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.

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.

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.

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 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.

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.

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.

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.

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.

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.

Carbon Emission of Regional Land Use and Its Decomposition Analysis: Case Study of Nanjing City, China

Through the matching relationship between land use types and carbon emission items, this paper estimated carbon emissions of different land use types in Nanjing City, China and analyzed the influencing factors of carbon emissions by Logarithmic Mean Divisia Index（LMDI） model. The main conclusions are as follows： 1） Total anthropogenic carbon emission of Nanjing increased from 1.22928 ×10^7 t in 2000 to 3.06939 × 10^7 t in 2009, in which the carbon emission of Inhabitation, mining ＆ manufacturing land accounted for 93% of the total. 2） The average land use carbon emission intensity of Nanjing in 2009 was 46.63 t/ha, in which carbon emission intensity of Inhabitation, mining ＆ manufacturing land was the highest（200.52 t/ha）, which was much higher than that of other land use types. 3） The average carbon source intensity in Nanjing was 16 times of the average carbon sink intensity（2.83 t/ha） in 2009, indicating that Nanjing was confronted with serious carbon deficit and huge carbon cycle pressure. 4） Land use area per unit GDP was an inhibitory factor for the increase of carbon emissions, while the other factors were all contributing factors. 5） Carbon emission effect evaluation should be introduced into land use activities to formulate low-carbon land use strategies in regional development.

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.

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.

Structural Decomposition Analysis of the Decline in China's CO_2 Emission Intensity 2005–2010

Here we utilize input-output tables for 2005 and 2010 to calculate the change in carbon dioxide emission intensity. Results show that total carbon dioxide emissions were 6.79 and 9.30 billion tons, and carbon dioxide emission intensity was 0.37 and 0.33 ton per thousand CNY in 2005 and 2010, respectively. Carbon dioxide emission intensity declined 11% over these five years. We used structural decomposition analysis modeling to measure the effect of four factors on this reduction in intensity. We found that the contribution values of energy structure, energy efficiency, economic growth mode and economic structure were -0.001, -0.102, 0.050, and 0.013 ton per thousand CNY, respectively. Changes in energy efficiency and energy structure are major factors promoting decreases in carbon dioxide emission intensity; the effect of the former is more distinct than the latter. Economic growth mode and economic structure are major factors that increase carbon dioxide emission intensity, whereby the effect of the former is more distinct than the latter.

CO_2 Emission of Fossil Fuel Consumption of China's Mainland from 1991 to 2010

In this article, we calculate China's Mainland’s CO2 emission of fossil fuel consumption from 1991 to 2010 following the apparent consumption method recommend by IPCC： （i） the scale of CO2 emissions has increased nearly to 4 times as that in 1991; （ii） coal consumption constitutes the highest proportion due to the richness of coal resources in China; （iii） per capita CO2 emission has increased from 1.98 to 5.57 t CO2 ; （iv） carbon emission intensity declined significantly from 6.66 to 1.07 kg CO2 USD -1 , but recently it tends to be stable; and （v） regional develop gaps remain in China's Mainland, for according to the provincial data, in many developing regions economic increase over-reliance on fossil fuel consumption. China has made the promises and already taken actions to deal with the high carbon emission. Comprehensively considering the sustainability of development and the uncertainties remaining in global climate change, healthier structures of industry, intensive usage of fossil fuel, and a more balanced development pattern among the southern, central and western China should be put more emphasis.

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.

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.

Role of CCUS in carbon neutral power system

Achieving carbon neutrality by 2060 is an ambitious goal to promote the green transition of economy and society in China.Highly relying on coal and contributing nearly half of CO_(2) emission,power industry is the key area for reaching carbon-neutral goal.On basis of carbon balance,a criterial equation of carbon neutral for power system is provided.By means of the equation,the different effects of three technical approaches to achieve carbon neutrality,including energy efficiency improvement,shifting energy structure and CO_(2) capture,utilization and storage(CCUS)technology,had been evaluated.The results indicate that building a carbon-neutral power system requires comprehensive coordination between energy efficiency,renewable energy and CCUS technology.In particular,the unique role of CCUS in achieving carbon neutral target was investigated.For any power systems with fossil energy input,CCUS and negative emission technologies is indispensable to reach carbon neutrality.However,rather high energy consumption and costs is the critical gas deterring the large scale deployment of CCUS.Considering the specific conditions of China’s power industry,before the time window between 2030 and 2040 being closed,CCUS would either be ready for large scale deployment by reducing energy consumption and costs,or be phased out along with the most coal power plants.Conclusively,carbon neutral scenario will give CCUS the last chance to decarbonize the fossil fuel,which has great significance for China.

多层次城市国土空间碳排放分配与评估框架——以兴安盟为例

It is proven a powerful tool to reduce carbon emissions by regulating urban land use structure.To leverage this tool,land-use carbon emission intensity(LUCEI)is the critical indicator to bridge carbon emissions effects of natural and human activities to land use structure.Current studies try to established the carbon emission allocation framework of“carbon emission inventory–land use category”and use it to estimate the LUCEI.However,none of the frameworks work at multiple spatial scales:the total carbon emissions and the land use category at different territorial levels do not conform with each other,impeding the synergetic effects of the low-carbon planning at different territorial levels.This study establishes a new framework of carbon emission estimation and allocation for the three territorial levels of municipality,city proper,and district and conducts a case study on Hinggan Prefecture.With the new framework,the carbon emission intensity of the entire land use category is being systematically differentiated,enabling the clarification of the linkages between LUCEI and the characteristics of energy structure,industrial structure,and urban forms of cities.The comparison of LUCEI of residential and transportation land between cities identifies the characteristics of urban form that are apt to high carbon emissions.The biggest contribution of the framework established in this study provides a technical tool to introduce carbon emission quantifi-cation into the territorial and spatial planning system.It may help deepen the understanding about the spatial pattern of carbon emissions and support a more refined estimation and comparison of the carbon effects of land use planning schemes.