A computational study of particulate emissions from Old Moor Quarry, UK

Joseph, G.M.D.; Lowndes, I.S.; Hargreaves, D.M.

Abstract

This paper presents an evaluation of a buoyancy-modified k--e dust dispersion model for predicting fugitive dust deposition from a surface quarry. The dust clouds are modelled as volumetric emissions and their dispersion simulated by coupling the flow-field with stochastic tracking of the particulates. The coefficients of the turbulence model are modified and source terms are added to the turbulence equations to permit simulation of both adiabatic and diabatic atmospheric stability conditions. These modifications ensure compatibility with Monin-Obukhuv similarity scaling of the atmospheric surface layer. Also, mesoscale wind direction variability is included. The Monin-Obukhuv scaling parameters have been derived from routine meteorological data recorded during a month-long monitoring campaign conducted at the quarry. Dust deposition measurements from a network of Frisbee deposition gauges are used to validate the predictions of the CFD model. A number of statistical performance metrics have been applied to evaluate the degree of uncertainty in the predictions. The dust deposition predictions of the CFD model are compared to those of the UK-ADMS, to demonstrate how the treatment of the terrain in the CFD model improves the accuracy of the deposition predictions.

Citation

Joseph, G., Lowndes, I., & Hargreaves, D. (2018). A computational study of particulate emissions from Old Moor Quarry, UK. Journal of Wind Engineering and Industrial Aerodynamics, 172, 68-84. https://doi.org/10.1016/j.jweia.2017.10.018

• Journal Article Type: Article
• Acceptance Date: Oct 17, 2017
• Online Publication Date: Nov 15, 2017
• Publication Date: Jan 31, 2018
• Deposit Date: Jan 17, 2019
• Publicly Available Date: Jan 17, 2019
• Journal: Journal of Wind Engineering and Industrial Aerodynamics
• Print ISSN: 0167-6105
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 172
• Pages: 68-84
• DOI: https://doi.org/10.1016/j.jweia.2017.10.018
• Keywords: Mechanical Engineering; Renewable Energy, Sustainability and the Environment; Civil and Structural Engineering
• Public URL: https://nottingham-repository.worktribe.com/output/1479308
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S0167610517304944?via%3Dihub