Overview

Project Highlights:

• The potential to quantify the extent of the Great Garbage Patches and contribute towards cleaning our oceans
• Opportunity (not compulsory) to spend a few months in a top-rank Chinese University
• An exciting multidisciplinary project combining lab work and satellite data processing

Overview:
The use of plastic based materials offers large societal benefits. However, a by-product of the production of 250 million tonnes of plastic a year1 is the contamination of natural ecosystems by fugitive plastics. The world’s oceans are one natural ecosystem where it is estimated that there are 5.25 trillion pieces of plastic (270,000 tonnes2) at present. Due to ocean currents, this plastic tends to accumulate within five major ocean gyres that are referred to as “Garbage Patches”. Plastic here represents a hazard to animals through entanglement and ingestion, as well as a threat to the food chain from the accumulation of persistent organic pollutants (Figure 1).
The first step in tackling this problem is to quantify it; a particularly challenging task however given the large extent and remoteness of the Garbage Patches. Currently, quantification is limited to extrapolating information from a relatively small number of ocean trawls covering a limited area. There is therefore a pressing need for an approach that can offer reliable maps of plastic contamination at a global scale. This project aims to address this requirement by using satellite data.

The successful candidate will undertake exciting multi-disciplinary work that involves:

  1. Laboratory experiments investigating the hypothesis that satellite data acquired by Synthetic Aperture Radar (SAR) can reliably detect plastics due to biofilm formation and a dampening of waves over the ocean surface3.
  2. Quantifying the amount of plastic in the world’s ocean gyres through the analysis of ESA Sentinel-1 satellite imagery.

In summary, this project aims to quantify plastic accumulation in the world’s oceans with unprecedented resolution and accuracy. The obtained maps will help optimise future clean-up activities.

Plastic litter in the marine environment (Source: BBC -http://www.bbc.co.uk/news/science-environment-34414710)

Methodology

This project includes lab work and data analysis.

The lab experiments: Ocean simulation of microbial colonisation and radar mapping of biofilms. This work would require the use of tanks to simulate ocean conditions. Micro-plastics will be added into the tank and the growth of biofilms monitored over several weeks using spectrophotometry and high powered electron microscopes. The ambient temperature and light levels would be monitored and/or fixed to simulate typical ocean conditions. Ocean waves will be simulated and the dampening properties of biofilms observed using a ground based radar and a high resolution camera.

Processing of satellite data: The candidate will download freely available ESA Sentinel-1 SAR images to observe and quantify the extent of plastic accumulation in oceans. The images will be processed using freely available ESA software and Python or Matlab.

Training and Skills

CENTA students are required to complete 45 days training throughout their PhD including a 10 day placement. In the first year, students will be trained as a single cohort on environmental science, research methods and core skills. Throughout the PhD, training will progress from core skills sets to master classes specific to CENTA research themes.

This is a multi-disciplinary project including topics related to (a) Earth observation; (b) radar and electronics; (c) waste management; (d) data handling and programing.

The successful candidate will have the opportunity to gain valuable skills in the context of: (a) carrying out laboratory experiments; (b) controlling electronic measurement devices; (c) analysing and processing satellite data using Python or Matlab.

Timeline

Year 1: Preparing a literature review on microwave scattering from ocean and microbial production of surfactants. Lab experiments monitoring biofilm formation.

Year 2: Analysis of experimental data will be tackled and further experiments undertaken. Exploration of Sentinel-1 data.

Year 3: The student will use the data collected in the two previous expriments to formulate their thesis chapters and expected submission of journal papers.

 

Partners and collaboration (including CASE)

This work is linked to another project with the ESA and the successful candidate could chose to visit a top-rank Chinese Universities in a training exchange and research collaboration for up to 6 months. This visit is optional and the successful completion does not dependent upon it.

Further Details

Students should have a strong background in engineering or physical sciences and enthusiasm for research and data acquisition. Experience of electronics, signal processing, waste management and programming is desirable. The student will join a well-established team researching radar remote sensing, waste management and mathematics at the Open University. Please contact Dr. Armando Marino for further information (Armando.marino@open.ac.uk).

Applications should include:

Apologies that some bits of information are requested multiple times on different forms. Please fill in everything requested. 

Applications should be sent to

STEM-EEES-PhD-Student-Recruitment@open.ac.uk  

by 5 pm on 25th January 2017