1,4-Dioxane is a probable human carcinogen, and industrial solvent stabilizer, and common groundwater chemical found co-occurring with chlorinated volatile organic compounds (CVOCs). Both classes of chemicals have proven challenging to sustainably remove from groundwater. This study examined the effectiveness of granular activated carbon bioaugmented with Pseudonocardia dioxanivorans CB1190 (bioGAC) at removing 1,4-dioxane and CVOCs simultaneously. This sorption-biodegradation synergistic treatment was investigated in bench-scale flow-through column reactors as well as in pilot-scale drums. The reactors consisted of fixed beds with 1.5% w/w GAC and 98.5% w/w sand homogenously distributed. Results demonstrate a 50% to 800% increase in 1,4-dioxane removal compared to non-bioaugmented controls. Hydraulic retention time (HRT), sufficient nutrient amendments, and consistent dissolved oxygen supply were identified as crucial parameters to sustain 1,4-dioxane degradation and mitigate desorption events to extend operational longevity of aerobic bioGAC systems. This research supports consideration of bioGAC systems to treat solvent impacted water resources.

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Effective management of diabetes mellitus, affecting tens of millions of patients, requires frequent assessment of plasma glucose. Patient compliance for sufficient testing is often reduced by the unpleasantness of current methodologies, which require blood samples and often cause pain and skin callusing. We propose that the analysis of volatile organic compounds (VOCs) in exhaled breath can be used as a novel, alternative, noninvasive means to monitor glycemia in these patients. Seventeen healthy (9 females and 8 males, 28.0 ± 1.0 yr) and eight type 1 diabetic (T1DM) volunteers (5 females and 3 males, 25.8 ± 1.7 yr) were enrolled in a 240-min triphasic intravenous dextrose infusion protocol (baseline, hyperglycemia, euglycemia-hyperinsulinemia). In T1DM patients, insulin was also administered (using differing protocols on 2 repeated visits to separate the effects of insulinemia on breath composition). Exhaled breath and room air samples were collected at 12 time points, and concentrations of ~100 VOCs were determined by gas chromatography and matched with direct plasma glucose measurements. Standard least squares regression was used on several subsets of exhaled gases to generate multilinear models to predict plasma glucose for each subject. Plasma glucose estimates based on two groups of four gases each (cluster A: acetone, methyl nitrate, ethanol, and ethyl benzene; cluster B: 2-pentyl nitrate, propane, methanol, and acetone) displayed very strong correlations with glucose concentrations (0.883 and 0.869 for clusters A and B, respectively) across nearly 300 measurements. Our study demonstrates the feasibility to accurately predict glycemia through exhaled breath analysis over a broad range of clinically relevant concentrations in both healthy and T1DM subjects.