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Source detection and treatment of microplastics

Department of Chemical and Process Engineering

About the Project

Microplastics pose an ecological risk, causing starvation, suffocation, laceration and death of marine organisms and disrupting critical ecosystem services and biological functions. Sewage sludge is a major reservoir and pathway for microplastics pollution. This is so because biosolids from wastewater treatment plants are often applied on agricultural lands as a nutrient source, which increases the risk of microplastics contamination. And though plastics break into smaller fragments due to mechanical forces ꟷsome degrading as a result of oxidation, ionizing radiation, thermal degradation etc, others do not degrade or persist and if at all proceeding slowly. Current waste treatment methods have not proven to efficiently remove microplastics without compromising sludge characteristics. The varying size, distribution and composition of microplastics makes it difficult to detect in the environment. This project aims to enhance the understanding of point-source detection of microplastic fragments using spectrophotometry and chemometric methods. Advanced thermal treatment processes e.g. pyrolysis will be explored for removing microplastics in sediments, sludges, and soil samples. Project outcomes are expected to contribute to improved environmental monitoring and ultimately to ensure prevent and control microplastic pollution.

In addition to undertaking cutting edge research, students are also registered for the Postgraduate Certificate in Researcher Development (PGCert), which is a supplementary qualification that develops a student’s skills, networks and career prospects.

Information about the host department can be found by visiting:

Funding Notes

This PhD project is initially offered on a self-funding basis. It is open to applicants with their own funding, or those applying to funding sources.

Students applying should have (or expect to achieve) a minimum 2.1 undergraduate degree in relevant engineering (e.g. chemical engineering, process engineering, mechanical engineering, energy engineering) or related science discipline and be highly motivated to undertake multidisciplinary research. Knowledge and/or experiences in chemometrics, material characterisation (chromatography/spectrometry methods), surface analysis, statistics/data science and key software packages e.g. Python, Matlab are desirable.

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