Development and application of a Py-GC/MS method for the quantification of microplastic contamination in terrestrial environments

This thesis details the development and application of a pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) method for the quantification of microplastic pollution in terrestrial samples. Initial analysis of plastic standards using Py-GC/MS revealed diagnostic pyrolytic products, which were utilised alongside internal standards and linear regression to create calibrations for each studied synthetic plastic. A microplastic extraction protocol for soils and sediments was developed, namely an overnight density separation with wet peroxide digestion, and its efficacy confirmed through spiking and recovery experiments. These laboratory methods were also validated through a contamination study, which revealed low levels of microplastic contamination from airborne deposition and laboratory reagents. Comparison with Fourier-transform infrared spectroscopy (FT-IR) further demonstrated the efficacy of pyrolysis for microplastic applications: the analysis of FT-IR filters revealed particles missed during manual selection, which is avoided in whole-filter pyrolytic analyses. Furthermore, false identification of FT-IR spectra was reduced through combined use with Py-GC/MS. Using the developed extraction and analytical protocols, microplastic concentrations were investigated in terrestrial samples from polar and equatorial regions. Beach samples from Signy Island, Antarctica, revealed low concentrations of microplastic, except for near the research station. This demonstrates that the research station is the main source of microplastic pollution and that medium/long-range transport is not a major microplastic pathway in this environment. The spatial distribution of microplastic from sediments in the Kota mangroves and the Nethravathi River, southwest India, also indicate that local sources are important. However, river dynamics and seasonal monsoon flooding events were also found to impact the microplastic concentrations observed. In addition, this dataset enabled further comparison of the developed method to FT-IR, exhibiting broadly similar results. Overall, these findings demonstrate that Py-GC/MS can be successfully applied for the determination of microplastic concentrations in terrestrial samples, with a view to establishing effective mitigation strategies.

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