Conduction pathways of resource endowment affecting carbon intensity:Based on interprovincial data in China

By establishing a mathematical model and a basic analytical framework for the impact of resource endowments on carbon intensity,a traditional panel model without spatial panel effects was firstly constructed,a Durbin-Wu-Hausman test was conducted,and the model was set as a fixed-effects model based on the statistical values;secondly,the traditional panel model without spatial effects was estimated,and LM tests and robustness tests were conducted on the regression residuals.The LM test was then used to remove the fixed effect terms by the de-meaning method,and the Matlab 7.0 software was used to estimate the model.The stepwise introduction of variables was used to observe the effect of each variable on economic growth and to analyze the relationship between the magnitude and significance of the regression parameters of each variable.Finally,the path of conduction effect of resource endowment through mediating variable sinfluencing economic growth and carbon emissions,and thus carbon intensity,was constructed.The conclusion is that carbon intensity is inversely proportional to economic growth for a given level of carbon emissions.Therefore,if resource endowment promotes economic growth through mediating variables,it will lead to a decrease in carbon intensity,which is conducive to the achievement of emission reduction targets;conversely,if resource endowment hinders economic growth through mediating variables,it will lead to an increase in carbon intensity,which is not conducive to the achievement of emission reduction targets.

Relationship between Industrial Coupling Coordination and Carbon Intensity in the Bohai Rim Economic Circle

Coordinated development of new high-tech industries and traditional industries is crucially important for economic growth and environmental sustainability,and it has become a focus of academic and governmental bodies.This study establishes the comprehensive evaluation index system of high-tech industries and traditional industries,and uses the method of principal component analysis,coupling and coupling coordination degree model to determine the level of industry coordinated development.Then,Pearson correlation test is used to further analyze the correlation between regional industrial coupling coordination and carbon intensity of the seven provinces in the Bohai Rim Economic Circle(BREC).The results are as follows.(1)There is a negative correlation between industrial coupling coordination and carbon intensity.(2)The degree of industrial coordination of Beijing,Tianjin,and Shandong is significantly higher than other provinces in the BREC,as both the high-tech industries and traditional industries of these three provinces have reached a high level of development and achieved high coupling.The high-tech industries of the three provinces show positive changes,whereas the traditional industries show negative changes,which indicates that the new high-tech industries are driving the upgrading of the traditional industries by the application of high technologies.(3)From 2011 to 2016,the number of provinces with a low degree of high-tech and traditional industrial coordination fell from three to one.The traditional industries in Hebei and Inner Mongolia have been upgraded by strengthening their technological innovation with the introduction of rapid high-tech industrial development.These findings are a useful reference for regional industrial coupling coordination and carbon emission reduction.

Inter-provincial carbon emission intensity factor analysis and carbon intensity projection calculation in China

The extended “STIRPAT” model and the GM(1,1) model are used to predict the factors influencing inter-provincial carbon emission intensity and carbon intensity in China respectively. In this paper, based on the collation of inter-provincial carbon emission data, the extended “STIRPAT” model is formulated for carbon dioxide emissions and carbon intensity emissions, and the Hausman test is used to determine the influence form of the models. The main influencing factors of carbon intensity were identified: economic development level, energy intensity, and energy consumption structure. The paper constructs GM(1,1) model for carbon emission intensity from 2010-2019 using the gray prediction method,and calculates the carbon emission intensity of China’s inter-provincial 2022 by residual test, correlation test, variance, and small error probability test, and then predicts the carbon demand of each province and city in 2022 according to the expected average annual growth rate, and finally concludes that using carbon emission intensity as the carbon emission reduction target of each region, and it cannot fundamentally solve the problem of carbon pollution in China. Compared to the regional carbon emission reduction target, there is a greater degree of regional imbalance in carbon intensity between provinces in China, and the target of reducing carbon emission intensity somehow avoids the fact that the carbon emission reduction intensity target can be achieved without reducing the absolute amount of carbon emissions that continue to increase. The focus of achieving the “double carbon” target lies in the reduction of total carbon emissions, and the target of reducing carbon intensity will eventually be transformed into a binding target of total carbon emissions in the process of implementation, so attention should be shifted from recessiontype carbon reduction and efficiency-type carbon reduction to innovative carbon reduction. It is necessary to increase investment in renewable energy, and gradually expand the scope of application of photovoltaic, and wind power to ensure the reduction of total carbon emissions.

Industrial Carbon Emission Distribution and Regional Joint Emission Reduction:A Case Study of Cities in the Pearl River Basin,China

China’s low-carbon development path will make significant contributions to achieving global sustainable development goals.Due to the diverse natural and economic conditions across different regions in China,there exists an imbalance in the distribution of car-bon emissions.Therefore,regional cooperation serves as an effective means to attain low-carbon development.This study examined the pattern of carbon emissions and proposed a potential joint emission reduction strategy by utilizing the industrial carbon emission intens-ity(ICEI)as a crucial factor.We utilized social network analysis and Local Indicators of Spatial Association(LISA)space-time trans-ition matrix to investigate the spatiotemporal connections and discrepancies of ICEI in the cities of the Pearl River Basin(PRB),China from 2010 to 2020.The primary drivers of the ICEI were determined through geographical detectors and multi-scale geographically weighted regression.The results were as follows:1)the overall ICEI in the Pearl River Basin is showing a downward trend,and there is a significant spatial imbalance.2)There are numerous network connections between cities regarding the ICEI,but the network structure is relatively fragile and unstable.3)Economically developed cities such as Guangzhou,Foshan,and Dongguan are in the center of the network while playing an intermediary role.4)Energy consumption,industrialization,per capita GDP,urbanization,science and techno-logy,and productivity are found to be the most influential variables in the spatial differentiation of ICEI,and their combination in-creased the explanatory power of the geographic variation of ICEI.Finally,through the analysis of differences and connections in urban carbon emissions under different economic levels and ICEI,the study suggests joint carbon reduction strategies,which are centered on carbon transfer,financial support,and technological assistance among cities.

Spatiotemporal dynamics of carbon intensity from energy consumption in China

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 spati- otemporal dynamics and dominating factors of China＇s carbon intensity from energy con- sumption 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 agglom- eration 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 economet- ric 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.

Impact of Greenization on the Marginal Utility of Intensity of Carbon Emissions and Factors Affecting it in China

The impact of greenization on the marginal utility of the intensity of carbon emissions in China and factors influ-encing this relationship are explored in this study.China’s level of greenization is evaluated by using an index system developed based on the comprehensive index method.The intensity of carbon emissions is determined by using the standards for the coefficients of conversion of coal equivalent and coefficients of carbon emission.The impact of greenization on the marginal utility of the intensity of carbon emissions is then evaluated by using an elastic formula and factors affecting this relationship are verified by regression analysis.The results are as fol-lows:(1)China’s level of greenization has exhibited a trend of constant increase.The intensity of carbon emissions has followed a continual downward trend while the impact of greenization on the marginal utility of the intensity of these emissions has been declining.(2)Urbanization as well as scientific and technological developments have slowed the reduction in the marginal utility of the intensity of carbon emissions,whereas the structure of energy consumption has expedited it under the diminishing impact of greenization.The standard of living of the popu-lation,intensity of environmental regulation,and environmental quality have had different influences under dif-ferent conditions.

A hefty target of reducing the intensity of carbon dioxide emissions

At the end of January, China formally handed over the report on pollution reduction targets to the United Nations.

A Distributed Computing Algorithm for Electricity Carbon Emission Flow and Carbon Emission Intensity

The calculation of the indirect carbon emis-sion is essential for power system policy making,carbon market development,and power grid planning.The em-bedded carbon emissions of the electricity system are commonly calculated by carbon emission flow theory.However,the calculation procedure is time-consuming,especially for a country with 500-1000 thousand nodes,making it challenging to obtain nationwide carbon emis-sions intensity precisely.Additionally,the calculation procedure requires to gather all the grid data with high classified levels from different power grid companies,which can prevent data sharing and cooperation among different companies.This paper proposes a distributed computing algorithm for indirect carbon emission that can reduce the time consumption and provide privacy protection.The core idea is to utilize the sparsity of the nodes’flow matrix of the nationwide grid to partition the computing procedure into parallel sub-procedures exe-cuted in multiple terminals.The flow and structure data of the regional grid are transformed irreversibly for pri-vacy protection,when transmitted between terminals.A 1-master-and-N-slave layout is adopted to verify the method.This algorithm is suitable for large grid compa-nies with headquarter and branches in provinces,such as the State Grid Corporation of China.

Spatial and temporal variation of energy carbon emissions in Yantai from 2001 to 2011

In order to understand the characteristics of spatial and temporal variation,as well as provide effective ideas on carbon emissions and regulatory policy in Yantai,this article analyzed spatial and temporal variation of carbon emissions in Yantai based on energy consumption statistics for a variety of energy sorts together with industrial sectors from 2001 to 2011.The results were as following:First of all,Yantai's carbon emissions grew by an average of 5.5%per year during the last 10 years,and there was a peak of 10.48 million carbon in the year of 2011.Second,compared with the gross domestic product(GDP) growth rate,the figures for energy carbon emissions growth rate were smaller;however the problem of carbon emissions were still more obvious.Furthermore,carbon emissions in Yantai increased rapidly before 2008;while after 2008,it increased more slowly and gradually become stable.Third,the energy consumption was different among regions in Yantai.For instance,the energy consumption in Longkou city was the largest,which occupied 50%of the total carbon emissions in Yantai;and the energy consumption in Chang Island was generally less than 1%of the Longkou consumption.Finally,there were relative close relationships among the spatial difference of carbon emissions,regional resources endowment,economic development,industrial structure,and energy efficiency.

Analysis on Carbon Emissions from Energy Consumption in Agriculture and Reduction Measures in Guangdong Province

[Objective] The aim was to study CO2 emissions from energy consumption in agricultural production in Guangdong Province and put forward feasible reduction measures.[Method] Based on the data from China Energy Statistical Yearbook and Guangdong Statistical Yearbook,CO2 emissions from agricultural energy use in Guangdong Province from 2000 to 2009 was estimated by using the formula of carbon emissions recommended by Intergovernmental Panel on Climate Change (IPCC),and corresponding reduction measures were put forward.[Result] With the rapid increase of agricultural output and energy consumption,CO2 emissions from energy consumption in agricultural production in Guangdong Province showed increasing trend from 2000 to 2009,that is to say,increasing from 423.63×104 t C million tons in 2000 to 605.99×104 t C in 2009,with annual growth rate of 4.1%.Meanwhile,carbon emissions intensity during energy consumption in agriculture went down in recent ten years,in other words,decreasing from 0.424 t C/×104 yuan in 2000 to 0.301 t C/×104 yuan in 2009,and its annual decreasing rate was 3.7%.The variation of CO2 emissions from energy consumption in agriculture mainly resulted from the increase of agricultural output,improvement of energy utilization efficiency,high carbonization in agricultural energy consumption structure and so forth.Therefore,in order to reduce CO2 emissions from energy consumption in agriculture,it is necessary to vigorously develop rural renewable energy,develop and popularize advanced technology for energy utilization,advance the energy conservation of agricultural machines,establish and improve the macroeconomic control mechanism for carbon emissions from the energy consumption in agricultural production in the further.[Conclusion] The study could provide references for the establishment of policy about reducing carbon emissions from agricultural energy consumption in Guangdong Province.

Effect of China's industrial structure adjustment on carbon emissions

Confronting the contradiction between the rapid development of economy and the effective protection of environment, and developing low carbon economy by optimizing the industrial structure have become one of the effective way to attract more attention. In the paper, we made a research on the correlation between china's three main industries and carbon emission intensity to find out the main factors which affect the intensity of carbon emission in China by measuring the gross emission in china's 28 main provinces in 2003-2013 and using Grey correlation analysis based on the change tendency. The results indicate that the second industry has the largest correlation with carbon emission intensity; the tertiary industry helps reduce the intensity of carbon emission, but it is not very obvious; the first industry has the least impact on carbon emission intensity. In the last part, according to the characteristics of industrial structure and carbon emission, we put forward the suggestions and strategies on the adjustment of china's industrial structure in future with the results analysis.

The role of green industrial transformation in mitigating carbon emissions:Exploring the channels of technological innovation and environmental regulation

The industrial sector is vital to economic progress,yet industrial pollution poses environmental and economic concerns.The purpose of the study was to investigate the influence of green industrial transformation in re-ducing Pakistan’s carbon intensity between 1975 and 2020.Carbon emissions are considered an endogenous construct,while foreign direct investment(FDI)inflows,technological innovation,green industrial transforma-tion,environmental legislation,and research and development(R&D)investment are possible mediators.The association between variables is assessed using the robust least-squares approach.Green industrial transforma-tion is connected with lower carbon emissions,yet technical innovation,R&D investment,and inbound FDI raise a country’s carbon emissions.The findings support the pollution haven hypothesis in a country.The causality esti-mates indicate that inward FDI contributes to environmental regulations;green industrial transformation directly relates to inbound FDI and R&D expenditures;and technological innovations correspond to inbound FDI,R&D ex-penditures,industrial ecofriendly progression,and environmental standards.According to the impulse response function,environmental policies are anticipated to have a differential effect on carbon emissions in 2023,2024,2028-2030,while they are likely to decrease in the years 2025-2027 and 2031 forward.Additionally,inward FDI and technology advancements would almost certainly result in a rise in carbon emissions over time.Green industrial transitions are projected to result in a ten-year reduction in carbon emissions.The variance decomposi-tion analysis indicates that eco-friendly industrial adaptations would likely have the largest variance error shock on carbon emissions(11.747%),followed by inbound FDI,technological advancements,and regulatory changes,with R&D spending having a minimal impact over time.Pakistan’s economy should foster a green industrial revolution to avoid pollution and increase environmental sustainability to meet its environmental goals.

Spatial Spillover Effects of the Impact of Agricultural Mechanization on Carbon Emission Intensity in Agriculture:An Empirical Study Based on the Panel Data of 282 Cities

The extreme weather caused by the global warming effect has triggered huge losses to agricultural production.A hot issue for governments and scholars is how to effectively reduce carbon emission intensity in agriculture.The agricultural farming practices that are high pollution and high energy cosuming have exacerbated the vulnerability of regional agroecosystems.The sustainable development of agriculture is faced with the two dilemmas of a low utilization rate of green resources and the serious pollution of farmland.Further,environmental and ecological carrying capacities have reached theirlimits,seriouslyhinderingtthe high-quality development of low-carbon agriculture in China.Thus,based on the panel data of 282 cities,the Spatial Dubin Model(SDM)is employed to examine the impact of agricultural mechanization on carbon emission intensity in agriculture.It is found that from 1999 to 2019 carbon emission intensity in agriculture showed an overall downward trend;as of 2019,the agricultural field had completed the target of carbon emission reduction,,oneyear aheadof schedule.From a local perspective,approximately 14.89%6of fagricultural industries in prefecture-level city have still not achieved carbon emission reduction targets,and agricultural carbon emission reduction tasks were better completed in major grain-producing areas than in nonmajor grain-producing areas.Agricultural mechanization has significantly reduced carbonemission intensityyinlocal agriculture production.The impact of agricultural mechanizationoncarbon emission intensity in agriculture has not only a significant negative spatial spillover effect but also a significant effect on spatial carbon emission reduction.Compared with non-major ggrain-producingareas,agricultural mechanization plays a greater role in reducing spatial carbon emissions in major grain-producing areas.Further studies find that agricultural mechanization is conducive to overcome difficulties,such as instability of property rights and land fragmentation,and to achieve large-scale agricultural production,thereby reducing agricultural carbon emissions in nearby regions.However,the transfer of rurallabor,adjustments to the structure of agricultural cultivation,and the centralized use of rural land restrict the development of the crossregional service market for agricultural machinery,which in turn weaken its contribution to spatial carbon emission reduction.At the end of this paper,it is suggested that Chinese governments at all levels should introduce subsidy policies for the cross-regional operation of agricultural machinery to solve the problem of their service market failure.Efforts should be made to stimulate the market to develop more energy-efficient and environmentally friendly agricultural machinery products while strictly controlling changes in the use of arableland in non-grain-producing areas,which aims to serve further agricultural mechanization and boost the high-quality development of low-carbon agriculture.

Research on Regional Differences and Influencing Factors of China's Carbon Emissions

This paper studies the regional differences,dynamic evolution and influencing factors of regional carbon emission intensity(CEI)in 262 cities and 5 regional urban agglomerations(UAs)in China.The Dagum Gini coefficient is used to analyze the intra-regional and inter-regional differences in carbon emissions,and the temporal evolution of the absolute differences of CEI among regions is analyzed by means of kernel density estimation(KDE).The paper provides an in-depth study on the spatial difference and temporal evolution of CEI in Chinese cities and major strategic regions.Through Moran index and LISA’s test,the spatial correlation of carbon emission in prefecture-level cities is tested,and its spatial agglomeration characteristics are described.It is found that China’s CEI is decreasing year by year,presenting a spatial pattern of“low in the south but high in the north”.Based on the calculation of carbon emission intensity at the urban level,this paper conducts LDMI factor decomposition research on carbon emission intensity at the national and key regions,and analyzes the impact of the impact factors on carbon emission intensity.The research results provide a path for China’s green development at the city level and urban agglomeration level,and a theoretical support for different regions and cities to introduce emission and carbon reduction policies.

Does the Belt and Road Initiative Increase the Carbon Emission Intensity of Paticipating Countries?

The impact that the Belt and Road Initiative(BRI)has had on carbon emissions is a hotly debated issue.Using a panel dataset of 178 countries from 2002 to 2017,and applying the quantile difference-in-difference method in different industries,this study finds that,first,the BRI overall tends to reduce the carbon emission intensity of BRI countries.Second,the impact of BRI on reducing the carbon emission intensity is significant for BRI countries at higher(0.8 and 0.9)and lower(0.2 and 0.3)carbon emission intensity quantiles but it is insignificant for those at medium levels.Third,the BRI has significant impacts on reducing carbon emission intensity in the energy-intensive industries,and this effect is the highest at the quantile level of 0.9 for all three industries considered here:transportation,electric and heating,and manufacturing and construction.These results indicate that establishing BRI cooperation with China will improve the environment and enhance the sustainable development ability of BRI countries.

Impact of the Construction of Ecological Civilization Demonstration Areas on Carbon Emission Intensity

The development path from attaching importance to environmental protection to the theory of ecological conservation,then to piloting ecological civilization demonstration areas,marks that China’s ecological conservation has gradually moved from theoretical construction to practical exploration,based on the new idea that“lucid waters and lush mountains are invaluable assets.”It is still an ordeal for China’s ecological conservation in the context of global warming how to reduce carbon emission intensity while maintaining sustained economic growth.Under the dual constraints of peaking carbon dioxide emissions before 2030 and achieving carbon neutrality before 2060(“dual carbon”goals),this paper employs the five national ecological civilization pilot demonstration areas(ECDAs)established in 2014 as quasi-natural experiments based on the panel data of 30 Chinese provincial regions from 2003 to 2019.Based on the analysis of the policy implementation background and the theoretical mechanism of its impact on carbon emission intensity,the synthetic control method and difference in differences method are adopted to test the impact of the construction of ECDAs on carbon emission intensity and examine the spatial spillover effect of the pilot policies.The study shows that the construction of ECDAs has significantly reduced carbon emission intensity as a whole,especially in Fujian,Guizhou,and Yunnan Provinces.Moreover,the conclusions successfully pass the robustness test.The mechanism analysis results demonstrate that the construction of ECDAs can lower carbon emission intensity through the positive incentives from boosting technological progress and developing green finance,and the reversal pressure mechanism of optimizing the energy structure and improving the market segmentation.The analysis results of the spatial spillover effect indicate that the construction of ECDAs plays a significant role in reducing carbon emission intensity in the region and its adjacent areas.Therefore,China should introduce ECDAs and the experience gained to more regions.Meanwhile,China should spare no effort to seek multi-dimensional paths to reduce carbon emissions in view of regional differences in green development,and strengthen cross-regional communications and cooperation to realize the goals of carbon emission reduction.

Uncertainty of temperature rise under nationally determined contributions and carbon neutral policies

Nationally determined contributions raised by Paris Agreement aim to control the temperature rise below 2°C or even 1.5°C at the end of the 21st century,compared to pre-industrial levels.However,the climate response of the Nationally Determined Contributions(NDCs)remains uncertain due to unstable policies and their credibility.In this study,we calculated the uncertainty of global temperature rise caused by uncertain NDCs and carbon-neutral policies and discussed the difficulty of policy implementation.The results show that there will be 8 GtC uncertainty in emission at the end of the 21st century,responsible for the temperature rise of 0.37°C(1.73–2.10°C).A delayed policy in emission reduction by major emitters would result in a temperature rise of over 2°C,while under non-delay policy,the 2°C target will be possibly achieved.Besides,low-emission countries would introduce a 30 GtC cumulative emission uncertainty at the end of the 21st century if there are no restrictions,leading to a 0.3°C global warming uncertainty.Developed countries need more substantial reductions in carbon intensity to achieve their climate policies while developing countries are under less pressure.The reduction of carbon intensity requires the strengthening of technical and economic methods.This study provides a reference for the realization of emission policies and temperature rise targets.

Pathways to peak carbon emissions in China by 2030: An analysis in relation to the economic growth rate

With less than ten years left to meet its pledge to peak carbon dioxide emissions(peak emissions hereafter) by 2030,China has entered a critical emissions reduction stage. How to meet this commitment in a context in which GDP per capita will double from 2020 by 2035 is a major decision-making issue for the Chinese government and people and one which warrants further study. To reveal the relationships between the GDP growth rate, the rate of decrease of carbon intensity and the time to reach peak emissions, this study translates the question as to “when China's carbon emissions peak will occur” into “how can one control the rate of carbon intensity decrease at a given GDP growth rate”. In the light of the results of a random forest algorithm used to identify and project the key drivers of carbon intensity in China, a mathematical model was developed to simulate different scenarios relating to decreases in carbon intensity. The date at which Chinese carbon emissions will peak is predicted by comparing the rate of decrease of carbon intensity with the GDP growth rate. The results show that the time to peak emissions depends on the relationship between the rate of decrease of carbon intensity and the GDP growth rate, where the former depends mainly on the energy structure and policy. If China's annual GDP growth rate were 5.0% during the 15th Five-Year Plan, and if the share of non-fossil energy in total energy consumption were 23.0% or above, China's carbon emissions will peak before2030. If the share of non-fossil fuels were 20.0% or less, China might not be able to reach its 2030 target. In this latter case an acceleration in the pace of energy restructuring would be required to reach peak emissions before 2030. The projected peak emissions scenarios suggest that the carbon peak will occur between 2025 to 2029, with average peak emissions of 11.2 billion tons and a distribution ranging from a minimum of 10.5 billion and a maximum of 11.9 billion tons. If the GDP growth rate were4.5%, 5.5% or 6.0% during the 15th Five-year Plan, the share of non-fossil energy must reach 23.0%, 25.0% or 27.0%,respectively, to ensure that emissions peak by 2030. The results of this study provide a series of reference points for China's pursuit of feasible pathways to peak carbon emissions by 2030.

Potential Effect of Interprovincial Carbon Trading in China

Taking provincial panel data of China as the sample,this paper simulates and analyzes the potential effect of carbon emissions trading in China under the condition of unconstrained and constrained respectively.The results are as follows.(1)As the theoretical basis of carbon trading,the shadow price of carbon dioxide is inclined to rise generally.The absolute gap among provinces and that among eight regions tend to expand,but the relative gap tends to narrow.(2)With the reduction of national carbon intensity to the greatest degree as the aim,carbon trading could reduce the carbon intensity by 20.06%under the condition of given national GDP.If the strict constraint of national GDP is relaxed,and the constraint of economic growth and environment conservation of each region is imposed,carbon trading could reduce the carbon intensity by 22.20%.(3)The current overall promotion process of carbon intensity in China has achieved the phased goal of the Copenhagen Conference commitment.The interprovincial carbon trading could strongly boost the improvement of carbon intensity,and the general requirements of Copenhagen Conference could be satisfied.

Carbon footprint of different industrial spaces based on energy consumption in China

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 industrial 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/hm^2, in which, carbon emission intensity of living ＆ industrial-commercial space and of transportation industrial space was 55.16 t/hm^2 and 49.65 t/hm^2 respectively, they were high-carbon-emission industrial spaces among others. （3） Carbon footprint caused by industrial activities of China in 2007 was 522.34×10^6 hm^2, which brought about ecological deficit of 28.69×10^6 hm^2, 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 ecological deficit caused by industrial activities was small in 2007. （4） Per unit area carbon footprint of industrial space in China was about 0.63 hm^2/hm^2 in 2007, in which that of living ＆ industrial-commercial space was the highest （17.5 hm^2/hm^2）. The per unit area carbon footprint of different industrial spaces all presented a declining trend from east to west of China.