Pollution Mechanisms and Source Apportionment of Typical Pollutants in Aquatic Environments
A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water Quality and Contamination".
Deadline for manuscript submissions: 5 November 2025 | Viewed by 215
Special Issue Editor
Interests: sources analysis; migration and transformation of biomass; evolution of water chemistry; water quality assessment
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue focuses on the pollution mechanisms and source apportionment of typical pollutants in various water systems within a watershed, including rivers, lakes, and groundwater. It aims to provide a comprehensive and in-depth academic exchange platform for researchers of water environments. The content of this Special Issue will cover water quality assessments, the pollution mechanisms of typical pollutants, the migration and transformation processes of pollutants, source tracking of pollution, the development and application of water quality models, as well as ecological impact assessments caused by water quality changes. These research findings will not only help us more accurately understand the dynamics of water quality within the watershed, but also provide a solid theoretical basis for formulating scientific and effective water quality protection measures. We sincerely invite water environment scientists, engineers, policymakers, and water resource managers to participate in this Special Issue. Our goal is to promote comprehensive exchanges across disciplines and fields and jointly advance the process of water environmental protection and sustainable development. We look forward to your active contributions to the academic developments and practical applications in this field.
Prof. Dr. Qianqian Zhang
Guest Editor
Manuscript Submission Information
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Keywords
- rivers, lakes, and groundwater
- water quality
- hydrochemistry
- pollution sources
- sources analysis
- assessment methods
- isotope technology
- machine learning
- multivariate statistical techniques
- models
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