Predicting the Fate and Transport of Contaminants in Soil and Groundwater with Machine Learning
A special issue of Toxics (ISSN 2305-6304). This special issue belongs to the section "Novel Methods in Toxicology Research".
Deadline for manuscript submissions: 21 February 2025 | Viewed by 120
Special Issue Editors
Interests: soil erosion and land degradation; ecosystem service; soil carbon cycle influenced by soil erosion; agricultural conservation
Interests: effects soil erosion on carbon and nitrogen cycle; soil ecosystem function; microbial diversity; plant functional traits
Special Issue Information
Dear Colleagues,
Soil and groundwater pollution issues are escalating, presenting a significant threat to both the ecological environment and human health. The fate and transport of contaminants in soil and groundwater have emerged as pivotal subjects in environmental science research. Recent advancements in machine learning technology have opened up new avenues for forecasting and modeling the behavior of these contaminants. We should note that soil erosion is also a critical factor that severely impacts the quality of soil and groundwater. Specifically, soil erosion can accelerate the release and migration of contaminants in the soil, affect the migration pathways and degradation processes of contaminants, and increase the risk of contaminants infiltrating groundwater, etc.
This Special Issue aims to collect original research as well as review articles exploring contaminant fate and transport in soil and groundwater, alonside different aspects of machine learning technology application. Topics for this call for papers include, but are not restricted to, the following:
- Transportation and transformation mechanisms of contaminants in complex environments, and complex environmental system modeling;
- Quantitative assessment of the impact of soil erosion on the fate and transport of soil and groundwater pollutants, modeling, and validation;
- Behavior of new pollutants (such as nanomaterials, emerging pollutants, etc.) in eroded soil and groundwater;
- Machine learning applications in pollutant concentration prediction, pollution source identification, and tracking;
- High-precision monitoring technology, and establishment of intelligent monitoring and warning systems.
Prof. Dr. Xingwu Duan
Dr. Li Rong
Dr. Yifan Dong
Guest Editors
Manuscript Submission Information
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Keywords
- transportation and transformation mechanisms of contaminants
- modeling and validation
- soil erosion
- behavior of new pollutants
- machine learning
- high-precision monitoring
- intelligent monitoring and warning systems
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