0
Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 2 ? Original research — experimental, observational, or case-control study. Direct primary evidence. Marine & Wildlife Sign in to save

Pyr-GC/MS analysis of microplastics extracted from the stomach content of benthivore fish from the Texas Gulf Coast

Marine Pollution Bulletin 2018 99 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count.
Colleen A. Peters, Erik M. Hendrickson, Elizabeth C. Minor, K. M. Schreiner, J. Halbur, Susan Power Bratton

Summary

Researchers applied pyrolysis-GC/MS to identify polymer types in microplastics extracted from the stomachs of benthivore fish from the Texas Gulf Coast, demonstrating the method's applicability for polymer characterization in biological samples where traditional spectroscopic methods face matrix interferences.

Body Systems
Study Type Environmental

Fish ingestion of microplastic has been widely documented throughout freshwater, marine, and estuarine species. While numerous studies have quantified and characterized microplastic particles, analytical methods for polymer identification are limited. This study investigated the applicability of pyr-GC/MS for polymer identification of microplastics extracted from the stomach content of marine fish from the Texas Gulf Coast. A total of 43 microplastic particles were analyzed, inclusive of 30 fibers, 3 fragments, and 10 spheres. Polyvinyl chloride (PVC) and polyethylene terephthalate (PET) were the most commonly identified polymers (44.1%), followed by nylon (9.3%), silicone (2.3%), and epoxy resin (2.3%). Approximately 42% of samples could not be classified into a specific polymer class, due to a limited formation of pyrolytic products, low product abundance, or a lack of comparative standards. Diethyl phthalate, a known plasticizer, was found in 16.3% of the total sample, including PVC (14.3%), silicone (14.3%), nylon (14.3%), and sample unknowns (57.2%).

Share this paper