Development of an Improved System to Allow for the Standardised Characterisation and Quantification of Microfibres from Water Environments

Microplastics, including microbeads and microfibers (typically defined as <5 mm), are currently a major concern for the environment as it has been proven that no place on earth has avoided this form of pollution, even remote marine environments. These microfibres are known to cause impacts to marine ecosystems, where the large surface area-to-volume ratio of microplastics, means they concentrate persistent organic pollutants. There are many synergies between microfibre analysis from environmental samples and forensic fibre examinations. Forensic fibre examination has been a fundamental part of criminal investigations for over 50 years. In this time, many important questions have had to be asked of fibres in order to understand their potential source, their ability to shed from garments, their persistence and degradation and their prevalence in different environments, including water environments. All of these questions are also important for microplastic analysis. In addition to these questions, forensic fibre examinations must minimise and monitor contamination whilst providing both screening techniques and detailed morphological and chemical information about the samples. Today, to improve the collection, analysis and interpretation of fibres evidence, automated systems which collect large amounts of data from fibres from different environments are being sought and developed. Such systems would be extremely beneficial for the analysis and interpretation of microfibres from marine environments. Contamination prevention measures used in forensic fibre examinations have already been successfully employed in microfibre analysis from deep sea sediment; the next step is to co-develop a system which automates the identification and characterisation of microfibres whilst collating results in a database that allows cross-comparison of locations, polymer type and microfibre morphology. The analysis of microplastics, specifically microfibers, is currently dominated by techniques such as Fourier Transform Infrared (FTIR) Spectroscopy which is time consuming, difficult for samples of this size and does not provide additional morphological information about the samples which would be useful for interpretation. This PhD project is focussed upon the below areas;

1. To improve the quantification techniques of microfibers in terms of time efficiency, contamination prevention, screening capabilities (in order to identify further classifications beyond polymer type) and surface area analysis, building upon past research.

2. To build upon the above by creating and testing an automated quantification and categorisation system utilising image processing and machine learning that provides data upon the prevalence of such microfibers and allows comparison to other samples for multi-site analysis

3. To investigate the use of the automated system in longevity studies for the creation of a centralised data collection of international microfiber distributions

Queries about the project can be directed to the principal supervisor, Dr Claire Gwinnett ([Email Address Removed])

Applicant Criteria

Applicants will normally be expected have a strong Masters degree in a relevant subject area. Individuals with appropriate analytical and problem solving skills and experience in either microplastic analysis or forensic fibres analysis or image processing and machine learning will be considered. If applicants have limited or no experience in image processing and machine learning, they must be willing to learn these new skills.

How to Apply

To apply please send a covering letter and CV to the Graduate School ([Email Address Removed]) by Friday 17th November 2017. In your covering letter please explain why you are interested in the specific project and what you will bring to it, your suggested focus and why you are confident that you will be able to complete the PhD successfully (this is in place of a Research Proposal). Applications that do not state which specific project they relate to will not be considered.