Elevated Concentrations of 4-Bromobiphenyl and 1,3,5-Tribromobenzene Found in Deep Water of Lake Geneva Based on GC×GC-ENCI-TOFMS and GC×GC-µECD.

We quantified the concentrations of two little-studied brominated pollutants, 1,3,5-tribromobenzene (TBB) and 4-bromobiphenyl (4BBP), in the deep water column and sediments of Lake Geneva. We found aqueous concentrations of 625 ± 68 pg L-1 for TBB and 668 ± 86 pg L-1 for 4BBP over a depth range of 70-191.5 m (near-bottom depth), based on duplicate measurements taken at five depths during three separate 1 month sampling periods at our sampling site near Vidy Bay. These levels of TBB and 4BBP were 1 or 2 orders of magnitude higher than the quantified aqueous concentrations of the components of the pentabrominated biphenyl ether technical mixture, which is a flame retardant product that had a high production volume in Europe before 2001. We observed statistically significant vertical concentration trends for both TBB and 2,2',4,4',6-pentabromobiphenyl ether in the deep water column, which indicates that transport and/or degradation processes affect these compounds. These measurements were enabled by application of a comprehensive two-dimensional gas chromatograph coupled to an electron capture negative chemical ionization time-of-flight mass spectrometer (GC×GC-ENCI-TOFMS) and to a micro-electron capture detector (GC×GC-µECD). GC×GC-ENCI-TOFMS and GC×GC-µECD were found to be >10× more sensitive toward brominated pollutants than conventional GC×GC-EI-TOFMS (with an electron impact (EI) ionization source), the latter of which had insufficient sensitivity to detect these emerging brominated pollutants in the analyzed samples. GC×GC also enabled the estimation of several environmentally relevant partitioning properties of TBB and 4BBP, further confirming previous evidence that these pollutants are bioaccumulative and have long-range transport potential.

GC×GC Quantification of Priority and Emerging Nonpolar Halogenated Micropollutants in All Types of Wastewater Matrices: Analysis Methodology, Chemical Occurrence, and Partitioning.

We report the development and validation of a method to detect and quantify diverse nonpolar halogenated micropollutants in wastewater treatment plant (WWTP) influent, effluent, primary sludge, and secondary sludge matrices (including both the liquid and particle phases) by comprehensive two-dimensional gas chromatography (GC×GC) coupled to micro- electron capture detector (µECD). The 59 target analytes included toxaphenes, polychlorinated naphthalenes, organochlorine pesticides, polychlorinated biphenyls, polybrominated diphenyl ethers, and emerging persistent and bioaccumulative chemicals. The method is robust for a wide range of nonpolar halogenated micropollutants in all matrices. For most analytes, recoveries fell between 70% and 130% in all matrix types. GC×GC-µECD detections of several target analytes were confirmed qualitatively by further analysis with GC×GC coupled to electron capture negative chemical ionization-time-of-flight mass spectrometry (ENCI-TOFMS). We then quantified the concentrations and apparent organic solid-water partition coefficients (Kp) of target micropollutants in samples from a municipal WWTP in Switzerland. Several analyzed pollutants exhibited a high frequency of occurrence in WWTP stream samples, including octachloronaphthalene, PCB-44, PCB-52, PCB-153, PCB-180, several organochlorine pesticides, PBDE-10, PBDE-28, PBDE-116, musk tibetene, and pentachloronitrobenzene. Our results suggest that sorption to dissolved organic carbon (DOC) can contribute substantially to the apparent solids-liquid distribution of hydrophobic micropollutants in WWTP streams.

Analyte quantification with comprehensive two-dimensional gas chromatography: assessment of methods for baseline correction, peak delineation, and matrix effect elimination for real samples.

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.

Mapping environmental partitioning properties of nonpolar complex mixtures by use of GC × GC.

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.

Robust algorithm for aligning two-dimensional chromatograms.

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.

Quantitative structure-activity relationships for kinetic parameters of polycyclic aromatic hydrocarbon biotransformation.

Quantitative structure-activity relationships (QSARs) were developed for three Monod-type parameters--qmax, Ks, and qmax/Ks--that express the kinetics of polycyclic aromatic hydrocarbon (PAH) biotransformation by Sphingomonas paucimobilis strain EPA505. The training sets contained high-quality experimental values of the kinetic parameters for 20 unsubstituted and methylated PAHs as well as values of 41 meaningful molecular descriptors. A genetic function approximation algorithm was used to develop the QSARs. Statistical evaluation of the developed QSARs showed that the relationships are statistically significant and satisfy the assumptions of linear-regression analysis. The Organization for Economic Co-operation and Development principles for (Q)SAR validation were followed to evaluate the developed QSARs, which showed that the QSARs are valid. The QSARs contain spatial, spatial and electronic, topological, and thermodynamic molecular descriptors. Whereas spatial descriptors were essential in explaining biotransformation kinetics, electronic descriptors were not. Mechanistic interpretation of the QSARs resulted in evidence that is consistent with the hypothesis of membrane transport as being the rate-limiting process in PAH biotransformation by strain EPA505. The present study demonstrates the value of QSAR not only as a predictive tool but also as a framework for understanding the mechanisms governing biodegradation at the molecular level.

Biodegradation kinetics of select polycyclic aromatic hydrocarbon (PAH) mixtures by Sphingomonas paucimobilis EPA505.

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.

Measurement of biodegradability parameters for single unsubstituted and methylated polycyclic aromatic hydrocarbons in liquid bacterial suspensions.

Substrate depletion experiments were conducted to characterize aerobic biodegradation of 20 single polycyclic aromatic hydrocarbons (PAHs) by induced Sphingomonas paucimobilis strain EPA505 in liquid suspensions. PAHs consisted of low molecular weight, unsubstituted, and methyl-substituted homologs. A material balance equation containing the Andrews kinetic model, an extension of the Monod model accounting for substrate inhibition, was numerically fitted to batch depletion data to estimate extant kinetic parameters including the maximal specific uptake rates, q(max), the affinity coefficients, K(S), and the substrate inhibition coefficients, K(I). Strain EPA505 degraded all PAHs tested. Applied kinetic models adequately simulated experimental data. A cell proliferation assay involving reduction of the tetrazolium dye WST-1 was used to evaluate the ability of strain EPA505 to utilize individual PAHs as sole energy and carbon sources. Of the 22 PAHs tested, 9 supported bacterial growth. Evaluation of the biokinetic data showed that q(max) correlated highly with transmembrane flux as theoretically estimated by a diffusion model, pointing to transmembrane transport as a potential rate-determining process. The biodegradability data generated in this study is essential for the development of quantitative structure-activity relationships (QSARs) for biodegradability and for modeling biodegradation of simple PAH mixtures.

Kinetics of biodegradation of binary and ternary mixtures of PAHs.

The kinetics of biodegradation of mixtures of polycyclic aromatic hydrocarbons (PAHs) by Sphingomonas paucimobilis strain EPA505 were investigated. The investigation focused on three- and four-ring PAHs, specifically 2-methylphenanthrene, fluoranthene, and pyrene. Uptake rates in aerobic batch suspended cultivations were measured for the individual PAHs and their binary and ternary mixtures. It was observed that kinetics were influenced by the mixture composition and the kinetic properties of the components. A material balance equation containing the Monod model was numerically fitted to uptake data to determine extant kinetic parameters for the individual PAHs. Similarly, equations containing kinetic interaction models derived from enzyme kinetics were fitted to the uptake data obtained from experiments with binary and ternary mixtures. The investigation considered the following interaction types: no-interaction (Monod), pure competitive interaction, noncompetitive or mixed-type interaction, uncompetitive inhibition, and nonspecific interaction based on pure competition (SKIP). Model fit was evaluated based on probabilistic and statistical criteria and inferences were reached about underlying interaction mechanisms based on model fit. Mixture kinetics were most adequately simulated by the pure competitive interaction model with mutual substrate exclusivity. This model is fully predictive, relying only on parameters determined in the sole-PAH experiments. It was shown that for low percent inhibition values and with limited data, pure competitive interaction kinetics may not be evident, resembling no-interaction kinetics. This study is a reasonable starting point for understanding and modeling biodegradation of complex PAH mixtures in engineered and natural systems.

The estimation of physicochemical properties of methyl and other alkyl naphthalenes.

The GLC and HPLC data of Autenrieth and co-workers (P. Dimitriou-Christidis, B. C. Harris, T. J. McDonald, E. Reese and R. L. Autenrieth, Chemosphere, 2003, 52, 869) has been used to obtain solvation descriptors for methyl naphthalenes for use in the Abraham solvation equations. These descriptors are then used to predict a large number of physicochemical properties, of environmental importance. These include solubility in water and the gas-water partition coefficient (equivalent to the Henry's Law constant for the water to gas partition). Predictions are in excellent agreement with those of Autenrieth and co-workers and with experimental observations, where available. Other important predictions are the gas-dry octanol and gas-wet octanol partition coefficients. Descriptors have also been obtained for the ethyl-, propyl- and butyl-naphthalenes which, again, can be used to predict numerous physicochemical properties.

Estimation of selected physicochemical properties for methylated naphthalene compounds.

Liquid aqueous solubility (S(w,L)), octanol/water partition coefficients (K(ow)), liquid vapor pressure (P(v,L)), and Henry's law constants (H(c)) were estimated for 20 methylated naphthalenes ranging from monomethyl to tetramethylnaphthalenes. Chromatographic methods were used for the estimation. Chromatographic retention measurements were conducted for 11 reference compounds and regressions were fit between the retention indices and the physicochemical properties. HPLC octadecylsilyl column with acetonitrile/water eluent was used for the estimation of S(w,L) and K(ow). Two GC columns, HP5-MS and a more hydrophobic HP-1, were tested for the estimation of P(v,L). Measured retention indices for the methylated naphthalenes were entered to the regression equations to calculate the physicochemical properties for these compounds. Literature values, where available, were used to validate the calculated values. The method accurately estimated the physicochemical properties. Estimated S(w,L) and P(v,L) decreased with the number of methyl groups. K(ow) increased with the number of methyl groups. There was no obvious relation between H(c) and the number of methyl groups. Log S(w,L) ranged from 0.885 for 1,2,5,6-tetramethylnaphthalene to 2.269 for 1-methylnaphthalene (mmol/m(3)). Log K(ow) varied from 3.89 for 1-methylnaphthalene to 4.95 for 1,2,5,6-tetramethylnaphthalene. Log P(v,L) ranged from -0.983 for 1,2,5,6-tetramethylnaphthalene to 0.789 for 2-methylnaphthalene (Pa). Log H(c) varied from 1.03 for 1,4,5-trimethylnaphthalene to 1.73 for 2,6-dimethylnaphthalene (Pa m(3)/mol). There were no apparent effects of GC column hydrophobicity on the accuracy of the results. Estimation of S(w,L) and K(ow) based on GC retention indices was not as accurate as with HPLC. Comparison of the estimated values with values predicted by EPIWIN indicated that EPIWIN is useful in giving order-of-magnitude prediction of physicochemical properties.