Effect of microbial activities on the mobility of copper in stabilised contaminated soil

Stabilisation, using a wide range of binders including wastes, is most effective for heavy metal soil contamination. Bioremediation techniques, including bioaugmentation to enhance soil microbial population, are most effective for organic contaminants in the soil. For mixed contaminant scenarios a combination of these two techniques is currently being investigated. An essential issue in this combined remediation system is the effect of microbial processes on the leachability of the heavy metals. This paper considers the use of zeolite and compost as binder additives combined with bioaugmentation treatments and their effect on copper leachability in a model contaminated soil. Different leaching test conditions are considered including both NRA and TCLP batch leaching tests as well as flow-through column tests. Two flow rates are applied in the flow-through tests and the two leaching tests are compared. Recommendations are given as to the effectiveness of this combined remediation technique in the immobilisation of copper. © 2005 Taylor & Francis Group.

Predicting surface vibration from underground railways through inhomogeneous soil

Noise and vibration from underground railways is a major source of disturbance to inhabitants near subways. To help designers meet noise and vibration limits, numerical models are used to understand vibration propagation from these underground railways. However, the models commonly assume the ground is homogeneous and neglect to include local variability in the soil properties. Such simplifying assumptions add a level of uncertainty to the predictions which is not well understood. The goal of the current paper is to quantify the effect of soil inhomogeneity on surface vibration. The thin-layer method (TLM) is suggested as an efficient and accurate means of simulating vibration from underground railways in arbitrarily layered half-spaces. Stochastic variability of the soils elastic modulus is introduced using a KL expansion; the modulus is assumed to have a log-normal distribution and a modified exponential covariance kernel. The effect of horizontal soil variability is investigated by comparing the stochastic results for soils varied only in the vertical direction to soils with 2D variability. Results suggest that local soil inhomogeneity can significantly affect surface velocity predictions; 90 percent confidence intervals showing 8 dB averages and peak values up to 12 dB are computed. This is a significant source of uncertainty and should be considered when using predictions from models assuming homogeneous soil properties. Furthermore, the effect of horizontal variability of the elastic modulus on the confidence interval appears to be negligible. This suggests that only vertical variation needs to be taken into account when modelling ground vibration from underground railways. © 2012 Elsevier Ltd. All rights reserved.