Abstract
The treatment of samples for microplastic (MP) analysis requires purification steps that sufficiently reduce the non-MP content while preserving the targeted particles integrity. Besides their macromolecular structure this also encompasses their in situ numbers and sizes. However, any step of sample manipulation will come at a cost: particle loss, fragmentation, coagulation or degradation may lead to distorted results, predominantly in the smaller fraction of the MP size range. Therefore, the evaluation of MP resistivity against applied methods such as chemical digestions is a vital criterion for obtaining meaningful results on MP content of a sample. We developed a framework to test the applicability of MP purification methods and apply it to four protocols commonly used to prepare environmental samples for MP particle identification. The approach was designed for MP particles being too small to be handled manually (i.e. 10–70 μm). The evaluation consists of a two-tiered assay: a simple particle suspension approach is used to confirm a post-treatment qualitative recognisability of the target polymers by the analysis method of choice (here Raman and FTIR). In a following quantitative part, immobilised particles are used to evaluate the preservation of particle numbers and areas after the treatment on an individual particle level. A Python image analysis package was written that identifies, matches and measures particles on pairs of pre- and post-treatment images, and is available as open source software. Our results show that the chemical digestions using hydrogen peroxide, cooled Fenton’s and a combined alkaline / oxidative treatment using potassium hydroxide and sodium hypochlorite are suitable methods for preparing MP samples for a microspectroscopic analyses. Also acidic sodium polytungstate solution used for MP density separations and a pentane based protocol for lipid removal were found applicable for small sized MP. Certain degradative effects were found when acrylonitrile butadiene styrene is exposed to acidic treatments, as well as for MP from acrylate and epoxy based paint resins in strong oxidative regimes. Several paint resins tested here were spectroscopically not identifiable by polymer attributed bands even before treatment, indicating that these materials might slip through analyses of environmental samples and consequently being underreported. We conclude that evaluating chemical treatment procedures on MP < 100 μm is feasible, despite limitations of the current methodology which we discuss. Our results provide more certainty on the tested methods for MP studies specifically targeting small sizes and should be extended for more protocols used in MP laboratory practises.
Highlights
It is noteworthy that these degradation processes appear to affect individual PVC particles differently, as we see from the varying spectral characteristics between the replicate measurements and from varying degrees of visual yellowing from white over beige to yellowish brown across particles
We identified the need in the scientific community for a method to evaluate the impact of treatment procedures on MP particles that are smaller than what can be be handled manually, e.g. using fine-tipped tweezers
Studies which aim at identifying MP in the lower μm sizes rely on the certainty that the investigated MP particles are not destroyed by the chosen sample purification protocol
Summary
Microplastic (MP) purification techniques were developed by a number of studies in order to facilitate measurements of abundance of this inhomogeneous group of environmental contaminants [1,2,3,4,5,6,7,8,9,10,11,12] and reviews of recent developments are available [13,14,15,16,17,18]. The challenge has been to extract all relevant particles from the large diversity of sample matrices. Depending on the system studied these matrices typically consist to large degrees of inorganic fractions like minerals from sediments and soils [19], and organic content such as detritus, tissue or microbial films, confounding spectroscopic analysis [20]. Physical density and chemical inertness to certain degradative agents are the two most harnessed properties of MP to facilitate a separation from the respective sample matrix. Both of these principles involve deficiencies contributing to uncertainties in the resulting numbers or masses of MP obtained through the subsequent analysis of the treated samples
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