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Development of a Semi-quantitative Non-Targeted Analysis Workflow for Emerging PFAS (SETAC EU)
Citation:
Pu, S., J. McCord, AND J. Sobus. Development of a Semi-quantitative Non-Targeted Analysis Workflow for Emerging PFAS (SETAC EU). SETAC Europe 33rd Annual Meeting, NA, Dublin, IRELAND, April 30 - May 04, 2023.
Impact/Purpose:
An approach for deriving quantitative measurements from non-targeted analysis screens. Current approaches for NTA emphasis qualitative compound identification, but quantitative results are an important mechanism for connecting to risk assessment and other downstream applications for environmental measurements.
Description:
Emerging chemical contaminants present a challenge for traditional chemical quantification as they lack reference standards; this is particularly true for per- and polyfluoroalkyl substances (PFAS) which have a wide range of structural diversity but limited availability of standard reference compounds. In the absence of available standards to estimate chemical concentrations, surrogate calibration curves based on related chemicals can be used to obtain semi-quantitative concentration estimates for emerging compounds detected via non-targeted analysis (NTA). The uncertainty of the concentration estimates is influenced by error inherent to NTA workflows, the choice of the surrogate(s), and the mathematical model used to predict the concentration from the observed instrument values. Obtaining accurate and statistically bounded estimates of chemical concentration using NTA data is an important step for interpreting environmental measurements in a risk-based context. We compared the performance of different mathematical models using a semi-quantitative non-targeted analysis workflow to provide concentration estimates with confidence intervals. The models were assessed using a set of 16 PFAS compounds with matched reference standards. We additionally compared the estimation error and uncertainty when using data processed using targeted and non-targeted workflows. Estimation error and uncertainty were larger for non-targeted analysis data, but performance of a given model type was generally similar regardless of the data type. However, calibration curves created using one data type did not predict accurate concentrations for the other data type. Semi-quantitative concentration estimates were then obtained for a set of emerging compounds, using the PFAS reference standards to construct surrogate calibration curves for each compound. The estimation error and uncertainty were compared across surrogates to select the best surrogate(s) for each compound. The developed NTA workflow may be used to expand analysis of emerging compounds from relative concentrations to estimated concentrations that can contribute to provisional risk evaluation.
