{"title":"基于长期演化的中国农村能源贫困评估与清洁能源转型预警","authors":"S. Yin, Man Wang, Yaqi Shi, Yumeng Zhao","doi":"10.1063/5.0209376","DOIUrl":null,"url":null,"abstract":"Rural China grapples with pervasive energy poverty. This study aims to measure China's rural energy poverty and propose early warning strategies. It establishes a rural energy relative poverty evaluation system based on four dimensions: energy service effectiveness, consumption cleanliness, management integrity, and development sustainability. Using the Analytic Hierarchy Process-Criteria Importance Though Intercriteria Correlation-Technique for Order Preference by Similarity to Ideal Solution model, it calculates rural energy poverty indices for Chinese provinces, while ward cluster analysis sets regional and hierarchical early warning criteria. Findings indicate: (1) China's rural energy poverty index varies widely, with a low range of 0.49–0.52 and a high range above 0.65. The top 14 regions average a rural energy poverty index of 0.62. (2) Over 2015–2021, there is a 9.70% decrease in the index, indicating a general downward trend. While rural energy services' efficiency and management integrity improve, consumption cleanliness and development sustainability decline. (3) Spatially, energy poverty is higher in the west and north, notably lower in the east and south. The eastern coastal and central regions exhibit significantly lower poverty levels due to better economic foundations and leading energy transformations. (4) Nine provinces are red warning areas, witnessing declining sustainability but improving service effectiveness, consumption cleanliness, and management integrity. Weak links in energy poverty vary across regions in terms of service effectiveness, consumption cleanliness, management integrity, and development sustainability. This study enhances the rural energy poverty evaluation system and proposes regional, hierarchical, and phased early warning standards.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Assessing rural energy poverty and early warning based on long-run evolution for clean energy transition in China\",\"authors\":\"S. Yin, Man Wang, Yaqi Shi, Yumeng Zhao\",\"doi\":\"10.1063/5.0209376\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Rural China grapples with pervasive energy poverty. This study aims to measure China's rural energy poverty and propose early warning strategies. It establishes a rural energy relative poverty evaluation system based on four dimensions: energy service effectiveness, consumption cleanliness, management integrity, and development sustainability. Using the Analytic Hierarchy Process-Criteria Importance Though Intercriteria Correlation-Technique for Order Preference by Similarity to Ideal Solution model, it calculates rural energy poverty indices for Chinese provinces, while ward cluster analysis sets regional and hierarchical early warning criteria. Findings indicate: (1) China's rural energy poverty index varies widely, with a low range of 0.49–0.52 and a high range above 0.65. The top 14 regions average a rural energy poverty index of 0.62. (2) Over 2015–2021, there is a 9.70% decrease in the index, indicating a general downward trend. While rural energy services' efficiency and management integrity improve, consumption cleanliness and development sustainability decline. (3) Spatially, energy poverty is higher in the west and north, notably lower in the east and south. The eastern coastal and central regions exhibit significantly lower poverty levels due to better economic foundations and leading energy transformations. (4) Nine provinces are red warning areas, witnessing declining sustainability but improving service effectiveness, consumption cleanliness, and management integrity. Weak links in energy poverty vary across regions in terms of service effectiveness, consumption cleanliness, management integrity, and development sustainability. This study enhances the rural energy poverty evaluation system and proposes regional, hierarchical, and phased early warning standards.\",\"PeriodicalId\":16953,\"journal\":{\"name\":\"Journal of Renewable and Sustainable Energy\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Renewable and Sustainable Energy\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1063/5.0209376\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Renewable and Sustainable Energy","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1063/5.0209376","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Assessing rural energy poverty and early warning based on long-run evolution for clean energy transition in China
Rural China grapples with pervasive energy poverty. This study aims to measure China's rural energy poverty and propose early warning strategies. It establishes a rural energy relative poverty evaluation system based on four dimensions: energy service effectiveness, consumption cleanliness, management integrity, and development sustainability. Using the Analytic Hierarchy Process-Criteria Importance Though Intercriteria Correlation-Technique for Order Preference by Similarity to Ideal Solution model, it calculates rural energy poverty indices for Chinese provinces, while ward cluster analysis sets regional and hierarchical early warning criteria. Findings indicate: (1) China's rural energy poverty index varies widely, with a low range of 0.49–0.52 and a high range above 0.65. The top 14 regions average a rural energy poverty index of 0.62. (2) Over 2015–2021, there is a 9.70% decrease in the index, indicating a general downward trend. While rural energy services' efficiency and management integrity improve, consumption cleanliness and development sustainability decline. (3) Spatially, energy poverty is higher in the west and north, notably lower in the east and south. The eastern coastal and central regions exhibit significantly lower poverty levels due to better economic foundations and leading energy transformations. (4) Nine provinces are red warning areas, witnessing declining sustainability but improving service effectiveness, consumption cleanliness, and management integrity. Weak links in energy poverty vary across regions in terms of service effectiveness, consumption cleanliness, management integrity, and development sustainability. This study enhances the rural energy poverty evaluation system and proposes regional, hierarchical, and phased early warning standards.
期刊介绍:
The Journal of Renewable and Sustainable Energy (JRSE) is an interdisciplinary, peer-reviewed journal covering all areas of renewable and sustainable energy relevant to the physical science and engineering communities. The interdisciplinary approach of the publication ensures that the editors draw from researchers worldwide in a diverse range of fields.
Topics covered include:
Renewable energy economics and policy
Renewable energy resource assessment
Solar energy: photovoltaics, solar thermal energy, solar energy for fuels
Wind energy: wind farms, rotors and blades, on- and offshore wind conditions, aerodynamics, fluid dynamics
Bioenergy: biofuels, biomass conversion, artificial photosynthesis
Distributed energy generation: rooftop PV, distributed fuel cells, distributed wind, micro-hydrogen power generation
Power distribution & systems modeling: power electronics and controls, smart grid
Energy efficient buildings: smart windows, PV, wind, power management
Energy conversion: flexoelectric, piezoelectric, thermoelectric, other technologies
Energy storage: batteries, supercapacitors, hydrogen storage, other fuels
Fuel cells: proton exchange membrane cells, solid oxide cells, hybrid fuel cells, other
Marine and hydroelectric energy: dams, tides, waves, other
Transportation: alternative vehicle technologies, plug-in technologies, other
Geothermal energy