The forecasting model research of rural energy transformation in Henan Province based on STIRPAT model

Wen, Lei; Song, Qianqian

doi:10.1007/s11356-022-21119-8

Cited by 3 publications

(3 citation statements)

References 56 publications

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“…Firstly, the indicator values were normalized according to the upper and lower bound on the 0-100 scale. Secondly, the Constant Elasticity of Substitution (CES) model was employed to aggregate the indicators using 6 SDGs [24].…”

Section: Evaluation and Analysis Methodsmentioning

confidence: 99%

“…There are also prominent bottlenecks in low-carbon technology, lacking effective incentive mechanisms and low-quality agricultural labor. Under the dual historical responsibility of the "dual carbon" goal and rural revitalization strategy, rural energy transformation is urgent [24]. SDG8 aims to promote inclusive and sustainable economic growth, employment, and decent work for all.…”

Section: Screening Of Sdgs For Agriculture Sustainabilitymentioning

confidence: 99%

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Study of the Spatio-Temporal Variation of Agricultural Sustainability at National and Provincial Levels in China

Zhan,

Xin,

Shao

et al. 2023

Sustainability

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As an important pillar of human civilization, the development of agriculture has gradually become the focus of the international community to solve the development dilemma and promote the implementation of the global Sustainable Development Goals (SDGs). Agricultural sustainability issues are widely addressed in scientific literature and various reports by international organizations. However, there are some problems in the existing studies, such as the design of agricultural sustainable development evaluation indicators does not consider the differences in development stages and data statistical capacity of various countries, and the research depth of spatial and temporal change of agricultural sustainable development is insufficient. Agriculture has become a bottleneck for the world and China to achieve the SDGs. Based on the global indicator framework of the Sustainable Development Goals and comprehensive consideration of agricultural development common problems and regional characteristics, this work has established a basic index library consisting of 86 indicators to evaluate the agricultural sustainable development in China and provide the basis for the assessment in different regions. In the indicator optimization process, having considered the development stage of China, the basic characteristics of agriculture, data availability, and reliability, we determined an evaluation index system of China’s agricultural sustainable development that includes 25 specific indicators. The constant elasticity of substitution (CES) model was used to assess the temporal and spatial changes in agricultural sustainability in China at the national, regional, and provincial levels. The results showed that China’s Agricultural Sustainable Development Index (ASDI) score increased from 44.76 in 2011 to 59.22 in 2021, and the ASDI scores of all agricultural regions and provinces also increased to varying degrees. In terms of goal scores, SDG2, SDG6, SDG7, SDG8, SDG9, and SDG12 all exhibited an overall upward trend, in which SDG6 performed the best, and SDG2 performed the worst, scoring 84.76 and 43.05 in 2021, respectively. This paper will provide a basis for systematically evaluating the progress of agricultural sustainable development goals and accurately identifying unsustainable problems in agricultural development to help China implement the 2030 Agenda for Sustainable Development.

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Section: Evaluation and Analysis Methodsmentioning

confidence: 99%

Section: Screening Of Sdgs For Agriculture Sustainabilitymentioning

confidence: 99%

Study of the Spatio-Temporal Variation of Agricultural Sustainability at National and Provincial Levels in China

Zhan,

Xin,

Shao

et al. 2023

Sustainability

View full text Add to dashboard Cite

show abstract

“…As stated in China's Strategic Plan for Rural Revitalization (CSPRR), it is explicitly required to promote the upgrading of rural energy consumption and greatly increase the proportion of electric energy in rural energy consumption. Improving the level of rural electrification is one of the vital ways to realize the transformation of low-carbon energy in China's rural areas [5]. However, some problems that China's rural energy consumption is currently facing are not conducive to the transformation of rural energy and the realization of carbon neutrality in peak CO 2 in the nation.…”

Section: Introductionmentioning

confidence: 99%

The Effects of Ecological Public Welfare Jobs on the Usage of Clean Energy by Farmers: Evidence from Tibet Areas—China

et al. 2022

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In several rural areas of China, ecological public welfare work is an effective way to improve farmers’ social participation. This job does not only increase farmers’ income but also greatly improves their enthusiasm for ecological environment protection. Under the goal of carbon neutrality in peak carbon dioxide (CO2) emissions, it is necessary to explore the impact of ecological public welfare jobs on the usage of Clean Energy (CE) in rural areas. Based on the data of 1100 farmers from Tibet areas in China, this paper applied the Ordered Probit model to explore the impact of ecological public welfare jobs on farmers’ use of CE. The results are as follows: (1) Holding ecological public welfare jobs can raise farmers’ willingness to use CE; (2) Holding ecological public welfare jobs can also promote farmers’ use of CE by enhancing their ecological environment cognition and influencing their social behavior; (3) The impact of ecological public welfare work on CE use has regional and income heterogeneities. Firstly, this effect is smaller in mixed pastoral-farming areas than in agricultural and pastoral areas. Secondly, this effect is more obvious in low-income groups. Our study provided several policies aimed at improving rural and environmental development.

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An Improved MGM (1, n) Model for Predicting Urban Electricity Consumption

Li,

2024

Energies

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The MGM (1, n) model has the characteristics of less data required, simple modeling, and high prediction accuracy. It has been successfully applied to short-term forecasting across various economic, social, and technological domains, yielding promising outcomes. There is insufficient attention paid to the interpolation coefficient of the model. The interpolation coefficients determine the extent of model fitting, which, in turn, impacts its prediction accuracy. This study made some improvements to the interpolation coefficients and proposed an improved MGM (1, n) model. IMGM (1, n) model and MGM (1, n) model were employed to compare the performance of the improved MGM (1, n) model. Upon a series of comparisons and analyses, it was concluded that the improved MGM (1, n) model has higher fitting and prediction accuracy than the other two forecasting methods. The method was used to forecast the short-term electricity consumption of Linfen City. The findings revealed that by 2030, the electricity demand in Linfen City is projected to be 563.7 billion kWh.

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The forecasting model research of rural energy transformation in Henan Province based on STIRPAT model

Cited by 3 publications

References 56 publications

Study of the Spatio-Temporal Variation of Agricultural Sustainability at National and Provincial Levels in China

Study of the Spatio-Temporal Variation of Agricultural Sustainability at National and Provincial Levels in China

The Effects of Ecological Public Welfare Jobs on the Usage of Clean Energy by Farmers: Evidence from Tibet Areas—China

An Improved MGM (1, n) Model for Predicting Urban Electricity Consumption

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