Fast HPLC-DAD quantification procedure for selected sulfonamids, metronidazole and chloramphenicol in wastewaters using second-order calibration based on MCR-ALS

The present work focuses on the application of multivariate curve resolution-alternating least squares (MCR-ALS) for analysis of five important antibiotics (sulfamethoxazole, metronidazole, chloramphenicol, sulfadizine and sulfamerazine) in highly complex wastewater samples, using solid phase extraction (SPE)-high performance liquid chromatography with diode-array detection (HPLC-DAD) on a short column, regarding the fast elution methodology. The samples were pre-concentrated on Bond Elut-ENV cartridges and separated on an ODS column (7 cm) in less than 4 min using an isocratic mode of elution with methanol-water (55:45, v/v) at pH=3.2. Due to the matrix interferences and the resulting sensitivity changes, a strategy implementing standard addition calibration in combination with MCR/ALS algorithm was applied. In this paper, the signal corresponding to background contribution was considered as a systematic part of the model during MCR/ALS data processing, so the background correction step was not necessary. The qualitative and quantitative results showed that the application of MCR/ALS algorithm in the traditional chromatographic method was appropriately able to resolve highly drifted background constituents as well as heavily overlapped peaks among the analytes and also between the analytes and the matrix interferences. Recoveries were ranged from 69.6% to 120.3% with relative standard deviations of less than or equal to 11.0% and showed the acceptable performance of the method. Additionally, statistical t-test as well as computed elliptical joint confidence region (EJCR) confirmed the accuracy of the proposed method and indicated the absence of both constant and proportional errors in the predicted concentrations. The results well explained that the second-order advantage for analytes was achieved in samples containing one or more uncalibrated components, which strongly related to wastewater samples. (C) 2013 Elsevier B.V. All rights reserved.