Environmental Profiling of River Water Using Q-TOF LC/MS and Mass Profiler Software

Significance of the Topic

Environmental contamination by emerging pollutants such as pharmaceuticals, pesticides and industrial chemicals poses a growing threat to water quality and ecosystem health. Conventional targeted mass spectrometric methods reliably quantify known compounds but fail to detect unexpected substances. Untargeted profiling using high-resolution LC/MS combined with statistical software addresses this gap, enabling comprehensive screening of complex environmental matrices.

Objectives and Study Overview

The primary goal of this study was to develop an untargeted workflow for profiling river water upstream and downstream of a wastewater treatment plant. Specific objectives included:

• Detect and compare chemical features in river water before and after treatment plant discharge.
• Extract and identify compounds unique to the downstream sample.
• Validate identifications using accurate mass databases, spectral libraries and in silico tools.

Methodology

Water samples were collected from two points along the Ammer River (Germany), upstream and downstream of a municipal treatment facility. Samples were enriched by solid phase extraction (SPE) using hydrophilic–lipophilic balanced (HLB) and ENV+ sorbents at a 500× concentration factor. Separation was achieved on an Agilent 1260 Infinity HPLC with a Polar-RP column (150×3 mm, 4 µm) and a gradient of water and methanol (both with 0.1% formic acid).

Instrumentation

Key instrumentation included:

• Agilent 6550 iFunnel Q-TOF LC/MS system in extended dynamic range mode
• Agilent MassHunter Qualitative Analysis software with Molecular Feature Extractor (MFE)
• Agilent MassProfiler statistical software for data alignment and comparison
• Agilent MassHunter Molecular Structure Correlator for in silico fragmentation

Results and Discussion

Data processing identified 1,564 molecular features in the downstream samples, of which 1,043 were unique compared to upstream water. Accurate mass matching assigned 894 molecular formulas within 5 ppm using C, H, N, O, S, P and Cl. Database searches yielded:

• 18 hits from an in-house aquatic contaminants library
• 144 hits from a forensic toxicology database
• 26 hits from a pesticide database

MS/MS library matching confirmed 21 compounds, including carbamazepine, and authentic standards validated 32 additional substances. For unknown formulas, in silico fragmentation via MSC and ChemSpider searches narrowed candidate structures, exemplified by the identification workflow for iopamidol.

Benefits and Practical Applications

This untargeted approach provides a powerful tool for environmental monitoring, offering:

• Broad-spectrum detection of known and unknown contaminants
• High confidence identifications through accurate mass and MS/MS matching
• Scalable workflows for routine water quality assessment and regulatory compliance

Future Trends and Applications

Emerging directions include expanding accurate mass databases with new environmental chemicals, integrating machine learning for feature annotation, and coupling suspect screening with effect-based assays to link chemical presence with biological activity. Advancements in data processing speed and spectral library coverage will further enhance untargeted environmental profiling.

Conclusion

The combination of high-resolution Q-TOF LC/MS and advanced chemometric software enables comprehensive environmental screening of river water. The workflow successfully differentiated upstream and downstream contamination profiles, identified dozens of known pollutants, and proposed structures for unknowns. This methodology supports more informed risk assessment and water management strategies.

References

1. Gust M, et al. Effects of short-term exposure to environmentally relevant concentrations of different pharmaceutical mixtures on the immune response of the pond snail Lymnaea stagnalis. Sci Total Environ. 2013;445–446:210-218.
2. Triebskorn RH, et al. Ultrastructural effects of pharmaceuticals (carbamazepine, clofibric acid, metoprolol, diclofenac) in rainbow trout (Oncorhynchus mykiss) and common carp (Cyprinus carpio). Anal Bioanal Chem. 2007;387(4):1405-1416.
3. Escher BI, et al. Most oxidative stress response in water samples comes from unknown chemicals: the need for effect-based water quality trigger values. Environ Sci Technol. 2013.
4. Zedda M, Zwiener C. Is nontarget screening of emerging contaminants by LC-HRMS successful? A plea for compound libraries and computer tools. Anal Bioanal Chem. 2012;403(9):2493-2502.