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Energy Research
12. Responsible consumption
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Energies

Energy Efficiency Evaluation Based on Data Envelopment Analysis: A Literature Review
descriptionPublicationkeyboard_double_arrow_right Article , Journal 2020Publisher:MDPI AG
Authors: Tao Xu; Jianxin You; Hui Li; Luning Shao;
doi: 10.3390/en13143548
doi: 10.3390/en13143548
The importance and urgency of energy efficiency in sustainable development are increasing. Accurate assessment of energy efficiency is of considerable significance and necessity. The data envelopment analysis (DEA) method has been widely used to study energy efficiency as a total factor efficiency assessment method. In order to summarize the latest research on DEA in the field of energy efficiency, this article first analyzes the overall situation of related literature published in 2011–2019. Subsequently, the definition, measurement and evaluation variables of energy efficiency are introduced. After that, this article reviews the current DEA model and its extension models and applications based on different scenarios. Finally, considering the shortcomings of the existing DEA model, possible future research topics are proposed.
Energiesarrow_drop_down
Energies
Article . 2020 . Peer-reviewed
License: CC BY
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Energies
Article
License: CC BY
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Energies
Article . 2020
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Energies
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Energies
Article . 2020 . Peer-reviewed
License: CC BY
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Article . 2020
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Energy Efficiency Evaluation Based on Data Envelopment Analysis: A Literature Review
descriptionPublicationkeyboard_double_arrow_right Article , Journal 2020Publisher:MDPI AG
Authors: Tao Xu; Jianxin You; Hui Li; Luning Shao;
doi: 10.3390/en13143548
doi: 10.3390/en13143548
The importance and urgency of energy efficiency in sustainable development are increasing. Accurate assessment of energy efficiency is of considerable significance and necessity. The data envelopment analysis (DEA) method has been widely used to study energy efficiency as a total factor efficiency assessment method. In order to summarize the latest research on DEA in the field of energy efficiency, this article first analyzes the overall situation of related literature published in 2011–2019. Subsequently, the definition, measurement and evaluation variables of energy efficiency are introduced. After that, this article reviews the current DEA model and its extension models and applications based on different scenarios. Finally, considering the shortcomings of the existing DEA model, possible future research topics are proposed.
Energiesarrow_drop_down
Energies
Article . 2020 . Peer-reviewed
License: CC BY
Data sources: Crossref
Energies
Article
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Energies
Article . 2020
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Energies
Article . 2020 . Peer-reviewed
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Analysis of Changes in the Aggregate Exergy Efficiency of China’s Energy System from 2005 to 2015
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2021Publisher:MDPI AG
Authors: Yuancheng Lin; Chinhao Chong; Linwei Ma; Zheng Li; +1 Authors
Yuancheng Lin; Chinhao Chong; Linwei Ma; Zheng Li; Weidou Ni;
doi: 10.3390/en14082304
doi: 10.3390/en14082304
Analysis of the change of overall energy efficiency performance of an energy system is a fundamental work for the energy-saving policymaking. However, previous studies seldom focus on energy stages from useful energy to final service, while most attention are paid on stages from energy source to useful energy. In this paper, we develop a high-resolution the Societal Exergy Analysis and Logarithmic Mean Divisia Index (SEA-LMDI) method to analysis changes and driving factors of the aggregate exergy efficiency, in which the boundary of the SEA is extended to passive systems and final services, and a LMDI decomposition method is developed to quantify contributions of efficiency factors and structure factors of all six stages on the aggregate exergy efficiency. A case study of China during 2005–2015 reveals that: (a) the aggregate exergy efficiency from energy source to final service is only from 3.7% to 4.8% during 2005–2015, showing a huge theoretical potential of efficiency improvement. (b) Large passive losses are identified in passive systems and nearly 2/3 of useful energy can be theoretically saved by improving passive systems. (c) Deep analysis of industrial coal-fired boilers indicates that the internal structural adjustments are also important for the aggregate improvement.
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Energiesarrow_drop_down
Energies
Other literature type . 2021
License: CC BY
Full-Text: http://www.mdpi.com/1996-1073/14/8/2304/pdf
Data sources: Multidisciplinary Digital Publishing Institute
Energies
Article . 2021 . Peer-reviewed
License: CC BY
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Energies
Article
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Energies
Article . 2021
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Energies
Other literature type . 2021
License: CC BY
Full-Text: http://www.mdpi.com/1996-1073/14/8/2304/pdf
Data sources: Multidisciplinary Digital Publishing Institute
Energies
Article . 2021 . Peer-reviewed
License: CC BY
Data sources: Crossref
Energies
Article
License: CC BY
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Energies
Article . 2021
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Analysis of Changes in the Aggregate Exergy Efficiency of China’s Energy System from 2005 to 2015
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2021Publisher:MDPI AG
Authors: Yuancheng Lin; Chinhao Chong; Linwei Ma; Zheng Li; +1 Authors
Yuancheng Lin; Chinhao Chong; Linwei Ma; Zheng Li; Weidou Ni;
doi: 10.3390/en14082304
doi: 10.3390/en14082304
Analysis of the change of overall energy efficiency performance of an energy system is a fundamental work for the energy-saving policymaking. However, previous studies seldom focus on energy stages from useful energy to final service, while most attention are paid on stages from energy source to useful energy. In this paper, we develop a high-resolution the Societal Exergy Analysis and Logarithmic Mean Divisia Index (SEA-LMDI) method to analysis changes and driving factors of the aggregate exergy efficiency, in which the boundary of the SEA is extended to passive systems and final services, and a LMDI decomposition method is developed to quantify contributions of efficiency factors and structure factors of all six stages on the aggregate exergy efficiency. A case study of China during 2005–2015 reveals that: (a) the aggregate exergy efficiency from energy source to final service is only from 3.7% to 4.8% during 2005–2015, showing a huge theoretical potential of efficiency improvement. (b) Large passive losses are identified in passive systems and nearly 2/3 of useful energy can be theoretically saved by improving passive systems. (c) Deep analysis of industrial coal-fired boilers indicates that the internal structural adjustments are also important for the aggregate improvement.
downloaddonwloadFull-Text
Energiesarrow_drop_down
Energies
Other literature type . 2021
License: CC BY
Full-Text: http://www.mdpi.com/1996-1073/14/8/2304/pdf
Data sources: Multidisciplinary Digital Publishing Institute
Energies
Article . 2021 . Peer-reviewed
License: CC BY
Data sources: Crossref
Energies
Article
License: CC BY
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Energies
Article . 2021
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Energies
Other literature type . 2021
License: CC BY
Full-Text: http://www.mdpi.com/1996-1073/14/8/2304/pdf
Data sources: Multidisciplinary Digital Publishing Institute
Energies
Article . 2021 . Peer-reviewed
License: CC BY
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Energies
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Article . 2021
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Perovskite CsPbBr3 Quantum Dots Prepared Using Discarded Lead–Acid Battery Recycled Waste
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2019Publisher:MDPI AG
Authors: Lung-Chien Chen; Ching-Ho Tien; Sin-Liang Ou; Kun-Yi Lee; +5 Authors
Lung-Chien Chen; Ching-Ho Tien; Sin-Liang Ou; Kun-Yi Lee; Jianjun Tian; Zong-Liang Tseng; Hao-Tian Chen; Hao-Chung Kuo; An-Cheng Sun;
doi: 10.3390/en12061117
doi: 10.3390/en12061117
Perovskite CsPbBr3 quantum dot (CsPbBr3-QD) recovery was performed using lead scrap from lead storage batteries. The perovskite CsPbBr3-QD characteristics were analyzed using different PbO/recycled PbO2 ratios. Scanning electron microscopy (SEM) was used to observe the film surface morphology and cross-section. High-resolution transmission electron microscopy (HRTEM) and X-ray diffraction (XRD) were used to observe the perovskite CsPbBr3-QDs’ structural characteristics. A photoluminescence (PL) measurement system was used to analyze the optical properties. The results show that lead scrap from lead–acid batteries as a material for perovskite CsPbBr3-QD production can be successfully synthesized. This saves material and also proves that recycling is valuable. The proposed approach is helpful for future material shortages and materials not easily accessible. Although the efficiency is not very high, this process will be purified using recycled lead in the future to achieve higher quantum yield.
downloaddonwloadFull-Text
Energiesarrow_drop_down
Energies
Other literature type . 2019
License: CC BY
Full-Text: http://www.mdpi.com/1996-1073/12/6/1117/pdf
Data sources: Multidisciplinary Digital Publishing Institute
Energies
Article . 2019 . Peer-reviewed
License: CC BY
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Article
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Article . 2019
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Energies
Other literature type . 2019
License: CC BY
Full-Text: http://www.mdpi.com/1996-1073/12/6/1117/pdf
Data sources: Multidisciplinary Digital Publishing Institute
Energies
Article . 2019 . Peer-reviewed
License: CC BY
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Energies
Article
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Energies
Article . 2019
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Perovskite CsPbBr3 Quantum Dots Prepared Using Discarded Lead–Acid Battery Recycled Waste
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2019Publisher:MDPI AG
Authors: Lung-Chien Chen; Ching-Ho Tien; Sin-Liang Ou; Kun-Yi Lee; +5 Authors
Lung-Chien Chen; Ching-Ho Tien; Sin-Liang Ou; Kun-Yi Lee; Jianjun Tian; Zong-Liang Tseng; Hao-Tian Chen; Hao-Chung Kuo; An-Cheng Sun;
doi: 10.3390/en12061117
doi: 10.3390/en12061117
Perovskite CsPbBr3 quantum dot (CsPbBr3-QD) recovery was performed using lead scrap from lead storage batteries. The perovskite CsPbBr3-QD characteristics were analyzed using different PbO/recycled PbO2 ratios. Scanning electron microscopy (SEM) was used to observe the film surface morphology and cross-section. High-resolution transmission electron microscopy (HRTEM) and X-ray diffraction (XRD) were used to observe the perovskite CsPbBr3-QDs’ structural characteristics. A photoluminescence (PL) measurement system was used to analyze the optical properties. The results show that lead scrap from lead–acid batteries as a material for perovskite CsPbBr3-QD production can be successfully synthesized. This saves material and also proves that recycling is valuable. The proposed approach is helpful for future material shortages and materials not easily accessible. Although the efficiency is not very high, this process will be purified using recycled lead in the future to achieve higher quantum yield.
downloaddonwloadFull-Text
Energiesarrow_drop_down
Energies
Other literature type . 2019
License: CC BY
Full-Text: http://www.mdpi.com/1996-1073/12/6/1117/pdf
Data sources: Multidisciplinary Digital Publishing Institute
Energies
Article . 2019 . Peer-reviewed
License: CC BY
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Energies
Article . 2019
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Energies
Other literature type . 2019
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Full-Text: http://www.mdpi.com/1996-1073/12/6/1117/pdf
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Energies
Article . 2019 . Peer-reviewed
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Causal Dynamic Relationships between Political–Economic Factors and Export Performance in the Renewable Energy Technologies Market
descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 2018Publisher:MDPI AG
Authors: Bongsuk Sung; Cui Wen;
doi: 10.3390/en11040874
doi: 10.3390/en11040874
This study explores how political–economic forces could affect export performance in the renewable energy technologies market. We conduct panel framework analyses to verify the characteristics of panel data for 19 countries before establishing the panel estimator meant to test the effects of political–economic forces on export specialization. We consider the results of the panel framework analyses and develop an empirical model to test casual dynamic relationships between political–economic forces and export performance. The results from the least squares dummy variable-corrected estimation indicate that the major factors promoting the export specialization of renewable energy technologies are, in order of decreasing importance, public pressure, market size, and government demand-pull policy. However, the traditional energy industry has no significant effect on export performance. Finally, this study finds that dynamic effects exist in all estimations.
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Energies
Other literature type . 2018
License: CC BY
Full-Text: http://www.mdpi.com/1996-1073/11/4/874/pdf
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Energies
Article . 2018 . Peer-reviewed
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Article . 2018
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Other literature type . 2018
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Energies
Article . 2018 . Peer-reviewed
License: CC BY
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Article . 2018
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Causal Dynamic Relationships between Political–Economic Factors and Export Performance in the Renewable Energy Technologies Market
descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 2018Publisher:MDPI AG
Authors: Bongsuk Sung; Cui Wen;
doi: 10.3390/en11040874
doi: 10.3390/en11040874
This study explores how political–economic forces could affect export performance in the renewable energy technologies market. We conduct panel framework analyses to verify the characteristics of panel data for 19 countries before establishing the panel estimator meant to test the effects of political–economic forces on export specialization. We consider the results of the panel framework analyses and develop an empirical model to test casual dynamic relationships between political–economic forces and export performance. The results from the least squares dummy variable-corrected estimation indicate that the major factors promoting the export specialization of renewable energy technologies are, in order of decreasing importance, public pressure, market size, and government demand-pull policy. However, the traditional energy industry has no significant effect on export performance. Finally, this study finds that dynamic effects exist in all estimations.
downloaddonwloadFull-Text
Energiesarrow_drop_down
Energies
Other literature type . 2018
License: CC BY
Full-Text: http://www.mdpi.com/1996-1073/11/4/874/pdf
Data sources: Multidisciplinary Digital Publishing Institute
Energies
Article . 2018 . Peer-reviewed
License: CC BY
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Energies
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Article . 2018
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Other literature type . 2018
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Energies
Article . 2018 . Peer-reviewed
License: CC BY
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How Can Sustainable Public Transport Be Improved? A Traffic Sign Recognition Approach Using Convolutional Neural Network
descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 2022 Australia Publisher:MDPI AG
Authors: Jingjing Liu; Hongwei Ge; Jiajie Li; Pengcheng He; +2 Authors
Jingjing Liu; Hongwei Ge; Jiajie Li; Pengcheng He; Zhangang Hao; Michael Hitch;
doi: 10.3390/en15197386
handle: 20.500.11937/89418
doi: 10.3390/en15197386
handle: 20.500.11937/89418
Sustainable public transport is an important factor to boost urban economic development, and it is also an important part of building a low-carbon environmental society. The application of driverless technology in public transport injects new impetus into its sustainable development. Road traffic sign recognition is the key technology of driverless public transport. It is particularly important to adopt innovative algorithms to optimize the accuracy of traffic sign recognition and build sustainable public transport. Therefore, this paper proposes a convolutional neural network (CNN) based on k-means to optimize the accuracy of traffic sign recognition, and it proposes a sparse maximum CNN to identify difficult traffic signs through hierarchical classification. In the rough classification stage, k-means CNN is used to extract features, and improved support vector machine (SVM) is used for classification. Then, in the fine classification stage, sparse maximum CNN is used for classification. The research results show that the algorithm improves the accuracy of traffic sign recognition more comprehensively and effectively, and it can be effectively applied in unmanned driving technology, which will also bring new breakthroughs for the sustainable development of public transport.
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How Can Sustainable Public Transport Be Improved? A Traffic Sign Recognition Approach Using Convolutional Neural Network
descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 2022 Australia Publisher:MDPI AG
Authors: Jingjing Liu; Hongwei Ge; Jiajie Li; Pengcheng He; +2 Authors
Jingjing Liu; Hongwei Ge; Jiajie Li; Pengcheng He; Zhangang Hao; Michael Hitch;
doi: 10.3390/en15197386
handle: 20.500.11937/89418
doi: 10.3390/en15197386
handle: 20.500.11937/89418
Sustainable public transport is an important factor to boost urban economic development, and it is also an important part of building a low-carbon environmental society. The application of driverless technology in public transport injects new impetus into its sustainable development. Road traffic sign recognition is the key technology of driverless public transport. It is particularly important to adopt innovative algorithms to optimize the accuracy of traffic sign recognition and build sustainable public transport. Therefore, this paper proposes a convolutional neural network (CNN) based on k-means to optimize the accuracy of traffic sign recognition, and it proposes a sparse maximum CNN to identify difficult traffic signs through hierarchical classification. In the rough classification stage, k-means CNN is used to extract features, and improved support vector machine (SVM) is used for classification. Then, in the fine classification stage, sparse maximum CNN is used for classification. The research results show that the algorithm improves the accuracy of traffic sign recognition more comprehensively and effectively, and it can be effectively applied in unmanned driving technology, which will also bring new breakthroughs for the sustainable development of public transport.
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An Analysis Based on SD Model for Energy-Related CO2 Mitigation in the Chinese Household Sector
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2016Publisher:MDPI AG
Authors: Xingpeng Chen; Guokui Wang; Xiaojia Guo; Jinxiu Fu;
doi: 10.3390/en9121062
doi: 10.3390/en9121062
Reducing carbon dioxide (CO2) emissions has become a global consensus in response to global warming and climate change, especially to China, the largest CO2 emitter in the world. Most studies have focused on CO2 emissions from the production sector, however, the household sector plays an important role in the total energy-related CO2 emissions. This study formulates an integrated model based on logarithmic mean Divisia index methodology and a system dynamics model to dynamically simulate household energy consumption and CO2 emissions under different conditions. Results show the following: (1) the integrated model performs well in calculating the contribution of influencing factors on household CO2 emissions and analyzing the options for CO2 emission mitigation; (2) the increase in income is the dominant driving force of household CO2 emissions, and as a result of the improved standard of living in China a sustained increase in household CO2 emissions can be expected; (3) with decreasing energy intensity, CO2 emissions will decrease to 404.26 Mt-CO2 in 2020, which is 9.84% lower than the emissions in 2014; (4) the reduction potential by developing non-fossil energy sources is limited, and raising the rate of urbanization cannot reduce the household CO2 emission under the comprehensive influence of other factors.
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An Analysis Based on SD Model for Energy-Related CO2 Mitigation in the Chinese Household Sector
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2016Publisher:MDPI AG
Authors: Xingpeng Chen; Guokui Wang; Xiaojia Guo; Jinxiu Fu;
doi: 10.3390/en9121062
doi: 10.3390/en9121062
Reducing carbon dioxide (CO2) emissions has become a global consensus in response to global warming and climate change, especially to China, the largest CO2 emitter in the world. Most studies have focused on CO2 emissions from the production sector, however, the household sector plays an important role in the total energy-related CO2 emissions. This study formulates an integrated model based on logarithmic mean Divisia index methodology and a system dynamics model to dynamically simulate household energy consumption and CO2 emissions under different conditions. Results show the following: (1) the integrated model performs well in calculating the contribution of influencing factors on household CO2 emissions and analyzing the options for CO2 emission mitigation; (2) the increase in income is the dominant driving force of household CO2 emissions, and as a result of the improved standard of living in China a sustained increase in household CO2 emissions can be expected; (3) with decreasing energy intensity, CO2 emissions will decrease to 404.26 Mt-CO2 in 2020, which is 9.84% lower than the emissions in 2014; (4) the reduction potential by developing non-fossil energy sources is limited, and raising the rate of urbanization cannot reduce the household CO2 emission under the comprehensive influence of other factors.
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The Scale, Structure and Influencing Factors of Total Carbon Emissions from Households in 30 Provinces of China—Based on the Extended STIRPAT Model
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2018Publisher:MDPI AG
Authors: Yong Wang; Guangchun Yang; Ying Dong; Yu Cheng; +1 Authors
Yong Wang; Guangchun Yang; Ying Dong; Yu Cheng; Peipei Shang;
doi: 10.3390/en11051125
doi: 10.3390/en11051125
Household carbon emissions are important components of total carbon emissions. The consumer side of energy-saving emissions reduction is an essential factor in reducing carbon emissions. In this paper, the carbon emissions coefficient method and Consumer Lifestyle Approach (CLA) were used to calculate the total carbon emissions of households in 30 provinces of China from 2006 to 2015, and based on the extended Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, the factors influencing the total carbon emissions of households were analyzed. The results indicated that, first, over the past ten years, the energy and products carbon emissions from China’s households have demonstrated a rapid growth trend and that regional distributions present obvious differences. Second, China’s energy carbon emissions due to household consumption primarily derived from the residents’ consumption of electricity and coal; China’s products household carbon emissions primarily derived from residents’ consumption of the high carbon emission categories: residences, food, transportation and communications. Third, in terms of influencing factors, the number of households in China plays a significant role in the total carbon emissions of China’s households. The ratio of children 0–14 years old and gender ratio (female = 100) are two factors that reflect the demographic structure, have significant effects on the total carbon emissions of China’s households, and are all positive. Gross Domestic Product (GDP) per capita plays a role in boosting the total carbon emissions of China’s households. The effect of the carbon emission intensity on total household carbon emissions is positive. The industrial structure (the proportion of secondary industries’ added value to the regional GDP) has curbed the growth of total carbon emissions from China’s household consumption. The results of this study provide data to support the assessment of the total carbon emissions of China’s households and provide a reasonable reference that the government can use to formulate energy-saving and emission-reduction measures.
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The Scale, Structure and Influencing Factors of Total Carbon Emissions from Households in 30 Provinces of China—Based on the Extended STIRPAT Model
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2018Publisher:MDPI AG
Authors: Yong Wang; Guangchun Yang; Ying Dong; Yu Cheng; +1 Authors
Yong Wang; Guangchun Yang; Ying Dong; Yu Cheng; Peipei Shang;
doi: 10.3390/en11051125
doi: 10.3390/en11051125
Household carbon emissions are important components of total carbon emissions. The consumer side of energy-saving emissions reduction is an essential factor in reducing carbon emissions. In this paper, the carbon emissions coefficient method and Consumer Lifestyle Approach (CLA) were used to calculate the total carbon emissions of households in 30 provinces of China from 2006 to 2015, and based on the extended Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, the factors influencing the total carbon emissions of households were analyzed. The results indicated that, first, over the past ten years, the energy and products carbon emissions from China’s households have demonstrated a rapid growth trend and that regional distributions present obvious differences. Second, China’s energy carbon emissions due to household consumption primarily derived from the residents’ consumption of electricity and coal; China’s products household carbon emissions primarily derived from residents’ consumption of the high carbon emission categories: residences, food, transportation and communications. Third, in terms of influencing factors, the number of households in China plays a significant role in the total carbon emissions of China’s households. The ratio of children 0–14 years old and gender ratio (female = 100) are two factors that reflect the demographic structure, have significant effects on the total carbon emissions of China’s households, and are all positive. Gross Domestic Product (GDP) per capita plays a role in boosting the total carbon emissions of China’s households. The effect of the carbon emission intensity on total household carbon emissions is positive. The industrial structure (the proportion of secondary industries’ added value to the regional GDP) has curbed the growth of total carbon emissions from China’s household consumption. The results of this study provide data to support the assessment of the total carbon emissions of China’s households and provide a reasonable reference that the government can use to formulate energy-saving and emission-reduction measures.
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Direct Shear Experimental Study on the Mobilized Dilation Behavior of Granite in Alxa Candidate Area for High-Level Radioactive Waste Disposal
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2019Publisher:MDPI AG
Authors: Nengxiong Xu; Cheng Cheng; Xiao Li; Bo Zheng;
doi: 10.3390/en13010122
doi: 10.3390/en13010122
Dilation behavior is of great importance for reasonable modeling of the stability of the host rock of the repository for high-level radioactive waste disposal. It is a suitable method for carrying out direct shear experiments to analyze the dilation behavior of rock with well understood physical meanings. Based on a series of direct shear experiments on granite samples from the Alxa candidate area under different normal stresses, the shear stress‒shear strain and shear stress‒normal strain relations have been studied in detail. Five typical stages have been divided associated with the fracturing process and deformation behaviors of the granite samples during the experimental process, and the method to determine the typical stress thresholds has been proposed. It has also been found that the increasing normal stress may reduce the maximum dilation angle, and when the normal stress is relatively lower, the negative dilation angle may occur during the post-peak stage. According to the data collected from the direct shear tests, an empirical model of the mobilized dilation angle dependent on normal stress and plastic shear strain is proposed. This mobilized dilation angle has clear physical meanings and can be used in plastic constitutive models of the host rock of the repository, and this analysis can also be put forward to other types of geomechanical problems, including the deformation behaviors related to landslide, earthquake, and so on.
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Direct Shear Experimental Study on the Mobilized Dilation Behavior of Granite in Alxa Candidate Area for High-Level Radioactive Waste Disposal
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2019Publisher:MDPI AG
Authors: Nengxiong Xu; Cheng Cheng; Xiao Li; Bo Zheng;
doi: 10.3390/en13010122
doi: 10.3390/en13010122
Dilation behavior is of great importance for reasonable modeling of the stability of the host rock of the repository for high-level radioactive waste disposal. It is a suitable method for carrying out direct shear experiments to analyze the dilation behavior of rock with well understood physical meanings. Based on a series of direct shear experiments on granite samples from the Alxa candidate area under different normal stresses, the shear stress‒shear strain and shear stress‒normal strain relations have been studied in detail. Five typical stages have been divided associated with the fracturing process and deformation behaviors of the granite samples during the experimental process, and the method to determine the typical stress thresholds has been proposed. It has also been found that the increasing normal stress may reduce the maximum dilation angle, and when the normal stress is relatively lower, the negative dilation angle may occur during the post-peak stage. According to the data collected from the direct shear tests, an empirical model of the mobilized dilation angle dependent on normal stress and plastic shear strain is proposed. This mobilized dilation angle has clear physical meanings and can be used in plastic constitutive models of the host rock of the repository, and this analysis can also be put forward to other types of geomechanical problems, including the deformation behaviors related to landslide, earthquake, and so on.
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A Study on Inter-Provincial Environmental Pollution Movement in China Based on the Input–Output Method
descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 2022Publisher:MDPI AG
Authors: Yong Shi; Anda Tang; Tongsheng Yao;
doi: 10.3390/en15186782
doi: 10.3390/en15186782
In China, environmental pollution responsibilities are divided according to administrative regions. However, because of the strong externality of environmental pollution, the movement of environmental pollution undoubtedly increases the complexity of pollution governance. To divide the responsibility of environmental pollution governance in each province, we effectively quantify the unequal relationship between environmental pollution costs and economic benefits in each province to understand the mechanism and characteristics of inter-provincial environmental pollution movement. Based on the regional input–output model and an inventory we compiled of sulfur dioxide(SO2) emissions of air pollutants in 2012, we calculate the implied inter-provincial environmental pollution emissions and economic benefits from trade, based on production and consumption (supply-side and demand-side). In addition, the movement relationship is explored, and the cost and economic value-added indexes of air pollution control are further constructed to provide effective evidence for a reasonable division of responsibility for environmental pollution control. The results show that there are obvious environmental inequities in the regional trade process in each province, indicating that environmental pollution has been moved. Developed provinces have more economic benefits but pay less in the process of trading goods with less-developed provinces due to the advantages of their industrial structure, while the opposite is true for less-developed provinces. Finally, we propose corresponding policy recommendations to change this condition.
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A Study on Inter-Provincial Environmental Pollution Movement in China Based on the Input–Output Method
descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 2022Publisher:MDPI AG
Authors: Yong Shi; Anda Tang; Tongsheng Yao;
doi: 10.3390/en15186782
doi: 10.3390/en15186782
In China, environmental pollution responsibilities are divided according to administrative regions. However, because of the strong externality of environmental pollution, the movement of environmental pollution undoubtedly increases the complexity of pollution governance. To divide the responsibility of environmental pollution governance in each province, we effectively quantify the unequal relationship between environmental pollution costs and economic benefits in each province to understand the mechanism and characteristics of inter-provincial environmental pollution movement. Based on the regional input–output model and an inventory we compiled of sulfur dioxide(SO2) emissions of air pollutants in 2012, we calculate the implied inter-provincial environmental pollution emissions and economic benefits from trade, based on production and consumption (supply-side and demand-side). In addition, the movement relationship is explored, and the cost and economic value-added indexes of air pollution control are further constructed to provide effective evidence for a reasonable division of responsibility for environmental pollution control. The results show that there are obvious environmental inequities in the regional trade process in each province, indicating that environmental pollution has been moved. Developed provinces have more economic benefits but pay less in the process of trading goods with less-developed provinces due to the advantages of their industrial structure, while the opposite is true for less-developed provinces. Finally, we propose corresponding policy recommendations to change this condition.
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Low-Carbon Development Patterns: Observations of Typical Chinese Cities
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2012Publisher:MDPI AG
Authors: Meirong Su; Chen Liang; Bin Chen; Shaoqing Chen; +1 Authors
Meirong Su; Chen Liang; Bin Chen; Shaoqing Chen; Zhifeng Yang;
doi: 10.3390/en5020291
doi: 10.3390/en5020291
Threatened by the huge pressure caused by climate change, low-carbon cities have become an inevitable part of urban evolution. It is essential to evaluate urban low-carbon development levels to smoothly promote the construction of low-carbon cities. This paper proposes an evaluation index system for urban low-carbon development from the points of view of economic development and social progress, energy structure and usage efficiency, living consumption, and development surroundings. A weighted sum model was also established. Selecting 12 typical Chinese cities as cases studies, an integrated evaluation was conducted based on the index system and the assessment model. The development speed and limiting factors of different cities were also analyzed. The 12 cities were ultimately classified into three groups in terms of their low-carbon development patterns by integrating all of the analysis results. Furthermore, suitable regulation and management for different patterns were suggested. This study both aids in assessing the executive effect of low-carbon city construction and helps to determine existing problems and suggest effective solutions.
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Low-Carbon Development Patterns: Observations of Typical Chinese Cities
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2012Publisher:MDPI AG
Authors: Meirong Su; Chen Liang; Bin Chen; Shaoqing Chen; +1 Authors
Meirong Su; Chen Liang; Bin Chen; Shaoqing Chen; Zhifeng Yang;
doi: 10.3390/en5020291
doi: 10.3390/en5020291
Threatened by the huge pressure caused by climate change, low-carbon cities have become an inevitable part of urban evolution. It is essential to evaluate urban low-carbon development levels to smoothly promote the construction of low-carbon cities. This paper proposes an evaluation index system for urban low-carbon development from the points of view of economic development and social progress, energy structure and usage efficiency, living consumption, and development surroundings. A weighted sum model was also established. Selecting 12 typical Chinese cities as cases studies, an integrated evaluation was conducted based on the index system and the assessment model. The development speed and limiting factors of different cities were also analyzed. The 12 cities were ultimately classified into three groups in terms of their low-carbon development patterns by integrating all of the analysis results. Furthermore, suitable regulation and management for different patterns were suggested. This study both aids in assessing the executive effect of low-carbon city construction and helps to determine existing problems and suggest effective solutions.
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Energy Efficiency Evaluation Based on Data Envelopment Analysis: A Literature Review
descriptionPublicationkeyboard_double_arrow_right Article , Journal 2020Publisher:MDPI AG
Authors: Tao Xu; Jianxin You; Hui Li; Luning Shao;
doi: 10.3390/en13143548
doi: 10.3390/en13143548
The importance and urgency of energy efficiency in sustainable development are increasing. Accurate assessment of energy efficiency is of considerable significance and necessity. The data envelopment analysis (DEA) method has been widely used to study energy efficiency as a total factor efficiency assessment method. In order to summarize the latest research on DEA in the field of energy efficiency, this article first analyzes the overall situation of related literature published in 2011–2019. Subsequently, the definition, measurement and evaluation variables of energy efficiency are introduced. After that, this article reviews the current DEA model and its extension models and applications based on different scenarios. Finally, considering the shortcomings of the existing DEA model, possible future research topics are proposed.
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Energy Efficiency Evaluation Based on Data Envelopment Analysis: A Literature Review
descriptionPublicationkeyboard_double_arrow_right Article , Journal 2020Publisher:MDPI AG
Authors: Tao Xu; Jianxin You; Hui Li; Luning Shao;
doi: 10.3390/en13143548
doi: 10.3390/en13143548
The importance and urgency of energy efficiency in sustainable development are increasing. Accurate assessment of energy efficiency is of considerable significance and necessity. The data envelopment analysis (DEA) method has been widely used to study energy efficiency as a total factor efficiency assessment method. In order to summarize the latest research on DEA in the field of energy efficiency, this article first analyzes the overall situation of related literature published in 2011–2019. Subsequently, the definition, measurement and evaluation variables of energy efficiency are introduced. After that, this article reviews the current DEA model and its extension models and applications based on different scenarios. Finally, considering the shortcomings of the existing DEA model, possible future research topics are proposed.
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Analysis of Changes in the Aggregate Exergy Efficiency of China’s Energy System from 2005 to 2015
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2021Publisher:MDPI AG
Authors: Yuancheng Lin; Chinhao Chong; Linwei Ma; Zheng Li; +1 Authors
Yuancheng Lin; Chinhao Chong; Linwei Ma; Zheng Li; Weidou Ni;
doi: 10.3390/en14082304
doi: 10.3390/en14082304
Analysis of the change of overall energy efficiency performance of an energy system is a fundamental work for the energy-saving policymaking. However, previous studies seldom focus on energy stages from useful energy to final service, while most attention are paid on stages from energy source to useful energy. In this paper, we develop a high-resolution the Societal Exergy Analysis and Logarithmic Mean Divisia Index (SEA-LMDI) method to analysis changes and driving factors of the aggregate exergy efficiency, in which the boundary of the SEA is extended to passive systems and final services, and a LMDI decomposition method is developed to quantify contributions of efficiency factors and structure factors of all six stages on the aggregate exergy efficiency. A case study of China during 2005–2015 reveals that: (a) the aggregate exergy efficiency from energy source to final service is only from 3.7% to 4.8% during 2005–2015, showing a huge theoretical potential of efficiency improvement. (b) Large passive losses are identified in passive systems and nearly 2/3 of useful energy can be theoretically saved by improving passive systems. (c) Deep analysis of industrial coal-fired boilers indicates that the internal structural adjustments are also important for the aggregate improvement.
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Analysis of Changes in the Aggregate Exergy Efficiency of China’s Energy System from 2005 to 2015
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2021Publisher:MDPI AG
Authors: Yuancheng Lin; Chinhao Chong; Linwei Ma; Zheng Li; +1 Authors
Yuancheng Lin; Chinhao Chong; Linwei Ma; Zheng Li; Weidou Ni;
doi: 10.3390/en14082304
doi: 10.3390/en14082304
Analysis of the change of overall energy efficiency performance of an energy system is a fundamental work for the energy-saving policymaking. However, previous studies seldom focus on energy stages from useful energy to final service, while most attention are paid on stages from energy source to useful energy. In this paper, we develop a high-resolution the Societal Exergy Analysis and Logarithmic Mean Divisia Index (SEA-LMDI) method to analysis changes and driving factors of the aggregate exergy efficiency, in which the boundary of the SEA is extended to passive systems and final services, and a LMDI decomposition method is developed to quantify contributions of efficiency factors and structure factors of all six stages on the aggregate exergy efficiency. A case study of China during 2005–2015 reveals that: (a) the aggregate exergy efficiency from energy source to final service is only from 3.7% to 4.8% during 2005–2015, showing a huge theoretical potential of efficiency improvement. (b) Large passive losses are identified in passive systems and nearly 2/3 of useful energy can be theoretically saved by improving passive systems. (c) Deep analysis of industrial coal-fired boilers indicates that the internal structural adjustments are also important for the aggregate improvement.
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Energies
Other literature type . 2021
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Perovskite CsPbBr3 Quantum Dots Prepared Using Discarded Lead–Acid Battery Recycled Waste
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2019Publisher:MDPI AG
Authors: Lung-Chien Chen; Ching-Ho Tien; Sin-Liang Ou; Kun-Yi Lee; +5 Authors
Lung-Chien Chen; Ching-Ho Tien; Sin-Liang Ou; Kun-Yi Lee; Jianjun Tian; Zong-Liang Tseng; Hao-Tian Chen; Hao-Chung Kuo; An-Cheng Sun;
doi: 10.3390/en12061117
doi: 10.3390/en12061117
Perovskite CsPbBr3 quantum dot (CsPbBr3-QD) recovery was performed using lead scrap from lead storage batteries. The perovskite CsPbBr3-QD characteristics were analyzed using different PbO/recycled PbO2 ratios. Scanning electron microscopy (SEM) was used to observe the film surface morphology and cross-section. High-resolution transmission electron microscopy (HRTEM) and X-ray diffraction (XRD) were used to observe the perovskite CsPbBr3-QDs’ structural characteristics. A photoluminescence (PL) measurement system was used to analyze the optical properties. The results show that lead scrap from lead–acid batteries as a material for perovskite CsPbBr3-QD production can be successfully synthesized. This saves material and also proves that recycling is valuable. The proposed approach is helpful for future material shortages and materials not easily accessible. Although the efficiency is not very high, this process will be purified using recycled lead in the future to achieve higher quantum yield.
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Perovskite CsPbBr3 Quantum Dots Prepared Using Discarded Lead–Acid Battery Recycled Waste
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2019Publisher:MDPI AG
Authors: Lung-Chien Chen; Ching-Ho Tien; Sin-Liang Ou; Kun-Yi Lee; +5 Authors
Lung-Chien Chen; Ching-Ho Tien; Sin-Liang Ou; Kun-Yi Lee; Jianjun Tian; Zong-Liang Tseng; Hao-Tian Chen; Hao-Chung Kuo; An-Cheng Sun;
doi: 10.3390/en12061117
doi: 10.3390/en12061117
Perovskite CsPbBr3 quantum dot (CsPbBr3-QD) recovery was performed using lead scrap from lead storage batteries. The perovskite CsPbBr3-QD characteristics were analyzed using different PbO/recycled PbO2 ratios. Scanning electron microscopy (SEM) was used to observe the film surface morphology and cross-section. High-resolution transmission electron microscopy (HRTEM) and X-ray diffraction (XRD) were used to observe the perovskite CsPbBr3-QDs’ structural characteristics. A photoluminescence (PL) measurement system was used to analyze the optical properties. The results show that lead scrap from lead–acid batteries as a material for perovskite CsPbBr3-QD production can be successfully synthesized. This saves material and also proves that recycling is valuable. The proposed approach is helpful for future material shortages and materials not easily accessible. Although the efficiency is not very high, this process will be purified using recycled lead in the future to achieve higher quantum yield.
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Causal Dynamic Relationships between Political–Economic Factors and Export Performance in the Renewable Energy Technologies Market
descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 2018Publisher:MDPI AG
Authors: Bongsuk Sung; Cui Wen;
doi: 10.3390/en11040874
doi: 10.3390/en11040874
This study explores how political–economic forces could affect export performance in the renewable energy technologies market. We conduct panel framework analyses to verify the characteristics of panel data for 19 countries before establishing the panel estimator meant to test the effects of political–economic forces on export specialization. We consider the results of the panel framework analyses and develop an empirical model to test casual dynamic relationships between political–economic forces and export performance. The results from the least squares dummy variable-corrected estimation indicate that the major factors promoting the export specialization of renewable energy technologies are, in order of decreasing importance, public pressure, market size, and government demand-pull policy. However, the traditional energy industry has no significant effect on export performance. Finally, this study finds that dynamic effects exist in all estimations.
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Causal Dynamic Relationships between Political–Economic Factors and Export Performance in the Renewable Energy Technologies Market
descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 2018Publisher:MDPI AG
Authors: Bongsuk Sung; Cui Wen;
doi: 10.3390/en11040874
doi: 10.3390/en11040874
This study explores how political–economic forces could affect export performance in the renewable energy technologies market. We conduct panel framework analyses to verify the characteristics of panel data for 19 countries before establishing the panel estimator meant to test the effects of political–economic forces on export specialization. We consider the results of the panel framework analyses and develop an empirical model to test casual dynamic relationships between political–economic forces and export performance. The results from the least squares dummy variable-corrected estimation indicate that the major factors promoting the export specialization of renewable energy technologies are, in order of decreasing importance, public pressure, market size, and government demand-pull policy. However, the traditional energy industry has no significant effect on export performance. Finally, this study finds that dynamic effects exist in all estimations.
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How Can Sustainable Public Transport Be Improved? A Traffic Sign Recognition Approach Using Convolutional Neural Network
descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 2022 Australia Publisher:MDPI AG
Authors: Jingjing Liu; Hongwei Ge; Jiajie Li; Pengcheng He; +2 Authors
Jingjing Liu; Hongwei Ge; Jiajie Li; Pengcheng He; Zhangang Hao; Michael Hitch;
doi: 10.3390/en15197386
handle: 20.500.11937/89418
doi: 10.3390/en15197386
handle: 20.500.11937/89418
Sustainable public transport is an important factor to boost urban economic development, and it is also an important part of building a low-carbon environmental society. The application of driverless technology in public transport injects new impetus into its sustainable development. Road traffic sign recognition is the key technology of driverless public transport. It is particularly important to adopt innovative algorithms to optimize the accuracy of traffic sign recognition and build sustainable public transport. Therefore, this paper proposes a convolutional neural network (CNN) based on k-means to optimize the accuracy of traffic sign recognition, and it proposes a sparse maximum CNN to identify difficult traffic signs through hierarchical classification. In the rough classification stage, k-means CNN is used to extract features, and improved support vector machine (SVM) is used for classification. Then, in the fine classification stage, sparse maximum CNN is used for classification. The research results show that the algorithm improves the accuracy of traffic sign recognition more comprehensively and effectively, and it can be effectively applied in unmanned driving technology, which will also bring new breakthroughs for the sustainable development of public transport.
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How Can Sustainable Public Transport Be Improved? A Traffic Sign Recognition Approach Using Convolutional Neural Network
descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 2022 Australia Publisher:MDPI AG
Authors: Jingjing Liu; Hongwei Ge; Jiajie Li; Pengcheng He; +2 Authors
Jingjing Liu; Hongwei Ge; Jiajie Li; Pengcheng He; Zhangang Hao; Michael Hitch;
doi: 10.3390/en15197386
handle: 20.500.11937/89418
doi: 10.3390/en15197386
handle: 20.500.11937/89418
Sustainable public transport is an important factor to boost urban economic development, and it is also an important part of building a low-carbon environmental society. The application of driverless technology in public transport injects new impetus into its sustainable development. Road traffic sign recognition is the key technology of driverless public transport. It is particularly important to adopt innovative algorithms to optimize the accuracy of traffic sign recognition and build sustainable public transport. Therefore, this paper proposes a convolutional neural network (CNN) based on k-means to optimize the accuracy of traffic sign recognition, and it proposes a sparse maximum CNN to identify difficult traffic signs through hierarchical classification. In the rough classification stage, k-means CNN is used to extract features, and improved support vector machine (SVM) is used for classification. Then, in the fine classification stage, sparse maximum CNN is used for classification. The research results show that the algorithm improves the accuracy of traffic sign recognition more comprehensively and effectively, and it can be effectively applied in unmanned driving technology, which will also bring new breakthroughs for the sustainable development of public transport.
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An Analysis Based on SD Model for Energy-Related CO2 Mitigation in the Chinese Household Sector
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2016Publisher:MDPI AG
Authors: Xingpeng Chen; Guokui Wang; Xiaojia Guo; Jinxiu Fu;
doi: 10.3390/en9121062
doi: 10.3390/en9121062
Reducing carbon dioxide (CO2) emissions has become a global consensus in response to global warming and climate change, especially to China, the largest CO2 emitter in the world. Most studies have focused on CO2 emissions from the production sector, however, the household sector plays an important role in the total energy-related CO2 emissions. This study formulates an integrated model based on logarithmic mean Divisia index methodology and a system dynamics model to dynamically simulate household energy consumption and CO2 emissions under different conditions. Results show the following: (1) the integrated model performs well in calculating the contribution of influencing factors on household CO2 emissions and analyzing the options for CO2 emission mitigation; (2) the increase in income is the dominant driving force of household CO2 emissions, and as a result of the improved standard of living in China a sustained increase in household CO2 emissions can be expected; (3) with decreasing energy intensity, CO2 emissions will decrease to 404.26 Mt-CO2 in 2020, which is 9.84% lower than the emissions in 2014; (4) the reduction potential by developing non-fossil energy sources is limited, and raising the rate of urbanization cannot reduce the household CO2 emission under the comprehensive influence of other factors.
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An Analysis Based on SD Model for Energy-Related CO2 Mitigation in the Chinese Household Sector
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2016Publisher:MDPI AG
Authors: Xingpeng Chen; Guokui Wang; Xiaojia Guo; Jinxiu Fu;
doi: 10.3390/en9121062
doi: 10.3390/en9121062
Reducing carbon dioxide (CO2) emissions has become a global consensus in response to global warming and climate change, especially to China, the largest CO2 emitter in the world. Most studies have focused on CO2 emissions from the production sector, however, the household sector plays an important role in the total energy-related CO2 emissions. This study formulates an integrated model based on logarithmic mean Divisia index methodology and a system dynamics model to dynamically simulate household energy consumption and CO2 emissions under different conditions. Results show the following: (1) the integrated model performs well in calculating the contribution of influencing factors on household CO2 emissions and analyzing the options for CO2 emission mitigation; (2) the increase in income is the dominant driving force of household CO2 emissions, and as a result of the improved standard of living in China a sustained increase in household CO2 emissions can be expected; (3) with decreasing energy intensity, CO2 emissions will decrease to 404.26 Mt-CO2 in 2020, which is 9.84% lower than the emissions in 2014; (4) the reduction potential by developing non-fossil energy sources is limited, and raising the rate of urbanization cannot reduce the household CO2 emission under the comprehensive influence of other factors.
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The Scale, Structure and Influencing Factors of Total Carbon Emissions from Households in 30 Provinces of China—Based on the Extended STIRPAT Model
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2018Publisher:MDPI AG
Authors: Yong Wang; Guangchun Yang; Ying Dong; Yu Cheng; +1 Authors
Yong Wang; Guangchun Yang; Ying Dong; Yu Cheng; Peipei Shang;
doi: 10.3390/en11051125
doi: 10.3390/en11051125
Household carbon emissions are important components of total carbon emissions. The consumer side of energy-saving emissions reduction is an essential factor in reducing carbon emissions. In this paper, the carbon emissions coefficient method and Consumer Lifestyle Approach (CLA) were used to calculate the total carbon emissions of households in 30 provinces of China from 2006 to 2015, and based on the extended Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, the factors influencing the total carbon emissions of households were analyzed. The results indicated that, first, over the past ten years, the energy and products carbon emissions from China’s households have demonstrated a rapid growth trend and that regional distributions present obvious differences. Second, China’s energy carbon emissions due to household consumption primarily derived from the residents’ consumption of electricity and coal; China’s products household carbon emissions primarily derived from residents’ consumption of the high carbon emission categories: residences, food, transportation and communications. Third, in terms of influencing factors, the number of households in China plays a significant role in the total carbon emissions of China’s households. The ratio of children 0–14 years old and gender ratio (female = 100) are two factors that reflect the demographic structure, have significant effects on the total carbon emissions of China’s households, and are all positive. Gross Domestic Product (GDP) per capita plays a role in boosting the total carbon emissions of China’s households. The effect of the carbon emission intensity on total household carbon emissions is positive. The industrial structure (the proportion of secondary industries’ added value to the regional GDP) has curbed the growth of total carbon emissions from China’s household consumption. The results of this study provide data to support the assessment of the total carbon emissions of China’s households and provide a reasonable reference that the government can use to formulate energy-saving and emission-reduction measures.
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The Scale, Structure and Influencing Factors of Total Carbon Emissions from Households in 30 Provinces of China—Based on the Extended STIRPAT Model
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2018Publisher:MDPI AG
Authors: Yong Wang; Guangchun Yang; Ying Dong; Yu Cheng; +1 Authors
Yong Wang; Guangchun Yang; Ying Dong; Yu Cheng; Peipei Shang;
doi: 10.3390/en11051125
doi: 10.3390/en11051125
Household carbon emissions are important components of total carbon emissions. The consumer side of energy-saving emissions reduction is an essential factor in reducing carbon emissions. In this paper, the carbon emissions coefficient method and Consumer Lifestyle Approach (CLA) were used to calculate the total carbon emissions of households in 30 provinces of China from 2006 to 2015, and based on the extended Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, the factors influencing the total carbon emissions of households were analyzed. The results indicated that, first, over the past ten years, the energy and products carbon emissions from China’s households have demonstrated a rapid growth trend and that regional distributions present obvious differences. Second, China’s energy carbon emissions due to household consumption primarily derived from the residents’ consumption of electricity and coal; China’s products household carbon emissions primarily derived from residents’ consumption of the high carbon emission categories: residences, food, transportation and communications. Third, in terms of influencing factors, the number of households in China plays a significant role in the total carbon emissions of China’s households. The ratio of children 0–14 years old and gender ratio (female = 100) are two factors that reflect the demographic structure, have significant effects on the total carbon emissions of China’s households, and are all positive. Gross Domestic Product (GDP) per capita plays a role in boosting the total carbon emissions of China’s households. The effect of the carbon emission intensity on total household carbon emissions is positive. The industrial structure (the proportion of secondary industries’ added value to the regional GDP) has curbed the growth of total carbon emissions from China’s household consumption. The results of this study provide data to support the assessment of the total carbon emissions of China’s households and provide a reasonable reference that the government can use to formulate energy-saving and emission-reduction measures.
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Direct Shear Experimental Study on the Mobilized Dilation Behavior of Granite in Alxa Candidate Area for High-Level Radioactive Waste Disposal
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2019Publisher:MDPI AG
Authors: Nengxiong Xu; Cheng Cheng; Xiao Li; Bo Zheng;
doi: 10.3390/en13010122
doi: 10.3390/en13010122
Dilation behavior is of great importance for reasonable modeling of the stability of the host rock of the repository for high-level radioactive waste disposal. It is a suitable method for carrying out direct shear experiments to analyze the dilation behavior of rock with well understood physical meanings. Based on a series of direct shear experiments on granite samples from the Alxa candidate area under different normal stresses, the shear stress‒shear strain and shear stress‒normal strain relations have been studied in detail. Five typical stages have been divided associated with the fracturing process and deformation behaviors of the granite samples during the experimental process, and the method to determine the typical stress thresholds has been proposed. It has also been found that the increasing normal stress may reduce the maximum dilation angle, and when the normal stress is relatively lower, the negative dilation angle may occur during the post-peak stage. According to the data collected from the direct shear tests, an empirical model of the mobilized dilation angle dependent on normal stress and plastic shear strain is proposed. This mobilized dilation angle has clear physical meanings and can be used in plastic constitutive models of the host rock of the repository, and this analysis can also be put forward to other types of geomechanical problems, including the deformation behaviors related to landslide, earthquake, and so on.
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Direct Shear Experimental Study on the Mobilized Dilation Behavior of Granite in Alxa Candidate Area for High-Level Radioactive Waste Disposal
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2019Publisher:MDPI AG
Authors: Nengxiong Xu; Cheng Cheng; Xiao Li; Bo Zheng;
doi: 10.3390/en13010122
doi: 10.3390/en13010122
Dilation behavior is of great importance for reasonable modeling of the stability of the host rock of the repository for high-level radioactive waste disposal. It is a suitable method for carrying out direct shear experiments to analyze the dilation behavior of rock with well understood physical meanings. Based on a series of direct shear experiments on granite samples from the Alxa candidate area under different normal stresses, the shear stress‒shear strain and shear stress‒normal strain relations have been studied in detail. Five typical stages have been divided associated with the fracturing process and deformation behaviors of the granite samples during the experimental process, and the method to determine the typical stress thresholds has been proposed. It has also been found that the increasing normal stress may reduce the maximum dilation angle, and when the normal stress is relatively lower, the negative dilation angle may occur during the post-peak stage. According to the data collected from the direct shear tests, an empirical model of the mobilized dilation angle dependent on normal stress and plastic shear strain is proposed. This mobilized dilation angle has clear physical meanings and can be used in plastic constitutive models of the host rock of the repository, and this analysis can also be put forward to other types of geomechanical problems, including the deformation behaviors related to landslide, earthquake, and so on.
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A Study on Inter-Provincial Environmental Pollution Movement in China Based on the Input–Output Method
descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 2022Publisher:MDPI AG
Authors: Yong Shi; Anda Tang; Tongsheng Yao;
doi: 10.3390/en15186782
doi: 10.3390/en15186782
In China, environmental pollution responsibilities are divided according to administrative regions. However, because of the strong externality of environmental pollution, the movement of environmental pollution undoubtedly increases the complexity of pollution governance. To divide the responsibility of environmental pollution governance in each province, we effectively quantify the unequal relationship between environmental pollution costs and economic benefits in each province to understand the mechanism and characteristics of inter-provincial environmental pollution movement. Based on the regional input–output model and an inventory we compiled of sulfur dioxide(SO2) emissions of air pollutants in 2012, we calculate the implied inter-provincial environmental pollution emissions and economic benefits from trade, based on production and consumption (supply-side and demand-side). In addition, the movement relationship is explored, and the cost and economic value-added indexes of air pollution control are further constructed to provide effective evidence for a reasonable division of responsibility for environmental pollution control. The results show that there are obvious environmental inequities in the regional trade process in each province, indicating that environmental pollution has been moved. Developed provinces have more economic benefits but pay less in the process of trading goods with less-developed provinces due to the advantages of their industrial structure, while the opposite is true for less-developed provinces. Finally, we propose corresponding policy recommendations to change this condition.
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A Study on Inter-Provincial Environmental Pollution Movement in China Based on the Input–Output Method
descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 2022Publisher:MDPI AG
Authors: Yong Shi; Anda Tang; Tongsheng Yao;
doi: 10.3390/en15186782
doi: 10.3390/en15186782
In China, environmental pollution responsibilities are divided according to administrative regions. However, because of the strong externality of environmental pollution, the movement of environmental pollution undoubtedly increases the complexity of pollution governance. To divide the responsibility of environmental pollution governance in each province, we effectively quantify the unequal relationship between environmental pollution costs and economic benefits in each province to understand the mechanism and characteristics of inter-provincial environmental pollution movement. Based on the regional input–output model and an inventory we compiled of sulfur dioxide(SO2) emissions of air pollutants in 2012, we calculate the implied inter-provincial environmental pollution emissions and economic benefits from trade, based on production and consumption (supply-side and demand-side). In addition, the movement relationship is explored, and the cost and economic value-added indexes of air pollution control are further constructed to provide effective evidence for a reasonable division of responsibility for environmental pollution control. The results show that there are obvious environmental inequities in the regional trade process in each province, indicating that environmental pollution has been moved. Developed provinces have more economic benefits but pay less in the process of trading goods with less-developed provinces due to the advantages of their industrial structure, while the opposite is true for less-developed provinces. Finally, we propose corresponding policy recommendations to change this condition.
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Low-Carbon Development Patterns: Observations of Typical Chinese Cities
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2012Publisher:MDPI AG
Authors: Meirong Su; Chen Liang; Bin Chen; Shaoqing Chen; +1 Authors
Meirong Su; Chen Liang; Bin Chen; Shaoqing Chen; Zhifeng Yang;
doi: 10.3390/en5020291
doi: 10.3390/en5020291
Threatened by the huge pressure caused by climate change, low-carbon cities have become an inevitable part of urban evolution. It is essential to evaluate urban low-carbon development levels to smoothly promote the construction of low-carbon cities. This paper proposes an evaluation index system for urban low-carbon development from the points of view of economic development and social progress, energy structure and usage efficiency, living consumption, and development surroundings. A weighted sum model was also established. Selecting 12 typical Chinese cities as cases studies, an integrated evaluation was conducted based on the index system and the assessment model. The development speed and limiting factors of different cities were also analyzed. The 12 cities were ultimately classified into three groups in terms of their low-carbon development patterns by integrating all of the analysis results. Furthermore, suitable regulation and management for different patterns were suggested. This study both aids in assessing the executive effect of low-carbon city construction and helps to determine existing problems and suggest effective solutions.
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Low-Carbon Development Patterns: Observations of Typical Chinese Cities
descriptionPublicationkeyboard_double_arrow_right Article , Journal , Other literature type 2012Publisher:MDPI AG
Authors: Meirong Su; Chen Liang; Bin Chen; Shaoqing Chen; +1 Authors
Meirong Su; Chen Liang; Bin Chen; Shaoqing Chen; Zhifeng Yang;
doi: 10.3390/en5020291
doi: 10.3390/en5020291
Threatened by the huge pressure caused by climate change, low-carbon cities have become an inevitable part of urban evolution. It is essential to evaluate urban low-carbon development levels to smoothly promote the construction of low-carbon cities. This paper proposes an evaluation index system for urban low-carbon development from the points of view of economic development and social progress, energy structure and usage efficiency, living consumption, and development surroundings. A weighted sum model was also established. Selecting 12 typical Chinese cities as cases studies, an integrated evaluation was conducted based on the index system and the assessment model. The development speed and limiting factors of different cities were also analyzed. The 12 cities were ultimately classified into three groups in terms of their low-carbon development patterns by integrating all of the analysis results. Furthermore, suitable regulation and management for different patterns were suggested. This study both aids in assessing the executive effect of low-carbon city construction and helps to determine existing problems and suggest effective solutions.
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downloaddonwloadFull-Text
Energiesarrow_drop_down
Energies
Other literature type . 2012
License: CC BY
Full-Text: http://www.mdpi.com/1996-1073/5/2/291/pdf
Data sources: Multidisciplinary Digital Publishing Institute
Energies
Article . 2012 . Peer-reviewed
License: CC BY
Data sources: Crossref
Energies
Article
License: CC BY
Data sources: UnpayWall
Energies
Article . 2012
Data sources: DOAJ
Energies
Journal
Data sources: Microsoft Academic Graph
Research Papers in Economics
Article . 2012
Data sources: Research Papers in Economics
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shareshareShare
citeCite
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Please grant OpenAIRE to access and update your ORCID works.
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