(ISSN 2766-6190)
Advances in Environmental and Engineering Research (AEER) is an international peer-reviewed Open Access journal published quarterly online by LIDSEN Publishing Inc. This periodical is devoted to publishing high-quality peer-reviewed papers that describe the most significant and cutting-edge research in all areas of environmental science and engineering. Work at any scale, from molecular biology to ecology, is welcomed.
Main research areas include (but are not limited to):
- Atmospheric pollutants
- Air pollution control engineering
- Climate change
- Ecological and human risk assessment
- Environmental management and policy
- Environmental impact and risk assessment
- Environmental microbiology
- Ecosystem services, biodiversity and natural capital
- Environmental economics
- Control and monitoring of pollutants
- Remediation of polluted soils and water
- Fate and transport of contaminants
- Water and wastewater treatment engineering
- Solid waste treatment
Advances in Environmental and Engineering Research publishes a variety of article types (Original Research, Review, Communication, Opinion, Comment, Conference Report, Technical Note, Book Review, etc.). We encourage authors to be succinct; however, authors should present their results in as much detail as necessary. Reviewers are expected to emphasize scientific rigor and reproducibility.
Special Issue
Artificial Intelligence and Machine Learning for Environmental Monitoring and Prediction
Submission Deadline: April 30, 2028 (Open) Submit Now
Guest Editor
Namal Rathnayake, PhD
- Advanced Institute for Marine Ecosystem Change (WPI-AIMEC), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), 3173-25, Showa-machi, Yokohama-shi, Kanagawa, 236-0001, Japan
- Graduate School of Science and Engineering, Department of Engineering, Ocean Civil Engineering Program, Kagoshima University, Kagoshima, Japan
Research Interests: Artificial Intelligence, Machine Learning, Environmental Monitoring, Ocean and Climate Sciences, Remote Sensing, Physics-Informed Machine Learning, Explainable AI, Environmental Prediction, Data-Driven Modeling, Earth System Science
About This Topic
Artificial intelligence and machine learning are increasingly transforming how environmental systems are observed, modeled, and predicted. This Special Issue presents recent advances in AI- and machine-learning-based approaches for environmental monitoring and prediction across terrestrial, atmospheric, oceanic, and aquatic systems. We welcome original research and review articles addressing topics including remote sensing, environmental sensor networks, forecasting, spatiotemporal modeling, anomaly and event detection, physics-informed machine learning, explainable AI, data assimilation, and environmental decision support. Particular interest is given to approaches that integrate heterogeneous observations, physical knowledge, and advanced computational methods to improve the accuracy, interpretability, and reliability of environmental predictions. Applications related to climate, oceans, hydrology, ecosystems, natural hazards, pollution, and environmental sustainability are particularly encouraged.
Manuscript Submission Information
Manuscripts should be submitted through the LIDSEN Submission System. Detailed information on manuscript preparation and submission is available in the Instructions for Authors. All submitted articles will be thoroughly refereed through a single-blind peer-review process and will be processed following the Editorial Process and Quality Control policy. Upon acceptance, the article will be immediately published in a regular issue of the journal and will be listed together on the special issue website, with a label that the article belongs to the Special Issue. LIDSEN distributes articles under the Creative Commons Attribution (CC BY 4.0) License in an open-access model. The authors own the copyright to the article, and the article can be free to access, distribute, and reuse provided that the original work is correctly cited.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). Research articles and review articles are highly invited. Authors are encouraged to send the tentative title and abstract of the planned paper to the Editorial Office (aeer@lidsen.com) for record. If you have any questions, please do not hesitate to contact the Editorial Office.
Welcome your submission!
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2025 
CiteScore SJR SNIP 2.5 0.289 0.395 - Newsletter