Dear Colleagues,

Efficiency and sustainability will be key for the natural resource conservation of the future. Predicting and monitoring the pollution concentration of various types of natural resources is an essential requirement for natural resource management. The pollutants generally come from automobile exhaust and industrial combustion process. The core of pollution prediction is to monitor the release of various exhaust gas in real time, accurately forecast the pollution concentration in advance, and form a maintenance decision plan for carbon neutral.

Artificial intelligence (AI) is leading to a deep methodology innovation, reducing pollution concentration, giving more importance to researchers. The advantage of AI is to learn, analyze and intelligently process a large amount of data, and make automatic judgments or assist humans to make judgments, so as to improve the reliability and time of early warning systems. The premise of accurate prediction of artificial intelligence is that a perfect theoretical model should be established. Nowadays, the monitoring methods of pollutants are more and more popular, and the means to deal with carbon neutralization are more and more demanded. However, the accuracy of monitoring is still very important in the prediction of pollution concentration. Thus, this special issue is particularly focus on accurately predict pollutants based on AI methods.

This Special Issue aims to gather high-quality papers emphasizing prediction of pollution concentration, carbon balance, nutrient economy, and their interactions at different scales. Submitted contributions will go through a peer-review process performed by independent reviewers. Original case studies and review papers are invited for publication.

Dr. Xiuli Wang
Dr. Yang Li
Guest Editors