Comprehensive two-dimensional gas chromatography (GC × GC) is effective for separating and quantifying nonpolar organic chemicals in complex mixtures. Here we present a model to estimate 11 environmental partitioning properties for nonpolar analytes based on GC × GC chromatogram retention time information. The considered partitioning properties span several phases including pure liquid, air, water, octanol, hexadecane, particle natural organic matter, dissolved organic matter, and organism lipids. The model training set and test sets are based on a literature compilation of 648 individual experimental partitioning property data. For a test set of 50 nonpolar environmental contaminants, predicted partition coefficients exhibit root-mean-squared errors ranging from 0.19 to 0.48 log unit, outperforming Abraham-type solvation models for the same chemical set. The approach is applicable to nonpolar organic chemicals containing C, H, F, Cl, Br, and I, having boiling points ≤402 °C. The presented model is calibrated, easy to apply, and requires the user only to identify a small set of known analytes that adapt the model to the GC × GC instrument program. The analyst can thus map partitioning property estimates onto GC × GC chromatograms of complex mixtures. For example, analyzed nonpolar chemicals can be screened for long-range transport potential, aquatic bioaccumulation potential, arctic contamination potential, and other characteristic partitioning behaviors.

Comprehensive two-dimensional gas chromatography (GC×GC) is used widely to separate and measure organic chemicals in complex mixtures. However, approaches to quantify analytes in real, complex samples have not been critically assessed. We quantified 7 PAHs in a certified diesel fuel using GC×GC coupled to flame ionization detector (FID), and we quantified 11 target chlorinated hydrocarbons in a lake water extract using GC×GC with electron capture detector (μECD), further confirmed qualitatively by GC×GC with electron capture negative chemical ionization time-of-flight mass spectrometer (ENCI-TOFMS). Target analyte peak volumes were determined using several existing baseline correction algorithms and peak delineation algorithms. Analyte quantifications were conducted using external standards and also using standard additions, enabling us to diagnose matrix effects. We then applied several chemometric tests to these data. We find that the choice of baseline correction algorithm and peak delineation algorithm strongly influence the reproducibility of analyte signal, error of the calibration offset, proportionality of integrated signal response, and accuracy of quantifications. Additionally, the choice of baseline correction and the peak delineation algorithm are essential for correctly discriminating analyte signal from unresolved complex mixture signal, and this is the chief consideration for controlling matrix effects during quantification. The diagnostic approaches presented here provide guidance for analyte quantification using GC×GC.

Many contaminated sites commonly have complex mixtures of polycyclic aromatic hydrocarbons (PAHs) whose individual microbial biodegradation may be altered in mixtures. Biodegradation kinetics for fluorene, naphthalene, 1,5-dimethylnaphthalene and 1-methylfluorene were evaluated in sole substrate, binary and ternary systems using Sphingomonas paucimobilis EPA505. The first order rate constants for fluorene, naphthalene, 1,5-dimethylnaphthalene, and 1-methylfluorene were comparable; yet Monod parameters were significantly different for the tested PAHs. S. paucimobilis completely degraded all the components in binary and ternary mixtures; however, the initial degradation rates of individual components decreased in the presence of competitive PAHs. Results from the mixture experiments indicate competitive interactions, demonstrated mathematically. The generated model appropriately predicted the biodegradation kinetics in mixtures using parameter estimates from the sole substrate experiments, validating the hypothesis of a common rate-determining step. Biodegradation kinetics in mixtures were affected by the affinity coefficients of the co-occurring PAHs and mixture composition. Experiments with equal concentrations of substrates demonstrated the effect of concentration on competitive inhibition. Ternary experiments with naphthalene, 1,5-dimethylnaphthalene and 1-methylfluorene revealed delayed degradation, where depletion of naphthalene and 1,5-dimethylnapthalene occurred rapidly only after the complete removal of 1-methylfluorene. The substrate interactions observed in mixtures require a multisubstrate model to account for simultaneous degradation of substrates. PAH contaminated sites are far more complex than even ternary mixtures; however these studies clearly demonstrate the effect that interactions can have on individual chemical kinetics. Consequently, predicting natural or enhanced degradation of PAHs cannot be based on single compound kinetics as this assumption would likely overestimate the rate of disappearance.

Comprehensive two-dimensional gas chromatography (GC × GC) chromatograms typically exhibit run-to-run retention time variability. Chromatogram alignment is often a desirable step prior to further analysis of the data, for example, in studies of environmental forensics or weathering of complex mixtures. We present a new algorithm for aligning whole GC × GC chromatograms. This technique is based on alignment points that have locations indicated by the user both in a target chromatogram and in a reference chromatogram. We applied the algorithm to two sets of samples. First, we aligned the chromatograms of twelve compositionally distinct oil spill samples, all analyzed using the same instrument parameters. Second, we applied the algorithm to two compositionally distinct wastewater extracts analyzed using two different instrument temperature programs, thus involving larger retention time shifts than the first sample set. For both sample sets, the new algorithm performed favorably compared to two other available alignment algorithms: that of Pierce, K. M.; Wood, Lianna F.; Wright, B. W.; Synovec, R. E. Anal. Chem.2005, 77, 7735-7743 and 2-D COW from Zhang, D.; Huang, X.; Regnier, F. E.; Zhang, M. Anal. Chem.2008, 80, 2664-2671. The new algorithm achieves the best matches of retention times for test analytes, avoids some artifacts which result from the other alignment algorithms, and incurs the least modification of quantitative signal information.