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In the era of the digital economy, traditional industries have begun to realize digital transformations. For commercial banks, digital transformation is a trend and a requirement and is the only way to achieve sustainable development. At the same time, at the helm of the enterprise, executives play an essential role in the development of commercial banks. This study explored the relationship between digital bank transformation and bank efficiency, environment, society, and corporate governance (ESG) through empirical analysis, and how executives' innovation awareness and executive technical background affect the relationships between digital bank transformation, bank efficiency, and ESG. This study used the regression method of fixed effects to conduct empirical research on the data of China's A-share listed banks from 2011 to 2021. The research results show that the digital transformation of banks has improved efficiency and promoted the ESG performance of commercial banks. At the same time, executives' innovation consciousness and technical background have played a positive regulatory role in banks' digital transformation to promote bank efficiency and ESG. The main research object of this study was Chinese commercial banks. The bank's digital transformation results were examined and the research was expanded to digital transformation and ESG. At the same time, this study has particular significance for investors who have a financial interest in banks. [ABSTRACT FROM AUTHOR]

This article aims to realize the combined application of satellite remote sensing data and Lidar data fusion of atmospheric ozone in the ozone distribution prediction in western China. Firstly, the ozone remote sensing data and Lidar vertical monitoring data detected by ozone monitoring instruments are collected from various provinces in western China; the recurrent neural network (RNN) model based on the gated recurrent unit and the convolutional neural network (CNN) model based on time series are constructed and integrated to obtain the RNN–CNN model for ozone concentration prediction, and the prediction performance is compared with that of the RNN and CNN model. Satellite remote sensing data show that the total ozone concentration in western China has obvious spatial distribution characteristics, and can be elevated with the increase in latitude; the ozone concentration in the north is higher and the ozone concentration in the south is lower in different seasons in western China, and it in autumn and summer is lower than that in spring and winter generally. The hour-by-hour change of ozone concentration shows that the ozone concentration in different seasons reaches a trough around 9–10 o'clock, and reaches a peak around 16–17 o'clock. When the RNN–CNN model is applied to predict the hourly change of ozone concentration within a day, it can achieve the best root-mean-squared error (18.13), mean absolute error (11.64), and index of agreement (0.973). The monitoring results of Lidar data at a certain site are compared and analyzed, and the results show that the fitness is the best between the predicted value of ozone concentration obtained by the RNN–CNN model and the actually measured value. This research provides the possibility for the intelligent prediction of atmospheric ozone concentration distribution and has reliable theoretical value and practical significance. [ABSTRACT FROM AUTHOR]

Soil erosion has been a widely studied hydrological issue, and the further deterioration of soil and water environments caused by soil erosion has attracted extensive attention from global scholars. At present, there are relatively few studies on preventing and controlling soil erosion to avoid the introduction of pollutants from surface runoff in grasslands during rainfall events. To identify the optimal vegetation coverage of Cynodon dactylon grassland for controlling soil erosion during rainfall events, bare land (0%) was used as the control in this experiment. Simulated rainfall experiments were carried out with three levels of coverage (30%, 60% and 90%) under four slope conditions (0°, 5°, 10° and 20°) and four rainfall intensities (20 mm/h, 30 mm/h, 60 mm/h and 90 mm/h). The results suggested that the capacity of Cynodon dactylon grassland to reduce the runoff coefficient and sediment yield decreased with increasing rainfall intensity and slope but increased with increasing vegetation coverage. The results of the structural equation model revealed close relationships between vegetation coverage and the reduction rate of the runoff coefficient and the reduction rate of the sediment yield. The results of the response surface methodology suggested that the vegetation coverage of Cynodon dactylon grassland should be higher than 86% to ensure that the reduction rate of the runoff and sediment of grassland is greater than 60%, and it is advisable that the planting slope of grassland not exceed 10°. The results of this study serve as a guide for the recovery and restoration of grasslands to control soil erosion and prevent the production as well as further spreading of pollutants in China. This study highlights the need to consider the prevention and control of soil erosion as a source of pollutants. Image 1 • We examined the effects of rainfall events on runoff production and sediment loss. • The optimal coverage of grassland was identified with response surface methodology. • The optimal coverage of grassland should be higher 86% for controlling soil erosion. • Planting slope of less 10° in grassland can reduce the risk of soil and water loss. [ABSTRACT FROM AUTHOR]