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A modeling approach to compare ΣPCB concentrations between congener-specific analyses.

Polly P Gibson1, Marc A Mills2, Johanna M Kraus3

  • 1Contractor, US Geological Survey, Fort Collins Science Center, Fort Collins, Colorado.

Integrated Environmental Assessment and Management
|July 19, 2016
PubMed
Summary

A new modeling approach allows for the comparison of polychlorinated biphenyl (PCB) concentrations across studies using different analytical methods. This method ensures consistent long-term environmental contamination trend assessment.

Keywords:
Congener-based analysisGreat Lakes Areas of ConcernManistique River and HarborPCBsRemedy effectiveness monitoring

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Area of Science:

  • Environmental Chemistry
  • Analytical Chemistry
  • Environmental Science

Background:

  • Assessing long-term environmental contamination trends by polychlorinated biphenyls (PCBs) is challenging due to evolving analytical methods.
  • Variations in congener-specific analyses, quantifying different subsets of the 209 PCB congeners, lead to inconsistent summed PCB (ΣPCB) concentrations across studies.

Purpose of the Study:

  • To develop and demonstrate a modeling approach using linear regression to compare ΣPCB concentrations derived from different congener-specific analytical methods.
  • To create a conversion model for comparing ΣPCB data from dissimilar congener sets within similar sample matrices and geographic origins.

Main Methods:

  • A linear regression modeling approach was employed to compare ΣPCB concentrations.
  • A conversion model was developed using example data from a low-resolution (119 congeners) and a high-resolution (209 congeners) analytical method.
  • The model was validated by comparing estimated and measured ΣPCB concentrations in sediment and biological samples.

Main Results:

  • The developed model successfully created a conversion between low-resolution and high-resolution PCB analytical data.
  • The 119-congener set was found to capture approximately 93% of the total Σ209 PCB concentration in environmental samples.
  • Estimated ΣPCB concentrations using the model showed close agreement with measured values, with a mean relative percent difference of 9.6%.

Conclusions:

  • The proposed modeling approach provides a reliable method for generating comparable ΣPCB concentrations across studies using different analytical techniques.
  • This approach is valuable for estimating the contribution of various congener sets to total PCB burden and for comparing long-term monitoring data.
  • The method facilitates consistent assessment of environmental contamination trends despite changes in analytical methodologies over time.