C. Aldrich

Treatment of acid mine water by use of heavy metal precipitation and ion exchange

Abstract Acid mine water from a South African gold mine was characterised and treated by the precipitation of heavy metals with lime and sulphides, followed by ion exchange. The novelty of the proposed process lies in the use of carrier magnetic materials for more effective separation of water and solids, as well as the oxidation pretreatment that is also used to sterilize the water. The process can generate very, pure water from acid mine water with a great flexibility and an acceptable cost. The oxidation and precipitation of heavy metals with lime and subsequent sulphide-carrier magnetic separation appeared to be particularly suitable for the removal of heavy metal ions from the effluent of the particular gold mine that was investigated. The cation exchange resin IR120 can be used to reduce the salinity of the effluent of mine water after removal of heavy metals by precipitation. Low cost sulphuric acid can be used as the cation resin regenerator. The anion exchange resin A375 could reduce the anions (sulphate, chloride, bromide and fluoride) to acceptably low levels in the mine water after precipitation of heavy metals. A combination of sodium hydroxide and saturated lime solution can be used as the anion resin regenerator. A mixture of acidic gypsum from the cation elution section and alkaline gypsum from the anion elution section could generate high quality gypsum as byproduct, which could be sold as a valuable raw material to the gypsum industry, to offset process cost. Although these experiments were conducted on the acid mine water of a specific mine, the process could be extended to other mine waters contaminated with heavy metals and high salinities.

Adsorption of heavy metals by biomaterials derived from the marine alga Ecklonia maxima

Abstract The adsorption of heavy metals onto biomaterial derived from the marine alga Ecklonia maxima was investigated via batch experiments. The adsorption equilibria of Cu, Pb and Cd could be represented by Langmuir isotherms and the capacity of fresh alga for Cu, Pb and Cd was approximately 85–94, 227–243 and 83.5 mg/g dry alga, respectively. The rate of adsorption onto the marine alga was high. The alga particle size played an important role in the adsorption behaviour. The coarse alga particles had a higher adsorption capacity and slower adsorption kinetics and could be regenerated without significant loss of capacity. In contrast, the fine alga particles had a lower adsorption capacity and faster adsorption kinetics and could not be regenerated without significant loss of capacity. Comparison with a commercial resin indicated that the activated biomass derived from E. maxima could be used as an efficient biosorbent for the treatment of waste waters containing heavy metals.

Ex situ diesel contaminated soil washing with mechanical methods

Abstract Soil washing is a dynamic, physical process that cleans contaminated soil through transfer of the contaminant into a liquid stream. Three mechanical washing methods, i.e. jet reactor, attrition and ultrasonic washing were evaluated on a laboratory scale. The operating parameters for each washing process were investigated in detail and mechanisms are proposed for the observed effects. In a techno—economic comparison of the three methods, the jet reactor performed best, followed by ultrasonic and attrition washing. Experimental results suggested that a combination of the three washing techniques could yield residual diesel levels of less than 1000 mg/l for sand particles with an approximate size of 0.1 mm and an initial diesel content of 5%.

Removal of heavy metals from wastewater effluents by biosorptive flotation.

Abstract The search for new technologies to remove hazardous metals from wastewaters has focused attention on the metal binding abilities of different biological materials. Various biomaterials have shown promise as sorbents to remove heavy metals from water. Several advantages of peat moss for such applications include its abundance, low cost, and high metal capacity. Consequently, the adsorption of heavy metals from aqueous solution was studied using a sphagnum peat moss. The adsorption process was found to be pH dependent, and the adsorption capacity increased with initial pH of the solution. The sorption equilibria could be expressed as Freundlich isotherms. The selectivity of the sphagnum peat moss for various heavy metal cations was Pb > Ni > Cu > Cd. The sorption behaviour of cations on the sphagnum peat moss was similar to that of cations on a gel type strong acid resin. Flotation was subsequently shown to be an effective solid-liquid separation process, avoiding the problem for the separation offine sponge-like moss flocs from the effluent by conventional filtration. A dispersed air flotation column was applied for the generation of fine bubbles to realise the solid-liquid separation. Biosorptive flotation may have practical applications for the removal of hazardous metals from contaminated water supplies.

Removal of heavy metal ions by carrier magnetic separation of adsorptive particulates

Abstract The removal of Pb, Cu, and Cd ions from diluted solutions by sorption onto clinoptilolite, together with magnetite–Fe(OH) 3 coprecipitation and magnetic filtration, was studied at laboratory scale. Low concentrations of clinoptilolite fines were used as heavy metal ion sorbent, while low dosages of magnetite fines were used as magnetic carrier materials. In addition, hydrolyzed Fe 3+ was used as coagulant. The magnetic clinoptilolite–magnetite–Fe(OH) 3 aggregates were removed by magnetic filtration. Experimental results showed that the process was very rapid and effective and yielded clear solutions with low residual concentrations of heavy metals.

The adsorption of precious metals and base metals on a quaternary ammonium group ion exchange resin

Abstract Adsorption tests were conducted with a quaternary ammonium group ion exchange resin to determine the equilibrium adsorption of precious- and base metals. The resin used is a macroreticular polystyrene type 1 strong base anion exchange resin. The adsorption was determined for synthetic single metal solutions as well as for multi-component solutions. The effect of the Cl − concentration on the equilibrium adsorption was determined for three different HCl concentrations, i. e. 6, 8 and 10%. The effect of chloride strength in the solution was also determined for mixed and base metal solutions. Pure metals, i.e. platinum, palladium and gold, were dissolved in aqua-regia and diluted to 2000 ppm (as metal) in 4M HCl. Ruthenium, rhodium and iridium were dissolved from pure salts in HCl. A 2000 ppm base-metal solution was prepared by dissolving all the required components, including precious metals, to match an in-plant industrial base-metals solution composition. For each precious metal the equilibrium adsorption was determined for typically two solution concentrations. Data points were established by varying the amount of resin added to the solution. The equilibrium concentrations were determined by ICP analysis after 24 hours exposure using the bottle-roll technique.

The effect of mothers on bubble size distributions in flotation pulp phases and surface froths

Abstract Froth dynamics, i.e. the stability and mobility of the froth, are crucial indicators of various important features of flotation systems. For example, it is desirable that the froth collapses as soon as possible after it is skimmed off the cell in order to curtail losses in throughput. On the other hand, if the froth is too prone to collapse, it will not be sufficiently stable to support its load prior to skimming. Likewise, the mobility of the froth gives similar information on the performance of the flotation cell. For example, a sharp contrast can be observed between dry viscous (immobile) froths and watery runny froths with high mobility. Several authors have recently shown that analysis of the structure of the froth in a flotation cell can be used to assess the performance of the cell. This implies that there is a close relationship between the bubble size distribution in the pulp and froth phases. Until very recently, it was not possible to verify this hypothesis direct, since reliable measurements of bubble size distributions in especially the froth phase could not be obtained. With recent improvements in the machine vision technology originally developed at the University of Stellenbosch, it is now possible to measure bubble size distributions and stability in froth structure with a high degree of accuracy. Unlike previous methods, these improved algorithms can provide a detailed map of flow patterns in the froths, which can give a significantly better idea of operating conditions in the flotation cell. Consequently, in this experimental study the bubble size distribution in the pulp phase of a laboratory flotation cell was measurement with a capillary tube system (UCT bubble size analyser), while the bubble size distribution in the froth phase was measured by use of digital image analysis. The relationship between these bubble size distributions in the pulp and froth phases is discussed.

Analysis of ore particles based on textural pattern recognition

Abstract Changes in mill feed conditions such as particle size distribution and ore type have a significant impact on grinding performance, but are process variables that have remained largely unexploited in control and optimisation strategies. This study documents the development of a machine vision strategy used to characterise particle features in ore feed systems. In contrast to algorithm based methods which explicitly target individual particle recognition, this paper explores a textural approach, viz. variance and range textural operators for ore type characterisation and surface particle size estimation. Promising preliminary results were obtained for mean particle size predictions on an industrial mill feeder.

Process system identification strategies based on the use of singular spectrum analysis

Abstract With increased emphasis on plant automation and the implementation of advanced process control systems in the mineral processing industries, the need for accurate process models has become greater than ever. These models are often developed or identified from historic process data, as the process systems may be too complex to model from first principles. Under these circumstances, identification can be a challenging task and in the process industries the problem is complicated considerably by the presence of noise from various sources, nonstationarity of the data and intermittence, such as observed in particulate flows. To complicate matters, it may not be possible to build satisfactory models with the aid of traditional methods, such as frequency analysis and linear modelling either. Similar problems arise with the application of nonlinear theory developed over the last few decades, where much of the analysis depends on embedding of the data in a phase space or pseudophase space, since these methods were not originally designed to deal with noisy systems. In contrast, most of these disadvantages can be surmounted by use of singular spectrum analysis. It allows the time series to be decomposed into different components, e.g. the underlying signal itself, as well as various noise components, which can subsequently be removed from the data. As is shown in this paper, removal of the minor components of the data can lead to significant improvement in the identification of the system. Four strategies are considered, viz. system identification with models fitted to the original data, models fitted to the smoothed data, an assembly of models fitted to the components of the time series and smoothing of the data based on multivariate embedding of time series.

Neural net analysis of the liberation of gold using diagnostic leaching data

Abstract The interrelationship between mineral liberation and leaching behaviour of a gold ore is ill defined, mainly due to the complexity of both leaching and mineral liberation. A better understanding of this relationship could result in lower operating costs on gold extraction plants, since an increase in the efficiency of gold dissolution and a decrease in costs related to the crushing and grinding operations could be expected. In this investigation artificial neural nets were used to analyse diagnostic leaching data of gold ores obtained from South African gold mines. A self-organising neural net with a Kohonen layer was used to generate order preserving topological maps of the characteristics of both the unmilled and milled ores. The arrangement and shapes of these clusters could then be used to develop simple neural net models which were capable of predicting the degree of liberation more accurately than previously proposed models. Moreover, the neural net models were also capable of providing direct estimates of the reliability of their predictions by comparing new inputs with the data in their training bases.