Abstract
Ph.D. (Geography)
The focus of Aeolian research has mainly been on wind-blown dust from desert and arid areas. Numerous dust emission schemes have been developed over the years aimed at accurately estimating dust emission rates from various soil types and land use surfaces. Limited research has been done on wind-blown dust from smaller area sources – such as mine tailings and ash storage facilities. Lately, the concern about the environmental and health impacts, caused by dust from mine tailings storage facilities and ash disposal sites, has become more prominent, calling for better methods in determining dust emissions and their related impacts.
This thesis established a practical approach for wind-blown dust emissions estimation and dispersion modelling from mine waste and ash storage facilities for the purpose of legal compliance assessment. Extensive research on the physics of wind erosion has been done over the past decade, compelling the re-evaluation of previously applied techniques. The latest and most widely applied dust emission schemes are evaluated to determine, through systematic testing of parameterisation and validation, using empirical mine waste and coal ash data, a best-practice prescription for quantifying wind-blown dust emissions and determining effects on a local scale using commercially available dispersion models.
The applicability of two dust-flux schemes, (one developed by Marticorena and Bergametti (1995) and the simplified Shao 2004 scheme, as reported in 2011) for the quantification of wind-blown dust emissions, were tested using site specific particle size distribution data, bulk density and moisture content from six gold- and one platinum- tailings storage facilities and from two ash storage facilities. The availability of the required input parameters and the uncertainty associated with these parameters, were tested. The dependency of the Shao et al. (2011) model on plastic pressure (P) and the coefficient cy, both of which are not easily determined, added to the uncertainty of the emission rates. In this study, P and cy were both interpolated using the range limits provided by Shao (2004) for natural soils. By calculating P, using the salt and calcium carbonate content, similar values were obtained. The minimally disturbed dust fraction, as required by the Shao et al. (2011) scheme were derived from particle size distribution analysis but found to be more representative of the fully disturbed particle size faction (𝜂fi) and therefore needed to be corrected to represent the minimally disturbed particle size faction (𝜂mi) through the application of a correction factor, CF𝜂mi.
Specific attention was given to the quantification of the threshold friction velocity (u*t) and the threshold velocities (u*), and how these two parameters relate to each under variable wind speed and time durations. This was tested using sub-hourly averaged meteorological data, one set reflected 5-minute intervals and the other 10-minute intervals. Dependent on the frequency and
strength of the sub-hourly wind gusts, the resulting dust-flux rates were found to vary significantly when based on hourly averaged wind data in comparison with 5- and 10-minute wind data.
Dispersion models are useful tools in air quality management. Whereas ambient monitoring provides actual ambient concentrations for specific pollutants at set locations, atmospheric dispersion models can be used to simulate any number of pollutants and determine the impacts at any location within the modelling domain. These dust-flux schemes of Marticorena and Bergametti (1995) and Shao et al. (2011) have been coupled with the US EPA regulatory Gaussian plume AERMOD dispersion model for the simulation of ground level concentrations resulting from wind-blown dust from mine tailings facilities. For this study, two Case Studies were evaluated; one included two of the gold mine tailings and the second focused on the platinum tailings. Simulated ambient near surface concentrations were validated with ambient monitored data for the same period as used in the model.
For the Marticorena and Bergametti (1995) dust-flux scheme, only z0 had to be adjusted to provide a good fit with measured data – whereas the Shao et al. (2011) scheme resulted in significantly higher concentrations, resulting in an over-prediction of the measured data. By applying the correction factor, CF𝜂mi, to the minimally disturbed dust fraction, the predicted concentrations improved considerably.
The coupling of the dust-flux schemes with a regulatory Gaussian plume model provided simulated ground level PM10 concentrations in good agreement with measured data. The best correlation was found under conditions of high wind speeds when the prevailing wind was from the direction of the tailings storage facility.
This thesis demonstrates that simulated impacts from complex source groups can be performed, within an acceptable range of certainty, using widely applied dust-flux schemes. These dust-flux schemes, developed primarily for large-scale desert and arid areas, have been demonstrated to be applicable also to small-scale sources, of the order of 1 km2, and can be coupled to regularly available dispersion models for impact evaluations of wind-blown dust. The value of this improved approach to the mining and mineral processing industries are substantial, allowing for more accurate health risks and adverse environmental assessments from wind-blown dust from large material storage piles, a source category that has hitherto been difficult to quantify.