A Strategy for an Unknown Screening Approach on Environmental Samples Using HRAM Mass Spectrometry

Significance of the Topic

Environmental monitoring of emerging contaminants requires both targeted quantification and non-targeted screening to detect known and unknown pollutants in water. High-resolution accurate-mass (HRAM) mass spectrometry combined with integrated software automation enhances sensitivity, selectivity, and throughput for environmental analyses.

Objectives and Study Overview

This study aimed to develop and demonstrate an automated workflow for unknown screening of environmental water samples using HRAM mass spectrometry and a unified software platform. Surface water, tap water, and analysis standards were processed to evaluate simultaneous targeted and non-targeted detection in a single run.

Methodology and Used Instrumentation

• Sample Preparation: Direct injection of 1 mL surface water samples, tap water reference, and neat standard without additional cleanup.
• Liquid Chromatography: Thermo Scientific EQuan online SPE system with 12 µm Hypersil GOLD preconcentration column and 3 µm Accucore RP-MS C18 analytical column. A 6.7 min solvent gradient yielded a 15 min total cycle time.
• Mass Spectrometry: Thermo Scientific Exactive Plus Orbitrap operated in full scan/all-ion fragmentation (AIF) mode. Resolution 70 000 FWHM at m/z 200 for full scans, 35 000 for AIF scans, mass range m/z 103–900.
• Software Workflow: Automated data processing using Thermo Scientific TraceFinder 3.1 and SIEVE 2.1 for target, suspect, and unknown screening, including data transfer and integrated reporting.

Main Results and Discussion

• Suspect Screening: A database of ~1 000 compounds and a spectral library of ~4 000 HRAM MS2 spectra enabled confirmation via retention time, isotope pattern, and MS2 matching. Several contaminants were identified, but database coverage remained limited.
• Unknown Screening: Initial detection of ~5 000 components in SIEVE. Filtering against tap-water background reduced the list to ~1 829 features; principal component analysis differentiated sample clusters. Further refinement for significant changes yielded ~1 671 features.
• Compound Identification: ChemSpider search returned 1 529 tentative identifications. The results were reimported into TraceFinder for unified confirmation and reporting.
• Resolution Impact: High resolving power allowed clear separation of analyte signals from matrix interferences. Examples include resolution of loxoprofen isotopes and propiconazole confirmation via accurate mass, retention time, and isotopic pattern.

Benefits and Practical Applications

• A single fully automated workflow supports targeted quantification and non-targeted discovery in environmental samples.
• High-resolution data ensures confident identification of low-abundance contaminants in complex matrices.
• Integrated software reduces manual data handling, enabling higher throughput and streamlined archiving.

Future Trends and Applications

• Expansion of spectral libraries and databases for broader suspect screening coverage.
• Integration of machine learning for pattern recognition and unknown compound annotation.
• Real-time and on-site environmental monitoring using portable HRAM mass spectrometers.
• Regulatory adoption of non-targeted workflows for comprehensive water quality assessments.

Conclusion

The study demonstrates that HRAM Orbitrap mass spectrometry combined with a unified software platform enables seamless targeted, suspect, and unknown screening of environmental water samples. High mass resolution and automated data processing enhance selectivity, reliability, and throughput in contaminant analysis.

References

No external literature references were provided in the source document.