scholarly journals Industrial ecological efficiency of cities in the Yellow River Basin in the background of China’s economic transformation: spatial-temporal characteristics and influencing factors

Author(s):  
Chengzhen Song ◽  
Guanwen Yin ◽  
Zhilin Lu ◽  
Yanbin Chen
2021 ◽  
Author(s):  
Chengzhen Song ◽  
Guanwen Yin ◽  
Zhilin Lu ◽  
Yanbin Chen

Abstract At present, China's economic development has entered a "new normal." Exploring Industrial ecological efficiency (IEE) in the background of economic transformation is of great significance to promote China's industrial transformation and upgrading and achieving high-quality economic development. Based on the Super-Efficiency DEA model, this study evaluated the IEE of cities in the Yellow River Basin from 2008 to 2017. Exploratory spatial data analysis methods were used to explore the spatial-temporal evolutionary characteristics, and a panel regression model was established to explore the influencing factors of IEE. The research results showed that: The IEE in the Yellow River Basin exhibited an elongated S-shaped evolutionary trend from 2008 to 2017, and the mean IEE of cities presented a trend whereby Yellow River Basin’s regions could be ranked in the following order: lower reaches > middle reaches > upper reaches. There was significant spatial autocorrelation of the IEE in the Yellow River Basin, and the hot and cold spots showed an obvious "spatial clubs" phenomenon. The results of panel regression show that the influence factors of IEE in the Yellow River Basin showed spatial heterogeneity in their effect.


Author(s):  
Yu Chen ◽  
Xuyang Su ◽  
Qian Zhou

The outbreak of COVID-19 has prompted consideration of the importance of urban resilience. Based on a multidimensional perspective, the authors of this paper established a comprehensive evaluation indicator system for evaluating urban resilience in the Yellow River basin (YRB), and various methods such as the entropy value method, Theil index, exploratory spatial data analysis (ESDA) model, and geographical detector model were used to measure the spatiotemporal characteristics and influencing factors of urban resilience in the YRB from 2011 to 2018. The results are as follows. (1) From 2011 to 2018, the urban resilience index (URI) of the YRB showed a “V”-shaped dynamic evolution in the time series, and the URI increased by 13.4% overall. The resilience of each subsystem showed the following hierarchical structure: economic resilience > social resilience > ecological resilience > infrastructure resilience. (2) The URI of the three major regions—upstream, midstream, and downstream—increased, and the resilience of each subsystem in the region showed obvious regional characteristics. The comprehensive difference in URI values within the basin was found to be shrinking, and intraregional differences have contributed most to the comprehensive difference. (3) There were obvious zonal differences in the URI from 2011 to 2018. Shandong Peninsula and Hohhot–Baotou–Ordos showed a “High–High” agglomeration, while the southern and southwestern regions showed a “Low–Low” agglomeration. (4) Among the humanist and social factors, economic, fiscal, market, urbanization, openness, and innovation were found to be the factors that exert a high impact on the URI, while the impacts of natural factors were found to be low. The impact of the interaction of each factor is greater than that of a single factor.


2020 ◽  
Vol 12 (6) ◽  
pp. 2488 ◽  
Author(s):  
Luping Shi ◽  
Zhongyao Cai ◽  
Xuhui Ding ◽  
Rong Di ◽  
Qianqian Xiao

Promoting new-type urbanization with the concept of green development has become an inevitable requirement for high-quality development in the Yellow River Basin. Grasping the development trend and influencing factors of green urbanization level in the Yellow River Basin is of great significance for implementing the international conventions on environmental protection and participating in global environmental governance. This paper selects the green urbanization level panel data of nine provinces in the Yellow River Basin from 2006 to 2018. Then, principal component analysis and factor analysis are applied to measure and evaluate the green urbanization level of each province. Furthermore, this paper constructs a dynamic panel estimation model and uses differential generalized method of moments (DIF-GMM) model and system generalized method of moments (SYS-GMM) model to explore the influencing factors. The results show that the overall level of green urbanization in the Yellow River Basin has steadily and rapidly increased, and there are significant spatial differences. The green urbanization level of eastern provinces is significantly higher than that of central and western provinces. In addition, the overall level of green urbanization shows a convergence trend. From the perspective of influencing factors, the factors that have significant positive effects on the level of green urbanization include economic development level, technological innovation level, and urban size. Industrial structure, foreign direct investment (FDI), and education level counteract the level of green urbanization. However, environmental regulation strength and opening degree fail to pass the significance test. Therefore, it is necessary to promote and upgrade industrial transformation, improve the quality of opening up, and strengthen cooperation in technological innovation and environmental governance. There are requirements that the government control the urban size and population scientifically and implement the environmental access system strictly in order to improve the level of green urbanization in the Yellow River Basin. It is more possible to achieve harmonious economic and ecological environment development.


2019 ◽  
Author(s):  
Ting Hua ◽  
Wenwu Zhao ◽  
Yanxu Liu ◽  
Yue Liu

Abstract. In the Yellow River basin, soil erosion is a significant natural hazard problem, seriously hindering the sustainable development of society. An in-depth assessment of soil erosion and a quantitative identification of the influencing factors are important and fundamental for soil and water conservation. The RUSLE model and geographical detector method were applied to evaluate and identify the dominant factors and spatiotemporal variability in the Yellow River basin. We found that topographical factors such as slope and surface roughness were the dominant factors influencing the spatial distribution of soil erosion in the Yellow River basin, while rainfall and vegetation were as follows. In the period of low rainfall and vegetation coverage, the interaction of rainfall and slope can enhance their impact on the distribution of soil erosion, while the combination of vegetation and slope was the dominant interacting factor in other periods. The dominant driving factors of soil erosion variability were affected by changes in rainfall, but the contribution decreased. The spatial and temporal heterogeneity of soil erosion on a monthly scale was higher, and July had the highest amount of soil erosion with a multi-year average of 12.385 ton/(km²·a). The results provide a better understanding of the relationships between soil erosion and its latent factors in the Yellow River basin. Given the temporal and spatial heterogeneity effects of geographical conditions, especially at the basin scale, policy-makers should form a collaborative environmental governance framework to minimize the risk of soil erosion.


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