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Quantification Approaches in Non-Target LC/ESI/HRMS Analysis: An Interlaboratory Comparison.

Louise Malm1, Jaanus Liigand2, Reza Aalizadeh3,4

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|October 1, 2024
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This summary is machine-generated.

Nontargeted screening (NTS) using LC/ESI/HRMS for environmental contaminants is challenging due to variable ionization. The RandFor-IE approach demonstrated the best accuracy for quantification without authentic standards across multiple labs.

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Area of Science:

  • Environmental Chemistry
  • Analytical Chemistry
  • Mass Spectrometry

Background:

  • Nontargeted screening (NTS) with liquid chromatography electrospray ionization high-resolution mass spectrometry (LC/ESI/HRMS) is vital for identifying environmental contaminants.
  • Variable ionization efficiencies in LC/ESI/HRMS complicate accurate quantification without authentic standards.
  • Existing methods for standard-free quantification in NTS lack comprehensive evaluation across diverse datasets and instruments.

Purpose of the Study:

  • To evaluate the accuracy and performance variability of five quantification approaches for NTS without authentic standards.
  • To compare different quantification strategies including surrogate standards and predicted ionization efficiencies.
  • To assess the robustness of these approaches across multiple laboratories, instruments, and water matrices.

Main Methods:

  • An interlaboratory comparison involving 37 laboratories and 41 NTS methods was conducted.
  • Five quantification approaches were evaluated: three surrogate standard methods and two predicted ionization efficiency methods (RandFor-IE and MLR-IE).
  • Water samples (HPLC grade, tap, surface) were spiked with 45 compounds and analyzed alongside 41 calibrants.

Main Results:

  • The RandFor-IE approach exhibited the best performance, with a mean prediction error of 15×.
  • Over 83% of compounds were quantified within a 10× error margin using the RandFor-IE approach.
  • The performance of the RandFor-IE approach remained stable across different laboratories, instruments, and water matrix complexities.

Conclusions:

  • The RandFor-IE approach offers a robust and accurate method for quantifying environmental contaminants in NTS without the need for authentic standards.
  • This study provides a comprehensive comparison of quantification strategies, highlighting the strengths of predicted ionization efficiency methods.
  • The findings support the wider adoption of advanced quantification techniques in environmental monitoring using NTS.