Document Type



Doctor of Philosophy (PhD)



First Advisor's Name

Piero R. Gardinali

First Advisor's Committee Title

Committee chair

Second Advisor's Name

Jose Almirall

Second Advisor's Committee Title

committee member

Third Advisor's Name

Anthony DeCaprio

Third Advisor's Committee Title

committee member

Fourth Advisor's Name

John Landrum

Fourth Advisor's Committee Title

committee member

Fifth Advisor's Name

Berrin Tansel

Fifth Advisor's Committee Title

committee member


Mass Spectrometry, Drugs of Abuse, Transformation Products, Surface Water Characterization

Date of Defense



Development and application of target and non-target techniques for routine analysis, identification of transformation products, and characterization of unknown compounds in water matrices using liquid-chromatography high-resolution mass spectrometry (HRMS) were explored in this dissertation. A novel analytical method based on online-SPE-LC-HRMS was developed for the detection of 18 drugs of abuse (DOAs) in raw sewage water from a college campus. Results showed the presence of 14 DOAs for which amphetamine and 11-nor-9-carcoxy-THC (THC metabolite) were the most prevalent and had the highest potential consumption rates.

A second study dedicated to the identification of transformation products (TPs) generated from DOAs was conducted using a combination of HR-MS/MS and metabolic identification and structural elucidation software. Findings confirmed the presence of multiple phase I and II DOA TPs (n=35) in raw sewage influents. Concentrations of all TPs were estimated based on the parent DOAs response factors, and used to calculate the percent mole fraction contributions of each TP to the parent concentrations. High abundance and frequency (compared to the parent drug) was determined for 9 of the TPs coming from drugs like oxycodone, morphine, codeine, methadone, LSD, cocaine, and MDEA.

Non-target analysis using HRMS was explored as a tool to characterize, and compare a series of interconnected water matrices along a river system. Several thousands of formulae were generated using automated heuristic rules from the full-scan acquisition at 140,000 resolution. Samples were part of a trajectory covering upstream, effluent, effluent mixing zone, downstream, drinking water intake, and treated drinking water locations. Graphical representations of the data were used to evaluate commonalities among the system. Using this approach, a total of 64 recalcitrant components were identified throughout the samples downstream of the effluent release point. Using a combination of MS/MS and computer-aid software techniques 4 out of the 64 compounds were tentatively confirmed. In addition, comparison of drinking water intake and finalized treated drinking water sites showed the presence of 1,152 chemical entities that were common to both locations; and 1,857 that were unique to the treated drinking water. Therefore, this non-target technique could be used to identify the potential formation of treatment byproducts.





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