Using FTIRS as pre-screening method for detection of microplastic in bulk sediment samples.

We present calibration models for the detection of two types of plastic (LDPE, PET) in sediments, developed from analysis of synthetic sediment mixtures and application of Fourier transform infrared spectroscopy (FTIRS) and partial least squares regression (PLSR) modeling. Synthetic sediment mixtures were produced using ground plastic particles mixed with various different sediment matrixes yielding LDPE and PET contents ranging from 0 to 5 wt%. The resulting PLSR calibration models between the FTIRS spectral information and the defined plastic concentration of the synthetic sediment mixtures show strong cross-validated correlations (R2CV = 0.73 and 0.72) as well as low root-mean square errors of cross-validation (RMSECV = 0.72 and 0.61; 14.4% and 12.2% when expressed as % of gradient). Application of the calibration to natural sediments shows that the method can be used to detect the presence of microplastics in sediment. The results are only semi-quantitative and semi-qualitative, and the method is suitable mainly for samples with very high microplastic concentrations (>1%). However the major advantage of this procedure is the time and cost efficiency. For studies with large amounts of samples (e.g. monitoring applications) we recommend this method as a pre-screening tool for selecting samples with plastic content for further analysis.