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Monitoring of microplastic concentrations in 132 Iowa lakes in relation to abiotic, biotic, and anthropogenic factors

2023 1 citation ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 30 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Psalm Solomon Blaine Amos

Summary

Researchers surveyed microplastic concentrations in 132 lakes across Iowa, examining how biological, physical, and human factors influence plastic levels. Lakes near populated areas and with greater human activity showed higher microplastic concentrations, demonstrating that freshwater lakes are broadly contaminated by plastic pollution.

Polymers
Study Type Environmental

Global annual plastic production rate is approaching 400 million metric tons, with substantial amounts invading aquatic environments yearly. Numerous studies have been conducted monitoring marine environment plastic litter. An understanding of plastic litter's magnitude in freshwater ecosystems is lagging, particularly for microplastics (MP(s) 100 nm to 5 mm in length/diameter). Their ubiquitous presence and small sizes are concerning, since MP effects remain inadequately understood. Our objective was to document MP concentration in lake surface waters, and investigate how abiotic, biotic, and anthropogenic elements explain MP concentration variability among lakes. We sampled MPs in 132 Iowa lakes, collected throughout the water column using a Wisconsin net (63µm mesh size). A fully automated custom-built Bruker LUMOS-II Fourier-transform infrared (FTIR) spectro-microscope was employed to identify MPs. Average MP concentration across lakes was 5.2 particles/L, with dimensions averaging 139 µm in length and 77 µm in width. Predominant MP polymers collected were polyvinyl chloride (46% of all MPs), polyester (30%), and polyethylene (11%). Two variance partitioning analysis models were created to explore variability in MP concentration. The first classical model explained 7.5% of data variability based on: roads; developed medium, and high intensity land cover; sewage plants; and thermocline. The second model, based on Louvain Groups, explained 8.3% of data variability based on: lake area; maximum lake depth; zooplankton tow depth; Secchi depth; lake perimeter; lake shoreline development factor; evergreen forest cover; and thermocline. Roads and developed intensity cover were positively correlated with MP concentrations, alongside household visits standardized to the lake area. Maximum lake depth, zooplankton tow depth, Secchi depth and thermocline presence were negatively correlated with MP concentration. In nine instances, MP concentrations exceeded 50% of the modeled hazardous concentration affecting 5% of aquatic species.

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