An interdisciplinary study of microplastic (MP) contamination in the water area of Lake Onego was conducted within a project funded by the Russian Science Foundation. The aim of the project was to assess the current state of this large water body, specifically its
contamination with synthetic polymer particles and the associated heavy metals, to identify the sources and areas of MP accumulation, patternsin its sedimentation and transport, and to conduct a hazard assessment of this pollution. The article provides an overview
and a summary of the obtained results. Based on seasonal hydrochemical data for 2019–2021, the current state of the lake was identified and the degree of its contamination with microplastics, heavy metals, and other chemicals was determined. The highest MP content was found in the water and in the bottom sediments of the upper, most heavily contaminated, part of the Kondopoga Bay, where wastewater from the Kondopoga Pulp
and Paper Mill enters the lake. Active accumulation of MP was detected in the bottom sediments of Lake Onego, its content being about twice that of the Baltic Sea. Spatial and seasonal patterns of MP distribution in the water column of Lake Onego were revealed.
It has been established that with the current level of Lake Onego littoral area contamination by irregularly shaped MP particles sized about 100 microns, their negative impact on the population of invasive species, Baikal amphipod Gmelinoides fasciatus, is unlikely.
Having applied SEM-EMF and Raman spectroscopy, we revealed the mechanism for mineralogical destruction of plastics driven by the crystallization and growth of microminerals, which leads to local ruptures of the plastic and accelerates its destruction. Methods
for fractionation of MP particles and desorption of metals from their surface have been developed, making it possible to obtain comparable and reproducible results when analyzing the metal content on their surface. For the first time, models were suggested to simulate microplastic generation from a set of macrofragments through stochastic destruction and filtering of three-dimensional microplastic fragments on a grid. The simulation results are in good agreement with the ratios obtained during field experiments.The revealed relationships can be used to adjust the detected levels of microplastics in the nature depending on the mesh size of the net used in sampling.