Sustainable Marine Pollution Control Through Microbial Processes
A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Marine Pollution".
Deadline for manuscript submissions: 25 May 2026 | Viewed by 4
Special Issue Editor
Interests: comparative metagenomic analysis of oil-degrading marine microbiome; development and application of environmental biotechnology for treatment of polluted soil and water
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Marine environments face increasing pollution from plastics, hydrocarbons, heavy metals, nutrients, persistent organic pollutants, and legacy contaminants, including sea-dumped explosives and chemical weapons. Microorganisms play crucial roles in degrading and detoxifying these pollutants, offering sustainable tools for ocean restoration. However, variable environmental conditions, ecosystem complexity, and scalability challenges still limit practical applications.
Recent advances in molecular microbial ecology, machine learning, and AI-driven modelling have improved our understanding of biodegradation processes and enhanced microbial bioremediation efficiency and control. This Special Issue invites studies focusing on microbial communities and metabolic pathways involved in pollutant degradation, transformation, and co-contamination effects, as well as computational and machine-learning approaches for process analysis and system optimisation, and novel biotechnological solutions for pollution mitigation in marine systems.
Topics of interest include, but are not limited to:
- Microbial communities and metabolic pathways responsible for pollutant degradation in different marine compartments.
- Microbial ecology and synergistic mechanisms of biodegradation and biotransformation under co-contamination scenarios (e.g., plastics, hydrocarbons, heavy metals, or legacy pollutants).
- Advanced computational, AI, and machine-learning approaches for analysing and optimising microbial degradation and bioremediation processes.
- Development, optimisation, and field application of biotechnological approaches for pollution mitigation in marine systems.
We warmly invite researchers to contribute original research articles, comprehensive reviews, and case studies that enhance the understanding of microbial degradation processes and support innovative, sustainable solutions to combat marine pollution.
Prof. Dr. Jaak Truu
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
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. Journal of Marine Science and Engineering 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 2600 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
- biodegradation
- bioremediation
- biotransformation
- marine microbiome
- co-contamination
- legacy contaminants, machine learning and artificial intelligence
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