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To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jenvman.2009.01.021 Byline: Y. Jeffrey Yang, Roy C. Haught, James A. Goodrich Abstract: Accurate detection and identification of natural or intentional contamination events in a drinking water pipe is critical to drinking water supply security and health risk management. To use conventional water quality sensors for the purpose, we have explored a real-time event adaptive detection, identification and warning (READiw) methodology and examined it using pilot-scale pipe flow experiments of 11 chemical and biological contaminants each at three concentration levels. The tested contaminants include pesticide and herbicides (aldicarb, glyphosate and dicamba), alkaloids (nicotine and colchicine), E. coli in terrific broth, biological growth media (nutrient broth, terrific broth, tryptic soy broth), and inorganic chemical compounds (mercuric chloride and potassium ferricyanide). First, through adaptive transformation of the sensor outputs, contaminant signals were enhanced and background noise was reduced in time-series plots leading to detection and identification of all simulated contamination events. The improved sensor detection threshold was 0.1% of the background for pH and oxidation-reduction potential (ORP), 0.9% for free chlorine, 1.6% for total chlorine, and 0.9% for chloride. Second, the relative changes calculated from adaptively transformed residual chlorine measurements were quantitatively related to contaminant-chlorine reactivity in drinking water. We have shown that based on these kinetic and chemical differences, the tested contaminants were distinguishable in forensic discrimination diagrams made of adaptively transformed sensor measurements. Author Affiliation: U.S. Environmental Protection Agency, National Risk Management Research Laboratory, Water Supply and Water Resources Division, 26 West Martin Luther King Dr., Cincinnati, OH 45268, USA Article History: Received 10 October 2007; Revised 24 December 2008; Accepted 21 January 2009

Vaporization and soil adsorption are the two mass transfer mechanisms that control contaminant recovery rates for soil vapor extraction (SVE) systems. At most soil remediation sites, contaminants are distributed among three phases, namely, soil particles, pore water, and soil vapor. Contaminant mass transfer from adsorption sites into a convective vapor stream involves desorption, diffusion through pore water, and vaporization into soil vapor. An SVE design model is proposed to describe this three-phase mass transfer process and assist the design and evaluation of SVE systems. The model contains analytical solutions developed to estimate contaminant concentrations in the vapor phase and predict contaminant removal rates. Monitoring data from two full-scale SVE systems were used for model development and calibration. The results suggest that contaminant diffusion through the pore water is the rate-limiting step and leads to remediation inefficiency of an SVE system. Mass transfer retardation from molecular diffusion in water is likely the major contributing component to the venting efficiency coefficient of Staudinger et al.

Introduction During well installation, a wellbore skin of finite thickness can develop between the well and formation. Auger rotation and retrieval can smear silt- and clay-sized sediments on the borehole [...]

Introduction Ground-water contamination is commonly the result of contaminant releases from a variety of industrial and/or municipal sources. As ground water flows in response to natural hydraulic gradients, a contaminant [...]

Hydrological responses vary spatially and temporally according to watershed characteristics. In this study, the hydrological models that we developed earlier for the Little Miami River (LMR) and Las Vegas Wash (LVW) watersheds in the USA were used for detailed sensitivity analyses. To compare the relative sensitivities of the hydrological parameters of these two models, we used normalized root mean square error (NRMSE). By combining the NRMSE index with the flow duration curve analysis, we derived an approach to measure parameter sensitivities under different flow regimes. Results show that the parameters related to groundwater are highly sensitive in the LMR watershed, whereas the LVW watershed is primarily sensitive to near-surface and impervious parameters. The high and medium flows are more impacted by most of the parameters. The low flow regime was highly sensitive to groundwater-related parameters. Moreover, our approach is found to be useful in facilitating model development and calibration. EDITOR D. Koutsoyiannis ASSOCIATE EDITOR S. Huang [ABSTRACT FROM AUTHOR]