Optimization of headspace experimental factors to determine chlorophenols in water by means of headspace solid-phase microextraction and gas chromatography coupled with mass spectrometry and parallel factor analysis

Abstract

In this work an analytical procedure based on headspace solid-phase microextraction and gas chromatography coupled with mass spectrometry (HS-SPME–GC/MS) is proposed to determine chlorophenols with prior derivatization step to improve analyte volatility and therefore the decision limit (CCα). After optimization, the analytical procedure was applied to analyze river water samples. The following analytes are studied: 2,4-dichlorophenol (2,4-DCP), 2,4,6-trichlorophenol (2,4,6-TrCP), 2,3,4,6-tetrachlorophenol (2,4,6-TeCP) and pentachlorophenol (PCP). A D-optimal design is used to study the parameters affecting the HS-SPME process and the derivatization step. Four experimental factors at two levels and one factor at three levels were considered: (i) equilibrium/extraction temperature, (ii) extraction time, (iii) sample volume, (iv) agitation time and (v) equilibrium time. In addition two interactions between four of them were considered. The D-optimal design enables the reduction of the number of experiments from 48 to 18 while maintaining enough precision in the estimation of the effects. As every analysis took 1h, the design is blocked in 2 days.The second-order property of the PARAFAC (parallel factor analysis) decomposition avoids the need of fitting a new calibration model each time that the experimental conditions change. In consequence, the standardized loadings in the sample mode estimated by a PARAFAC decomposition are the response used in the design because they are proportional to the amount of analyte extracted.It has been found that block effect is significant and that 60°C equilibrium temperature together with 25min extraction time are necessary to achieve the best extraction for the chlorophenols analyzed. The other factors and interactions were not significant. After that, a calibration based in a PARAFAC2 decomposition provided the following values of CCα: 120, 208, 86, 39ngL−1 for 2,4-DCP, 2,4,6-TrCP, 2,3,4,5-TeCP and PCP respectively for a probability of false positive set at 5%. Also, the accuracy (trueness and precision) of the procedure is assessed. Finally, river water samples have been analyzed with the proposed method showing the absence of the chlorophenols studied.