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In this paper, we proposed an assessment system of forest environmental carrying capacity from many aspects and comprehensively evaluated and predicted the forest environmental carrying capacity of 40 cities in the Yangtze River Delta of China by using the proposed deep learning-based model. In addition, the proposed model is used to dynamically evaluate the comprehensive scores of forest environmental carrying capacity of 34 provinces and cities in China between 2015 and 2020. This paper also has the following contributions: (1) a deeply integrated unidirectional bidirectional LSTM considering the correlation of time series is proposed. The bidirectional LSTM network is used to deal with the backward dependence of input data to prevent the omission of some useful information, which is beneficial to the prediction results. (2) In terms of missing data processing, the Mask layer is added to subtly skip the processing of missing data, which will help to enhance the evaluation results., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Song Linshu et al.)

This study examines the impact of economic and financial activities on air pollution in China using prefecture-level panel data from 2004 to 2015. Recruiting the air quality index (AQI) as a measure of overall air quality in Chinese cities, we find that industrial production, financial development, and economic integration lead to higher overall air pollution. Nevertheless, efficiency in urban planning through public transportation and population density alleviates this environmental degradation. A closer look into the two main air pollutants in China, sulphur dioxide and dust, further highlights the complexity of the issue. We find that trade openness reduces both sulphur dioxide and dust emissions, whereas financial development reduces sulphur dioxide emissions but increases dust in Chinese cities. Our findings are of particular interest to policymakers when devising environmental policies in support of sustainable economic development.