Permeable reactive barriers (PRBs) have shown great promise as an alternative to pump and treat for the remediation of groundwater containing a wide array of contaminants including organics, metals, and radionuclides. Analyses to date have focused on individual case studies, rather than considering broad performance issues. In response to this need, this study analyzed data from field installations of in situ zerovalent iron (ZVI) PRBs to determine what parameters contribute to PRB failure. Although emphasis has been placed on losses of reactivity and permeability, imperfect hydraulic characterization was the most common cause of the few PRB failures reported in the literature. Graphical and statistical analyses suggested that internal E H , influent pH, and influent concentrations of alkalinity, NO 3 Ϫ and Cl Ϫ are likely to be the strongest predictors of PRBs that could be at risk for diminished performance. Parameters often cited in the literature such as saturation indices, dissolved oxygen, and total dissolved solids did not seem to have much predictive capability. Because of the relationship between the predictive parameters and corrosion inhibition, it appears that reactivity of the ZVI, rather than the reduction in permeability, is more likely the factor that limits PRB longevity in the field. Due to the sparseness of field monitoring of parameters such as E H , the data available for these analyses were limited. Consequently, these results need to be corroborated as additional measurements become available.

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Quantitative descriptions of two‐phase flow in the subsurface require knowledge of the capillary pressure‐saturation relationships. The effect of interfacial forces on the drainage capillary pressure‐saturation relationship for organic liquid‐water systems is usually expressed by the ratio of the liquid‐liquid interfacial tensions as given by Leverett's (1941) function. To assess the appropriateness of this approach for primary drainage of organic liquid‐water systems typical of hazardous waste sites and to evaluate its extendability to spontaneous imbibition, measurements were made of these relationships for various immiscible liquid systems in unconsolidated sand. The results showed increasing deviations with decreasing interfacial forces between the measured values and those predicted by a ratio of interfacial tensions. To improve the predictive capability of Leverett's function, forms including the intrinsic contact angle and roughness were examined. Scaling of the capillary pressure relationships was best achieved by including a correction for both interface curvature and roughness. These corrections became significant for drainage for contact angles larger than 35°–55°, and for imbibition for contact angles larger than 15°–25°. None of the forms of Leverett's function examined predicted the increased residual saturation with decreasing interfacial forces observed in this study. Consequently, their ability to scale the measured data was predicated on posing the saturation of the wetting phase in terms of the variable effective saturation.

The reverse KM estimator is recommended for estimation of the distribution function and population percentiles in preference to commonly used methods such as substituting LOD/2 or LOD/ radical2 for values below the LOD, assuming a known parametric distribution, or using imputation to replace the left-censored values.

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Many studies of transport through soil assume that the laboratory columns used in the experiments are packed homogeneously. This research evaluated a variety of dry and wet packing techniques for their ability to produce uniform packings of clean sands without the use of specialized equipment. The best dry packing technique consisted of the deposition of 0.2‐cm layers followed by compaction with a metal pestle. For the sand used in this study, this technique resulted in a porosity of 0.325 ± 0.0020. The best wet packing technique consisted of the deposition of thin layers of saturated sand into water while vibrating the column. This technique resulted in a denser and more uniform packing, with the porosity equaling 0.315 ± 0.0018. No significant lateral particle‐size segregation was observed for either technique. Despite their success in producing homogeneous columns, the techniques proved time consuming, taking about 1 h per 5 cm of packed depth to pack a 15‐cm square column.

BackgroundWe conducted a population-based human exposure study in response to concerns among the population of Midland and Saginaw counties, Michigan, that discharges by the Dow Chemical Company of dioxin-like compounds into the nearby river and air had led to an increase in residents’ body burdens of polychlorinated dibenzofurans (PCDDs), polychlorinated dibenzofurans (PCDFs), and dioxin-like polychlorinated biphenyls (PCBs), here collectively referred to as “dioxins.”ObjectivesWe sought to identify factors that explained variation in serum dioxin concentrations among the residents of Midland and Saginaw counties. Exposures to dioxins in soil, river sediments, household dust, historic emissions, and contaminated fish and game were of primary interest.MethodsWe studied 946 people in four populations in the contaminated area and in a referent population, by interview and by collection of serum, household dust, and residential soil. Linear regression was used to identify factors associated with serum dioxins.ResultsDemographic factors explained a large proportion of variation in serum dioxin concentrations. Historic exposures before 1980, including living in the Midland/Saginaw area, hunting and fishing in the contaminated areas, and working at Dow, contributed to serum dioxin levels. Exposures since 1980 in Midland and Saginaw counties contributed little to serum dioxins.ConclusionsThis study provides valuable insights into the relationships between serum dioxins and environmental factors, age, sex, body mass index, smoking, and breast-feeding. These factors together explain a substantial proportion of the variation in serum dioxin concentrations in the general population. Historic exposures to environmental contamination appeared to be of greater importance than recent exposures for dioxins.

Deposition of pollutants around point sources of contamination, such as incinerators, can display complex spatial patterns depending on prevailing weather conditions, the local topography and the characteristics of the source. Deterministic dispersion models often fail to capture the complexity observed in the field, resulting in uncertain predictions that might hamper subsequent decisionmaking, such as delineation of areas targeted for additional sampling or remediation. This paper describes a geostatistical simulation-based methodology that combines the detailed process-based modeling of atmospheric deposition from an incinerator with the probabilistic modeling of residual variability of field samples. The approach is used to delineate areas with high level of dioxin TEQ DF -WHO 98 (Toxic Equivalents) around an incinerator, accounting for 53 field data and the output of the EPA Industrial Source Complex (ISC3) dispersion model. The dispersion model explains 43.7% of the variance in soil TEQ data, while the regression residuals are spatially correlated with a range of 776 meters. One hundred realizations of soil TEQ values are simulated on a grid with a 50 meter spacing. The benefit of stochastic simulation over spatial interpolation is twofold: 1) maps of simulated point TEQ values can easily be aggregated to the geography that is the most relevant for decision making (e.g. census block, ZIP codes); and 2) the uncertainty at the larger scale is simply modeled by the empirical distribution of block-averaged simulated values. Incorporating the output of the atmospheric deposition model as spatial trend yields a more realistic prediction of the spatial distribution of TEQ value than lognormal kriging using only the field data, in particular in sparsely sampled areas away from the incinerator. The geostatistical model provided guidance for the study design (census block-based population sampling) of the University of Michigan Dioxin Exposure Study (UMDES), focused on quantifying exposure pathways to dioxins from industrial sources, relative to background exposures. *Corresponding author phone: 734-913-1098; fax: 734-913-2201; e-mail: goovaerts@biomedware.com. Corresponding author address: BioMedware Inc, 516 North State Street Ann Arbor, MI 48104 (USA). Brief This paper describes a geostatistical simulation-based methodology that combines the detailed process-based modeling of atmospheric deposition from an incinerator with the probabilistic modeling of residual field variability.