Screening Disinfection Byproducts in Arid-Coastal Wastewater: A Workflow Using GC×GC-TOFMS, Passive Sampling, and NMF Deconvolution Algorithm.

Disinfection during tertiary municipal wastewater treatment is a necessary step to control the spread of pathogens; unfortunately, it also gives rise to numerous disinfection byproducts (DBPs), only a few of which are regulated because of the analytical challenges associated with the vast number of potential DBPs. This study utilized polydimethylsiloxane (PDMS) passive samplers, comprehensive two-dimensional gas chromatography (GC×GC) coupled with time-of-flight mass spectrometry (TOFMS), and non-negative matrix factorization (NMF) spectral deconvolution for suspect screening of DBPs in treated wastewater. PDMS samplers were deployed upstream and downstream of the chlorination unit in a municipal wastewater treatment plant located in Abu Dhabi, and their extracts were analyzed using GC×GC-TOFMS. A workflow incorporating a multi-tiered, eight-filter screening process was developed, which successfully enabled the reliable isolation of 22 candidate DBPs from thousands of peaks. The NMF spectral deconvolution improved the match factor score of unknown mass spectra to the reference mass spectra available in the NIST library by 17% and facilitated the identification of seven additional DBPs. The close match of the first-dimension retention index data and the GC×GC elution patterns of DBPs, both predicted using the Abraham solvation model, with their respective experimental counterparts-with the measured data available in the NIST WebBook and the GC×GC elution patterns being those observed for the candidate peaks-significantly enhanced the accuracy of peak assignment. Isotopic pattern analysis revealed a close correspondence for 11 DBPs with clearly visible isotopologues in reference spectra, thereby further strengthening the confidence in the peak assignment of these DBPs. Brominated analogues were prevalent among the detected DBPs, possibly due to seawater intrusion. The fate, behavior, persistence, and toxicity of tentatively identified DBPs were assessed using EPI Suite™ and the CompTox Chemicals Dashboard. This revealed their significant toxicity to aquatic organisms, including developmental, mutagenic, and endocrine-disrupting effects in certain DBPs. Some DBPs also showed activity in various CompTox bioassays, implicating them in adverse molecular pathways. Additionally, 11 DBPs demonstrated high environmental persistence and resistance to biodegradation. This combined approach offers a powerful tool for future research and environmental monitoring, enabling accurate identification and assessment of DBPs and their potential risks.

Novel Models for Accurate Estimation of Air-Blood Partitioning: Applications to Individual Compounds and Complex Mixtures of Neutral Organic Compounds.

The air-blood partition coefficient (Kab) is extensively employed in human health risk assessment for chemical exposure. However, current Kab estimation approaches either require an extensive number of parameters or lack precision. In this study, we present two novel and parsimonious models to accurately estimate Kab values for individual neutral organic compounds, as well as their complex mixtures. The first model, termed the GC×GC model, was developed based on the retention times of nonpolar chemical analytes on comprehensive two-dimensional gas chromatography (GC×GC). This model is unique in its ability to estimate the Kab values for complex mixtures of nonpolar organic chemicals. The GC×GC model successfully accounted for the Kab variance (R2 = 0.97) and demonstrated strong prediction power (RMSE = 0.31 log unit) for an independent set of nonpolar chemical analytes. Overall, the GC×GC model can be used to estimate Kab values for complex mixtures of neutral organic compounds. The second model, termed the partition model (PM), is based on two types of partition coefficients: octanol to water (Kow) and air to water (Kaw). The PM was able to effectively account for the variability in Kab data (n = 344), yielding an R2 value of 0.93 and root-mean-square error (RMSE) of 0.34 log unit. The predictive power and explanatory performance of the PM were found to be comparable to those of the parameter-intensive Abraham solvation models (ASMs). Additionally, the PM can be integrated into the software EPI Suite, which is widely used in chemical risk assessment for initial screening. The PM provides quick and reliable estimation of Kab compared to ASMs, while the GC×GC model is uniquely suited for estimating Kab values for complex mixtures of neutral organic compounds. In summary, our study introduces two novel and parsimonious models for the accurate estimation of Kab values for both individual compounds and complex mixtures.

Reliable prediction of sensory irritation threshold values of organic compounds using new models based on linear free energy relationships and GC×GC retention parameters.

The human sensory irritation threshold (SIT) is an important biochemical parameter for the exposure assessment of organic air pollutants. First, we recalibrated the Abraham solvation models (ASMs) for 9 SIT endpoints by curating 720 individual experimental SIT values to find an accurate and parsimonious ASM variant, which exhibited root mean square error (RMSE) = 0.174-0.473 log unit. Second, we report linear free energy relationships - henceforth called partition models (PMs) - which exploit the correlations of 9 SIT endpoints with the linear combinations of partition coefficients for octanol-water and air-water systems showing RMSE = 0.221-0.591 log unit. These PMs can easily be integrated into widely used EPI-Suite™ screening tool. The explanatory and predictive performance of PMs were like parameter-intensive ASMs. Third, we present GC × GC models that are based on the retention times of the nonpolar analytes on the comprehensive two-dimensional gas chromatography (GC × GC), which successfully described the SIT variance (R2=0.959-0.996) and depicted a strong predictive power (RMSE = 0.359-0.660 log unit) for an independent set of nonpolar analytes. Taken together, PMs allow easy SIT screening of organic chemicals compared to ASMs. Unlike ASMs, our GC × GC models can be applied to estimate SIT of complex nonpolar mixtures.

Exploring the role of octanol-water partition coefficient and Henry's law constant in predicting the lipid-water partition coefficients of organic chemicals.

Partition coefficients for storage lipid-water (logKlw) and phospholipid-water (logKpw) phases are key parameters to understand the bioaccumulation and toxicity of organic contaminants. However, the published experimental databases of these properties are dwarfs and current estimation approaches are cumbersome. Here, we present partition models that exploit the correlations of logKlw, and of logKpw with the linear combinations of the octanol-water partition coefficient (logKow) and the dimensionless Henry's law constant (air-water partition coefficient, logKaw). The calibrated partition models successfully describe the variations in logKlw data (n = 305, R2 = 0.971, root-mean-square-error (rmse) = 0.375), and in logKpw data (n = 131, R2 = 0.953, rmse = 0.413). With the inputs of logKow and logKaw estimated from the U.S. EPA's EPI Suite, our models of logKlw and logKpw have exhibited rmse = 0.52 with respect to experimental values indicating suitability of these models for inclusion in the EPI Suite. Our models perform similar to or better than the previously reported models such as one parameter partition models, Abraham solvation models, and models based on quantum-chemical calculations. Taken together, our models are robust, easy-to-use, and provide insight into variations of logKlw and logKpw in terms of hydrophobicity and volatility trait of chemicals.

Relook on the Linear Free Energy Relationships Describing the Partitioning Behavior of Diverse Chemicals for Polyethylene Water Passive Samplers.

Over the past 3 decades, low-density polyethylene (PE) passive sampling devices have been widely used to scout organic chemicals in air, water, sediments, and biotic phases. Experimental partition coefficient data, required to calculate the concentrations in environmental compartments, are not widely available. In this study, we developed and rigorously evaluated linear free energy relationships (LFERs) to predict the partition coefficient between the PE and the water phase (log K pe-w). Poly-parameter (pp) LFERs based on Abraham solute parameters performed better (root-mean-square error, rmse = 0.333-0.350 log unit) in predicting log K pe-w compared to the two one-parameter (op) LFERs built on n-hexadecane-water and octanol-water partition coefficients (rmse = 0.41-0.42 log unit), indicating that one parameter is not able to account for all types of interactions experienced by a chemical during PE-water exchange. Dimensionality analyses show that the calibration dataset used to train pp-LFERs fulfills all the requirements to obtain a robust model for log K pe-w. Van der Waals interactions of the molecule tend to favor the PE phase, and polar interactions of the molecule favor the water phase. The PE phase is the most sensitive to polarizable chemicals compared to other commonly used passive sampling polymeric phases such as polydimethylsiloxane, polyoxymethylene, and polyacrylate. For op-LFERs, the PE phase is better represented by the hexadecane phase than by the octanol phase. A computational method based on the conductor-like screening model for real solvents theory did good job in estimating log K pe-w for chemicals that were neither very hydrophobic nor very hydrophilic in nature. Our models can be used to reliably predict the log K pe-w values of simple neutral organic chemicals. This study provides insights into the partitioning behavior of PE samplers compared to other commonly used passive samplers.

Development and evaluation of two-parameter linear free energy models for the prediction of human skin permeability coefficient of neutral organic chemicals.

The experimental values of skin permeability coefficients, required for dermal exposure assessment, are not readily available for many chemicals. The existing estimation approaches are either less accurate or require many parameters that are not readily available. Furthermore, current estimation methods are not easy to apply to complex environmental mixtures. We present two models to estimate the skin permeability coefficients of neutral organic chemicals. The first model, referred to here as the 2-parameter partitioning model (PPM), exploits a linear free energy relationship (LFER) of skin permeability coefficient with a linear combination of partition coefficients for octanol-water and air-water systems. The second model is based on the retention time information of nonpolar analytes on comprehensive two-dimensional gas chromatography (GC × GC). The PPM successfully explained variability in the skin permeability data (n = 175) with R2 = 0.82 and root mean square error (RMSE) = 0.47 log unit. In comparison, the US-EPA's model DERMWIN™ exhibited an RMSE of 0.78 log unit. The Zhang model-a 5-parameter LFER equation based on experimental Abraham solute descriptors (ASDs)-performed slightly better with an RMSE value of 0.44 log unit. However, the Zhang model is limited by the scarcity of experimental ASDs. The GC × GC model successfully explained the variance in skin permeability data of nonpolar chemicals (n = 79) with R2 = 0.90 and RMSE = 0.23 log unit. The PPM can easily be implemented in US-EPA's Estimation Program Interface Suite (EPI Suite™). The GC × GC model can be applied to the complex mixtures of nonpolar chemicals.

Occurrence and quantification of prevalent antibiotics in wastewater samples from Rawalpindi and Islamabad, Pakistan.

Release of emerging pollutants including antibiotics to the environment is a serious concern for environmentalist as well as policy makers. To explore the presence and real situation analysis, a study was conducted focusing on detection and quantification of selected antibiotics in wastewater channels of Rawalpindi/Islamabad, Pakistan along with development of a simple High-Performance Liquid Chromatography (HPLC) based method. The samples were collected in triplicates from all the main wastewater streams of the study area with potential presence of antibiotics in the wastewater coming from the surrounding industries, hospitals, drug formulation units and residential localities. Optimized method for detection and quantification was established and validated through spiked as well as real samples. The highest concentration was of Ciprofloxacin 332.154 µg mL-1 followed by Ofloxacin > Ampicillin > Levofloxacin > Sulfamethoxazole. The results showed the presence of antibiotics due to indiscriminate use that could lead to presence of resistant strains and thus ultimately causing the spread of antibiotic resistance.

Mixture Touch: A Web Platform for the Evaluation of Complex Chemical Mixtures.

Risk assessment of chemical mixtures isRisk assessment of chemical mixtures is challenging because information about the chemical structure, concentration, properties, and toxicity, down to the individual compounds, is generally not readily accessible. To cope with this challenge, we think Mixture Touch- a web platform that offers a one-window solution, for free, for the risk assessment of complex mixtures that are analyzed with comprehensive two-dimensional gas chromatography (GC × GC). GC × GC is a powerful analytical technique for target and nontarget analysis of complex mixtures. Our web platform allows users to visualize the GC × GC data, conduct spectral identification, estimate properties, and analyze potential risks based on established methods. For illustration purpose, we show how to assess the aquatic bioaccumulation potential of short-chain chlorinated paraffin (SCCP), which is an industrially manufactured mixture. The platform readily demonstrated that most of the SCCP congeners did not have the tendency to accumulate in aquatic organisms but in humans. The platform can bridge the gap between the GC × GC experts, GC × GC users, analytical experts, and risk assessors. It could enhance the level of risk assessments of mixtures utilizing the high performance of the state-of-the-art analytical instruments.

Comprehensive two-dimensional gas-chromatography-based property estimation to assess the fate and behavior of complex mixtures: A case study of vehicle engine oil.

A method was developed to estimate the properties and assess the potential environmental risk of analytes in a complex mixture by comprehensive two-dimensional gas chromatography (GC × GC). A GC × GC-based estimation model was calibrated for 12 physicochemical properties that were relevant to the environment or to biological organisms, including human beings. Vehicle engine oil that had been contaminated by numerous compounds during its use was investigated as a case study to which the GC × GC model could be applied. Engine-oil samples were collected from a vehicle at intervals over a distance of 11407 km. The carbon and nitrogen contents in the oil remained unchanged at 83%-84% and 2%-5%, respectively, during the run; however, in excess of 100 compounds were present in the oil upon completion of the run. Post analyses of the studied mixture samples were performed with the developed GC × GC model, which links mass spectral information for structural identification. The GC × GC model allows us to classify the detected analytes in complex mixtures in terms of their properties, such as their aquatic bioaccumulation potential. The application of the model showed that the analyzed engine oil contained in excess of 100 compounds that could accumulate in aquatic biota and reach the arctic via long-range transport, which suggests that the components in the complex mixture of engine oil could pose a risk. The newly developed model that was derived in this study shows great potential for use in the mixture assessment.

How Persistent and Bioavailable Are Oxygenated Deepwater Horizon Oil Transformation Products?

About half of the surface oil floating on the Gulf of Mexico in the aftermath of the 2010 Deepwater Horizon spill was transformed into oxygenated hydrocarbons (OxHC) within days to weeks. These OxHC persist for years in oil/sand aggregates in nearshore and beach environments, and there is concern that these aggregates might represent a long-term source of toxic compounds. However, because this OxHC fraction is a continuum of transformation products that are not well chemically characterized, it is not included in current oil spill fate and effect models. This challenges an accurate environmental risk assessment of weathered oil. Here, we used molecular and bulk analytical techniques to constrain the chemical composition and environmental fate of weathered oil samples collected on the sea surface and beaches of the Gulf of Mexico. We found that approximately 50% of the weathering-related disappearance of saturated and aromatic compounds in these samples was compensated by an increase in OxHC. Furthermore, we identified and quantified a suite of oxygenated aliphatic compounds that are more water-soluble and less hydrophobic than its presumed precursors, but only represent <1% of the oil residues' mass. Lastly, dissolution experiments showed that compounds in the OxHC fraction can leach into the water; however, the mass loss of this process is small. Overall, this study shows that the OxHC fraction is prevalent and persistent in weathered oil/sand aggregates, which can act as a long-term source of dissolved oil-derived compounds.

Predicting Partitioning and Diffusion Properties of Nonpolar Chemicals in Biotic Media and Passive Sampler Phases by GC × GC.

The chemical parameters needed to explain and predict bioavailability, biodynamics, and baseline toxicity are not readily available for most nonpolar chemicals detected in the environment. Here, we demonstrate that comprehensive two-dimensional gas chromatography (GC × GC) retention times can be used to predict 26 relevant properties for nonpolar chemicals, specifically: partition coefficients for diverse biotic media and passive sampler phases; aquatic baseline toxicity; and relevant diffusion coefficients. The considered biotic and passive sampler phases include membrane and storage lipids, serum and muscle proteins, carbohydrates, algae, mussels, polydimethylsiloxane, polyethylene, polyoxymethylene, polyacrylate, polyurethane, and semipermeable membrane devices. GC × GC-based chemical property predictions are validated with a compilation of 1038 experimental property data collected from the literature. As an example application, we overlay a map of baseline toxicity to fathead minnows onto the separated analyte signal of a polychlorinated alkanes (chlorinated paraffins) technical mixture that contains 7820 congeners. In a second application, GC × GC-estimated properties are used to parametrize multiphase partitioning models for mammalian tissues and organs. In a third example, we estimate chemical depuration kinetics for mussels. Finally, we illustrate an approach to screen the GC × GC chromatogram for nonpolar chemicals of potentially high concern, defined based on their GC × GC-estimated biopartitioning properties, diffusion properties, and baseline toxicity.

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.

First day of an oil spill on the open sea: early mass transfers of hydrocarbons to air and water.

During the first hours after release of petroleum at sea, crude oil hydrocarbons partition rapidly into air and water. However, limited information is available about very early evaporation and dissolution processes. We report on the composition of the oil slick during the first day after a permitted, unrestrained 4.3 m(3) oil release conducted on the North Sea. Rapid mass transfers of volatile and soluble hydrocarbons were observed, with >50% of ≤C17 hydrocarbons disappearing within 25 h from this oil slick of <10 km(2) area and <10 µm thickness. For oil sheen, >50% losses of ≤C16 hydrocarbons were observed after 1 h. We developed a mass transfer model to describe the evolution of oil slick chemical composition and water column hydrocarbon concentrations. The model was parametrized based on environmental conditions and hydrocarbon partitioning properties estimated from comprehensive two-dimensional gas chromatography (GC×GC) retention data. The model correctly predicted the observed fractionation of petroleum hydrocarbons in the oil slick resulting from evaporation and dissolution. This is the first report on the broad-spectrum compositional changes in oil during the first day of a spill at the sea surface. Expected outcomes under other environmental conditions are discussed, as well as comparisons to other models.

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.

Evaluation of the adsorption potential of titanium dioxide nanoparticles for arsenic removal.

The adsorption potential of titanium dioxide (TiO2) nanoparticles for removing arsenic from drinking water was evaluated. Pure and iron-doped TiO2 particles are synthesized via sol-gel method. The synthesized TiO2 nanoparticles were then immobilized on ordinary sand for adsorption studies. Adsorption isotherms were conducted on the synthesized nanoparticles as well as the sand coated with TiO2 nanoparticles under varying conditions of air and light, namely, the air-sunlight (A-SL), air-light (AL), air-dark (AD) and nitrogen-dark (ND). X-ray diffraction (XRD) analysis showed that the pure and iron-doped TiO2 nanoparticles were in 100% anatase crystalline phase with crystal sizes of 108 and 65 nm, respectively. Adsorption of arsenic on the three adsorbents was non-linear that could be described by the Freundlich and Langmuir adsorption models. Iron doping enhanced the adsorption capacity of TiO2 nanoparticles by arresting the grain growth and making it visible light responsive resulting in a higher affinity for arsenic. Similarly, the arsenic removal by adsorption on the sand coated with TiO2 nanoparticles was the highest among the three types of sand used. In all cases, As(V) was adsorbed more compared with As(III). The solution pH appeared to be the most important factor in controlling the amount of arsenic adsorbed.