Dr Fay Couceiro
University of Portsmouth
Analytical windows into the world of microplastics - as defined by sampling and analytical constraints
Novel Approaches for the Screening, Isolation and Analysis of Microplastic from Environmental Samples
Microplastics, Analytical methods, Interlaboratory comparison, Data analysis, Harmonization
Need more time? Detecting Microplastic Fibres using YOLO v7 and Mask R-CNN
Compositional Analysis of Tyre and Road Wear Particles for Suitable Marker Identification
Microplastics Methods workshop
|Analytical windows into the world of microplastics - as defined by sampling and analytical constraints
|Richard Cross1, A. C. Johnson1, M. D. Jürgens1, D. S. Read1, G. A. Adediran1, R. Cox,1 F. N. Chetiu2, C. Graham2, A, Hunt2, G. Dos Santos Pereira2
1. UK Centre for Ecology and Hydrology, Wallingford, Oxfordshire, UK
2. UK Centre for Ecology and Hydrology, Lancaster, UK
|I have a strong academic background in ecotoxicology and a keen interest in research communication. I have a keen interest in understanding the specific fate and behaviours of engineered nanomaterials, microplastics and nanoplastics and how this relates to their biological interactions. This research has been in the context of the developing field of environmental risk assessment of engineered nanomaterials and plastic pollution. In particular, I am interested in how we can establish robust and reproducible methods to quantify microplastics in the environment so that the evidence base for possible policy and societal interventions is sound.
I am lucky enough for my work to take me out of the office from time-to-time. On occasion, I will find myself out in the “field” (read sewage treatment works), helping to develop representative approaches to monitoring and characterising plastic contamination in the environment.
No single method can identify and quantify the diverse contaminant that is “microplastic universe” across the whole range of polymers, sizes and forms that are encompassed within this term. Rather complimentary techniques will be required, each of which has its own specific window into this universe. This “analytical window” is the operational space within the multiple dimensions that can describe microplastic material and must be defined every time we report on microplastic concentrations from the field.
There are several key principles around which we can start to define our analytical windows for each technique. This includes both considerations around sampling and technical contraints and perfomance of different instruments. Here we will take the example of µ-FTIR, one of the most commonly employed techniques to quantify microplastics by their polymer type in the research community.
Considering sampling, questions must be asked of your study design and data, such as how patchy or variable is the environment I’m sampling from? How does this affect my achievable accuracy? What level of granularity in the data can be acheived based on the aquired sample volumes? This talk aims to highlight and explain some key concepts that can help us in the research community to bring more clarity to the data we generate and ensure its (re)usibility into the future.
|Novel Approaches for the Screening, Isolation and Analysis of Microplastic from Environmental Samples
|Louise B. Hamdy1, Gareth H. Rogers1, Meredith Cave1, David P. Gold1
|Louise Hamdy is a senior research scientist based at CGG. She is a chemist by background having obtained her Masters degree at the University of Glasgow, which included an industrial research placement with Sasol Technology UK, and her PhD in supramolecular chemistry from the University of Bath. She completed her post-doctoral research at the Energy Safety Research Institute (ESRI) in Swansea, where she developed cross-linked polymeric adsorbents for carbon dioxide capture. Now at CGG, she follows her interests in addressing environment and energy-related issues, specifically in microplastics research focusing on new laboratory techniques, and in carbon capture and storage technologies.
Microplastic has been discovered in every environment across the globe and its potential impact on our health is under increasing scrutiny. To avoid its release into the environment, be it air, water or into the ground, it is vital to establish highly polluted sites. Although sediments are often found to contain microplastic, the identification of the worst affected areas and the analysis of particles can be challenging – not least since methods to identify the presence of microplastic often involve labour intensive processes. These include the isolation of particles by picking, sieving or by using wet techniques such as density separation, often involving hazardous chemicals. To this end, we have developed a new workflow to prepare, compare, process and analyse, solid, heterogeneous environmental samples.
The workflow commences with the application of a unique automated mineralogy approach to rapidly screen multiple samples in a high-throughput manner. Automated mineralogy is generally applied to the study of mineralogical samples. However in the process presented here, the sample preparation procedures and analytical parameters are significantly adapted so that rather than identifying minerals, the method highlights the presence of carbon-based materials which are likely to be microplastic. This method has shown some success in determining the relative quantities of plastic, compared to mineral and/or natural biological matter. The use of this method facilitates the data-driven targeting of key samples for further analysis, allowing efforts of microplastic separation to be focused on samples of interest.
To isolate microplastic from a complex matrix such as sediments, we have adapted techniques to improve the effectiveness and maximise the recovery of microplastic to over 98%, while reducing reliance on hazardous and toxic chemicals. The combination of separation by density while selecting on the basis of affinity for oil, has shown improved recovery for a wide range of plastics compared to standard techniques. This allows the analysis of a concentrated microplastic isolation using advanced microscopy techniques. In this way quantitative data on essential information such as particle size and morphological detail is collected, giving us access to new insights into microplastic pollution and supporting systematic efforts to prevent it.
|Accuracy vs. efficiency: How can we better quantify nature of microplastic pollution in the ocean?
|Stephanie Wang1, Shreyas Patankar1, Lori-jon Waugh1, Kevin Landrini1, Maite Maldonado2, Abolghasem Pilechi3
1. Ocean Wise Conservation Association, 101-440 Cambie St., Vancouver, Canada
2. Department of Earth, Ocean, and Atmospheric Sciences, University of British Columbia, Vancouver, Canada
3. National Research Council, Ocean Coastal and River Engineering Research Center, Ottawa, Canada
|Lead author biography: Stephanie Wang is the lab manager of Plastics Lab at Ocean Wise, a global conservation non-profit organization based in Vancouver, Canada. Her specialty is focused on identifying and understanding the urban source and pathway of microplastics such as municipal solid and liquid waste in the coastal region. She holds a Master of Science degree in Environmental Engineering from Queen’s University and previously worked on the feasibility study of using municipal biosolid as biomass materials.
Microplastic pollution in the ocean is a pressing issue of global concern, however, researchers have consistently identified inconsistent data and lack of harmonized methods as a barrier to communicating the prevalence of plastics in the environment . Recent studies have identified urban sources, such as combined sewer overflows (CSOs), wastewater treatment plants (WWTPs), rivers, etc., as major contributors to microplastics entering the ocean . The relatively high microparticle density in samples from these sources present a challenge to getting accurate representative chemical information of microplastics and other constituent particles. At the same time, it is important to measure a breadth of these types of samples from different matrices and across geographical distribution to get actionable information on microplastics abundance.
The Ocean Wise Plastics Lab has developed methods that aim to strike a balance between efficiency and accuracy in quantifying environmental microplastics. We use a combination of statistical subsampling and big data tools to extract chemical information on microplastics from environmental samples. Our confidence in these new methods is informed by our results in a recent interlab comparison study organized by the EUROqCHARM consortium . Using analytical methods, we have also obtained some preliminary data on abundance and characteristics of microplastics in surface water samples from the Salish Sea off the coast of Vancouver, Canada. We hope that attention to methodological improvements like these will promote harmonization and increase reliability of global microplastics data.
 Win Cowger, et al., "Reporting Guidelines to Increase the Reproducibility and Comparability of Research on Microplastics," Appl. Spectrosc. 74, 1066-1077 (2020)
 Chengqian Wang, et al. "Microplastics in urban runoff: Global occurrence and fate." Water Research (2022): 119129.
 Macro- & microplastics monitoring - EUROqCHAR
|Need more time? Detecting Microplastic Fibres using YOLO v7 and Mask R-CNN
|Stamatia Galata1, Kostas Kiriakoulakis1, Jon Dick1, Timothy Lane1, Ian Walkington1
1. Liverpool John Moors University
|After completing my BA in History, Archaeology, and History of Art, MA in the Black Sea, and MSc in Maritime Archaeology, life took me in totally unexpected and interesting career path. At Liverpool John Moores University, I started my Ph.D. project, which is on the automated quantification of microplastics using open-source python code. However, my project doesn’t involve only plastic particles, at the same time I study the quantity and quality of the organic matter in the deep-sea sediment and organisms.
Microplastics are a major anthropogenic pollutant to the environment, animal and human life. In recent decades, many innovative techniques developed to detect microplastics in marine and terrestrial environments. However, the quantification of microplastics is time-consuming, and in complex environments not a trivial undertaking. In this paper, we present two freely available open-source visual recognition models to identify fibres (< 5 mm) in single images. The models, YOLOv7 and R-CNN, analyse real-world images from samples and detect microfibres in them, substantially reducing the quantification time. We introduce two models, which can be applied to quantify the contamination of microplastics in different environmental matrices and widen the accessibility to the analysis. The models need only seconds to detect fibres with relatively high accuracy from the YOLOv7 model, 71.4%, which are free, easy to employ and faster than human labour. Future research on quantifying microplastics in microplastics may be aided by the expanding datasets.
|Compositional Analysis of Tyre and Road Wear Particles for Suitable Marker Identification
|Zainab Tariq1, Ian Williams1, Malcolm Hudson2, Andrew Cundy3, Lina Zapata Restrepo1
1. Faculty of Engineering and Physical Sciences, University of Southampton, Highfield Campus, University Road, Southampton SO17 1BJ, United Kingdom
2. Faculty of Environmental and Life Sciences, University of Southampton, Highfield Campus, University Road, Southampton SO17 1BJ, United Kingdom
3. School of Ocean and Earth Science, National Oceanography Centre, University of Southampton, Southampton SO14 3ZH, United Kingdom
|I am an Environmental Scientist, working on microplastics. My Masters research highlighted that how barrages influence the transport of microplastics. Now in my PhD project, I am working on the method development for the identification of tyre and road wear particles. The study will highlight the significance of this issue to others, encouraging change in the future.
Plastic pollution is a significant global environmental issue. Tyre and road wear particles (TRWP) have recently been categorized as a source of microplastic pollution to the freshwater environment. Whilst there is a concern about the potential environmental impacts associated with microplastics, tyre and road wear particles are of particular concern because of the additives they contain. These additives are used during the manufacturing of tyres and remain there in the final product. However, extensive understanding about the composition of TRWP is hampered due to lack of standard methods and generalized protocols.
This study aimed to develop a standard laboratory method for generation of TRWP and investigate the arising qualitative/quantitative composition. A suitable, cost effective and environmentally friendly extraction method for TRWP from road dust will be developed. This method will be applied to selected environmental samples (gully pot sediments) for optimization of the proposed method, followed by analysis of TRWP by using Scanning Electron Microscopy (SEM) and Pyrolysis Gas Chromatography Mass Spectrometry (Py-GC/MS). This devised methodology will facilitate a more standardised approach to investigation of the impacts of TRWP on the environment and in a better understanding of the constituents of TRWPs that will assist in evaluating the associated environmental risks