Summary review of the chemical characterization of liquid and sludge contained in the Old Hydrofracture tanks, Oak Ridge National Laboratory, Oak Ridge, Tennessee

This report presents analytical data developed from samples collected from the five inactive tanks located at the Old Hydrofracture Facility (OHF) at the Oak Ridge National Laboratory (ORNL) in Oak Ridge, Tennessee. The samples were collected during December 1995 and January 1996. The purpose of the sampling and analysis project was (1) to determine whether the tank contents meet ORNL waste acceptance criteria, as specified in the Oak Ridge National Laboratory, Liquid Waste Treatment Systems, Waste Evaluation Criteria; (2) to determine various physical properties of the tank contents that would affect the design of a sludge mobilization system; and (3) to gather information to support a baseline risk assessment. The report focuses on the analytical results used to evaluate the tank contents with regard to nuclear criticality safety requirements and to regulatory waste characterization

Soil mobility of surface applied polyaromatic hydrocarbons in response to simulated rainfall

Polyaromatic hydrocarbons (PAHs) are emitted from a variety of sources and can accumulate on and within surface soil layers. To investigate the level of potential risk posed by surface contaminated soils, vertical soil column experiments were conducted to assess the mobility, when leached with simulated rainwater, of six selected PAHs (naphthalene, phenanthrene, fluoranthene, pyrene, benzo(e)pyrene and benzo(ghi)perylene) with contrasting hydrophobic characteristics and molecular weights/sizes. The only PAH found in the leachate within the experimental period of 26 days was naphthalene. The lack of migration of the other applied PAHs were consistent with their low mobilities within the soil columns which generally parallelled their log Koc values. Thus only 2.3% of fluoranthene, 1.8% of pyrene, 0.2% of benzo(e)pyrene and 0.4% of benzo(ghi)perylene were translocated below the surface layer. The PAH distributions in the soil columns followed decreasing power relationships with 90% reductions in the starting levels being shown to occur within a maximum average depth of 0.94 cm compared to an average starting depth of 0.5 cm. A simple predictive model identifies the extensive time periods, in excess of 10 years, required to mobilise 50% of the benzo(e)pyrene and benzo(ghi)perylene from the surface soil layer. Although this reduces to between 2 and 7 years for fluoranthene and pyrene, it is concluded that the possibility of surface applied PAHs reaching and contaminating a groundwater aquifer is unlikely

Combined artificial bee colony algorithm and machine learning techniques for prediction of online consumer repurchase intention

A novel paradigm in the service sector i.e. services through the web is a progressive mechanism for rendering offerings over diverse environments. Internet provides huge opportunities for companies to provide personalized online services to their customers. But prompt novel web services introduction may unfavorably affect the quality and user gratification. Subsequently, prediction of the consumer intention is of supreme importance in selecting the web services for an application. The aim of study is to predict online consumer repurchase intention and to achieve this objective a hybrid approach which a combination of machine learning techniques and Artificial Bee Colony (ABC) algorithm has been used. The study is divided into three phases. Initially, shopping mall and consumer characteristic’s for repurchase intention has been identified through extensive literature review. Secondly, ABC has been used to determine the feature selection of consumers’ characteristics and shopping malls’ attributes (with > 0.1 threshold value) for the prediction model. Finally, validation using K-fold cross has been employed to measure the best classification model robustness. The classification models viz., Decision Trees (C5.0), AdaBoost, Random Forest (RF), Support Vector Machine (SVM) and Neural Network (NN), are utilized for prediction of consumer purchase intention. Performance evaluation of identified models on training-testing partitions (70-30%) of the data set, shows that AdaBoost method outperforms other classification models with sensitivity and accuracy of 0.95 and 97.58% respectively, on testing data set. This study is a revolutionary attempt that considers both, shopping mall and consumer characteristics in examine the consumer purchase intention.N/

Biodegradation of Trichloroethylene in Continuous-Recycle Expanded-Bed Bioreactors

Experimental bioreactors operated as recirculated closed systems were inoculated with bacterial cultures that utilized methane, propane, and tryptone-yeast extract as aerobic carbon and energy sources and degraded trichloroethylene (TCE). Up to 95% removal of TCE was observed after 5 days of incubation. Uninoculated bioreactors inhibited with 0.5% Formalin and 0.2% sodium azide retained greater than 95% of their TCE after 20 days. Each bioreactor consisted of an expanded-bed column through which the liquid phase was recirculated and a gas recharge column which allowed direct headspace sampling. Pulses of TCE (20 mg/liter) were added to bioreactors, and gas chromatography was used to monitor TCE, propane, methane, and carbon dioxide. Pulsed feeding of methane and propane with air resulted in 1 mol of TCE degraded per 55 mol of substrate utilized. Perturbation studies revealed that pH shifts from 7.2 to 7.5 decreased TCE degradation by 85%. The bioreactors recovered to baseline activities within 1 day after the pH returned to neutrality

Trichloroethylene Biodegradation by a Methane-Oxidizing Bacterium

Trichloroethylene (TCE), a common groundwater contaminant, is a suspected carcinogen that is highly resistant to aerobic biodegradation. An aerobic, methane-oxidizing bacterium was isolated that degrades TCE in pure culture at concentrations commonly observed in contaminated groundwater. Strain 46-1, a type I methanotrophic bacterium, degraded TCE if grown on methane or methanol, producing CO(2) and water-soluble products. Gas chromatography and (14)C radiotracer techniques were used to determine the rate, methane dependence, and mechanism of TCE biodegradation. TCE biodegradation by strain 46-1 appears to be a cometabolic process that occurs when the organism is actively metabolizing a suitable growth substrate such as methane or methanol. It is proposed that TCE biodegradation by methanotrophs occurs by formation of TCE epoxide, which breaks down spontaneously in water to form dichloroacetic and glyoxylic acids and one-carbon products