Current PhD Student
The use of low-cost sensors for monitoring and modelling dynamical temporal microplastic pollution in freshwater
Research Project Summary: This research intends to develop an innovative and integrated framework for tracking and assessing freshwater vulnerability in real-time by applying integrated machine learning, Geographic Information System (GIS), remote sensing and statistical downscaling methods, and low-cost water quality sensors. This study will use appropriate low-cost sensors to collect real-time data on microplastic pollution and freshwater quality. The results from this study will aid the government and water managers in land use planning and strategy developments for the maintenance, treatment, and protection of freshwater by selecting, prioritizing, and monitoring current and future sites with high potential risks of freshwater pollution from microplastics.
- To quantify the distribution of microplastic pollution in freshwater and the future trends in North-West Ireland.
- To assess the impact of climate change and human activities on freshwater vulnerability to microplastic pollution.
- To develop models for monitoring and predicting sources and pathways of microplastic pollution in freshwater.
- To carry out Spatio-temporal assessment and distribution of freshwater quality parameters.
- Delineate freshwater bodies and catchments in North-West Ireland with the highest susceptibility to microplastic pollution.
- To develop a novel integrated framework for assessing freshwater vulnerability to microplastic pollution at a fine temporal scale (less than 1-day time step).