Purpose: Instrumental capabilities and software tools of modern hybrid mass spectrometry (MS) instruments such as high-resolution mass spectrometry (HRMS), quadrupole time-of-flight (QTOF), and quadrupole linear ion trap (QLIT) were experimentally investigated for the study of emerging contaminants in Henares River water samples.

Methods: Automated screening and confirmatory capabilities of QTOF working in full-scan MS and tandem MS (MS/MS) were explored when dealing with real samples. Investigations on the effect of sensitivity and resolution power influence on mass accuracy were studied for the correct assignment of the amoxicillin transformation product 5(R) amoxicillin-diketopiperazine-2',5' as an example of a nontarget compound. On the other hand, a comparison of quantitative and qualitative strategies based on direct injection analysis and off-line solid-phase extraction sample treatment were assayed using two different QLIT instruments for a selected group of emerging contaminants when operating in selected reaction monitoring (SRM) and information-dependent acquisition (IDA) modes.

Results And Discussion: Software-aided screening usually needs a further confirmatory step. Resolving power and MS/MS feature of QTOF showed to confirm/reject most findings in river water, although sensitivity-related limitations are usually found. Superior sensitivity of modern QLIT-MS/MS offered the possibility of direct injection analysis for proper quantitative study of a variety of contaminants, while it simultaneously reduced the matrix effect and increased the reliability of the results. Confirmation of ethylamphetamine, which lacks on a second SRM transition, was accomplished by using the IDA feature.

Conclusion: Hybrid MS instruments equipped with high resolution and high sensitivity contributes to enlarge the scope of targeted analytes in river waters. However, in the tested instruments, there is a margin of improvement principally in required sensitivity and data treatment software tools devoted to reliable confirmation and improved automated data processing.

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Source
http://dx.doi.org/10.1007/s11356-011-0585-2DOI Listing

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