Investigating the Efficacy of Water-sprinkling as a Fugitive Dust Mitigation Strategy using the Terrestrial Laser Scanning (TLS) Technique.

Damilare Immanuel Ogungbemide, Trent University, Environmental & Life Sciences Program, Peterborough, ON, Canada, Cheryl McKenna Neuman, Trent University, Geography, Peterborough, ON, Canada and Joanna M Nield, University of Southampton, School of Geography and Environmental Sciences, Southampton, United Kingdom

Contact First Author: Damilare Immanuel Ogungbemide; dogungbemide@trentu.ca

Previously Published Material: A part of this presentation was previously reported (poster presentation) at the Latornell Conference (Nov. 18-20) 2014 in Alliston, Ontario.

Abstract ID#: 35990

 

English Abstract:
Water-sprinkling is one of the most widely used dust mitigation strategies in the mining industry. It increases surface moisture, which in turn increases the threshold shear velocity necessary for particle entrainment, thus reducing the prevalence of dust emission. However, this moisture-induced resistance only lasts for a finite amount of time. It is therefore pertinent for the operators of a mining site to understand the spatio-temporal variability in the moisture content of a surface after the application of water. Indeed, effective monitoring of surface moisture is essential to developing an optimum water-sprinkling schedule.

While there are several methods for measuring moisture content, the Terrestrial Laser Scanning (TLS) technique offers several potential advantages, such as tremendous time-saving and non-invasiveness, over the conventional methods, especially when a large area is to be monitored over a relatively short period of time. This study was therefore designed to investigate, using the TLS technique, the efficacy of water-sprinkling on a system of tailings ponds located in Southern Ontario by monitoring the temporal surface drying of the tailings immediately after water application. The entire study area was scanned using a Leica® Scanstation C10 repeatedly for a total of 30 consecutive times, over a 5-hour period, as the surface dried out under ambient environmental conditions. The raw intensity values obtained by the TLS scanner, [in addition to 3D point-cloud spatial metrics (x, y, z coordinates)], were converted to standard intensity ratios, and further converted to surface moisture content through calibrations from controlled experiments. It is hoped that the generated models can be applied to other potential dust-emitting surfaces to provide a quick and accurate estimate of their moisture content.