Identifying Disinfection Byproducts in Treated Water

Importance of the Topic

Swimming pools and hot tubs require disinfection to protect users, but disinfectants react with organic matter and swimmer-derived chemicals to form potentially harmful byproducts. Comprehensive chemical characterization of these disinfection byproducts (DBPs) is critical for health risk assessment and water treatment optimization.

Objectives and Study Overview

This study aimed to identify both “known unknowns” and “unknown unknowns” in pool and hot tub water using high-resolution time-of-flight GC–MS and advanced data processing workflows:

• Known unknowns: Detected via library searches of high-resolution deconvoluted spectra.
• Unknown unknowns: Tentatively identified through complementary electron ionization (EI) and chemical ionization (CI) accurate mass data for elemental composition and structure elucidation.

Methodology and Instrumentation

Samples (10 L each) were extracted on Amberlite XAD resins, concentrated to 1 mL, and acids derivatized with diazomethane. Data acquisition and processing leveraged LECO’s Pegasus GC-HRT coupled with ChromaTOF-HRT software, featuring Automated Peak Finding, High Resolution Deconvolution (HRD), library searches, mass defect plots with a Cl–H reference, and isotope-pattern filtering to target halogenated species.

Instrumentation Used

• Gas Chromatograph: Agilent 7890 with 7693 autosampler and MMI injector
• Column: Rxi-5MS, 30 m × 0.25 mm i.d., 0.25 µm film
• Temperature Program: 35 °C (4 min) to 280 °C at 9 °C/min (20 min)
• Mass Spectrometer: LECO Pegasus GC-HRT (25,000 FWHM HR; 50,000 FWHM UHR)
• Ion Sources: EI and CI (5% NH₃ in CH₄ at 1 mL/min)
• Mass Range: EI 33–650 m/z; CI 60–650 m/z; Acquisition Rate: 5 spectra/s

Results and Discussion

• HRD separated coeluting background ions, yielding clean spectra for confident identification of compounds such as dibromo-pyridinamine derivatives.
• Library matches accounted for less than 5% of peaks, underscoring the prevalence of unknown DBPs.
• CI data provided strong ammonium adduct signals, facilitating accurate molecular formula assignments and structure proposals.
• Mass defect plots and halogen isotope filters efficiently isolated halogenated DBPs for targeted post-analysis.

Benefits and Practical Applications

The workflow enhances non-target screening in complex water matrices, supporting risk management and regulatory compliance by uncovering a broader range of DBPs. Automated software tools accelerate processing and reduce manual interpretation time.

Future Trends and Potential Applications

• Combining orthogonal ionization techniques with machine learning will further expand unknown contaminant coverage.
• Enhanced spectral databases and in silico fragmentation tools will improve structure elucidation confidence.
• Application of these methods to other environmental and industrial matrices can drive comprehensive contaminant discovery.

Conclusion

The integration of high-resolution GC–TOF-MS with HRD, mass defect filtering, and complementary EI/CI workflows enables the identification of both known and novel DBPs in recreational waters, offering a robust platform for non-target analysis of complex samples.