Application of Biologically Based Lumping To Investigate the Toxicokinetic Interactions of a Complex Gasoline Mixture.

People are often exposed to complex mixtures of environmental chemicals such as gasoline, tobacco smoke, water contaminants, or food additives. We developed an approach that applies chemical lumping methods to complex mixtures, in this case gasoline, based on biologically relevant parameters used in physiologically based pharmacokinetic (PBPK) modeling. Inhalation exposures were performed with rats to evaluate the performance of our PBPK model and chemical lumping method. There were 109 chemicals identified and quantified in the vapor in the chamber. The time-course toxicokinetic profiles of 10 target chemicals were also determined from blood samples collected during and following the in vivo experiments. A general PBPK model was used to compare the experimental data to the simulated values of blood concentration for 10 target chemicals with various numbers of lumps, iteratively increasing from 0 to 99. Large reductions in simulation error were gained by incorporating enzymatic chemical interactions, in comparison to simulating the individual chemicals separately. The error was further reduced by lumping the 99 nontarget chemicals. The same biologically based lumping approach can be used to simplify any complex mixture with tens, hundreds, or thousands of constituents.

Heuristic optimization of a continuous flow point-of-use UV-LED disinfection reactor using computational fluid dynamics.

Alternative disinfection sources such as ultraviolet light (UV) are being pursued to inactivate pathogenic microorganisms such as Cryptosporidium and Giardia, while simultaneously reducing the risk of exposure to carcinogenic disinfection by-products (DBPs) in drinking water. UV-LEDs offer a UV disinfecting source that do not contain mercury, have the potential for long lifetimes, are robust, and have a high degree of design flexibility. However, the increased flexibility in design options will add a substantial level of complexity when developing a UV-LED reactor, particularly with regards to reactor shape, size, spatial orientation of light, and germicidal emission wavelength. Anticipating that LEDs are the future of UV disinfection, new methods are needed for designing such reactors. In this research study, the evaluation of a new design paradigm using a point-of-use UV-LED disinfection reactor has been performed. ModeFrontier, a numerical optimization platform, was coupled with COMSOL Multi-physics, a computational fluid dynamics (CFD) software package, to generate an optimized UV-LED continuous flow reactor. Three optimality conditions were considered: 1) single objective analysis minimizing input supply power while achieving at least (2.0) log10 inactivation of Escherichia coli ATCC 11229; and 2) two multi-objective analyses (one of which maximized the log10 inactivation of E. coli ATCC 11229 and minimized the supply power). All tests were completed at a flow rate of 109 mL/min and 92% UVT (measured at 254 nm). The numerical solution for the first objective was validated experimentally using biodosimetry. The optimal design predictions displayed good agreement with the experimental data and contained several non-intuitive features, particularly with the UV-LED spatial arrangement, where the lights were unevenly populated throughout the reactor. The optimal designs may not have been developed from experienced designers due to the increased degrees of freedom offered by using UV-LEDs. The results of this study revealed that the coupled optimization routine with CFD was effective at significantly decreasing the engineer's design decision space and finding a potentially near-optimal UV-LED reactor solution.