Assessment of rural ecological environment development in China’s moderately developed areas: a case study of Xinxiang, Henan province

Xu, Wei; Fen, XU; Liu, Yunzhe; Zhang, Dan

doi:10.1007/s10661-021-09383-6

Cited by 9 publications

(2 citation statements)

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“…To evaluate the coupling coordination of industrial convergence and ecological environment in rural areas, we must first construct the evaluation index system for the two subsystems. Most of the indexes in the evaluation system are selected from the previous studies by statistic technique (Cao et al, 2010;Feng et al, 2016;Li et al, 2017;Wang et al, 2017;Li and Ran, 2019;Chen et al, 2021;Tan and Yao, 2021;Xu et al, 2021). However, there are also some new indexes coming from newly formulated polices.…”

Section: Evaluation Index Systemmentioning

confidence: 99%

“…The development of rural society and economy has put great pressure on the rural ecological environment, which has been widely concerned by scholars (Dufumier, 1992;Liu and Li, 2020). Most studies on assessment of rural ecological environment use the AHP method to build the evaluation system, which is a subjective weighting method (Xu et al, 2021;Yu, 2021). This study employs EWM, an objective weighting method, to assign weight, which can reduce the subjective deviation caused by the human factors.…”

Section: Establishment Of the Evaluation Index Systemmentioning

confidence: 99%

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Research on the coupling coordination and prediction of industrial convergence and ecological environment in rural of China

Zheng

Zhang

2022

Front. Environ. Sci.

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Coordination of rural industrial convergence and ecological environment is an important issue in rural social and economic development. This study aims to introduce a comprehensive evaluation index system and construct an integrated approach to evaluate and predict the coupling coordination between rural industrial convergence and ecological environment. Firstly, an index system including 40 indexes is developed for evaluating the two subsystems, and then entropy weight method is applied to determine the weights. Finally, a coupling coordination model and a grey prediction model are developed using provincial panel data from 2017 to 2021 for 29 provinces in China. There are three main findings: 1) penetration of new technologies and agricultural industrialization are the main driving factors of rural industrial convergence. In the three dimensions of ecological environment, environmental pressure has been the smallest contributor, implying that environmental pressure in rural China still needs attention in the next decade. 2) the coupling coordination between rural industrial convergence and ecological environment shows a fluctuating upward trend in China during the studied period and will continue to rise in the next 12 years. Among the 29 provinces studied, only 4 eastern developed provinces have reached primary coordination. The forecast data suggests that coordination with ecological environment will promote the development of rural industrial convergence. 3) the spatial differences of the coupling coordination are related to the level of economic and cultural development, application of agricultural technology, convergence of information technology, energy consumption structure and stock of natural resources. In conclusion, the research develops a rational index system and an effective approach to measure and predict the coupling coordination between rural industrial convergence and ecological environment, providing a theoretical basis for the environmental considerations in the rural industrial convergence policy-making.

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Section: Evaluation Index Systemmentioning

confidence: 99%

Section: Establishment Of the Evaluation Index Systemmentioning

confidence: 99%