The monitoring and maintenance of the Inner Mongolia section of the Yellow River Basin is of great significance to the safety and development of China’s Yellow River Economic Belt and to the protection of the Yellow River ecology. In this study, we calculated diagnostic values from a total of 520 Landsat OLI/TM remote sensing images of the Yellow River Basin of Inner Mongolia from 2001 to 2020. Using the RSEI and the GEE Cloud Computing Jigsaw, we analyzed the spatial and temporal distribution of diagnostic values representative of the basin’s ecological status. Further, Mantel and Pearson correlations were used to analyze the significance of environmental factors in affecting the ecological quality of cities along the Yellow River within the study area. The results indicated that the overall mean of RSEI values rose at first and then fell. The RSEI grade to land area ratio was calculated to be highest in 2015 (excellent) and worst in 2001. From 2001 to 2020, ecological quality monitoring process of main cities in the Inner Mongolia region of the Yellow River Basin. Hohhot, Baotou, and Linhe all have an RSEI score greater than 0.5, considered average. However, Dongsheng had its best score (0.60, good) in 2005, which then declined and increased to an average rating in 2020. The RSEI value for Wuhai reached excellent in 2010 but then became poor in 2020, dropping to 0.28. The analysis of ecological quality in the city shows that the greenness index (NDVI) carried the most significant impact on the ecological environment, followed by the humidity index (Wet), the dryness index (NDBSI), the temperature index (Lst), land use, and then regional gross product (RGP). The significance of this study is to provide a real-time, accurate, and rapid understanding of trends in the spatial and temporal distribution of ecological and environmental quality along the Yellow River, thereby providing a theoretical basis and technical support for ecological and environmental protection and high-quality development of the Yellow River Basin.
In this work, we performed density functional theory calculations to explore reaction pathways of ethanol to 1,3butadiene on the surfaces of MgO(100) and MgO(110). The overall activation barrier and reaction energy were calculated for the Meerwein−Ponndorf−Verley (MPV) reaction and relative side reactions, cross aldol condensation, and hydrogenation reaction. It is verified that the acidity and basicity sites on MgO(110) are stronger than those on MgO(100), which is favorable for the MPV reaction and cross aldol condensation. On MgO(110), the MPV reaction takes place via the ethoxy and crotonaldehyde route due to dissociated ethanol and directly deoxidizes to produce 1,3butadiene rather than the proton return reaction finally. The ratedetermining step of the MPV reaction is proton transfer reaction on both surfaces. In addition, the cross aldol condensation is less likely to occur on MgO(100) and the hydrogenation side reaction is less likely to occur on MgO(110).
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