A fully automated and quantitative method for Metaldehyde in water using GC/QqQ

Significance of the topic

NDMA is a highly potent N-nitrosamine formed during chloramination of sewage and drinking waters. Classified as probably carcinogenic by IARC and EPA, it has very low guideline limits (WHO sets 100 ng/l, California 10 ng/l and Ontario 9 ng/l). Reliable detection at sub-ng/l levels is essential for regulatory compliance, public health and water treatment optimisation.

Objectives and study overview

This work presents a fully automated workflow for sample preparation and analysis of NDMA in potable and environmental waters using GC-QqQ. Key aims included:

• Developing an electron ionisation (EI) based method in contrast to common chemical ionisation approaches.
• Automating solid phase extraction (SPE) and large volume injection (LVI) to improve throughput and reproducibility.
• Achieving method detection limits (MDLs) and quantification down to 0.13–0.39 ng/l to meet Drinking Water Inspectorate requirements.

Instrumentation

The analytical platform comprised:

• Agilent 7890A GC coupled to 7000B Triple Quadrupole MS with extractor lens and EI source.
• GERSTEL MPS 2 XL-xt autosampler with 2.5 ml headspace syringe and 57 mm SPE needle.
• CIS 4 PTV inlet in solvent vent mode with Universal Peltier Cooling.
• ITSP Hardware kit and Coconut Charcoal SPE cartridges (25 mg).
• Agilent MassHunter and GERSTEL Maestro software for instrument control and data processing.

Methodology

Water samples (10 ml) were spiked with NDMA and isotopically labelled NDMA-d6, then processed via SPE on coconut charcoal cartridges using automated conditioning, equilibration, loading and elution (400 µl DCM eluent, 25 µl/s). A DB-WAX capillary column separated analytes with a temperature program from 35 °C to 240 °C (total 10.5 min). The MS operated in MRM mode monitoring two transitions per compound with 70 eV EI, optimized collision energies, 25 ms dwell times and wide resolution (1.2 amu). Seven-point calibrations were prepared in DCM and methanol, yielding linearity (r²=0.999) across 0.006–0.375 ng/ml (DCM) and 1.25–75 ng/l in aqueous matrices.

Main results and discussion

Method performance included:

• Instrument detection limit (IDL) of 0.25 pg on column (S/N>3).
• Method detection limits (MDLs) of 0.13 ng/l (ultrapure), 0.39 ng/l (tap) and 0.30 ng/l (river) employing EPA 1030C statistics (99% confidence).
• Absolute recoveries of NDMA ranged 63–84% across matrices; relative recoveries corrected by NDMA-d6 were 98–115%.
• Precision for 1 ng/l spikes: RSD 4.3% (ultrapure), 10.7% (tap), 7.2% (river).
• Calibration accuracies between 94.6–104% (DCM) and 95.5–103.3% (aqueous extracts).

The use of EI at varied source temperatures (150–350 °C) and ionisation energies (10–80 eV) showed no significant impact on fragmentation or sensitivity. Extensive blank controls and sunlight treatment removed NDMA background in LC-MS grade water.

Benefits and practical applications

This fully automated GC-QqQ method offers:

• High throughput and reduced operator variability through autosampler-driven SPE and LVI.
• Robust quantification at sub-ng/l levels fulfilling international regulatory limits.
• Enhanced specificity from tandem MS, minimizing interferences and lowering MDLs.
• Applicability to diverse water types without additional manual clean-up.

Future trends and application possibilities

Upcoming work includes interlaboratory comparisons with Anglian Water Services and expansion to a broader suite of nitrosamines. Integration with online SPE-LC-MS workflows or high-resolution MS could further improve sensitivity and selectivity. Adoption of similar fully automated platforms may accelerate routine monitoring of other trace disinfection by-products and emerging contaminants.

Conclusion

The developed automated GC-EI-QqQ method achieves sensitive, accurate and reproducible determination of NDMA in drinking and environmental waters. Incorporation of SPE, isotopic internal standardisation and MRM detection ensures compliance with stringent regulatory requirements. This approach demonstrates a scalable solution for routine water quality monitoring and supports ongoing efforts to safeguard public health.

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