Assessing the coordination of regional water and soil resources and ecological-environment system based on speed characteristics

Cheng, Kun; He, Kangxu; Fu, Qiang; Tagawa, Kotaro; Guo, Xinxin

doi:10.1016/j.jclepro.2022.130718

Cited by 24 publications

(7 citation statements)

References 9 publications

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“…The basic principle of the entropy method is to determine the objective weights of indicators based on their discreteness. The greater the discreteness of an indicator sample, the greater the weight assigned to the indicator [45].…”

Section: Entropy Methodsmentioning

confidence: 99%

Temporal–Spatial Evolution, Influencing Factors, and Driving Mechanisms of Environmental Regulation Performance Disparities: Evidence from China

Han

Zhao

2023

Sustainability

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Countries worldwide are facing ecological crises, and improving global ecological quality through environmental regulations is key to achieving sustainable development. As the largest developing country, China’s response to diverse ecological conflicts in different regions through environmental regulations considerably impacts global ecological conservation. Based on 2008–2020 panel data from 30 provinces, this study measures the spatial distribution patterns and time-series evolutionary trends in environmental regulation performance differences using the entropy weight method and the Theil index model. Quadratic assignment procedure and qualitative comparative analysis models were combined to explore the determinants and driving mechanisms of differences in environmental regulation performance. The results show that the prevalent uneven development of environmental regulations and disparities in regulation performance mainly originate from inter-regional differences. Political factors affecting performance differences include decision value and decision decentralization; administrative factors are command-based regulations; and rule-of-law factors include project, financial, and subject regulation. Furthermore, these three factor types can interact to form eight high environmental regulation performance paths and seven non-high environmental regulation paths, which together constitute the driving mechanism for performance differences. This study enriches the theoretical understanding of environmental regulation performance differences from the public management perspective, which can guide environmental regulation policy optimization and promote high-level, balanced environmental development.

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Section: Entropy Methodsmentioning

confidence: 99%

Temporal–Spatial Evolution, Influencing Factors, and Driving Mechanisms of Environmental Regulation Performance Disparities: Evidence from China

Han

Zhao

2023

Sustainability

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“…Fang et al used the coupling degree model to study the interaction between urbanization and ecosystem [29]. Kun et al used the coupling coordination index to evaluate the coordination between regional water and soil resources and ecological environment systems [30]. In the study of the coordination between economy and environment with the coupling model, many scholars further put forward that the coordinated development between economy and environment is a necessary condition for achieving sustainable development [31][32][33][34].…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis on the Mechanism and Influencing Factors of the Coordinated Development of Economy and Environment in China’s Resource-Based Cities

et al. 2022

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In order to explore how to achieve the coordinated development of the economy and environment, this paper uses the logistic model to verify that the city economy and the environment can achieve coordinated symbiosis. Next, an evaluation index system was used as empirical testing in order to measure the performance of the economy and environment. Further, the degree of coupling and coordination between them was obtained, and an econometric model was used to find the factors that affect the coordination and symbiosis between them. Finally, the following conclusions were obtained: (1) Resource-based cities of different development types do not show obvious differences in environmental carrying capacity and are basically at a medium carrying capacity level. (2) The level of the economic strength of resource-based cities is constantly improving, although with short-term fluctuations but with a general pace of improvement. (3) The synergy between economy and environment in resource-based cities is not high that the environment lags behind obviously. (4) The factors affecting the coordinated development of the environment and economy of resource-based cities are the annual average population and industrial wastewater discharge, which are contributing to the coordinated development of the economy and environment in resource-based cities. At the same time, the proportion of secondary industry in GDP, investment in fixed assets, and comprehensive utilization rate of general industrial solid waste inhibit the coordinated development of the economy and environment in resource-based cities. Based on the above conclusions, the paper puts forward relevant countermeasures and suggestions.

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“…The ecological environment is a complex ecosystem related to the sustainable development of society and the economy, and it is a comprehensive reflection of environmental pollution and environmental governance [38]. Therefore, we chose the pollution intensity of the ecological environment, the governance intensity of the ecological environment, the construction level of the ecological environment, and energy intensity to calculate ecological environmental development.…”

Section: The Calculation Of Green Finance and The Ecological Environmentmentioning

confidence: 99%

The Spatiotemporal Evolutionary Trend and Driving Factors of the Coupling Coordinated Development between Regional Green Finance and Ecological Environment

Shi

2022

IJERPH

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Based on the 30 inland provincial samples of China from 2003 to 2019, this article analyzes the evolutionary characteristics of the coupling coordination between green finance and the ecological environment (CCFE) using ArcGIS 10.5 software and employs the spatial Durbin model to analyze the driving factors of the CCFE. The results can be concluded as follows: (1) the CCFE of China is at a moderately low level, with a fluctuating upward trend. Spatially, it presents a spatial distribution pattern—higher in the east and lower in other regions. In terms of types, the regions of the CCFE are more in primary coordination and basic un-coordination and less in moderate un-coordination and moderate coordination. There are more regions of the green finance lagged type, and relatively few regions have achieved the financial ecological synchronization type. (2) The CCFE hotspots are concentrated in the Pearl River Delta, with a spatial “increase–decrease” development trend. Additionally, the CCFE cold spots are concentrated in the upper Yellow River Basin, with a relatively stable spatial scope. (3) The CCFE shows a positive spillover effect and accumulative delivery effect in the economic geospatial space. The population urbanization rate and the number of granted patent applications have a significant positive impact on the CCFE, and the percentage of secondary industries to GDP has a negative impact accordingly. Spatially, the percentage of secondary industries to GDP and the number of granted patent applications of nearby provinces in the economic geospatial space have a negative impact on the local CCFE. (4) The impact and spatial effect of different factors on the CCFE are obviously different. Finally, policy implications on the coordinated development of green finance and the ecological environment are also made.

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Assessing the coordination of regional water and soil resources and ecological-environment system based on speed characteristics

Cited by 24 publications

References 9 publications

Temporal–Spatial Evolution, Influencing Factors, and Driving Mechanisms of Environmental Regulation Performance Disparities: Evidence from China

Temporal–Spatial Evolution, Influencing Factors, and Driving Mechanisms of Environmental Regulation Performance Disparities: Evidence from China

Analysis on the Mechanism and Influencing Factors of the Coordinated Development of Economy and Environment in China’s Resource-Based Cities

The Spatiotemporal Evolutionary Trend and Driving Factors of the Coupling Coordinated Development between Regional Green Finance and Ecological Environment

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