Volatile organic compounds in the unsaturated zone from radioactive wastes

Volatile organic compounds (VOCs) are often comingled with low-level radioactive wastes (LLRW), but little is known about subsurface VOC emanations from LLRW landfills. The current study systematically quantified VOCs associated with LLRW over an 11-yr period at the USGS Amargosa Desert Research Site (ADRS) in southwestern Nevada. Unsaturated-zone gas samples of VOCs were collected by adsorption on resin cartridges and analyzed by thermal desorption and GC/MS. Sixty of 87 VOC method analytes were detected in the 110-m-thick unsaturated zone surrounding a LLRW disposal facility. Chlorofluorocarbons (CFCs) were detected in 100% of samples collected. Chlorofluorocarbons are powerful greenhouse gases, deplete stratospheric ozone, and are likely released from LLRW facilities worldwide. Soil-gas samples collected from a depth of 24 m and a horizontal distance 100 m south of the nearest waste-disposal trench contained >60,000 ppbv total VOCs, including >37,000 ppbv CFCs. Extensive sampling in the shallow unsaturated zone (0-2 m deep) identified areas where total VOC concentrations exceeded 5000 ppbv at the 1.5-m depth. Volatile organic compound concentrations exceeded background levels up to 300 m from the facility. Maximum vertical diffusive fluxes of total VOCs were estimated to be 1 g m yr. Volatile organic compound distributions were similar but not identical to those previously determined for tritium and elemental mercury. To our knowledge, this study is the first to characterize the unsaturated zone distribution of VOCs emanating from a LLRW landfill. Our results may help explain anomalous transport of radionuclides at the ADRS and elsewhere.     

Cross-reactivity of anti-Salmonella egg-yolk antibodies to Salmonella serovars

The cross-reactivity of egg yolk antibodies specific to antigens of Salmonella Enteritidis and Salmonella Typhimurium to killed bacterial cells of common Salmonella serovars were tested using an indirect Enzyme Linked Immunosorbent Assay (ELISA). Egg yolk antibodies were produced against purified fimbriae, flagella and lipopolysaccharide (LPS) of S. Enteritidis strain ATCC13076 and flagella, LPS and outer membrane proteins (OMP) of S. Typhimurium strain ATCC13311. For immunological specificity of egg yolk antibodies against killed bacterial cells, we found that the titers of the anti-S. Enteritidis egg yolk antibodies were higher than those of the anti-S. Typhimurium antibodies. In the evaluation of cross-reactivity of these egg yolk antibodies to various Salmonella serovars, we observed that the anti-S. Enteritidis antibodies exhibited more specific affinity than those of the anti-S. Typhimurium antibodies. All S. Enteritidis strains reacted specifically with the anti-S. Enteritidis fimbrial and flagellar egg yolk antibody whereas anti-S. Enteritidis LPS and anti-S. Typhimurium LPS, OMP and flagellar antibodies displayed non-specific reactivity to all Salmonella serovars used in this study. This finding suggests that it may be possible to design a anti-fimbrial egg yolk antibody of S. Enteritidis as a diagnostic tool and a cocktail of OMP and LPS antigens of S. Enteritidis and S. Typhimurium could be used for administering broad spectrum passive immunity to protect against the colonization of pathogenic Salmonella strains in food animals.     

Improved Predictions of Plume Perception with a Human Visual System Model

This paper describes incorporation of a human visual system model in the widely used plume visibility model PLUVUE. The results will be of interest to all involved with siting new sources for which visibility of the plume is a concern and to visibility researchers. The human visual system model allows inclusion of size and shape effects on the perceptibility of a plume. Example calculations are given for 2250- and 1600-MW power plants which show that size and shape effects can reduce the predicted perceptibility by up to a factor of three.     

A Pilot Indoor-Outdoor Study of Organic Particulate Matter and Particulate Mutagenicity

Abstract

Many large metropolitan areas experience elevated concentrations of ground-level ozone pollution during the summertime “smog season”. Local environmental or health agencies often need to make daily air pollution forecasts for public advisories and for input into decisions regarding abatement measures and air quality management. Such forecasts are usually based on statistical relationships between weather conditions and ambient air pollution concentrations. Multivariate linear regression models have been widely used for this purpose, and well-specified regressions can provide reasonable results. However, pollution-weather relationships are typically complex and nonlinear—especially for ozone—properties that might be better captured by neural networks. This study investigates the potential for using neural networks to forecast ozone pollution, as compared to traditional regression models. Multiple regression models and neural networks are examined for a range of cities under different climate and ozone regimes, enabling a comparative study of the two approaches. Model comparison statistics indicate that neural network techniques are somewhat (but not dramatically) better than regression models for daily ozone prediction, and that all types of models are sensitive to different weather-ozone regimes and the role of persistence in aiding predictions.     

A Review of Treatment Alternatives for Wastes Containing Treatment Technologies For Hazardous Wastes: Part V

The Hazardous and Solid Waste Amendments to the Resource Conservation and Recovery Act direct the Environmental Protection Agency to determine the available treatment technologies for a number of hazardous waste streams, including halogenated organics. If it is determined that existing technology and capacity is sufficient for the safe management of the designated halogenated organic wastes, these wastes will be prohibited from land disposal, effective July 8,1987. This article summarizes the general characteristics and treatment alternatives for this waste category.     

Preformed Amide-containing biopolymer for Improving the Environmental Performance of Synthesized Urea–formaldehyde in Agro-fiber Composites

Investigations have continued for production high performance agro-based composites using environmentally acceptable approaches. This study examines the role of adding amide-containing biopolymers during synthesis of urea–formaldehyde (UF) on properties of adhesive produced, especially its adhesion potential. The environmental performance of UF-resin synthesized in the presence of modified amide-containing biopolymer was evaluated by evaluating the free-HCHO of both adhesive (during processing) and of the eventual engineered composite product. Also, the benefits of this synthesis-modified adhesive in enhancing the bondability of sugar-cane fibers used in engineered composite panels was evaluated and compared to using UF-resin. The results obtained show that, static bending of the produced composites varied from 27.7 to 33.13 N/mm² of modulus of rupture (MOR) and from 2860 to 3374 N/mm² of Modulus of Elasticity (MOE); while for internal bond (IB) it’s varied from 0.64 to 0.866 N/mm². Based on the ANSI and EN Standards modified UF-based agro composites produced meet the performance requirements for high grade particleboards with respect to static bending strength. These agro-based composite also tested out as having free-HCHO values of ~13 mg/100 g board.     

Distribution patterns of plants explained by human movement behaviour

Distribution patterns of plants are affected by human activities such as creation, destruction or modification of habitats. However, another important question is to what extent humans shape plant distributions by acting as dispersal vectors. In order to answer this question we developed a simulation model for the spread of plant species between human settlements. This was done on the basis of extensive sociological and ecological data on a regional scale. With regard to the sociological data, human movement behaviour defined the amount of exchange between the settlements. Gardening types represented the potential habitat in our model. The ecological data was derived from a vegetation survey carried out in 2003, which was a repeat of a survey between 1974 and 1981 along the same transects. From these surveys, we studied the distributions of 13 species in 67 settlements. In our model, the earlier survey provided the data for the initial distribution. The simulated pattern was consequently compared with the distribution pattern in 2003. In the model, dispersal kernels based on patterns of human movement between settlements led to a better match with the distribution patterns than a null model simulating pure distance dependent dispersal for all species. This was statistically significant for seven of the thirteen species. A striking result was that alien species seem to benefit more from human dispersal than native species. We emphasize the importance of the sociological data on human movement behaviour in parameterizing our regional scale model. This study provides quantitative evidence on the impact of human movement behaviour on the distribution of plant species in suburban areas.