Investigating the correlation between morphological features of microplastics (5–500 µm) and their analytical recovery

Abstract As a direct result of laboratory sample manipulation required to identify microplastics (MPs) within a given matrix, some MPs are inevitably lost. The extent of this loss can be quite significant and varies greatly depending on the sample matrix, choice of protocol and target MPs in question. Defining analytical MP recovery is therefore a critical component in ensuring the quality of MP protocols. The potential relationship between particle size and recovery rate has been widely discussed but remains uncertain. To determine whether MP loss correlated with particle size, three aliquots of polyethylene fragments in the 5–50 µm size range and three aliquots of polypropylene fragments in the 50–500 µm size range, were consecutively transferred back and forth from filter to liquid. After each individual transfer the analytical recovery within specified size groups, was evaluated by applying high-resolution darkfield microscopy. Average recovery across the entire size range was estimated at 80% with a standard deviation (std. dev.) of 26%. Notably, particle coverage on filters (A%) showed a more significant impact on recovery than particle size. Maintaining A% below 5% on filters for microscopic analysis is advised to prevent excessive loss due to particle agglomeration. To determine whether the use of red polyethylene fragments in the 5–50 µm size range in combination with darkfield microscopy could potentially improve MP recovery evaluation in environmental samples, three aliquots of 0.5 g of dry brown trout muscle tissue were spiked and treated according to a relevant protocol. This size-discriminating approach accurately determined average recovery at 52% with a std. dev. of 4% and demonstrated the potential for correction of the concentration enhancement of smaller MPs resulting from particle breakup during sample pre-treatment, which would otherwise lead to overestimation of smaller size fractions.