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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 The city of Pecs in Hungary has developed an energy strategy to be implemented in the years to come which proposes structural changes in both the supply and demand sides. This paper offers a model based on the proposed system aimed at providing a basis for comparison for decision-makers. The model has been developed with the help of energy system analysis tool energyPRO, and covers the three basic sectors of heat, electricity and transport. It shows the energy system of Pecs in terms of hourly production and demand levels – and these values enable the model to analyse intermittent energy sources. The model is also validated – to ensure that it is satisfactory for the simulation of future energy systems. It analyses two scenarios – one where the city does not implement the changes proposed in the strategy, and one where it does. The paper compares the two scenarios based on sustainability, energy security and affordability.

Abstract The city of Pecs in Hungary has developed an energy strategy to be implemented in the years to come which proposes structural changes in both the supply and demand sides. This paper offers a model based on the proposed system aimed at providing a basis for comparison for decision-makers. The model has been developed with the help of energy system analysis tool energyPRO, and covers the three basic sectors of heat, electricity and transport. It shows the energy system of Pecs in terms of hourly production and demand levels – and these values enable the model to analyse intermittent energy sources. The model is also validated – to ensure that it is satisfactory for the simulation of future energy systems. It analyses two scenarios – one where the city does not implement the changes proposed in the strategy, and one where it does. The paper compares the two scenarios based on sustainability, energy security and affordability.

Abstract The use of fossil fuel vehicles is one of the factors responsible for the degradation of air quality in urban areas. In order to reduce levels of air pollution in metropolitan areas, several countries have encouraged the use of electric vehicles in the cities. However, due to the high investment costs in this class of vehicles, it is expected that the spatial distribution of electric vehicles' adopters will be heterogeneous. The additional charging power required by electric vehicles' batteries can change operation and expansion planning of power distribution utilities. In addition, urban planning agencies should analyze the most suitable locations for the construction of electric vehicle recharging stations. Thus, in order to provide information for the planning of electric mobility services in the city, this paper presents a spatiotemporal model for estimating the rate of electric vehicles' adopters per subareas. Results are spatial databases that can be viewed in geographic information systems to observe regions with greater expectancy of residential electric vehicle adopters. These outcomes can help utilities to develop new services that ground on the rising availability of electric mobility in urban zones.

Abstract The use of fossil fuel vehicles is one of the factors responsible for the degradation of air quality in urban areas. In order to reduce levels of air pollution in metropolitan areas, several countries have encouraged the use of electric vehicles in the cities. However, due to the high investment costs in this class of vehicles, it is expected that the spatial distribution of electric vehicles' adopters will be heterogeneous. The additional charging power required by electric vehicles' batteries can change operation and expansion planning of power distribution utilities. In addition, urban planning agencies should analyze the most suitable locations for the construction of electric vehicle recharging stations. Thus, in order to provide information for the planning of electric mobility services in the city, this paper presents a spatiotemporal model for estimating the rate of electric vehicles' adopters per subareas. Results are spatial databases that can be viewed in geographic information systems to observe regions with greater expectancy of residential electric vehicle adopters. These outcomes can help utilities to develop new services that ground on the rising availability of electric mobility in urban zones.

A balance between industrial pollution and economic growth becomes a major policy issue to attain a sustainable society in the world. To discuss the problem from economics and business perspectives, this study proposes a new use of DEA (Data Envelopment Analysis) as a methodology for unified (operational and environmental) assessment. A unique feature of the proposed approach is that it separates outputs into desirable and undesirable categories. Such separation is important because energy industries usually produce both desirable and undesirable outputs. This study discusses how to unify the two types of outputs under natural and managerial disposability. The proposed DEA approach evaluates various organizations by the three efficiency measures such as OE (Operational Efficiency), UEN (Unified Efficiency under Natural disposability) and UENM (Unified Efficiency under Natural and Managerial disposability). An important feature of UENM is that it separates inputs into two categories and unifies them under the two disposability concepts in addition to the proposed output separation and unification. This study incorporates an amount of capital assets for technology innovation, as one of the two input group, into the measurement of UENM. Then, it compares UENM with the other two efficiency measures. This study is the first research effort in which DEA has an analytical capability to quantify the importance of investment on capital assets for technology innovation. To confirm the practicality of the proposed approach, this study applies the three efficiency measures to a data set regarding manufacturing and non-manufacturing industries of 47 prefectures in Japan. This study empirically confirms the validity of Porter hypothesis in Japanese manufacturing industries, so implying that environmental regulation has been effective for betterment on the performance of Japanese manufacturing industries. Another important finding is that the emission of greenhouse gases is a main source of unified inefficiency in the two groups of industries. Therefore, Japanese industries, examined in this study, need to make their efforts to reduce the greenhouse gas emissions and air pollution substances by investing in capital assets for technology innovation.

A balance between industrial pollution and economic growth becomes a major policy issue to attain a sustainable society in the world. To discuss the problem from economics and business perspectives, this study proposes a new use of DEA (Data Envelopment Analysis) as a methodology for unified (operational and environmental) assessment. A unique feature of the proposed approach is that it separates outputs into desirable and undesirable categories. Such separation is important because energy industries usually produce both desirable and undesirable outputs. This study discusses how to unify the two types of outputs under natural and managerial disposability. The proposed DEA approach evaluates various organizations by the three efficiency measures such as OE (Operational Efficiency), UEN (Unified Efficiency under Natural disposability) and UENM (Unified Efficiency under Natural and Managerial disposability). An important feature of UENM is that it separates inputs into two categories and unifies them under the two disposability concepts in addition to the proposed output separation and unification. This study incorporates an amount of capital assets for technology innovation, as one of the two input group, into the measurement of UENM. Then, it compares UENM with the other two efficiency measures. This study is the first research effort in which DEA has an analytical capability to quantify the importance of investment on capital assets for technology innovation. To confirm the practicality of the proposed approach, this study applies the three efficiency measures to a data set regarding manufacturing and non-manufacturing industries of 47 prefectures in Japan. This study empirically confirms the validity of Porter hypothesis in Japanese manufacturing industries, so implying that environmental regulation has been effective for betterment on the performance of Japanese manufacturing industries. Another important finding is that the emission of greenhouse gases is a main source of unified inefficiency in the two groups of industries. Therefore, Japanese industries, examined in this study, need to make their efforts to reduce the greenhouse gas emissions and air pollution substances by investing in capital assets for technology innovation.

Abstract In the summer of 1989 a survey was conducted to collect data on household-energy consumption in Indian cities. The survey was conducted in three urban areas of varying sizes. The end-uses considered were cooking, water heating, lighting, air cooling, entertainment, cold storage, and washing/laundry. The surveys involved examination of the types and quantities of energy used to satisfy each of these services. The survey sample in each of the three cities was broken down by income group, allowing for a careful examination of the influence of household income on lifestyle patterns and related energy use choices. Among the houses surveyed were 75 households in Pune, India, that took part in a 1982 household energy study as well. The re-surveying process allowed for an analysis of longitudinal changes in residential energy use. Based on the survey findings, a number of recommendations are provided for improving the provision and use of energy in urban households in India.