Extraction of selected pollutants in open tubular capillary columns

Direct determination of halogenated POPs in aqueous samples by in-tube SPME, focalization and GC-ECD analysis

A rapid analytical screening method allowing simultaneous analysis of few halogenated persistent organic pollutants (POPs) in water samples at ultra-trace levels was developed.

Enrichment of phenols from water with in-situ derivatization by in-tube solid phase microextraction–solvent desorption prior to off-line gas chromatographic determination with large-volume injection

Sorption of phenols from water into the stationary phase of open tubular columns (named in-tube solid phase microextraction) as an enrichment method for gas chromatographic (GC) analysis of aqueous samples was studied. The effect of operating conditions (stationary phase polarity, swelling of the stationary phase by solvents, number of sampling cycles, salting-out effect, sampling velocity, flow rate of desorption solvent) on the process efficiency was evaluated. Real water samples were also used in this study. Swelling of the stationary phase by organic solvent enables the volume of the stationary phase to be increased and its properties to be modified. The use of toluene or tetrachloromethane for the purpose results in high extraction efficiencies for most phenols. The results demonstrated a direct relationship between the extracted amount of phenols and its initial concentration in the sample. The limit of detection in off-line analyses applying large-volume injection was lower than 0.04 microg L(-1). These results of the use of in-tube solid phase microextraction with solvent desorption as a non-exhaustive (equilibrium sorptive) enrichment method show a great potential for on-line chromatographic analysis of micropollutants in real water samples.

Capillary microextraction for simultaneous analysis of multi-residual semivolatile organic compounds in water

Capillary microextractor (CME) in combination with a gas chromatograph-mass spectrometer (GC-MS) was employed for the determination of trace priority hazardous substances in water. Three groups of semivolatile organic compounds (SVOCs), i.e., chlorinated hydrocarbons, pesticides and polycyclic aromatic hydrocarbons (PAHs), were simultaneously determined. SVOCs were extracted from 7 mL of water samples on a 100 cm commercial gas chromatographic column (0.32 mm id x film thickness 0.25 microm, HP-5 capillary column) and eluted with only 3 microL of acetonitrile. The extractant was analyzed by GC-MS in the selected ion monitoring mode. The method showed good linearity over the concentration range 10 ng L(-1) to 3.0 mg L(-1) with correlation coefficients (r) greater than 0.99 and low limits of detection ranged from 10 ng L(-1) to 1.0 mg L(-1). High recovery (more than 80%) was obtained with relative standard deviation less than 10%. The method was successfully applied for trace level analyses of SVOCs in water samples.

Development of a Model to Predict Partition Coefficient of Organic Pollutants in Cloud Point Extraction Process

A quantitative structure property relationship (QSPR) study has been performed to establish a model to relate structural descriptors of 45 organic compounds to their partition coefficients in water-hexadecylpyridinium chloride (CPC) micelles at 298K using partial least squares (PLS). 510 of six different categories of structural descriptors were calculated by Dragon software. The descriptors with 0.9 mutually pair correlations and with less than 0.1 with dependent variables were excluded at the early stage of the preprocessing of the structural data matrix. The data set was randomly divided into two groups: training set (40 molecules) and test set (5 molecules). In the final model 50 of the most effective of the structural descriptors on the partition coefficient were remained to model building by PLS calibration method. The optimum number of latent variables 5, which spanned 80% of the original variations of data matrix, was selected using leave one out cross validation method. Prediction ability of the model was tested by prediction of the partition coefficients of five unknown compounds and the mean relative error of prediction was 3.6%. The outliers were treated using leverage and score plots of the first third principal components. The efficiency of the new model was compared with Abraham model and it was found that the proposed model has more prediction ability.

Determination of phenols in lake and ground water samples by stir bar sorptive extraction–thermal desorption–gas chromatography–mass spectrometry

A simple and inexpensive method for sorptive extraction of phenols from water samples is presented. A polydimethyl siloxane (PDMS) stir bar (Twister) is used as an extraction medium for derivatized phenols, which is thermally desorbed and analyzed by gas chromatography-mass spectrometry (GC-MS). Its performance was illustrated and evaluated for the enrichment of microg l(-1) to ng l(-1) of phenol and selected chlorophenols in water samples. The method showed good linearity, recoveries and blank levels, as well as advantages such as sensitivity, simplicity, low cost and high feasibility, being successfully applied for the analysis of phenolic compounds in natural water samples.