Imperial College London

Dr Joseph Levermore

Faculty of MedicineSchool of Public Health

Research Associate







Norfolk PlaceSt Mary's Campus





Publication Type

4 results found

Allen D, Allen S, Abbasi S, Baker A, Bergmann M, Brahney J, Butler T, Duce RA, Eckhardt S, Evangeliou N, Jickells T, Kanakidou M, Kershaw P, Laj P, Levermore J, Li D, Liss P, Liu K, Mahowald N, Masque P, Materic D, Mayes AG, McGinnity P, Osvath I, Prather KA, Prospero JM, Revell LE, Sander SG, Shim WJ, Slade J, Stein A, Tarasova O, Wright Set al., 2022, Microplastics and nanoplastics in the marine-atmosphere environment, NATURE REVIEWS EARTH & ENVIRONMENT, Vol: 3, Pages: 393-405

Journal article

Batool I, Qadir A, Levermore JM, Kelly FJet al., 2021, Dynamics of airborne microplastics, appraisal and distributional behaviour in atmosphere; a review, SCIENCE OF THE TOTAL ENVIRONMENT, Vol: 806, ISSN: 0048-9697

Journal article

Levermore JM, Smith TEL, Kelly FJ, Wright SLet al., 2020, Detection of microplastics in ambient particulate matter using Raman spectral imaging and chemometric analysis, Analytical Chemistry, Vol: 92, Pages: 8732-8740, ISSN: 0003-2700

Microplastics have been observed in indoor and outdoor air. This raises concern for human exposure, especially should they occur in small enough sizes, which if inhaled, reach the central airway and distal lung. As yet, methods for their detection have not spectroscopically verified the chemical composition of microplastics in this size-range. One proposed method is an automated spectroscopic technique, Raman spectral imaging; however, this generates large and complex data sets. This study aims to optimize Raman spectral imaging for the identification of microplastics (≥2 μm) in ambient particulate matter, using different chemometric techniques. We show that Raman spectral images analyzed using chemometric statistical approaches are appropriate for the identification of both virgin and environmental microplastics ≥2 μm in size. On the basis of the sensitivity, we recommend using the developed Pearson’s correlation and agglomerative hierarchical cluster analysis for the identification of microplastics in spectral data sets. Finally, we show their applicability by identifying airborne microplastics >4.7 μm in an outdoor particulate matter sample obtained at an urban sampling site in London, United Kingdom. This semiquantitative method will enable the procurement of exposure concentrations of airborne microplastics guiding future toxicological assessments.

Journal article

Wright SL, Levermore JM, Kelly FJ, 2019, Raman spectral imaging for the detection of inhalable microplastics in ambient particulate matter samples, Environmental science & technology, Vol: 53, Pages: 8947-8956, ISSN: 0013-936X

Microplastics are ubiquitous contaminants, with preliminary evidence indicating they are a novel component of air pollution. This presents a plausible inhalation exposure pathway, should microplastics occur in the inhalable size range; however, this remains an analytical challenge. Here, we develop a filter-based sampling method compatible with both air quality monitoring and Raman spectral imaging (RSI) for the detection of inhalable-sized microplastics. Clean and particulate matter (PM) contaminated filters of a range of compositions were screened. RSI was validated using a plastic microbead suspension (poly(methyl methacrylate) (5-27 μm), polyethylene (10-27 μm), and polystyrene (4 and 10 μm)). Filters were loaded with the suspension before being analyzed. RSI analysis was conducted using a univariate analysis, fitting unique plastic bands to the spectral data sets, where high spatial intensity indicated the presence of microplastics. Inhalable microplastics were not visibly detectable against quartz or spectroscopically detectable against polytetrafluoroethylene (PTFE)- and alumina-based filters. While microplastics were detectable against cellulose, the PM-contaminated filters (4 and 24 h) burned during analysis. The greatest intensities for microplastics were observed against the silver membrane filter, and inhalable microplastics were still detectable in a 24 h PM sample. These findings will facilitate the acquisition of inhalable microplastic concentrations, which are necessary for understanding microplastic exposure and, ultimately, what their potential role in PM-associated health effects might be.

Journal article

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