The pain of inequality:Income gap and carbon intensity of well-being

The 2030 Agenda for Sustainable Development of the United Nations sets out 17 sustainable development goals(SDGs)that call for global action to end poverty,protect the planet,and improve the lives and futures of all people,including reducing inequality and taking climate action.The academic and policy issues corresponding to these two goals are income distribution and low-carbon development respectively.This paper makes a connection between the two and examines the impact of income gap on carbon intensity of well-being(CIWB)based on panel data of 40 countries around the world,which has important theoretical significance and empirical reference value.The main conclusions are as follows:(1)During the sample period,the carbon intensity of well-being of 36 in the 40 countries showed a downward trend,indicating that the pressure brought by the increase of unit well-being level on carbon emission space was gradually decreasing.The biggest drop in carbon intensity of well-being is in Estonia.(2)According to the average value of the past years,the income gaps are large in Colombia,Costa Rica,Paraguay,Ecuador and Peru,and the five countries with the smallest income gap are Ukraine,Slovenia,Belarus,the Czech Republic and Kyrgyzstan Republic.(3)The regression results of the econometric model with carbon intensity of well-being as the dependent variable,income gap as the independent variable,and urbanization rate,energy consumption structure and export trade as the control variables show that the increase of income gap will increase carbon intensity of well-being,and the increase of urbanization rate,renewable energy consumption and export dependence will reduce carbon intensity of well-being.Finally,according to the research conclusions,the policy implications for China's future high-quality development are extracted.

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.

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.

Study on carbon intensity trading market based on carbon finance mechanism

As the largest developing country in the world, China has not be involved in the obligation of emissions reduction in the （〈Kyoto Protocol）） . But it has become the largest CO2 emissions countries in the world. This makes China confronted with more pressure of carbon emissions reduction in the post-Kyoto era, and face great challenges in response to climate change issues. On one hand, China＇ s economic growth stage has decided that the situation of more energy consumption and increased carbon emissions is diffficult to reverse in the short term; On the other hand, the traditional policy under the control of total amount of carbon emission has largely restricted economic development. If a developing country in economic transition is carried out compulsory absolute amount of carbon reduction policies, its economic activity and social consumption will be imposed additional constraints inevitably, which will eventually lead to lower economic competitiveness and decline in social standards of living. Ultimately it will affect the good effects of carbon emissions reduction, so the policy can not achieve a satisfactory result. This paper introduces the financial mechanism into the carbon market model, extends the time of model from one phase to multi-phase. And this paper tries to establish a cross-time carbon credits trade system, and the current strength of the traditional carbon emission market trade model is extended. The paper designs two type of option mechanism model--call options trade carbon emissions model and put options carbon emissions model. Models＇ results show that choosing options tool to extend our traditional carbon market model can bring following impacts on carbon market development： trade costs have fallen, the carbon intensity also has descended, and has realized the flow of carbon intensity in diffident time; it enables manufacturers to effectively avoid the risk of carbon emissions trade; it increases the flexibility and maneuverability of the carbon trade market. Finally, the policy recommendations in the financial mechanisms carbon market trade are put forward.

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.

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.

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.

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.

Assessing China 2030 carbon emissions from fossil fuels:based on system dynamics model

The Chinese government has set ambitious targets to reduce the per unit of GDP by 40% ~45% during 2005 to 2020 and achieve the intensity peaking of carbon emissions of CO2 emissions a- round 2030. The T21 national development model for China was developed for the purpose of analy- zing the effects of long-term national policies that relate to carbon emissions, loss of farm land, water shortage, energy security, food security, and their contributions to this reduction target. The focus of this paper is on the policies that have substantial impacts on carbon emissions from fossil fuels. Four scenarios are developed with the model to simulate future carbon emissions ： 1 ） the BAU （ busi- ness as usual） scenario, showing the likely results of continuing current policies; 2 ） the TECH （technology） scenario showing the effects of more investment in renewable energy sources and promoting more energy efficient technologies; 3 ） the BEHAVIOR scenario, showing how government tax and price policies, together with public education programs, would instigate behaviour changes towards more sustainable living; and 4 ） the TECH＆BEHA scenario, which shows the results of combining scenarios 2 and 3. The simulation results show that CO2 emissions reduction targets of China are achievable, but also require great effort to put in.

Industrial Carbon Emissions Status and Analysis Based on Energy Consumption

With frequent disastrous weathers and increasingly prominent GHG effects in recent years, normal existence and development of mankind are facing unprecedented threats and challenges. GHG emissions mitigation for the global climate changes has been the focus of concern of the world. As the biggest developing country and the second largest country of carbon-emission, China attaches importance to the carbon emission reduction. The major GHG component is carbon dioxide and in China, the emis- sion of carbon dioxide is mainly from industrial production. In the paper, the status and trend of Coz emission from industrial departments, high-carbon emission and its specific industries are shown in statistics. Meanwhile, the policy environment, industrial organization structure and technology of carbon high emission are all discussed based on practical situations in these departments and industries. At the end, through the analysis of gray correlation, correlativity is explored for both fossil energy consumption and total carbon emission, and also for the production value and carbon emission of each industrial sector. Some policy proposals for the establishment of low-carbon industries and transition of economic development pattern are set forth.

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.

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.

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.

Tire Manufacturer Fighting Climate Changes

This paper presents methods and strategy promoted by an operator of tire rubber manufacturer in order to reduce CO2 emissions. This paper presents calculation methods of GHG emissions and data on production activities, as well as fuel consumption, energy, etc. This example shows that environmental investments are effective primarily in the environmental aspect, but they can become profitable （the carbon trading market of GHG allowances and by providing alternative energy in national energy system, resulting in ＂green certificates＂）.

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.

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.

Empirically Analysis of the CO_2 Emissions Embodied in Exports of China

In this paper,using the input-output model,the author first calculated the CO 2 emissions embodied in exports of China in 2002 and 2007.Then,the author empirically analyzed problems existing in the composition of exported products and analyzed its possible reasons.The research results of this paper are as follows:Since China's entry into WTO,the CO 2 emissions embodied in exports of China have been increasing rapidly;the value of exported products of high-carbon emissions industries accounts for a relatively higher proportion to China's total exports value because China's carbon intensive products have a certain competitive advantage.Additionally,this paper has put forward relevant suggestions based on these results.