The disposal of industrial and mineral processing residues represents a major concern for human health and the environment as a whole. In order to reduce the impact on soil and groundwater due to the waste leachability, the implementation of environmental regulations worldwide has favored the conversion of the disposal techniques from wet to dry (i.e., dry stacking or dry disposal). Such a change in the storage practice may cause the increase of particulate matter (PM) emission from the dry surfaces of the tailings exposed to wind erosion. Considering the significance of the environmental issue on a global scale and the increasingly stricter orientation of environmental policies, the need for modeling tools capable of estimating the contribution of tailing basins to air pollution becomes apparent. The paper deals with the disposal of red mud resulting from the bauxite processing in the alumina industry. An experimental research was carried with an environmental wind tunnel to estimate the Emission Factor (EF) of the basin surfaces as a function of the main affecting variables (i.e., residue water content and wind velocity). The article reports the results of the experimental test carried out on the red mud from a major basin located in Sardinia (Italy).
A physical-mathematical model has been designed to estimate the emission of dust from the surface of granular materials exposed to wind erosion. The emission model implements the Monte Carlo probabilistic approach, which for a given wind velocity (i.e., shear stress velocity) ascribes the probability of saltation to the particle aggregates composing the erodible surface and calculates the emission of dust aerosol based on the main laws governing the physics of wind-blown particles. The article discusses the application of the emission code to the surfaces of two metal sulphides (PbS and ZnS), which are typically stored in stockpiles in the open yards of industrial plants that operate in the commodity sector, to be used as raw materials for the production of lead and zinc (non-ferrous metals). The results of the simulation were found to be in agreement with the indication provided by the technical literature about the emission potential of the two metal sulphides. The emission model hereby proposed intends to provide an analytical integration to the experimental and empirical Emission Factors (EF) already suggested by the technical and scientific literature about industrial wind erosion.
The article describes an original conceptual model that intends to explain the emission mechanism of Particulate Matter from the surfaces of tailing basins exposed to wind erosion. In order to estimate the site-specific parameters of the Emission Factors in the proposed model, the reproduction of the wind flow acting over the erodible surfaces becomes essential. Based on the parameters determined on site and assumed as project objectives, an Environmental Wind Tunnel has been designed to generate a part-depth Atmospheric Boundary Layer (ABL). The measurements performed in the tunnel proved the simulated wind profiles to be representative of the required ABL.
Numerical simulations of the wind flow around isolated stockpiles of bulk material are performed to assess the emission potential (P) of particulate matter (PM) from the pile surfaces exposed to wind erosion (i.e., industrial wind erosion). The analysis is focused on two metal sulphides (lead and zinc sulphides), which are typically stored in the open yards of industrial plants that operate in the commodity sector for the production of non-ferrous metals. The EPA methodology is applied to the numerical simulated flow fields to quantify the effect of the wind stress over the erodible surfaces of the two ores. Two alternative open bay geometries and different volumes of material stocked within the enclosing walls are considered. Moreover, the protective effect of the walls is assessed by comparing the same pile configurations without walls. This is found to be highly dependent on the wind direction, as well as to the pile configuration. A methodology that can be easily customized to specific industrial sites is proposed to define the best storage configuration for PM emission prevention and control.
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