安徽省能源消费碳消费排放影响因素分解分析

为探寻安徽省碳排放总量变动的影响因素以实现节能减排的目标,基于安徽省1995～2009年能源碳排放量,利用Kaya恒等式和Laspeyres指数分解方法,分析了碳排放强度、能源强度、人均GDP和常住人口规模对碳排放变动的贡献。结果表明,人均产出效应是促进碳排放增加的主要拉动因素,累积贡献率为149.03%;能源强度效应是唯一抑制碳排放增加的因素,累积贡献率为-100.12%;其他两因素对碳排放增加的促进作用不明显,并从改善能源结构、提高能源效率、重点关注高耗能高排放行业三方面提出了政策建议。     

Investigating the driving factors of regional CO2 emissions in China using the IDA-PDA-MMI method

In this paper, we systematically summarized existing research on the driving factors of CO₂ emissions and found that changes in technology gap may be one of the key driving factors of CO₂ emissions. Technology efficiency, technology progress, and technology gap were decomposed by using the Meta-frontier Malmquist index (MMI), which was then combined it with the Index Decomposition Analysis (IDA) and the Production-theoretical Decomposition Analysis (PDA). Our framework was applied to Chinese provincial data from 2000 to 2016. We identified nine factors to explain changes of regional CO₂ emissions. Results demonstrate that economic scale, energy technology efficiency, and output technology efficiency increased CO₂ emissions in Eastern, Central, and Western regions of China, with the economic scale being the largest contributor. Energy structure, energy intensity, energy technology progress, and output technology progress decreased regional CO₂ emissions, with the energy technology progress playing the strongest role. Energy technology gap and output technology gap led to an increase in CO₂ emissions in Central China and, to a lesser extent, in Western China. The effects of each driving factor on CO₂ emissions varied across provinces. Finally, policy implications are suggested to reduce CO₂ emissions in China.     

Transport sector CO2 emissions growth in Asia: Underlying factors and policy options

This study analyze the potential factors influencing the growth of transport sector carbon dioxide (CO₂) emissions in selected Asian countries during the 1980–2005 period by decomposing annual emissions growth into components representing changes in fuel mix, modal shift, per capita gross domestic product (GDP) and population, as well as changes in emission coefficients and transportation energy intensity. We find that changes in per capita GDP, population growth and transportation energy intensity are the main factors driving transport sector CO₂ emission growth in the countries considered. While growth in per capita income and population are responsible for the increasing trend of transport sector CO₂ emissions in China, India, Indonesia, Republic of Korea, Malaysia, Pakistan, Sri Lanka and Thailand; the decline of transportation energy intensity is driving CO₂ emissions down in Mongolia. Per capita GDP, population and transportation energy intensity effects are all found responsible for transport sector CO₂ emissions growth in Bangladesh, the Philippines and Vietnam. The study also reviews existing government policies to limit CO₂ emissions growth, such as fiscal instruments, fuel economy standards and policies to encourage switching to less emission intensive fuels and transportation modes.     

Carbon emissions reduction in China's food industry

In this paper, we evaluate the changes in carbon dioxide emissions from energy consumption in China's food industry from 1986 to 2010 based on the Logarithmic Mean Divisia Index (LMDI) method. The results show that energy intensity (EI) and industrial activity (IA) are the main determinants of the changes in carbon dioxide. Energy intensity (EI) contributes to decrease in emissions within 25 years while industrial activity (IA) acts in a positive way to increase the emissions level. Industry scale (IS) mostly contributes to increase in emissions except for the time interval 1996–2000. However, for both carbon intensity (CI) and energy structure (ES), they have a volatile but not significant influence on emissions in the different time intervals. To further understand the effects, we analyze the cumulative emission during the whole period 1986–2010. The results further testify that energy intensity and industrial activity are the most important factors affecting reduction and growth of carbon emissions. The results indicate that efforts to reduce emission in China's food industry should focus on the enhancement of energy efficiency, the optimization of industrial scale and the restructuring energy use. Finally, recommendations are provided for the reduction of carbon dioxide in China's food industry.     

中国能源消费碳排放变化的影响因素分析——基于投入产出模型

从产业关联的角度出发,采用结构分解分析法(SDA)给出了中国能源消费碳排放的投入产出分析模型.基于投入产出模型,利用1997年、2002年、2005年、2007年的投入产出数据和能源消费数据,依据政府间气候变化专门委员会(IPCC)给出的二氧化碳排放量的计算公式计算了各产业部门的碳排放量,并进而计算了各部门的直接碳排放强度,然后依据结构分解方法对中国能源消费碳排放的影响因素进行了详细的分解分析.研究结果发现:碳排放强度在1997 ～ 2002年和2005～2007年均有大幅度的降低,而在2002～2005年却有一个小幅上升.反映能源使用效率的部门直接碳排放强度系数和反映生产技术的完全需求系数是我国碳排放强度变化的两个最主要的影响因素.建议各行业各部门要用高新技术和先进适用技术改造和提升传统产业,加大投资结构调整力度,坚决淘汰落后产能,切实抑制低水平重复建设和高耗能产业的扩张,逐步加大对环保产业、新能源产业和高新技术产业的投资倾斜.     

国外石化公司二氧化碳减排对策分析

我国2005年二氧化碳排放总量为51×10^8t．居世界第二位。炼化行业的二氧化碳排放比重也在不断增加．其中燃烧排放占绝大部分,生产过程排放其次．国外行化公司为应对二氧化碳减排,采取了改进燃料系统、提高能量利用效率、大力开发可再生能源、利用CCS技术提高油气田采收率、灵活应用二氧化碳排放贸易体系和CDM机制等对策。建议我国石化企业应重点关注常减压、催化重整、催化裂化、制氧、乙烯、合成氨等二氧化碳高排放装置的节能减排,开展二氧化碳综合利用技术的研究与应用,开发可再生能源,运用各种减排政策和机制参与减排活动。     

二氧化碳排放量化方法探讨

目前,通用的量化二氧化碳排放方法是IPCC排放因子法,但IPCC的排放因子是否适用于我国的排放源有待商榷。利用现场监测的烟道内的温度、压力、二氧化碳浓度、一氧化碳浓度、烟气流速、水蒸气体积百分比等参数,采用质量比法、时间比法、负荷法以及IPCC排放因子法等多种方法,对某企业不同时间段内的二氧化碳排放情况进行量化。结果表明,如果国内企业采用国际通用的量化二氧化碳排放方法,则得到的二氧化碳排放量偏大。为了能更准确地获得燃烧排放源的二氧化碳排放情况,需要采用现场监测的方法。质量比法与IPCC排放因子法的量化结果,其准确性严重依赖于燃料计量数据的准确性,不推荐采用。时间比法的量化结果虽然优于质量比法,但不适合用于量化较长时间段内的二氧化碳排放量。负荷法由于考虑了负荷的影响,其量化结果更为可靠。建议企业通过监测手段,采用负荷法量化燃烧排放源的二氧化碳排放量。为了尽可能减小由客观因素带来的排放量的不确定性,建议选择不同时间段、不同工况多次监测量化燃烧排放源某年度的二氧化碳排放量。     

An analysis of Chinese provincial carbon dioxide emission efficiencies based on energy consumption structure

China plans to reduce carbon dioxide emissions from 2005 levels by 40–45% by 2020 and by 60–65% by 2030. This research project addresses this challenge by analyzing Chinese provincial carbon dioxide emission efficiencies and the energy consumption structure. The study applies the Slacks Based Measure (SBM) model to analyze the data from 30 regions in China from 2000 to 2011. The situation of provincial carbon dioxide emission efficiency, the characteristics of the energy consumption structure in each province, and the differences among these provinces are quantitatively analyzed. Based on the K-means cluster analysis, this research suggests that China be divided into five groups in the energy consumption structure: the inefficient and less reasonable group, the inefficient and more reasonable group, the efficient and less reasonable group, the efficient and more reasonable group, and the efficient and most reasonable group. The study offers recommendations for the government to develop policies to effectively and efficiently reduce carbon dioxide emission levels for each group. It also has profound implications for government administration in developing countries to guide the energy consumption and to control environmental pollution for the healthy development of the economy.     

Analysis of energy efficiency and carbon dioxide reduction in the Chinese pulp and paper industry

Pulp and paper production, an energy-intensive process, is among the main light industries contributing to energy saving and pollution emission reduction in China. The improvement of energy efficiency is essential for energy consumption and sustainable development. This study analyzes the negative factors in the pulp and paper sector by calculating energy efficiency from the lengthways time and investigating the gap between China and foreign countries through a horizontal comparison. Accordingly, energy efficiency has increased in the Chinese pulp and paper industry with years of efforts, but its transformation remains unclear. Furthermore, the energy-saving potential, energy cost saving, and carbon dioxide emission reduction in the pulp and paper industry are evaluated according to the Twelfth Five-year Plan (2011–2015). The results show that the pulp and paper industry has further capabilities for energy-saving and carbon dioxide emission reduction by improving energy efficiency in China, resulting in great economic benefit. In brief, new technology and energy structure adjustment are long-term strategies for energy conversation, with changes in the scale of mills expected to provide huge opportunities to improve energy efficiency in China within a short period.     

我国二氧化碳排放的特点、趋势及政策取向

改革开放以来。我国二氧化碳排放总量从1978年的148329×10^4t增加到2008年的689654×10^4t．年均增长5．3％。与此同时,二氧化碳排放强度总体上呈较快下降趋势,但1999年以后下降速度放缓。我国二氧化碳排放强度明显高于国际水平。分析其原因,从需求结构看是经济增长过度依赖出口：从产业结构看是由于过度依赖工业,尤其是重化工业：而以煤为主的能源资源结构和能源生产结构,直接导致我国单位能源使用排放的二氧化碳高于其他国家。我国2015年二氧化碳排放量预测值在82．28×10^8-90．508×10^8t之间,减排形势不容乐观。由于我国还处在工业化、城镇化加快发展阶段,在以煤为主的特定资源禀赋条件下,减缓二氧化碳排放的主要路径是减少能源消费,即节能。节能的主要着力点在于充分发挥政府和市场的作用,加快提高能源技术效率,包括深化能源产品定价机制改革;加强政府的社会性管制,使环境社会成本充分内部化;建立绿色税收体系,支持低碳经济发展;培育碳排放交易市场。     

Energy use and CO2 emissions in Mexico's iron and steel industry

Energy use and carbon dioxide emissions for the Mexican iron and steel industry are analyzed from 1970 to 1996. To assess the trends in energy use and carbon dioxide emissions, we used a decomposition analysis based on physical indicators to decompose the intra-sectoral structural changes and efficiency improvements. We used a structure/efficiency analysis for international comparisons, considering industrial structure and the best available technology. This study shows that steel production growth drove up primary energy use by 211% between 1970 and 1996, while structural changes (production and process mix) decreased primary energy use by 12% and energy efficiency changes drove down energy use by 51%. In addition, carbon dioxide emissions would have increased by 9% if the primary fuel mix had remained constant at 1970 levels.     

广东省主体功能区碳排放特征及驱动因素研究

基于不同类型主体功能区的发展定位与碳排放驱动要素分解,提出有针对性的区域差异化低碳发展路径是推进主体功能区可持续发展的重要内容。基于调研资料,分析了广东省各主体功能区自2010年以来的碳排放演变特征,从人口效应、经济效应、能源强度效应、产业结构效应以及碳排放因子效应五个因素对造成不同主体功能区碳排放差异的原因进行了分析。要素分解发现,经济规模和人口数量增长对优化开发区碳排放量增长的贡献率最大;产业结构的优化从2012年开始成为使优化开发区碳排放量降低的影响因素,对重点开发区和生态发展区碳排放量降低的作用仍不明显;产业能源强度变动均使三类功能区碳排放量降低,但是贡献率呈现明显差异。建议：（1）加快发展优化开发区服务业,积极推动实施居民碳排放管理;（2）重点开发区应以提高能效和推进低碳技术为主实施低碳转型;（3）生态发展区要大力推广清洁能源,促使农业低碳化发展。     

低碳发展时代的世界与中国能源格局

哥本哈根会议认定了"2℃"和"在2050年前全球排放量减到1990年的一半",到2050年,碳减排要求世界人均能耗不高于2.5t标煤/a。能源碳强度ω是一个反映碳排放与能源结构关系的新指标,利用它与一次能源消费中生成并排放二氧化碳的各种形式能源所占比率γ的关联式ω=2.4γ进行推算:按照450情景方案,二氧化碳排放峰值307×108t出现在2020年,而能耗峰值在2030年左右;按照丹麦方案,二氧化碳排放峰值320×108t出现在2025年,能耗峰值也大约在2030年,将达到273×108t标煤/a,人均3.3t标煤/a。碳排放峰值年越推迟,达到2050年远期目标的难度越大。按照丹麦方案,2030~2050年的20年间,需平均每年减排10×108t二氧化碳,同时与450情景方案相比,大气中二氧化碳总量将增加400×108t以上。根据中国政府宣布的2010~2020年的减排目标推算,2020年能耗为41×108t标煤,二氧化碳排放约74×108t,中国只要能做到能耗强度每5年降低20%,就能够实现此目标。中国应在2020年之前快速发展非化石能源、加速产业转型、大力发展天然气、大幅提高能效,这样就完全能够与世界减排同行。     

Analysis and forecast of the Tianjin industrial carbon dioxide emissions resulted from energy consumption

This paper analyses the carbon dioxide emissions caused by industrial energy consumption of Tianjin from 2005 to 2012. The carbon emissions decomposition illustrated that the scale of production factor played a major role in the growth of Tianjin industrial carbon emissions and the average contribution of carbon emissions is up to 220.8975% in the statistical period; the intensity of energy factor played an important role in slowing down the growth of industrial carbon dioxide emissions. The average contribution of carbon emissions was ?136.1994% in the statistical period. The prediction model based on carbon emissions data from industrial energy consumption from 2003 to 2012 reached a high accuracy, with an average error of 1.78% for stochastic impacts by regression on population, affluence, and technology (STIRPAT) model, 2.41% for the Logistic regression model and an average error of 1.54% for the grey model. This research can contribute to predict the carbon emission and through it some suggestions can be made.     

Evaluating carbon dioxide emissions in international trade of China

China is the world's largest emitter of carbon dioxide (CO₂). As exports account for about one-third of China's GDP, the CO₂ emissions are related to not only China's own consumption but also external demand. Using the input–output analysis (IOA), we analyze the embodied CO₂ emissions of China's import and export. Our results show that about 3357 million tons CO₂ emissions were embodied in the exports and the emissions avoided by imports (EAI) were 2333 million tons in 2005. The average contribution to embodied emission factors by electricity generation was over 35%. And that by cement production was about 20%. It implies that the production-based emissions of China are more than the consumption-based emissions, which is evidence that carbon leakage occurs under the current climate policies and international trade rules. In addition to the call for a new global framework to allocate emission responsibilities, China should make great efforts to improve its energy efficiency, carry out electricity pricing reforms and increase renewable energy. In particular, to use advanced technology in cement production will be helpful to China's CO₂ abatement.     

Potentials for energy efficiency improvement in the US cement industry

This paper reports on an in-depth analysis of the US cement industry, identifying cost-effective energy efficiency measures and potentials. Between 1970 and 1997, primary physical energy intensity for cement production (SIC 324) dropped 30%, from 7.9 GJ/t to 5.6 GJ/t, while specific carbon dioxide emissions due to fuel consumption and clinker calcination dropped 17%, from 0.29 tC/tonne to 0.24 tC/tonne. We examined 30 energy-efficient technologies and measures and estimated energy savings, carbon dioxide savings, investment costs, and operation and maintenance costs for each of the measures. We constructed an energy conservation supply curve for the US cement industry which found a total cost-effective energy saving of 11% of 1994 energy use for cement making and a saving of 5% of total 1994 carbon dioxide emissions. Assuming the increased production of blended cement, the technical potential for energy efficiency improvement would not change considerably. However, the cost-effective potential would increase to 18% of total energy use, and carbon dioxide emissions would be reduced by 16%. This demonstrates that the use of blended cements is a key cost-effective strategy for energy efficiency improvement and carbon dioxide emission reductions in the US cement industry.     

Decomposition of CO2 emissions change from energy consumption in Brazil: Challenges and policy implications

This study evaluates the changes in CO₂ emissions from energy consumption in Brazil for the period 1970–2009. Emissions are decomposed into production and consumption activities allowing computing the full set of energy sources consumed in the country. This study aims to develop a comprehensive and updated picture of the underlying determinants of emissions change from energy consumption in Brazil along the last four decades, including for the first time the recently released data for 2009. Results demonstrate that economic activity and demographic pressure are the leading forces explaining emission increase. On the other hand, carbon intensity reductions and diversification of energy mix towards cleaner sources are the main factors contributing to emission mitigation, which are also the driving factors responsible for the observed decoupling between CO₂ emissions and economic growth after 2004. The cyclical patterns of energy intensity and economy structure are associated to both increments and mitigation on total emission change depending on the interval. The evidences demonstrate that Brazilian efforts to reduce emissions are concentrated on energy mix diversification and carbon intensity control while technology intensive alternatives like energy intensity has not demonstrated relevant progress. Residential sector displays a marginal weight in the total emission change.     

中国中长期碳减排战略目标初探(Ⅰ)——中国分阶段温室气体减排目标的提出及其依据

减少温室气体排放已刻不容缓,一系列研究显示,温升2℃是人类生活不受气候变化干扰的上限,大致550μL/L二氧化碳当量的温室气体浓度或约450～500μL/L的二氧化碳浓度对应2℃的温升。达到稳定浓度时的2005年以后的累积排放量和2005年的排碳数据一起才可以计算出最终的减排量化指标,而拐点年代和逐年排放量是可调控的动态指标。核实本世纪上半叶的累积排放量,并将排放额度分解到各个国家和地区是一项十分艰巨且很迫切的任务。我国的碳减排可分为2005～2020年的前期、2021～2035年的中期和2036～2050年的后期。权威部门曾推算了一系列数据,但与当前掌握的实际数据对比,对2010年的碳排放预测数据均偏低。有学者提出我国2005～2050年间的排碳额度为370Gt,约为全世界的28%,比例基本合理。如果2050年二氧化碳排放总量确定为140×108t,则中国为40×108t,人均2.6t,形势非常严峻。把我国2020年二氧化碳排放量控制在100×108t以内十分必要;我国碳减排中期处于拐点过渡期,我国的拐点将直接影响世界的拐点,应争取拐点出现在2025年,过渡期为2020～2030年;我国2050年与2035年的二氧化碳排放量差值应为45×108t,只要依靠非化石能源替代化石能源、采用CCS技术、最大限度地采用零碳排放甚至负碳排放的替代燃料就能得到控制,但仍然存在许多不确定因素,有待深入研究。     

CO2 emissions embodied in China–US trade: Input–output analysis based on the emergy/dollar ratio

To gain insight into changes in CO₂ emissions embodied in China–US trade, an input–output analysis based on the emergy/dollar ratio (EDR) is used to estimate embodied CO₂ emissions; a structural decomposition analysis (SDA) is employed to analyze the driving factors for changes in CO₂ emissions embodied in China's exports to the US during 2002–2007. The results of the input–output analysis show that net export of CO₂ emissions increased quickly from 2002 to 2005 but decreased from 2005 to 2007. These trends are due to a reduction in total CO₂ emission intensity, a decrease in the exchange rate, and small imports of embodied CO₂ emissions. The results of the SDA demonstrate that total export volume was the largest driving factor for the increase in embodied CO₂ emissions during 2002–2007, followed by intermediate input structure. Direct CO₂ emissions intensity had a negative effect on changes in embodied CO₂ emissions. The results suggest that China should establish a framework for allocating emission responsibilities, enhance energy efficiency, and improve intermediate input structure.     

Decomposing the change of CO2 emissions: A joint production theoretical approach

This paper presents an alternative decomposition method to explore the driving forces of change in carbon emissions by using distance functions estimated by data envelopment analysis. The proposed approach can isolate the effects of changes in GDP composition and energy supply composition on the change of carbon emissions. In addition, it is capable of identifying the effects of changes in different input ratios, which may be very important if there are substitution effects among different inputs. Moreover, the proposed model can measure the effects of changes in good and bad output technical efficiencies. Consequently, this decomposition technique allows a change of carbon emissions to be decomposed into contributions from ten factors, which provides more insights for policy makers. We apply this model to decompose carbon emissions in 25 OECD counties and China. For the sample countries as a whole, the empirical results indicate that the economic growth is the crucial driver to carbon emissions increase, while the changes in GDP composition and capital–energy ratio are two main drivers to carbon emissions reduction. In particular, we discuss in detail the driving forces of China's carbon emissions change in order to propose some valuable policy implications for China from an international perspective.