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Efficiency Evaluation in Atmospheric Environment
This special issue belongs to the section “Atmospheric Techniques, Instruments, and Modeling“.
Special Issue Information
Dear Colleagues,
With the increase of human social activities, environmental protection and atmospheric environmental efficiency improvement have attracted increasing attention from the environment and atmospheric research communities, especially in the atmosphere, water resources, renewable energy, and process industries, etc. Traditional mechanism model analysis and actual production verification methods lead to the disadvantages of difficult efficiency evaluation, high complexity, and excessive cost. Through data analysis and artificial intelligence technologies such as neural networks, principal component analysis, data computing, etc., atmospheric and environmental utilization efficiency can be evaluated based on data-driven methods. This can reduce the unnecessary influence factors in the actual atmospheric and environmental efficiency evaluation process, and quickly establish the atmospheric and environmental efficiency evaluation model, which is conducive to the realization of atmosphere protection and emission reduction, and then improve the environmental protection efficiency.
Dr. Yongming Han
Dr. Nanjun Chen
Dr. Merja Tölle
Guest Editors
Manuscript Submission Information
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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- Data and model driven
- Intelligent optimization
- Environmental impact and risk assessment
- Atmospheric and environmental physics
- Climate change and variability
- Land–atmosphere interactions
- Efficiency evaluation
- Artificial intelligence
- Data mining and fusion
- Environmental protection
- Energy saving and optimization
- Air pollution emissions
- Renewable energy
- Hydrology and hydrogen energy
- High-efficiency energy devices
- Water and wastewater treatment
- Neural network
- Deep learning
- Urban heat island
- Environmental engineering
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