Streamlining HRMS data interpretation for wastewater impact on water quality

Significance of the Topic

High-resolution mass spectrometry (HRMS) has become indispensable for detecting trace levels of emerging contaminants in surface waters. Pharmaceuticals, personal care products, pesticides and their metabolites frequently enter rivers via treated wastewater. Their complex mixtures and unknown degradation products pose challenges for environmental monitoring and risk assessment.

Objectives and Study Overview

This study aimed to develop a robust non-targeted workflow combining data-independent and data-dependent HRMS acquisition with statistical analysis to identify unknown contaminants along the Big Thompson River. Over a five-year period, 58 samples were collected at six locations ranging from pristine mountain streams to sites downstream of an urban wastewater treatment plant.

Methodology

The analytical protocol included:

• Collection of 1 L river water, spiking 125 mL aliquots with carbamazepine-d10 (80 ng/L) as internal standard
• Automated solid-phase extraction on Oasis HLB cartridges using a Gilson GX-271 ASPEC system
• Elution with methanol, nitrogen drying to 0.5 mL, and injection of 20 µL into LC/Q-TOF
• Reverse-phase chromatography coupled to positive-mode electrospray HRMS
• Data-independent All Ions MS/MS and iterative data-dependent MS/MS acquisition

Instrumentation Used

The workflow employed:

• Agilent 1290 Infinity II liquid chromatograph
• Agilent 6546 Q-TOF mass spectrometer
• Gilson GX-271 ASPEC automated SPE system

Main Results and Discussion

Data preprocessing with LOESS normalization enabled integration of multiple acquisition batches. Out of 6 745 extracted features, 6 036 were consistently observed in pooled quality controls. One-way ANOVA highlighted 1 705 statistically significant compounds (p≤0.05) relative to the upstream control. Filtering for ≥10-fold changes downstream yielded 275 features, of which 29 matched authentic standards of known pharmaceuticals, pesticides or metabolites. Eight additional compounds were putatively identified through spectral library matching, and roughly 20% of the remaining features had MS/MS spectra suggesting plausible structures pending further confirmation. An illustrative example was lidocaine, which appeared after the wastewater outfall and gradually decreased downstream.

Benefits and Practical Applications

This integrated HRMS approach offers:

• Rapid screening of thousands of unknowns in a single run
• Robust multi-batch comparison using LOESS normalization
• Increased confidence via combined All Ions and iterative MS/MS acquisition
• Targeted prioritization of contaminants based on statistical significance and fold change

Future Trends and Opportunities

Advances in spectral library curation, machine learning-driven feature annotation and real-time data processing will further enhance non-targeted workflows. Expanding databases of environmental transformation products and integrating ion mobility separation promise deeper insight into complex mixtures and faster identification of emerging threats.

Conclusion

The combination of complementary HRMS acquisition modes and a structured statistical pipeline enables effective discovery and identification of emerging contaminants in surface waters. This workflow supports environmental monitoring, regulatory compliance and risk assessment by focusing on compounds of highest concern.

Reference

• Thurman EM, Ferrer I, Pyke JS. Streamlining HRMS data interpretation for wastewater impact on water quality. ASMS 2023 Th090.