Characterization of Microplastics in the Water Column of Western Lake Superior

Abstract

The amount of plastic waste in the natural environment has increased precipitously over the past 60 years and plastic contamination is now ubiquitous in aquatic systems across the planet. Microplastic represents a particularly pernicious form of plastic pollution as it is impossible to practically remediate owing to its size and already extensive distribution throughout the environment. While the reality of microplastic in the Laurentian Great Lakes has received substantial scientific attention, more work is required to fully characterize its behavior and fate in this unique freshwater system. At present, very little is known regarding the vertical distribution of microplastics throughout the water column. Most sampling campaigns in the Great Lakes have to this point focused on surface waters, sediments, and shorelines, leaving the water column conspicuously under sampled and undiscussed in the literature. In this research, we characterized the vertical distribution of microplastics in the water column of Western Lake Superior. We hypothesize the chlorophyll maximum to have the largest abundance of microplastics because it coincides with the depth of the pycnocline where the change in water density may allow trapping of microplastics that become too dense to float yet are not dense enough to reach benthic sediments. To achieve this work, we compared several novel methods for collecting microplastic samples from the water column, including Niskin bottle volume-sampling, in situ pumping, and serial filtration in a custom-built filter tower. In this research, we found evidence that in strongly stratified water columns, microplastic particles aggregate at the depth of the chlorophyll maximum, although this aggregation was not observed at sites with well-mixed water columns. Additionally, subsurface waters tended to have the highest abundance of microplastic particles indicating that buoyant microplastics are likely to preferentially accumulate in surface waters. Beyond characterization of the water column, this thesis work also sought to build a completely automated analytical pipeline for the bias-free characterization and quantification of microplastic particles in natural samples. To this end, a program was developed to count and detect microplastic particles based on two-dimensional spectral data obtained using an FTIR microscope. Computational analysis of the data yielded microplastic counts on the same order of magnitude as the manual analysis and yielded very similar trends. Overall, this research is an important first step towards a better understanding of the distribution of microplastics in the water column of Lake Superior and demonstrated an analytical approach for the bias-free detection of microplastics in natural samples using FTIR microscopy.