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Strategies for Assessing and Addressing Confounding

Strategies for Assessing and Addressing Confounding

Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...

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Updated: Sep 19, 2025

Vegetated Treatment Systems for Removing Contaminants Associated with Surface Water Toxicity in Agriculture and Urban Runoff

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Overcoming Matrix Effects in Non-Target Screening: A Novel Strategy for Urban Runoff Analysis.

Thomas Molnár Karlsson¹, Jan H Christensen¹

¹Analytical Chemistry Group, Department of Plant and Environmental Science Faculty of Science, University of Copenhagen, Thorvaldsensvej 40, 1871 Frederiksberg C, Denmark.

Analytical Chemistry

|June 17, 2025

Summary

This summary is machine-generated.

Matrix effects (MEs) in urban runoff analysis are a major challenge. A new Individual Sample-Matched Internal Standard (IS-MIS) strategy significantly improves data reliability for non-target screening (NTS).

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Area of Science:

Environmental Chemistry
Analytical Chemistry
Environmental Science

Background:

Matrix effects (MEs) compromise the reliability of target and non-target screening (NTS) in urban runoff analysis.
Sample heterogeneity in urban runoff makes pooled samples unsuitable for method development, validation, and ME corrections.

Purpose of the Study:

To investigate MEs in diverse urban runoff samples.
To develop and validate a novel ME correction strategy for urban runoff analysis.

Main Methods:

Analyzed 21 urban runoff samples with varying heterogeneity.
Investigated MEs across different relative enrichment factors (REFs).
Developed and applied an Individual Sample-Matched Internal Standard (IS-MIS) strategy.

Main Results:

Observed high variability in signal suppression (0-67% median at REF 50×).
"Dirty" runoff samples required enrichment below REF 50 to avoid >50% suppression.
IS-MIS strategy achieved <20% RSD for 80% of features, outperforming pooled sample methods (70% of features).

Conclusions:

The IS-MIS strategy significantly enhances accuracy and reliability in urban runoff monitoring.
Despite increased analysis time, IS-MIS is a cost-effective solution for large-scale NTS.
IS-MIS provides data for improved peak reliability assessment, aiding data preprocessing and method development.