Two Nontargeted Screening Approaches for Examination of Drinking Water Before and After Treatment

Significance of the Topic

High-resolution mass spectrometry-based nontargeted screening is essential for detecting trace-level organic contaminants in drinking water, ensuring treatment efficacy, and protecting public health. This approach enables comprehensive identification of known unknowns and emerging pollutants that may elude targeted analyses.

Objectives and Study Overview

• Deploy two complementary LC-MS workflows to analyze raw and treated water samples from drinking water treatment trains.
• Compare suspect screening and statistical-driven strategies for identifying suspect and unknown species.
• Assess changes in contaminant profiles before and after treatment processes.

Methodology and Instrumentation Used

Water samples from reservoirs, treatment influents, effluents, and advanced processes (microfiltration, reverse osmosis, advanced oxidation) were concentrated by solid phase extraction using Waters Oasis HLB cartridges. Reconstituted extracts were analyzed by an ExionLC AD system with a Phenomenex Kinetex C18 column under a 16-minute formic acid/methanol gradient. A SCIEX X500R QTOF mass spectrometer with ESI source acquired data in positive and negative modes combining SWATH® (data independent) and IDA (data dependent) acquisitions. High-resolution accurate mass and MS/MS spectra were processed using SCIEX OS Software for library searching and Formula Finder, while MarkerView Software supported PCA, t-tests, and feature selection.

Main Results and Discussion

Both workflows detected a variety of compounds including corrosion inhibitors, artificial sweeteners, pharmaceuticals, and herbicide transformation products. Suspect screening provided broad coverage but generated extensive feature lists, while the statistical workflow efficiently highlighted differentiating peaks between sample groups. Examples include tentative identification of N-HOEAmP-FPrSA in reverse osmosis backflush, 2-hydroxy-atrazine in raw reservoir water, and pharmaceutical compounds such as fexofenadine showing removal or transformation during treatment. Feature profiles clearly distinguished raw, treated, and advanced treated waters, demonstrating the power of combining HRAM data with multivariate analysis.

Benefits and Practical Applications

• Comprehensive detection of known and unknown water contaminants without predefined targets.
• Enhanced confidence in candidate identifications through HRAM and MS/MS library matching.
• Ability to monitor treatment efficacy and identify transformation products formed during water treatment.
• Prioritization of features using statistical tools reduces data complexity and focuses investigation on key differentiating compounds.

Future Trends and Possibilities

Advances in real-time data processing, machine learning for pattern recognition, expanded high-resolution spectral libraries, and integration of orthogonal separation techniques promise further improvements in nontargeted screening. Emerging applications include automated contaminant surveillance in distribution systems and predictive modeling of treatment performance.

Conclusion

Nontargeted screening combining SWATH® acquisition and statistical feature selection provides versatile workflows tailored to different analysis goals. Suspect screening offers broad initial coverage, while statistical preselection focuses on the most relevant sample differences. These complementary strategies enhance the detection and identification of trace organic contaminants in drinking water treatment studies.

Used Instrumentation

• ExionLC AD liquid chromatography system with Phenomenex Kinetex C18 column
• SCIEX X500R QTOF mass spectrometer with Turbo V source and ESI probe
• Waters Oasis HLB solid phase extraction cartridges
• SWATH® and IDA acquisition modes
• SCIEX OS Software and MarkerView Software for data processing and statistical analysis

References

1. Schymanski EL, Jeon J, Gulde R, Fenner K, Ru M, Singer HP, Hollender J. Identifying Small Molecules via High Resolution Mass Spectrometry: Communicating Confidence. Environ Sci Technol. 2014;48(4):2097–2098.
2. Schreiber A, Pace N. Identifying Unexpected Environmental Contaminants with High-Resolution, Accurate Mass LC–MS/MS. LCGC Chromatography Online. 2010.