Simultaneous spectrophotometric quantification of dinitrobenzene isomers in water samples using multivariate calibration methods

Abstract A facile yet efficient strategy was proposed by means of a combination of ultraviolet (UV) spectrophotometry with multivariate calibration methods, through which 1,2-dinitrobenzene, 1,3-dinitrobenzene and 1,4-dinitrobenzene in water samples could be simultaneously determined without any pre-separation process. The competitive adaptive reweighted sampling combined with successive projections algorithm (CARS–SPA) approach was used to diminish uninformative variables and select the important ones from spectral data measured. The multivariate calibration models were constructed by partial least squares (PLS-1) regression with high accuracy, in which the coefficients of determination of prediction ( R pred 2 ) were 0.9935, 0.9969, and 0.9971 and the root mean square error of prediction (RMSEP) were 0.7850, 0.5411 and 0.5414 for 1,2-dinitrobenzene, 1,3-dinitrobenzene and 1,4-dinitrobenzene, respectively. The optimized model was successfully applied to simultaneously determine the content of the three studied analytes in several real water samples with good recovery close to 100%. Finally, the elliptical joint confidence region (EJCR) tests further confirm that the proposed method has no proportional and constant error in the predicted concentrations, providing a statistic support for the accuracy of the model. These results indicate that it is promise for UV spectroscopy coupled to the multivariate calibration technique to establish a simple, quick, accurate and reliable analysis method for simultaneous determination of some nitroaromatic compounds in real environments. Also, the strategy proposed by the work will advance the analytical methods used in the other complicated sample systems.