Fluorescence Spectroscopy as a Rapid, Cost-Effective Method to Monitor and Analyze Low Levels of Pharmaceuticals and Personal Care Products in Environmental Water Samples

Pharmaceutical and personal care product (PPCP) compounds are contaminants of emerging concern in U.S. water supplies. Although individual concentrations may be low, the number of PPCP compounds detected are large. The effects of chronic PPCP exposure on humans and ecosystems are poorly understood. There is a need for new analytical technologies that can detect PPCPs quickly at the low concentrations found to support exposure modeling and assessment. This study evaluates the use of two different fluorescent spectroscopy techniques to identify and model the behavior of mixtures of PPCPs in natural water samples. The first technique, synchronous fluorescence spectroscopy (SFS), involves scanning both the excitation and emission sides of the fluorometer simultaneously at an experimentally determined fixed wavelength difference. This technique has been used successfully to identify mixtures of petroleum hydrocarbons in soil and water samples. SFS can identify components of a mixture of 17α-ethynylestradiol, triclosan and caffeine in spiked natural water samples. In laboratory samples, these compounds, along with bisphenol A, have been identified as individual components of a mixture at 1 x 10^-11M concentrations. The second technique, excitation emission matrix (EEM) spectroscopy, collects a complete fluorescent profile of a sample along both emission and excitation wavelengths. The multi-dimensional spectra generated during EEM spectroscopy is a potential tool for rapid and inexpensive identification and quantification of PPCP contamination in water. Combining EEM spectra with parallel factor analysis (PARAFAC), a multi-way data analysis method, can model multiple complex EEM landscapes into chemically relevant spectral components. An added benefit of both techniques is that water samples need no preparation prior to analysis. Results from environmental samples collected from the Penobscot River (Maine) will be presented to demonstrate these techniques.