MULTI INCREMENT® TCE vadose‐zone investigation

MULTI INCREMENT® and discrete sampling strategies were used to estimate the average concentration and the three‐dimensional distribution of TCE in a 3,300‐m³ zone composed of two decision units (e.g., area of concern, population, exposure unit). Authors of this article and a private contractor (Stanley Consultants Inc.), respectively, implemented these two sampling strategies independently. Compared to discrete sampling, the MULTI INCREMENT sampling strategy identified more locations where percent‐level concentrations of TCE have migrated, is more economical, and provided greater data quality. © 2008 Wiley Periodicals, Inc.     

Field demonstration of the combined effects of absorption and evapotranspiration on septic system drainfield capacity.

Drainfields for disposal of septic tank effluents are typically designed by considering the loss of water by either upward evapotranspiration into the atmosphere or lateral and downward absorption into the adjacent soil. While this approach is appropriate for evapotranspiration systems, absorption systems allow water loss by both mechanisms. It was proposed that, in areas where high evapotranspiration rates coincide with permeable soils, drainfield sizes could be substantially reduced by accounting for both mechanisms. A two-year field demonstration was conducted to determine appropriate design criteria for areas typical of the Texas High Plains. The study consisted of evaluating the long-term acceptance rates for three different drainfield configurations: evapotranspiration only, absorption only, and combined conditions. A second field demonstration repeated the experiments for additional observation of the combined evapotranspiration and absorption and achieved similar results as the first study. The field tests indicated that the current design loading criteria may be increased by at least a factor of two for the Texas High Plains region and other Texas areas with similar soil composition and evapotranspiration rates, while still retaining a factor of safety of two.     

Spatial contaminant heterogeneity: quantification with scale of measurement at contrasting sites

Material within the terrestrial environment is rarely homogeneously distributed, either spatially or temporally. One consequence of heterogeneity is that uncertainty is usually generated in measurements that are taken with the aim of characterising the environment. For example, a measurement of analyte concentration within soil taken from one sampling location on contaminated land can vary substantially when compared against another sample taken at effectively the same nominal location. The measurement uncertainty arising from the heterogeneity can substantially limit the reliability of the interpretations made upon environmental investigations. The sampling uncertainty usually outweighs the analytical uncertainty from the laboratory, often by a factor of 20 or more. One approach to reducing the uncertainty is to design a more suitable sampling strategy. This might be achieved by predicting the degree of heterogeneity prior to the investigation, but this is often difficult to achieve accurately. Another approach, which was investigated here, is to actually characterise the heterogeneity prior to the main investigation using rapid and inexpensive technology, such as in situ measurement techniques. In situ portable X-ray fluorescence (PXRF) and X-ray microprobe (XMP) techniques were employed to test the feasibility of this approach. Two contrasting contaminated land sites were chosen to characterise the two-dimensional spatial heterogeneity of heavy metal contamination in topsoil at a range of scales (50 m to 0.001 m). The spatial heterogeneity of contaminants, expressed as relative standard deviations, was found to differ between the two sites by a factor of two, largely due to the mode of deposition of pollution. The study also indicated that the heterogeneity did not change systematically with the scale of measurement between sampling locations at either site.     

The effect of particle size reduction by grinding on subsampling variance for explosives residues in soil

Efforts to characterize the surface soil contamination on military training ranges have been compromised by the inability to obtain representative subsamples of soils submitted to analytical laboratories for determination of explosives residues. Two factors affecting subsampling error for explosives residues were examined using soils collected from hand grenade and anti-tank ranges. These factors were increased subsample size and particle size reduction prior to subsampling of soils. Increasing the subsample size from 2 to 50 g did not reduce the soil subsampling error because of the extreme heterogeneous distribution of the solid contaminants. Alternatively, particle size reduction by machine grinding on a ring mill reduced subsampling error to less than 10% relative standard deviation for replicate analyses using 10-g subsamples.     

Persistence models for mark-recapture

The stable of models available for analyzing mark-recapture data (Otis et al. Wild Momogr 66:135, 1978) includes those having behavioral characteristics, time variation, heterogeneity, along with combinations of those characteristics. This paper proposes use of a series of models based on the persistence model of Ramsey and Usner (Biometrics 59:331–339, 2003). We show that persistence can be modeled in combination with behavior and with time variation. We apply the persistence model to situations in which capture occasions are not equally-spaced in time. Two case studies illustrate the use of these extended persistence models.     

Chemical speciation and bioaccessibility of lead in surface soil and house dust,Lavrion urban area,Attiki, Hellas

In the Lavrion urban area study, Hellas, a five-step sequential extraction method was applied on samples of ‘soil’ (n = 224), affected by long-term mining and metallurgical activities, and house dust (n = 127), for the purpose of studying the potential bioaccessibility of lead and other metals to humans. In this paper, the Pb concentrations in soil and house dust samples are discussed, together with those in rocks and children’s blood. Lead is mainly associated with the carbonate, Fe–Mn oxides and residual fractions in soil and house dust. Considering the very low pH of gastric fluids (1–3), a high amount of metals, present in soil (810–152,000 mg/kg Pb) and house dust (418–18,600 mg/kg Pb), could be potentially bioaccessible. Consequently, children in the neighbourhoods with a large amount of metallurgical processing wastes have high blood-Pb concentrations (5.98–60.49 μg/100 ml; median 17.83 μg/100 ml; n = 235). It is concluded that the Lavrion urban and sub-urban environment is extremely hazardous to human health, and the Hellenic State authorities should urgently tackle this health-related hazard in order to improve the living conditions of local residents.     

Coastal Flood Inundation Monitoring with Satellite C‐band and L‐band Synthetic Aperture Radar Data

Satellite Synthetic Aperture Radar (SAR) was evaluated as a method to operationally monitor the occurrence and distribution of storm‐ and tidal‐related flooding of spatially extensive coastal marshes within the north‐central Gulf of Mexico. Maps representing the occurrence of marsh surface inundation were created from available Advanced Land Observation Satellite (ALOS) Phased Array type L‐Band SAR (PALSAR) (L‐band) (21 scenes with HH polarizations in Wide Beam [100 m]) data and Environmental Satellite (ENVISAT) Advanced SAR (ASAR) (C‐band) data (24 scenes with VV and HH polarizations in Wide Swath [150 m]) during 2006‐2009 covering 500 km of the Louisiana coastal zone. Mapping was primarily based on a decrease in backscatter between reference and target scenes, and as an extension of previous studies, the flood inundation mapping performance was assessed by the degree of correspondence between inundation mapping and inland water levels. Both PALSAR‐ and ASAR‐based mapping at times were based on suboptimal reference scenes; however, ASAR performance seemed more sensitive to reference‐scene quality and other types of scene variability. Related to water depth, PALSAR and ASAR mapping accuracies tended to be lower when water depths were shallow and increased as water levels decreased below or increased above the ground surface, but this pattern was more pronounced with ASAR. Overall, PALSAR‐based inundation accuracies averaged 84% (n = 160), while ASAR‐based mapping accuracies averaged 62% (n = 245).     

The National Vegetation Classification Standard applied to the remote sensing classification of two semiarid environments

The National Vegetation Classification Standard (NVCS) was implemented at two US National Park Service (NPS) sites in Texas, the Padre Island National Seashore (PINS) and the Lake Meredith National Recreation Area (LMNRA), to provide information for NPS oil and gas management plans. Because NVCS landcover classifications did not exist for these two areas prior to this study, we created landcover classes, through intensive ground and aerial reconnaissance, that characterized the general landscape features and at the same time complied with NVCS guidelines. The created landcover classes were useful for the resource management and were conducive to classification with optical remote sensing systems, such as the Landsat Thematic Mapper (TM). In the LMNRA, topographic elevation data were added to the TM data to reduce confusion between cliff, high plains, and forest classes. Classification accuracies (kappa statistics) of 89.9% (0.89) and 88.2% (0.87) in PINS and LMNRA, respectively, verified that the two NPS landholdings were adequately mapped with TM data. Improved sensor systems with higher spectral and spatial resolutions will ultimately refine the broad classes defined in this classification; however, the landcover classifications created in this study have already provided valuable information for the management of both NPS lands. Habitat information provided by the classifications has aided in the placement of inventory and monitoring plots, has assisted oil and gas operators by providing information on sensitive habitats, and has allowed park managers to better use resources when fighting wildland fires and in protecting visitors and the infrastructure of NPS lands.