基于能源消费的中国不同产业空间的碳足迹分析

Using energy consumption and land use data of each region of China in 2007,this paper established carbon emission and carbon footprint model based on energy consumption,and estimated the carbon emission amount of fossil energy and rural biomass energy of dif-ferent regions of China in 2007.Through matching the energy consumption items with indus-trial spaces,this paper divided industrial spaces into five types:agricultural space,living & industrial-commercial space,transportation industrial space,fishery and water conservancy space,and other industrial space.Then the author analyzed the carbon emission intensity and carbon footprint of each industrial space.Finally,advices of decreasing industrial carbon footprint and optimizing industrial space pattern were put forward.The main conclusions are as following:(1) Total amount of carbon emission from energy consumption of China in 2007 was about 1.65 GtC,in which the proportion of carbon emission from fossil energy was 89%.(2) Carbon emission intensity of industrial space of China in 2007 was 1.98 t/hm2,in which,carbon emission intensity of living & industrial-commercial space and of transportation in-dustrial space was 55.16 t/hm2 and 49.65 t/hm2 respectively,they were high-carbon-emission industrial spaces among others.(3) Carbon footprint caused by industrial activities of China in 2007 was 522.34 106 hm2,which brought about ecological deficit of 28.69 106 hm2,which means that the productive lands were not sufficient to compensate for carbon footprint of industrial activities,and the compensating rate was 94.5%.As to the regional carbon footprint,several regions have ecological profit while others have not.In general,the present ecologi-cal deficit caused by industrial activities was small in 2007.(4) Per unit area carbon footprint of industrial space in China was about 0.63 hm2/hm2 in 2007,in which that of living & indus-trial-commercial space was the highest (17.5 hm2/hm2).The per unit area carbon footprint of different industrial spaces all presented a declining trend from east to west of China.     

中国不同区域能源消费碳足迹的时空变化(英文)

Study on regional carbon emission is one of the hot topics under the background of global climate change and low-carbon economic development, and also help to establish different low-carbon strategies for different regions. On the basis of energy consumption and land use data of different regions in China from 1999 to 2008, this paper established carbon emission and carbon footprint models based on total energy consumption, and calculated the amount of carbon emissions and carbon footprint in different regions of China from 1999 to 2008. The author also analyzed carbon emission density and per unit area carbon footprint for each region. Finally, advices for decreasing carbon footprint were put forward. The main conclusions are as follows: (1) Carbon emissions from total energy consumption increased 129% from 1999 to 2008 in China, but its spatial distribution pattern among different regions just slightly changed, the sorting of carbon emission amount was: Eastern China > Northern China > Central and Southern China > Southwest China > Northwest China. (2) The sorting of carbon emission density was: Eastern China > Northeast China > Central and Southern China > Northern China > Southwest China > Northwest China from 1999 to 2003, but from 2004 Central and Southern China began to have higher carbon emission density than Northeast China, the order of other regions did not change. (3) Carbon footprint increased significantly since the rapid increasing of carbon emissions and less increasing area of pro-ductive land in different regions of China from 1999 to 2008. Northern China had the largest carbon footprint, and Northwest China, Eastern China, Northern China, Central and Southern China followed in turn, while Southwest China presented the lowest area of carbon footprint and the highest percentage of carbon absorption. (4) Mainly influenced by regional land area, Northern China presented the highest per unit area carbon footprint and followed by Eastern China, and Northeast China; Central and Southern China, and Northwest China had a similar medium per unit area carbon footprint; Southwest China always had the lowest per unit area carbon footprint. (5) China faced great ecological pressure brought by carbon emission. Some measures should be taken both from reducing carbon emission and increasing carbon absorption.     

1980-2017年中国碳强度关键影响因子变化特征

The Chinese government ratified the Paris Climate Agreement in 2016.Accordingly,China aims to reduce carbon dioxide emissions per unit of gross domestic product(carbon intensity)to 60%–65%of 2005 levels by 2030.However,since numerous factors influence carbon intensity in China,it is critical to assess their relative importance to determine the most important factors.As traditional methods are inadequate for identifying key factors from a range of factors acting in concert,machine learning was applied in this study.Specifically,random forest algorithm,which is based on decision tree theory,was employed because it is insensitive to multicollinearity,is robust to missing and unbalanced data,and provides reasonable predictive results.We identified the key factors affecting carbon intensity in China using random forest algorithm and analyzed the evolution in the key factors from 1980 to 2017.The dominant factors affecting carbon intensity in China from 1980 to 1991 included the scale and proportion of energy-intensive industry,the proportion of fossil fuel-based energy,and technological progress.The Chinese economy developed rapidly between 1992 and 2007;during this time,the effects of the proportion of service industry,price of fossil fuel,and traditional residential consumption on carbon intensity increased.Subsequently,the Chinese economy entered a period of structural adjustment after the 2008 global financial crisis;during this period,reductions in emissions and the availability of new energy types began to have effects on carbon intensity,and the importance of residential consumption increased.The results suggest that optimizing the energy and industrial structures,promoting technological advancement,increasing green consumption,and reducing emissions are keys to decreasing carbon intensity within China in the future.These approaches will help achieve the goal of reducing carbon intensity to 60%–65%of the 2005 level by 2030.     

中国能源消费碳排放强度及其影响因素的空间计量(英文)

The sustainable development has been seriously challenged by global climate change due to carbon emissions. As a developing country, China promised to reduce 40%–45% below the level of the year 2005 on its carbon intensity by 2020. The realization of this target depends on not only the substantive transition of society and economy at the national scale, but also the action and share of energy saving and emissions reduction at the provincial scale. Based on the method provided by the IPCC, this paper examines the spatiotemporal dynamics and dominating factors of China's carbon intensity from energy consumption in 1997–2010. The aim is to provide scientific basis for policy making on energy conservation and carbon emission reduction in China. The results are shown as follows. Firstly, China's carbon emissions increased from 4.16 Gt to 11.29 Gt from 1997 to 2010, with an annual growth rate of 7.15%, which was much lower than that of GDP(11.72%). Secondly, the trend of Moran's I indicated that China's carbon intensity has a growing spatial agglomeration at the provincial scale. The provinces with either high or low values appeared to be path-dependent or space-locked to some extent. Third, according to spatial panel econometric model, energy intensity, energy structure, industrial structure and urbanization rate were the dominating factors shaping the spatiotemporal patterns of China's carbon intensity from energy consumption. Therefore, in order to realize the targets of energy conservation and emission reduction, China should improve the efficiency of energy utilization, optimize energy and industrial structure, choose the low-carbon urbanization approach and implement regional cooperation strategy of energy conservation and emissions reduction.     

基于土地集约利用的长株潭城市群建设用地供需仿真模拟（英文）

Urban land intensive use is an important indicator in harmonizing the relationship between land supply and demand. The system dynamics(SD) can be used to construct the feedback loop between urban construction land supply and demand and index variable function. Based on this, this study built a supply and demand system dynamic model of urban construction land for Chang-Zhu-Tan urban agglomeration. This model can simulate the change trends of supply and demand of construction land, industrial land, and residential land in 2016–2030 by three scenarios of low, medium, and high intensity modes. The results showed that the scale of construction land of urban agglomeration is expanding, with a rapid increase rate for the urban construction land. The scale and speed of land use based on the three intensity modes existed differences. The large scale and supply of construction land in the low intensity mode caused easily the waste of land resources. In high intensity mode, the scale and supply of construction land were reduced against the healthy development of new-type urbanization. In the medium intensity mode, the scale and supply of land use adapted to the socio-economic development and at the same time reflected the concept of modern urban development. In addition, the results of this study found that the proportion of industrial land in construction land ranged from 15% to 21%, which increased year by year in the low intensity mode, and decreased slowly and stabilized in medium and high intensity modes. The proportion of residential land in construction land ranged from 27% to 35%, which decreased in the low and the medium intensity modes, and maintained a high level in the higher intensity mode. This study contributes to provide scientific reference for decision-making optimization of land supply and demand, urban planning, and land supply-side reform.     

基于LMDI分解和STIRPAT模型的哈萨克斯坦能源碳排放影响因素的定量分析（英文）

Quantitative analysis of the impact factors in energy-related CO_2 emissions serves as an important guide for reducing carbon emissions and building an environmentally-friendly society. This paper aims to use LMDI method and a modified STIRPAT model to research the conventional energy-related CO_2 emissions in Kazakhstan after the collapse of the Soviet Union. The results show that the trajectory of CO_2 emissions displayed U-shaped curve from 1992 to 2013. Based on the extended Kaya identity and additive LMDI method, we decomposed total CO_2 emissions into four influencing factors. Of those, the economic active effect is the most influential factor driving CO_2 emissions, which produced 110.86 Mt CO_2 emissions, with a contribution rate of 43.92%. The second driving factor is the population effect, which led to 11.87 Mt CO_2 emissions with a contribution rate of 4.7%. On the contrary, the energy intensity effect is the most inhibiting factor, which caused –110.90 Mt CO_2 emissions with a contribution rate of –43.94%, followed by the energy carbon structure effect resulting in –18.76 Mt CO_2 emissions with a contribution rate of –7.43%. In order to provide an in-depth examination of the change response between energy-related CO_2 emissions and each impact factor, we construct a modified STIRPAT model based on ridge regression estimation. The results indicate that for every 1% increase in population size, economic activity, energy intensity and energy carbon structure, there is a subsequent increase in CO_2 emissions of 3.13%, 0.41%, 0.30% and 0.63%, respectively.     

Spatiotemporal evolution of urban carbon emission performance in China and prediction of future trends

Climate change resulting from CO_2 emissions has become an important global environmental issue in recent years.Improving carbon emission performance is one way to reduce carbon emissions.Although carbon emission performance has been discussed at the national and industrial levels,city-level studies are lacking due to the limited availability of statistics on energy consumption.In this study,based on city-level remote sensing data on carbon emissions in China from 1992–2013,we used the slacks-based measure of super-efficiency to evaluate urban carbon emission performance.The traditional Markov probability transfer matrix and spatial Markov probability transfer matrix were constructed to explore the spatiotemporal evolution of urban carbon emission performance in China for the first time and predict long-term trends in carbon emission performance.The results show that urban carbon emission performance in China steadily increased during the study period with some fluctuations.However,the overall level of carbon emission performance remains low,indicating great potential for improvements in energy conservation and emission reduction.The spatial pattern of urban carbon emission performance in China can be described as"high in the south and low in the north,"and significant differences in carbon emission performance were found between cities.The spatial Markov probabilistic transfer matrix results indicate that the transfer of carbon emission performance in Chinese cities is stable,resulting in a"club convergence"phenomenon.Furthermore,neighborhood backgrounds play an important role in the transfer between carbon emission performance types.Based on the prediction of long-term trends in carbon emission performance,carbon emission performance is expected to improve gradually over time.Therefore,China should continue to strengthen research and development aimed at improving urban carbon emission performance and achieving the national energy conservation and emission reduction goals.Meanwhile,neighboring cities with different neighborhood backgrounds should pursue cooperative economic strategies that balance economic growth,energy conservation,and emission reductions to realize low-carbon construction and sustainable development.     

西安市土地利用与环境关系的协调研究

In this paper we adopt annual land use conditions change data, land sifting data, social, economic and population data and environment information of nine districts and four counties in Xi＇an city from 1980 to 2000 to analyze its structural and degree change of land use since the 1980s, and calculate the benefits and transformation of land use type. The results show that the non-agricultural land increased rapidly, especially the urban and rural residential spots and industrial and mining （RIM） land use increased mostly rapidly, an increase of 64%. Meanwhile, the intensity of land exploitation was accelerating, land was transformed to industries with better benefit and areas experiencing faster urbanization process. By analyzing the harmonious degree of land exploitation in economic and environmental aspects, we find out that the land use imbalance mainly existed in the municipal area of Xi＇an, and the imbalance index of land use based on GDP and non-agricultural population were respectively 12.37 and 14.67 in 2000, which were far higher than those in other regions. Nevertheless the environmental harmonious degree in the municipal area of Xi＇an ranges between 0.6 and 0.8, which was better than that of suburban area. Some proposals addressing to the problems of harmonious level in all scales, resources utilization, projects management and feasibility analysis and intensive urbanization are also put forward.     

城市能源利用与CO_2排放的多尺度综合评价(英文)

Accurate and detailed accounting of energy-induced carbon dioxide(CO2) emissions is crucial to the evaluation of pressures on natural resources and the environment, as well as to the assignment of responsibility for emission reductions. However, previous emission inventories were usually production- or consumption-based accounting, and few studies have comprehensively documented the linkages among socio-economic activities and external transaction in urban areas. Therefore, we address this gap in proposing an analytical framework and accounting system with three dimensions of boundaries to comprehensively assess urban energy use and related CO2 emissions. The analytical framework depicted the input, transformation, transfer and discharge process of the carbon-based(fossil) energy flows through the complex urban ecosystems, and defined the accounting scopes and boundaries on the strength of ‘carbon footprint' and ‘urban metabolism'. The accounting system highlighted the assessment for the transfer and discharge of socio-economic subsystems with different spatial boundaries. Three kinds methods applied to Beijing City explicitly exhibited the accounting characteristics. Our research firstly suggests that urban carbon-based energy metabolism can be used to analyze the process and structure of urban energy consumption and CO2 emissions. Secondly, three kinds of accounting methods use different benchmarks to estimate urban energy use and CO2 emissions with their distinct strength and weakness. Thirdly, the empirical analysis in Beijing City demonstrate that the three kinds of methods are complementary and give different insights to discuss urban energy-induced CO2 emissions reduction. We deduce a conclusion that carbon reductions responsibility can be assigned in the light of production, consumption and shared responsibility based principles. Overall, from perspective of the industrial and energy restructuring and the residential lifestyle changes, our results shed new light on the analysis on the evolutionary mechanism and pattern of urban energy-induced CO2 emissions with the combination of three kinds of methods. And the spatial structure adjustment and technical progress provides further elements for consideration about the scenarios of change in urban energy use and CO2 emissions.     

中国城镇化水平、经济增长和二氧化碳排放的面板协整和因果分析（英文）

Elucidating the complex mechanism between urbanization,economic growth,carbon dioxide emissions is fundamental necessary to inform effective strategies on energy saving and emission reduction in China. Based on a balanced panel data of 31 provinces in China over the period 1997–2010,this study empirically examines the relationships among urbanization,economic growth and carbon dioxide(CO2) emissions at the national and regional levels using panel cointegration and vector error correction model and Granger causality tests. Results showed that urbanization,economic growth and CO2 emissions are integrated of order one. Urbanization contributes to economic growth,both of which increase CO2 emissions in China and its eastern,central and western regions. The impact of urbanization on CO2 emissions in the western region was larger than that in the eastern and central regions. But economic growth had a larger impact on CO2 emissions in the eastern region than that in the central and western regions. Panel causality analysis revealed a bidirectional long-run causal relationship among urbanization,economic growth and CO2 emissions,indicating that in the long run,urbanization does have a causal effect on economic growth in China,both of which have causal effect on CO2 emissions. At the regional level,we also found a bidirectional long-run causality between land urbanization and economic growth in eastern and central China. These results demonstrated that it might be difficult for China to pursue carbon emissions reduction policy and to control urban expansion without impeding economic growth in the long run. In the short-run,we observed a unidirectional causation running from land urbanization to CO2 emissions and from economic growth to CO2 emissions in the eastern and central regions. Further investigations revealed an inverted N-shaped relationship between CO2 emissions and economic growth in China,not supporting the environmental Kuznets curve(EKC) hypothesis. Our empirical findings have an important reference value for policy-makers in formulating effective energy saving and emission reduction strategies for China.     

Urban carbon footprint and carbon cycle pressure：The case study of Nanjing

Urban carbon footprint reflects the impact and pressure of human activities on urban environment. Based on city level, this paper estimated carbon emissions and carbon footprint of Nanjing city, analyzed urban carbon footprint intensity and carbon cycle pressure and discussed the influencing factors of carbon footprint through LMDI decomposition model. The main conclusions are as follows: (1) The total carbon emissions of Nanjing increased rapidly since 2000, in which the carbon emission from the use of fossil energy was the largest. Meanwhile, carbon sinks of Nanjing presented a declining trend since 2000, which caused the decrease of carbon compensation rate and the increase of urban carbon cycle pressure. (2) The total carbon footprint of Nanjing increased rapidly since 2000, and the carbon deficit was more than ten times of total land areas of Nanjing in 2009, which means Nanjing confronted high carbon cycle pressure. (3) Generally, carbon footprint intensity of Nanjing was on decrease and the carbon footprint productivity was on increase. This indicated that energy utilization rate and carbon efficiency of Nanjing was improved since 2000, and the policy for energy conservation and emission reduction taken by Nanjing's government received better effects. (4) Economic development, population and industrial structure are promoting factors for the increase of carbon footprint of Nanjing, while the industrial carbon footprint intensity was inhibitory factor. (5) Several countermeasures should be taken to decrease urban carbon footprint and alleviate carbon cycle pressure, such as: improvement of the energy efficiency, industrial structure reconstruction, afforestation and environmental protection and land use control. Generally, transition to low-carbon economy is essential for Chinese cities to realize sustainable development in the future.     

城市碳足迹与碳循环压力分析——以南京市为例（英文）

Urban carbon footprint reflects the impact and pressure of human activities on urban environment.Based on city level,this paper estimated carbon emissions and carbon footprint of Nanjing city,analyzed urban carbon footprint intensity and carbon cycle pressure and discussed the influencing factors of carbon footprint through LMDI decomposition model.The main conclusions are as follows:(1) The total carbon emissions of Nanjing increased rapidly since 2000,in which the carbon emission from the use of fossil energy was the largest.Meanwhile,carbon sinks of Nanjing presented a declining trend since 2000,which caused the decrease of carbon compensation rate and the increase of urban carbon cycle pressure.(2) The total carbon footprint of Nanjing increased rapidly since 2000,and the carbon deficit was more than ten times of total land areas of Nanjing in 2009,which means Nanjing confronted high carbon cycle pressure.(3) Generally,carbon footprint intensity of Nanjing was on decrease and the carbon footprint productivity was on increase.This indicated that energy utilization rate and carbon efficiency of Nanjing was improved since 2000,and the policy for energy conservation and emission reduction taken by Nanjing's government received better effects.(4) Economic development,population and industrial structure are promoting factors for the increase of carbon footprint of Nanjing,while the industrial carbon footprint intensity was inhibitory factor.(5) Several countermeasures should be taken to decrease urban carbon footprint and alleviate carbon cycle pressure,such as:improvement of the energy efficiency,industrial structure reconstruction,afforestation and environmental protection and land use control.Generally,transition to low-carbon economy is essential for Chinese cities to realize sustainable development in the future.     

南京城市系统碳循环与碳平衡分析

城市是人类能源活动和碳排放的集中地,开展城市系统碳循环研究有助于深入了解城市在区域碳循环过程中的地位和作用。本文集成了城市碳储量和碳通量的核算方法,并以南京市为例开展了城市系统碳循环与碳平衡的实证研究。结论如下:① 南京市城市碳储量呈缓慢上升趋势,2009 年为6937 万t,其中自然碳储量占88%,且总量基本保持稳定;人为碳储量(特别是城市绿地和建筑物碳库) 呈大幅增长趋势;② 垂直碳输入通量以植物光合作用和水域碳吸收为主,历年来基本稳定;水平碳输入通量大幅增长,2009 年为3043 万t,其中能源和木材碳输入呈增长趋势,而食物碳输入则呈下降趋势;③ 垂直碳输出通量呈增长趋势,2009年为3295 万t,其中化石能源碳排放占近80%,自然过程仅占6%;水平碳输出通量以能源制品、水产品和含碳废弃物为主,其总量呈明显下降趋势;④ 南京市历年城市碳输出均高于碳输入,且两者的差额呈现扩大趋势。总体而言,“隐流碳和加工需求碳”的比重有所下降,说明碳的利用率有所提升;⑤ 南京市碳补偿率明显下降,这表明自然生态系统的碳吸收能力不足以补偿人为活动的碳排放,城市碳循环压力在不断加大。     

基于能源消费的江苏省土地利用碳排放与碳足迹

采用2003~2007年江苏省能源消费和土地利用等数据,通过构建能源消费的碳排放模型,对江苏省5年来能源消费碳排放进行了核算,并通过土地利用类型和碳排放项目的对应,对不同土地利用方式的碳排放及碳足迹进行了定量分析。结论如下:(1)江苏省能源消费碳排放总量从2003年的8794.24万t上升到2007年的16329.85万t,涨幅达86%。其中,终端能源消费碳排放占53.6%。(2)江苏全省土地单位面积碳排放从2003年8.24t/hm²上升到2007年15.53 t/hm²,增幅为88.5%。其中,居民点及工矿用地单位面积碳排放最大,为95.62 t/hm²。(3)江苏全省能源消费碳足迹大于生产性土地的实际面积,由此造成的生态赤字达1351.285万hm²。(4)不同土地利用类型的碳足迹大小顺序为:居民点及工矿用地＞交通用地＞未利用地及特殊用地＞农用地和水利用地,其中居民点及工矿用地的碳足迹高达10.89 hm²/ hm²。(5)江苏全省单位面积碳足迹也呈明显的扩大趋势,从2003年的0.938 hm²/ hm²上升到2007年的1.769 hm²/ hm²。     

Temporospatial changes of carbon footprint based on energy consumption in China

Study on regional carbon emission is one of the hot topics under the background of global climate change and low-carbon economic development, and also help to establish different low-carbon strategies for different regions. On the basis of energy consumption and land use data of different regions in China from 1999 to 2008, this paper established carbon emission and carbon footprint models based on total energy consumption, and calculated the amount of carbon emissions and carbon footprint in different regions of China from 1999 to 2008. The author also analyzed carbon emission density and per unit area carbon footprint for each region. Finally, advices for decreasing carbon footprint were put forward. The main conclusions are as follows: (1) Carbon emissions from total energy consumption increased 129% from 1999 to 2008 in China, but its spatial distribution pattern among different regions just slightly changed, the sorting of carbon emission amount was: Eastern China > Northern China > Central and Southern China > Southwest China > Northwest China. (2) The sorting of carbon emission density was: Eastern China > Northeast China > Central and Southern China > Northern China > Southwest China > Northwest China from 1999 to 2003, but from 2004 Central and Southern China began to have higher carbon emission density than Northeast China, the order of other regions did not change. (3) Carbon footprint increased significantly since the rapid increasing of carbon emissions and less increasing area of productive land in different regions of China from 1999 to 2008. Northern China had the largest carbon footprint, and Northwest China, Eastern China, Northern China, Central and Southern China followed in turn, while Southwest China presented the lowest area of carbon footprint and the highest percentage of carbon absorption. (4) Mainly influenced by regional land area, Northern China presented the highest per unit area carbon footprint and followed by Eastern China, and Northeast China; Central and Southern China, and Northwest China had a similar medium per unit area carbon footprint; Southwest China always had the lowest per unit area carbon footprint. (5) China faced great ecological pressure brought by carbon emission. Some measures should be taken both from reducing carbon emission and increasing carbon absorption.     

南京市土地利用结构碳排放效率增长及其空间相关性

采用南京市11个区2005-2014年的相关数据,首先对不同类型土地的碳排放量进行核算,进一步将其作为非期望产出引入DEA模型并采用Hicks-Moorsteen指数对南京市各区的土地利用结构碳排放效率增长进行估算、比较和分析。研究结果表明：① 碳排放的主要来源是建设用地的间接碳排放,研究期内的土地利用碳排放量呈现出持续增长的发展态势。② 全要素碳排放效率增长及其分解要素均低于传统全要素生产率增长,即不考虑碳排放约束的全要素生产率增长高估了实际的土地利用效率增长水平。全要素碳排放效率增长在研究期内表现出收敛态势和区域之间均衡性的发展特征,源于“低碳和高效”发展理念的深入人心,单位GDP能耗不断降低。③ 南京市各区的技术效率值较低,“技术追赶”效应不明显,开始出现土地利用的规模经济效应,但是范围经济效应不显著。④ 全要素碳排放效率增长在南京市范围内具有空间正相关性,且表现出空间集聚特征。基于此,提出了一些有益的建议。     

城市开发区工业企业的碳排放效率比较 ——以南京江宁经济技术开发区为例

以南京市江宁经济技术开发区为例,基于199家企业样本,采用碳排放强度、单位碳排放的用水效率、单位碳排放的废弃物排放强度指数及单位产品的虚拟水含量和隐含碳排放等指标,对27种不同类型工业企业的碳排放效率进行了评价和分析。得出的主要结论为：1）不同类型工业企业的碳排放强度差异明显。南京市江宁区27类行业的平均碳排放强度为0.35 t/万元,其中电力、热力生产和供应业的碳排放强度最高,而仪器仪表制造业碳排放强度最低。2）尽管企业碳排放效率和水资源利用效率有一定的行业关联,但企业碳排放效率主要受经济效益、生产工艺、原料和能源类型等因素的影响。3）不同企业单位产品的隐含碳排放和虚拟水含量具有较大的差异。其中,轿车、铁矿石、金属铸件和摩托车等产品的虚拟水和隐含碳排放明显高于其他行业产品。4）企业碳排放与相应的三废排放强度具有一定的关联性。其中,碳排放与废气排放强度的关联度最高。5）在对未来企业排放效率评估、碳核查及碳配额分配中,不仅要考虑企业碳排放的经济效益,也要考虑企业的资源消耗和废弃物排放效率,并建立基于碳排放综合绩效评估的企业碳配额分配方案,这对于落实碳减排、推动资源节约和生产方式转变以及加强环境治理的多重目标的实现具有重要意义。     

郑汴都市区一次能源消费的碳排放变化及机理

城市发展面临着向低碳生态转型的挑战,探析城市一次能源消费的碳排放变化及机理是郑汴都市区低碳生态化研究的基点。采用LMDI分析法对2000~2009年间郑汴都市区化石能源碳排放变化、2004~2007年间一次能源碳排放与主要农作物碳吸收变化机理进行研究,构建低碳发展判别函数进一步辨析郑汴都市区产业低碳发展的类型与方向。结果发现：郑汴都市区的碳排放量逐年增加,但两市的增长速度与方式有所不同;碳排放量是在经济发展水平与人口规模、能源强度与能源结构、种植结构、播种面积及产出强度等7个因子相互作用下变化的,经济发展水平的提高是促进碳排放增加的显著因素,能源强度、播种面积和产出强度的增加是抑制碳排放的显著因素;郑汴都市区的产业错位发展有利于消减碳排放总量,但多种产业的产能和结构亟待提高与调整。郑汴城市复合生态系统之间的低碳耦合发展路径、各子系统之间的相互作用机理是应继续深入的方向。     

基于能源消费的中国省级区域碳足迹时空演变分析

碳足迹作为衡量生产某一产品在其生命周期所直接或间接排放的CO₂量,其能够反应人类某项活动或某种产品对生态环境的压力程度。本文采用1997-2008年全国省级区域化石能源消费数据和土地利用结构数据,构建碳足迹计算模型,测算不同时间、不同区域的碳足迹、碳生态承载力和碳赤字,并引入物理学中重心的概念,测算1997-2008年全国各省级区域碳足迹的重心,进行碳足迹重心的时空演变趋势分析,掌握区域间能源消费碳排放的差异性;同时构建能源消费碳足迹压力指数模型,计算1997-2008年各省的碳足迹压力指数,对研究区域进行生态压力强度分级,并考察各省级区域碳足迹压力指数在两个相邻时间点之间的变化强度,进行生态压力变化强度的级别划分。