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Abstract China's carbon emissions have been ranking first in the world. This study filled in the gaps in research, decomposed carbon intensity from the perspective of time, space and industry. A decoupling effort model based on factor decomposition models was constructed to analyze the driving factors of carbon emissions and economic decoupling, which builded a foundation for achieving sustainable economic development. Using the Logarithmic Mean Divisia Index method (LMDI), the paper measured the carbon emission intensity of 29 provinces and cities in China from 1998 to 2019, and decomposed the decoupling effect between GDP and carbon emission on the basis of factor decomposition by tapio. The results showed that: (1) Carbon intensity declined first, then rise lightly, and finally declined steadily. For the primary industry and the tertiary industry, the carbon intensity declined steadily, while the carbon intensity increased accordingly to the overall carbon intensity. In terms of spatial evolution, the regional differences between different provinces decreased correspondingly. (2) The cumulative contribution rates of these three effects, i.e., technological progress, industrial structure and regional scale were 106.3299%, −15.1486% and 8.8188%, respectively. There were obvious differences of these cumulative contribution rates of carbon intensity among different provinces. (3) From the perspective of industrial, technological progress effect is the largest contribution for carbon intensity in the secondary industry. The Industrial structure effect mainly affects the primary and tertiary industries; and no significant difference in regional scale effect. (4) The decoupling effect gradually improved, and technological progress has played an absolute leading role in promoting the decoupling effect. Based on the research results, the key policy recommendation are put forward as follows: (1) Further improve the technological level and support clean technology enterprises. (2) Promote industrial upgrading in backward industrial provinces (3) Promote regional assistance and the introduction of high-quality foreign investment.

Abstract China's carbon emissions have been ranking first in the world. This study filled in the gaps in research, decomposed carbon intensity from the perspective of time, space and industry. A decoupling effort model based on factor decomposition models was constructed to analyze the driving factors of carbon emissions and economic decoupling, which builded a foundation for achieving sustainable economic development. Using the Logarithmic Mean Divisia Index method (LMDI), the paper measured the carbon emission intensity of 29 provinces and cities in China from 1998 to 2019, and decomposed the decoupling effect between GDP and carbon emission on the basis of factor decomposition by tapio. The results showed that: (1) Carbon intensity declined first, then rise lightly, and finally declined steadily. For the primary industry and the tertiary industry, the carbon intensity declined steadily, while the carbon intensity increased accordingly to the overall carbon intensity. In terms of spatial evolution, the regional differences between different provinces decreased correspondingly. (2) The cumulative contribution rates of these three effects, i.e., technological progress, industrial structure and regional scale were 106.3299%, −15.1486% and 8.8188%, respectively. There were obvious differences of these cumulative contribution rates of carbon intensity among different provinces. (3) From the perspective of industrial, technological progress effect is the largest contribution for carbon intensity in the secondary industry. The Industrial structure effect mainly affects the primary and tertiary industries; and no significant difference in regional scale effect. (4) The decoupling effect gradually improved, and technological progress has played an absolute leading role in promoting the decoupling effect. Based on the research results, the key policy recommendation are put forward as follows: (1) Further improve the technological level and support clean technology enterprises. (2) Promote industrial upgrading in backward industrial provinces (3) Promote regional assistance and the introduction of high-quality foreign investment.

Abstract There will be many issues in the coming period of energy transition, not least of which is the fate of the jobs in the current energy sector and the communities supported by those jobs. The technical challenges are described, and the value of CCUS as a technology that can strongly mitigate potential negative impacts is shown. The need for governmental support if CCUS is to be successful and current options for governmental support of CCUS are discussed.

Abstract There will be many issues in the coming period of energy transition, not least of which is the fate of the jobs in the current energy sector and the communities supported by those jobs. The technical challenges are described, and the value of CCUS as a technology that can strongly mitigate potential negative impacts is shown. The need for governmental support if CCUS is to be successful and current options for governmental support of CCUS are discussed.

Abstract The ecological footprint is a measure of the resources necessary to produce the goods that an individual or population consumes. It is also used as a measure of sustainability, though evidence suggests that it falls short. The assumptions behind footprint calculations have been extensively criticized; I present here further evidence that it fails to satisfy simple economic principles because the basic assumptions are contradicted by both theory and historical data. Specifically, I argue that the footprint arbitrarily assumes both zero greenhouse gas emissions, which may not be ex ante optimal, and national boundaries, which makes extrapolating from the average ecological footprint problematic. The footprint also cannot take into account intensive production, and so comparisons to biocapacity are erroneous. Using only the assumptions of the footprint then, one could argue that the Earth can sustain greatly increased production, though there are important limitations that the footprint cannot address, such as land degradation. Finally, the lack of correlation between land degradation and the ecological footprint obscures the effects of a larger sustainability problem. Better measures of sustainability would address these issues directly.

Abstract The ecological footprint is a measure of the resources necessary to produce the goods that an individual or population consumes. It is also used as a measure of sustainability, though evidence suggests that it falls short. The assumptions behind footprint calculations have been extensively criticized; I present here further evidence that it fails to satisfy simple economic principles because the basic assumptions are contradicted by both theory and historical data. Specifically, I argue that the footprint arbitrarily assumes both zero greenhouse gas emissions, which may not be ex ante optimal, and national boundaries, which makes extrapolating from the average ecological footprint problematic. The footprint also cannot take into account intensive production, and so comparisons to biocapacity are erroneous. Using only the assumptions of the footprint then, one could argue that the Earth can sustain greatly increased production, though there are important limitations that the footprint cannot address, such as land degradation. Finally, the lack of correlation between land degradation and the ecological footprint obscures the effects of a larger sustainability problem. Better measures of sustainability would address these issues directly.

In an idealised industrial ecosystem (IE), firms and organisations utilise each other's material and energy flows including wastes and by-products to reduce the system's virgin material and energy input as well as the waste and emission output from the system as a whole, and contribute to sustainable development (SD). IE complements the more conventional individual flow, product, process, organisation, individual actor or sector-focused environmental management approaches and tools with network or systems level approaches. The first research objective of this paper is to construct indicators for IE. The second task is to test the use of these indicators with "what if?" material and energy flow scenarios for the energy and waste system of Satakunta region in Finland including 28 municipalities. Using literature analysis as a source, we arrive at environmental indicators of carbon dioxide (CO2) equivalents, and at economic indicators of fuel, energy and waste management costs and revenues. The social indicators show the employment effects of the waste management system. The scenarios analyse the current situation (0-scenario) against alternative situations in the future. The future scenarios are developed according to the known and anticipated trends in international and national policy and legislation. The indicator application in the scenarios produces social, environmental and economic effects of waste management in four categories: direct negative, direct positive, indirect negative and indirect positive. Industrial ecosystem theory emphasises the utilisation of wastes as a resource with value alongside the objective of reducing waste. Therefore, the indirect positive effects of waste management are important, as well as the conventional focus of waste management, which has usually been on direct positive effects. The main difficulties in our argument are the system boundary definition, the qualitatively different nature of environmental, economic and social effects and indicators as well as the lack of qualitative or interview data on the preferences and interests of the actors involved.

In an idealised industrial ecosystem (IE), firms and organisations utilise each other's material and energy flows including wastes and by-products to reduce the system's virgin material and energy input as well as the waste and emission output from the system as a whole, and contribute to sustainable development (SD). IE complements the more conventional individual flow, product, process, organisation, individual actor or sector-focused environmental management approaches and tools with network or systems level approaches. The first research objective of this paper is to construct indicators for IE. The second task is to test the use of these indicators with "what if?" material and energy flow scenarios for the energy and waste system of Satakunta region in Finland including 28 municipalities. Using literature analysis as a source, we arrive at environmental indicators of carbon dioxide (CO2) equivalents, and at economic indicators of fuel, energy and waste management costs and revenues. The social indicators show the employment effects of the waste management system. The scenarios analyse the current situation (0-scenario) against alternative situations in the future. The future scenarios are developed according to the known and anticipated trends in international and national policy and legislation. The indicator application in the scenarios produces social, environmental and economic effects of waste management in four categories: direct negative, direct positive, indirect negative and indirect positive. Industrial ecosystem theory emphasises the utilisation of wastes as a resource with value alongside the objective of reducing waste. Therefore, the indirect positive effects of waste management are important, as well as the conventional focus of waste management, which has usually been on direct positive effects. The main difficulties in our argument are the system boundary definition, the qualitatively different nature of environmental, economic and social effects and indicators as well as the lack of qualitative or interview data on the preferences and interests of the actors involved.

The purpose of this paper is to research the relation among environmental quality and renewable energy in the RECAI country group. The study used per capita CO2 emission, energy intensity, and Aggregate National Savings as a measure of environmental quality. Other variables used in the study are renewable energy consumption, fossil fuel consumption, GDP per capita, and foreign direct investments. In the study, three different models to see different environmental quality indicators by panel quantile method for 19202090-. According to the results obtained, unlike other models, renewable energy consumption in model 1 positively affects energy intensity in all quantiles. In other words, renewable energy consumption negatively affects environmental quality. In model 1 and model 3, the coefficients of fossil fuel consumption were positive and negative, respectively. Unlike model 2, the coefficient estimates of fossil fuel consumption in model 3 were predominantly negative. Fossil fuel consumption shows a positive effect on environmental quality, which is similar to model 1. Economic growth negatively affects environmental quality in all models. There is a one-way causal relationship from renewable energy consumption to energy intensity and energy intensity to growth.