PCB Contamination in Laboratory Settings – UROP Spring Symposium 2022

PCB Contamination in Laboratory Settings

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Elizabeth White

Pronouns: she/her/hers

Research Mentor(s): Stuart Batterman
Co-Presenter:
Research Mentor School/College/Department: EHS / Public Health
Presentation Date: April 20
Presentation Type: Poster
Session: Session 3 – 1:40pm – 2:30 pm
Room: League Ballroom
Authors: Elizabeth White, Stuart Batterman
Presenter: 104

Abstract

Despite the vast research by Environmental Health Scientists on the presence of pesticides in human blood samples, few questions have been raised regarding the effectiveness and reliability of laboratory conditions. The integrity of blood analysis depends on the reliability of every step, from human conducted procedures to interpreting computational results and lab equipment. Employing Gas Chromatography Mass Spectroscopy instruction to document data, this study compares 20-30 data points of consistent evidence of PCB presence in human blood to another set of 20-30 data points of contaminated or inconsistent chemical data in an attempt to consider the possible sources of contamination or error. By conducting multiple trials with varying glassware and laboratory objects (such as removing caps and utilizing different material vials), the contamination was found to be present whenever the vial caps were used. Upon further examination, these vial caps were lined with teflon. While teflon is often convenient to use in laboratory settings due to its chemical compatibility, it is also known to absorb chemicals, like PCBs. A connection between these results and literature regarding the presence of PCBs and pesticides in other buildings suggests the saturated PCB results are from air contamination inside the building. The absorption of the teflon lined caps further complicated the role of teflon in the laboratory, contributing to literature investigating its safety and toxicity. Furthermore, these findings shed light on possible sources of contamination in laboratory settings and how that might affect data accuracy and negatively impact the conclusions then built off such data.

Presentation link

Engineering, Natural/Life Sciences

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