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1.
PLoS One ; 19(2): e0295186, 2024.
Artículo en Inglés | MEDLINE | ID: mdl-38377110

RESUMEN

With economic progression in China, Yellow River Basin serves as a critical economic belt, which has also been recognized as a cradle of Chinese culture. A watershed is a complex structure of social, economic, and natural factors, and the diversity of its components determines its complexity. Studies on the spatiotemporal distribution characteristics and factors influencing the tourism eco-efficiency at the watershed scale are crucial for the sustainable regional socio-economic development, maintaining a virtuous cycle of various ecosystems, and comprehensively considering the utilization and coordinated development of various elements. Based on tourism eco-efficiency, the coordination degree of regional human-land system and the sustainable development levels can be accurately measured. With the tourism eco-efficiency in the Yellow River Basin from 2009 to 2019, the present study considers 63 cities in the Yellow River Basin as the research area by adopting the super-efficiency slacks-based measure (Super-SBM) model. Methods such as trend surface analysis, spatial autocorrelation analysis, elliptic standard deviation analysis, and hot spot analysis were used to explore their spatiotemporal distribution and evolution characteristics. The geographical and temporal weighted regression (GTWR) model was used to determine the factors influencing the tourism eco-efficiency value. The findings are as follows: ①The level of tourism eco-efficiency in the Yellow River Basin is not high, exhibiting a fluctuating upward trend. ②The tourism eco-efficiency in the Yellow River Basin shows significant spatial interdependence and agglomeration. Furthermore, the track of the center of gravity moves from northeast to southwest. ③ The tourism eco-efficiency in the Yellow River Basin is affected by various factors, with the economic development level having the greatest influence.


Asunto(s)
Ecosistema , Ríos , Turismo , China , Desarrollo Económico
2.
Huan Jing Ke Xue ; 44(11): 6095-6105, 2023 Nov 08.
Artículo en Chino | MEDLINE | ID: mdl-37973093

RESUMEN

Heavy metal pollution in urban river sediments is an important threat to river ecosystem health. To explore the temporal and spatial distribution characteristics of heavy metals in river sediments of Kaifeng City, the surface sediments of rivers were sampled in 2015 and 2021, respectively, and the contents of Cd, Cr, Cu, Ni, Pb, and Zn in sediments at different periods were compared. The heavy metal pollution in the two periods was evaluated using the indices of geo-accumulation, bio-toxicity risk assessment, and potential ecological risk. The results showed that the content of heavy metals in river sediments of Kaifeng City in 2021 were decreased significantly compared with that in 2015. Cd, Cr, Cu, Ni, Pb, and Zn decreased by 94.42%, 18.4%, 85.7%, 45.19%, 75.61%, and 92.28%, respectively. The heavy metal content in the Huafei River and Huiji River was higher than that in other rivers in both periods. Correlation and principal component analyses showed that the heavy metal pollution sources of river sediments in Kaifeng City were highly similar, and human activities such as industrial layout, road traffic, and land use were the main pollution sources. However, the results showed that the main pollutants were different between the two sampling times. In 2015, Cd, Cr, Pb, and Zn were the main pollutants, and in 2021, Cd, Cu, Pb, and Zn were the main pollutants. The results of the geo-accumulation, bio-toxicity risk assessment, and potential ecological risk indices showed that the temporal and spatial differences in heavy metal pollution in river sediments in Kaifeng City were large. However, the heavy metal pollution of the Huiji River and Huafei River was still serious, with contents in the medium and high pollution levels, especially to Cd. The heavy metal treatment of rivers in Kaifeng City has a long way to go, and it is particularly necessary to strengthen the engineering treatment for key river sections and effectively monitor key pollution elements.

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