Assessing rural energy poverty and early warning based on long-run evolution for clean energy transition in China

Author:

Yin Shi1ORCID,Wang Man1,Shi Yaqi1,Zhao Yumeng1

Affiliation:

1. College of Economics and Management, Hebei Agricultural University , Baoding 071000, China

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.

Funder

National Social Science Fund of China

Publisher

AIP Publishing

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