Cadmium leachability and microbial population dynamics in a stabilized and bioaugmented model contaminated soil

This article presents a laboratory study on the consequences of the application of combined soil stabilization and bioaugmentation in the remediation of a model contaminated soil. Stabilization and bioaugmentation are two techniques commonly applied independently for the remediation of heavy metal and organic contamination respectively. However, for a cocktail of contaminants combined treatments are currently being considered. The model soil was contaminated with a cocktail of organics and heavy metals based on the soil and contaminant conditions in a real contaminated site. The soil stabilization treatment was applied using either zeolite or green waste compost as additives and a commercially available hydrocarbon degrading microbial consortium was used for the bioaugmentation treatment. The effects of stabilization with or without bioaugmentation on the leachability of cadmium and copper was observed using an EU batch leaching test procedure and a flow-through column leaching test, both using deionized water at a pH of 5.6. In addition, the population of hydrocarbon degrading microorganisms was monitored using a modified plate count procedure in cases where bioaugmentation was applied. It was found that while the stabilization treatment reduced the metal leachability by up to 60%, the bioaugmentation treatment increased it by up to 100% Microbial survival was also higher in the stabilized soil samples.

Toward automated generation of parametric BIMs based on hybrid video and laser scanning data

Only very few constructed facilities today have a complete record of as-built information. Despite the growing use of Building Information Modelling and the improvement in as-built records, several more years will be required before guidelines that require as-built data modelling will be implemented for the majority of constructed facilities, and this will still not address the stock of existing buildings. A technical solution for scanning buildings and compiling Building Information Models is needed. However, this is a multidisciplinary problem, requiring expertise in scanning, computer vision and videogrammetry, machine learning, and parametric object modelling. This paper outlines the technical approach proposed by a consortium of researchers that has gathered to tackle the ambitious goal of automating as-built modelling as far as possible. The top level framework of the proposed solution is presented, and each process, input and output is explained, along with the steps needed to validate them. Preliminary experiments on the earlier stages (i.e. processes) of the framework proposed are conducted and results are shown; the work toward implementation of the remainder is ongoing.