Determination of organic contaminants in aqueous samples by near-infrared spectroscopy

The feasibility of determining low levels of organic solvents in water by n ear-infrared (near-IR) spectroscopy is investigated. Mixture samples of tri butyl phosphate (TBP) and methyl iso-butyl ketone (MIBK) are determined in aqueous solutions over the concentration range of 1-160 ppm. Through the us e of C-H combination bands in the region of 5000-4000 cm(-1), sufficient se lectivity is obtained to determine each compound in the presence of the oth er. Separate multivariate calibration models are computed for each compound by use of a combination of bandpass Fourier digital filtering and partial least-squares (PLS) regression with both analysis of absorbance and single- beam spectra. A genetic algorithm is used to implement a joint optimization of the parameters governing the filtering and PLS calculations. Through th e use of this procedure, a calibration model based on absorbance spectra is computed for MIBK with a standard error of prediction (SEP) of 3.82 ppm ov er the 1-160 ppm range. This five-term model utilizes the spectral range of 4495-4335 cm(-1). A similar nine-term model based on absorbance spectra is computed for TBP over the 4620-4320 cm(-1) range. For the range of 1-100 p pm, an SEP of 4.84 ppm is achieved. The results obtained from the analysis of single-beam spectra are comparable with those obtained in the analysis o f absorbance data. Calibration models computed with samples prepared in nat ural water are also found to have a similar level of performance. These res ults establish the feasibility of using near-IR spectroscopy to screen wate r samples for solvent contamination.