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Accurate prediction of the sorption coefficients of volatile organic compounds (VOCs) on carbon nanotubes (CNTs) is of major importance for developing an effective VOC removal process and risk assessment of released nanomaterial-carrying contaminants. The linear free energy relationship (LFER) approach was applied to investigate the adsorption mechanisms of VOCs on multiwalled CNTs (MWCNTs). The gas-solid partition coefficients (log K d ) of 17 VOCs were determined at 0%, 55%, and 90% relative humidity (RH). The cavity/dispersion interaction is generally the most influential adsorption mechanism for all RH cases. The hydrogen-accepting interactions declined but with constant hydrogen-donating interactions during the increase of RH, suggesting that the acidity of VOC was important in forming sorptive interaction with the MWCNT surface. Moreover, the comparison of log K d of VOCs on MWCNTs and other sorbents revealed that the sorption performance of MWCNTs is much more stable over a wider range of RHs due to better site availability and site quality. Furthermore, for all 6 adsorbents in all RHs, the positive contribution of hydrogen bonding ability was found as compared to the negative one found for sorbents completely in water, indicating that the hydrogen-bond donor and acceptor on the sorbent surface contribute to the sorption in the gas phase. In conclusion, the LFER-derived coefficients can be useful in predicting the performance of VOC adsorption on adsorbents and in facilitating the design of efficient VOC removal systems.

Growing concern for the biological fate of organic contaminants and their metabolites and the urge to connect in vitro and in vivo toxicokinetics have prompted researchers to characterize the biotransformation behavior of organic contaminants in biota. The whole body biotransformation rate constant (k M ) is currently determined by the difference approach, which has significant methodological limitations. A new approach for determining k M from the kinetic observations of the parent contaminant and its intermediate metabolites is proposed. In this method, k M can be determined by fitting kinetic data of the parent contaminant and the metabolites to analytical equations that depict the bioaccumulation kinetics. The application of the proposed method is illustrated using worm bioaccumulation-biotransformation data collected from the literature. Furthermore, a metabolite parent concentration factor (MPCF) is also proposed to characterize the persistence of the metabolite in biota. Because both the proposed k M method and MPCF build on the existing theoretical framework for bioaccumulation, they can be readily incorporated into standard experimental bioaccumulation protocols or risk assessment procedures or frameworks. Possible limitations, implications, and future directions are elaborated. Environ Toxicol Chem 2016;35:2903-2909. © 2016 SETAC., (© 2016 SETAC.)

The bioconcentration factor (BCF) of neutral and weakly polar organic chemicals in fish is modeled using independently calibrated models of chemical partitioning (freely dissolved fraction of chemical in the aqueous phase [φsys ] and wet-weight fish-water partition coefficient [KFW ]), respiratory exchange (respiratory update rate constant [k1 ], and respiratory elimination rate constant [k2  = k1 /KFW ]), and biotransformation (whole-body biotransformation rate constant [kM ]) as BCF = φsys KFW /(1 + kM /k2 ). Existing k1 models tend to overestimate for chemicals with log KOW  < 3.5, which constituted 30% to 50% of the examined chemicals. A revised k1 model covering a wider log KOW range (0-8.5) is presented k1  = (5.46 × 10(-6) MW + 0.261/KOW )(-1) , where MW is the molecular weight. The biotransformation rate constant kM is modeled using biota internal partitioning and Abraham parameters as reactivity descriptors. The reductionist model was tested using 3 different BCF data sets (US Environmental Protection Agency's Estimation Programs Interface [EPI], n = 548; Hertfordshire, n = 210; Arnot-Gobas, n = 1855) and compared with the following 3 state-of-the-art models: 1) the EPI Suite BCFBAF module, 2) the European Commision's Computer Assisted Evaluation of industrial chemical Substances According to Regulations (CAESAR), and 3) the EPI/Arnot mechanistic kinetic model. The reductionist model performed comparably with the alternative models (root mean square errors [RMSEs] = 0.72-0.77), with only 5 fitting parameters and no training against experimental BCFs. Respiratory elimination and biotransformation dominate the total depuration (i.e., [k2  + kM ]/kT  ≥ 0.8) for approximately 98% of the data entries, thus validating the reductionist approximation. Mechanistic models provide greater insights into bioaccumulation and are more sensitive to biological variation. All three BCF data sets and relevant properties and checkpoint values necessary for reproducing predictions of the reductionist model have been documented. The present study shows that a streamlined mechanistic model of BCF is possible for assessment purposes., (Copyright © 2013 SETAC.)

A model for whole-body in vivo biotransformation of neutral and weakly polar organic chemicals in fish is presented. It considers internal chemical partitioning and uses Abraham solvation parameters as reactivity descriptors. It assumes that only chemicals freely dissolved in the body fluid may bind with enzymes and subsequently undergo biotransformation reactions. Consequently, the whole-body biotransformation rate of a chemical is retarded by the extent of its distribution in different biological compartments. Using a randomly generated training set (n = 64), the biotransformation model is found to be: log (HLφfish ) = 2.2 (±0.3)B - 2.1 (±0.2)V - 0.6 (±0.3) (root mean square error of prediction [RMSE] = 0.71), where HL is the whole-body biotransformation half-life in days, φfish is the freely dissolved fraction in body fluid, and B and V are the chemical's H-bond acceptance capacity and molecular volume. Abraham-type linear free energy equations were also developed for lipid-water (Klipidw ) and protein-water (Kprotw ) partition coefficients needed for the computation of φfish from independent determinations. These were found to be 1) log Klipidw  = 0.77E - 1.10S - 0.47A - 3.52B + 3.37V + 0.84 (in Lwat /kglipid ; n = 248, RMSE = 0.57) and 2) log Kprotw  = 0.74E - 0.37S - 0.13A - 1.37B + 1.06V - 0.88 (in Lwat /kgprot ; n = 69, RMSE = 0.38), where E, S, and A quantify dispersive/polarization, dipolar, and H-bond-donating interactions, respectively. The biotransformation model performs well in the validation of HL (n = 424, RMSE = 0.71). The predicted rate constants do not exceed the transport limit due to circulatory flow. Furthermore, the model adequately captures variation in biotransformation rate between chemicals with varying log octanol-water partitioning coefficient, B, and V and exhibits high degree of independence from the choice of training chemicals. The present study suggests a new framework for modeling chemical reactivity in biological systems., (Copyright © 2013 SETAC.)

We investigated desorption of native pyrene from field-aged sediments using time-gated, laser-induced fluorescence (LIF) spectroscopy. LIF is superior to conventional analytical methods for the measurement of quickly changing dissolved pyrene because it allows observations at minute-scale resolution, has a low detection limit (approximately 1 ng/L), and minimizes sample loss and disturbance since it requires no system subsampling and chemical analysis. The efficacy of LIF was demonstrated in studies of pyrene desorption from Boston Harbor sediment segregated into different size-fractions (38-75, 75-106, and 180-250 microm diameter) and used in varying solid-to-water ratios (20, 70, and 280 mg(solid)/L). The effects of particle size and solid loading on desorption were consistent with diffusion physics. For suspension conditions between 20 and 280 mg(solids)/L, we observed desorption continuing toward an apparent plateau level over the course of weeks to months. This implies that the characteristic desorption time of pyrene from fine sediments and, by inference, other sediment-bound hydrophobic organic compounds (HOCs) of similar hydrophobicity, exceeds the typical characteristic times for pore water flushing and resuspension events. Consequently, the assumption of local sorption equilibrium in modeling efforts would be inappropriate.