Screening for Water Pollutants With the Agilent SureTarget GC/MSD Water Pollutants Screener, SureTarget Workflow, and Customized Reporting

Importance of the Topic

Effective monitoring of trace organic pollutants in water is critical for environmental protection, public health, and regulatory compliance. Qualitative pre-screening helps laboratories prioritize samples for detailed quantitation, reduce manual review time, and ensure no contaminants are overlooked in complex matrices.

Objectives and Overview of the Study

This study evaluated the Agilent SureTarget GC/MSD Water Pollutants Screener workflow to automate qualitative screening of water samples. It aimed to compare its performance against manual deconvolution using AMDIS, assess identification rates across standard mixtures and real-world samples, and demonstrate reporting capabilities for rapid implementation in environmental labs.

Methodology

Liquid–liquid extraction (LLE) was applied to tap water and wastewater effluent samples using dichloromethane. Agilent 7890B GC coupled to a 5977B MSD with CO₂-cooled multimode inlet and HP-5MS UI column enabled separation. Reference mixtures of 86 semi-volatile compounds (Method 8270) spiked with reference gas oil matrix were analyzed at 1 ppm, 200 ppb, and 100 ppb. Deconvolution and library matching were performed in MassHunter Quantitative Analysis (SureTarget) and compared to ChemStation/AMDIS results.

Used Instrumentation

• Agilent 7890B Gas Chromatograph
• Agilent 5977B InertPlus Mass Selective Detector
• CO₂-cooled multimode inlet (MMI)
• Agilent HP-5MS UI column (30 m × 0.25 mm, 0.25 µm)
• MassHunter Quantitative Analysis software (Version B.08.00) with SureTarget feature
• AMDIS deconvolution via ChemStation Data Analysis

Main Results and Discussion

• SureTarget and AMDIS identified comparable numbers of compounds (within 2–4 compounds) and produced similar library match scores across standard concentrations.
• In tap water, both workflows detected trihalomethanes, volatile chlorinated solvents, and bisphenol A with high confidence (LMS > 80).
• Wastewater effluents revealed the fate of various pollutants: some compounds (DEET, caffeine) were removed during treatment, while others (1,4-dioxane, codeine, phentermine) persisted.
• SureTarget’s automated deconvolution reduced manual review time significantly and allowed screening of over 1,000 possible compounds per sample.

Benefits and Practical Applications

• Streamlined qualitative screening accelerates time-to-result and minimizes analyst bias.
• Preconfigured methods enable rapid adoption in environmental and QA/QC laboratories.
• Automated alternative peak detection and NIST search improve reliability in complex matrices.
• Customizable PDF reports facilitate data review and regulatory communication.

Future Trends and Potential Applications

• Expansion of compound libraries to include emerging contaminants (e.g., PFAS, pharmaceuticals).
• Integration with high-resolution mass spectrometry and advanced chemometric algorithms.
• Real-time monitoring applications using inline sampling and automated workflows.
• Machine learning approaches for improved deconvolution and anomaly detection.

Conclusion

The Agilent SureTarget GC/MSD Water Pollutants Screener provides a robust, unbiased, and efficient workflow for qualitative screening of water samples. It matches or surpasses traditional AMDIS workflows in performance while enabling rapid reporting and high-throughput screening, making it an impactful solution for modern environmental analysis.