Abstract. Several relationships exist for predicting unsaturated hydraulic conductivity K(½) from saturated hydraulic conductivity Ks and the soil-water retention curve. These relationships are convenient for modeling of field scale system sensitivity to spatial variability in K(½). It is, however, faster and simpler to measure air permeability ka at •t = -100 cm H20 , than Ks. This study explores the existence of a general prediction relationship between ka, measured at -100 cm H20 , and Ks. Comparative analyses between k a-Ks relationships for nine Danish and Norwegian soils, six different soil treatments, and three horizons validated the establishment of a soil type, soil treatment, and depth/horizon independent log-log linear k a-Ks relationship. The general k a-Ks relationship is based on data from a total of 1614 undisturbed, 100-cm ø core samples and displays general prediction accuracy better than _+0.7 orders of magnitude. The accuracy and usefulness of the general relationship was evaluated through stochastic analyses of field scale infiltration and ponding during a rainstorm event. These analyses showed possible prediction bias associated with the general k a-Ks relationship, but also revealed that sampling uncertainty associated with estimation of field scale variability in Ks from a, limited number of samples could easily be larger than the possible prediction bias.

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Our understanding of vapor intrusion has evolved rapidly since the discovery of the first high profile vapor intrusion sites in the late 1990s and early 2000s. Research efforts and field investigations have improved our understanding of vapor intrusion processes including the role of preferential pathways and natural barriers to vapor intrusion. This review paper addresses recent developments in the regulatory framework and conceptual model for vapor intrusion. In addition, a number of innovative investigation methods are discussed.

Bench testing of petroleum biodegradation rates in vadose zone soils is typically associated with errors because transport conditions in laboratory systems are different from those found in the vadose zone. This work addressed the effect of soil structure and gas transport properties on hydrocarbon biodegradation in the unsaturated zone and we present a novel method for measuring biodegradation rates in intact and undisturbed soil columns of 100 cm3. To determine whether soil structure and gas diffusivity, defined as the ratio of the gas diffusion coefficient in soil to that in free air (Dp/D0), influence the outcome of aerobic benzene biodegradation experiments, measurements using identical sandy soils were performed on (i) undisturbed 100‐cm3 core samples; (ii) sieved (2‐mm) and repacked 100‐cm3 core samples; and (iii) soil samples (10 g) prepared as slurry microcosms. While slurry reactor experiments changed the first‐order rate constant (kw,1) significantly compared with undisturbed core samples, this was not the case for soil cores that had been sieved and repacked. This suggests that soil structure on a millimeter scale does not affect aerobic biodegradation in relatively unstructured sandy soils. Within differently textured soil cores, the biodegradation rate was found to increase with gas diffusivity when Dp/D0 < 0.02. This establishes gaseous O2 and petroleum vapor diffusion and distribution in soil profiles as a controlling factor for natural biodegradation of petroleum vapors.

Abstract:The time required at a field site to obtain a few measurements of saturated hydraulic conductivity (K s ) will allow for many measurements of soil air permeability (k a ). This study investigates if k a measured in situ (k a,in situ ) can be a substitute for measurement of K s in relation to infiltration and surface runoff modelling. Measurements of k a,in situ were carried out in two small agricultural catchments. A spatial correlation of the log-transformed values existed having a range of approximately 100 m. A predictive relationship between K s and k a measured on 100-cm 3 soil samples in the laboratory was derived for one of the field slopes and showed good agreement with an earlier suggested predictive K s -k a relationship. In situ measurements of K s and k a suggested that the predictive relationships also could be used at larger scale. The K s -k a relationships together with the k a,in situ data were applied in a distributed surface runoff (DSR) model, simulating a high-intensity rainfall event. The DSR simulation results were highly dependent on whether the geometric average of k a,in situ or kriged values of k a,in situ was used as model input. When increasing the resolution of K s in the DSR model, a limit of 30-40 m was found for both field slopes. Below this limit, the simulated runoff and hydrograph peaks were independent of resolution scale. If only a few randomly chosen values of K s were used to represent the spatial variation within the field slope, very large deviations in repeated DSR simulation results were obtained, both with respect to peak height and hydrograph shape. In contrast, when using many predicted K s values based on a K s -k a relationship and measured k a,in situ data, the DSR model generally captured the correct hydrograph shape although simulations were sensitive to the chosen K s -k a relationship. As massive measurement efforts normally will be required to obtain a satisfactory representation of the spatial variability in K s , the use of k a,in situ to assess spatial variability in K s appears a promising alternative.