to 2007 using a national panel data set. The statistical and emission intensity methodologies are used for analyzing the data series. The study finds evidence supporting parameters which conclude the stability of significant correlation between CO₂ emission and economic development over time during the years under investigation in Iran. This relationship is investigated and discussed for the energy sectors of the country as well. The results confirm that in all sectors except of agricultural, there is a positive strong correlation between CO₂ emission and economic growth throughout the study period. In most sectors, CO₂ emission intensity (the emission per unit of GDP) doesn’t show increasing trends while the absolute emission is rapidly increasing by the economic growth.     

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.      

The evolution of CO<Subscript>2</Subscript> emissions in international trade for major economies: a perspective from the global supply chain

Employing global multi-regional input–output models, this paper revisits the carbon dioxide (CO₂) emission trade (including exports and imports) and assesses their positions in the national emissions of 14 major countries with large national emissions or large emission trades during 1995–2009. It especially explores the evolution of the emission trades of these countries from both continuous time series and comparative perspectives, in order to provide an explanation for CO₂ emission spillovers across countries. The main findings obtained were as follows: (1) China was the largest CO₂ exporter to other countries, accounting for over 20 % of global exports since 2005; the CO₂ exports of the United States of America (USA), Germany, and Japan varied slightly over this time period, but overall, their proportions had decreased. (2) The CO₂ imports of the USA were the largest, occupying around 20 % of the global CO₂ imports; meanwhile, China’s CO₂ imports increased rapidly and ranked the second largest. (3) For Chinese Taiwan, its proportion of CO₂ exports in production-based emissions ranked the highest while that of the USA ranked the lowest; highly CO₂ import-dependent countries with an over 40 % proportion of CO₂ imports in its consumption-based emissions included France, Germany, Italy, and Spain, while China, India, and Russia remained the lowest, distinguished from their physical energy imports. These results suggested that the global policy makers should take the CO₂ emissions in trade into consideration when carefully accounting for national emissions inventories.     

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.     

广东省交通碳排放核算及影响因素分析

交通领域是二氧化碳排放的重要领域,为研究广东省的交通碳排放及影响因素,利用IPCC（联合国政府间气候变化专门委员会）在温室气体清单指南中提供的方法估算了广东交通碳排放量,并应用LMDI分解法（对数平均指数法）对广东交通碳排放进行因素分解分析.结果表明:① 2001-2010年广东交通碳排放量从1 950.98×104 t增至6 068.41×104 t,其中交通运输业碳排放是广东交通碳排放的主体,私人交通碳排放已成为广东交通碳排放不可忽视的组成部分.② 交通运输业中的公路碳排放量占比最大,占56%~64%;铁路的碳排放量占比最小,占0.6%~1.6%;水运具有较大的节能优势;民航单位周转量碳排放量最高.③ 交通运输业发展水平、运输结构、私人汽车数量规模对广东交通碳排放增加的贡献率分别为68.79%、36.14%、18.66%,是拉动广东交通碳排放增长的主要因素;运输强度与能源强度的贡献率分别为-18.1%、-6.46%,是抑制交通碳排放增长的因素.广东可以通过采取优化交通运输结构、使用替代清洁能源等措施减少交通碳排放.      

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%.     

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.