Application of artificial neural networks for classification of uranium distribution in the Central Rand goldfield,South Africa

Mine tailings generate significant environmental impacts and contribute to water pollution. The Central Rand goldfield, South Africa is replete with gold mine tailings which have contributed significantly to water pollution as a result of acid mine drainage (AMD). Water quality is affected by mine tailings and spillages, especially from active slimes dams, currently reprocessed tailings, as well as footprints left behind after reprocessing. The release and distribution of uranium from these sites was studied. Correlation matrices show a strong link between different variables as a result of AMD produced. Principal component analysis (PCA) was used to identify very influential variables which account for the pollution trends. Artificial neural networks (ANN) using the Kohonen algorithm were applied to visualise these trends and patterns in the distribution of uranium. High concentrations of this radionuclide were detected in streams in the vicinity of the tailings dumps, active slimes and reprocessing areas. The concentrations are reduced drastically in dams and wetlands as a result of precipitation and dilution effects.     

Adsorption and desorption of tetraalkyllead and dibutyltin compounds on contaminated soils

Adsorption and desorption of di-n-butyltin (IV) (DBT), tetramethyllead (TML), and tetraethyllead (TEL) on four types of soil were studied. Although, all K _d values for desorption are higher than the K _d values for adsorptions, which shows that the adsorption process is reversible, the lower percentages of desorption indicate that very low concentration of these organometallic compounds can be more easily leached from the soil. The adsorption ranging between 48.8% and 88.3% for DBT, between 9.1% and 38.3% for TEL, and between 24.9% and 44.2% for TML was measured. The desorption was obtained between 9.4% and 23.7% for DBT, between 19.3% and 38.9% for TEL, and between 21.5% and 32.7% for TML. These results show that the nonpolar (TML, TEL) organometallic compounds can be easier leached than the ionic forms (DBT). Adsorption kinetics and adsorption as a function of pH were also evaluated. DBT and tetraalkyllead adsorption equilibrium were reached after 12 and 24 h, respectively. The tetraalkyllead is strongly adsorbed at pH 7–8 and DBT at pH 6.     

Evaluation of the performance of rural wastewater treatment plants using chemical measurements in combination with statistical techniques: a case study

The performance of a wastewater treatment plant was assessed statistically using multivariate cluster and principle component analysis. This was after measuring some physico-chemical properties in the influent, effluent, downstream, and upstream waters over a 4-month period. The cluster analysis grouped the sampling sites into three clusters: relatively non-polluted (upstream), medium polluted (downstream), and polluted (influent and effluent). The polluted water was further subdivided into very highly (influent) and highly (effluent) polluted. The grouping of influent and effluent into one cluster was due to some water quality parameters such as amount of copper, lead, and phosphates that are not efficiently removed by the plant. Using principal component analysis, samples from the same site taken over a period of 4 months were scattered, indicating inconsistencies in the performance of the plant. This was more pronounced during the rainy season, suggesting that increased water volumes from open sewers make the already poorly performing plant worse. The major loading factors found by principle component analysis were phosphate, lead, iron, zinc, copper, pH, and conductivity. Generally, the wastewater treatment system was found to be efficient in removing heavy metals and these were found in the sludge, but not anions. The mean percentage metal removal could be arranged in the following decreasing order: iron (85%)?>?zinc (57%)?>?copper (40%) and lead (38%) following the concentrations (mg?kg^?1) found in the sludge: iron (11,300)?>?zinc (820)?>?copper (180)?>?lead (20)?>?cadmium (3). Phosphate and iron concentrations in the effluent were found to be above the South African Bureau of Standards (SABS) recommendations. The major cause of poor performance is the high volume of the wastewater, exceeding the capacity of the plant 10 times.     

Adsorptive removal of mercury from acid mine drainage: a comparison of silica and maghemite nanoparticles

Mercury adsorption by silica and maghemite nanoparticles (NPs) was studied with the aim of comparing their performance in the remediation of acid mine drainage (AMD) contaminated water. Calculated distribution coefficients (K_d) showed that both NPs are exceptional adsorbents. However, adsorbate coverage per unit area was 30 times higher for maghemite than for silica NPs, despite the latter having a surface area ～15 times greater. Maghemite adsorbed 75% of available Hg compared to 56% by silica, making it a more efficient sorbent than silica under AMD conditions. Kinetics and isotherm data for both adsorbents were fitted by the pseudo-second-order (R² = 1) and the Freundlich (R² ≥ 0.98) models, implying that adsorption to both NP types was by chemisorption. Adsorption increased with NP concentrations and pH and was enhanced in the presence of manganese and sulfate ions although adsorption to silica was inhibited in 1:2 Hg-to-Mn systems. Importantly, trends in simulated wastewater were replicated in actual AMD-contaminated water samples. This study highlights the fact that properties besides surface area and charge of adsorbents determine adsorbent performance, and superior attributes may not always lead to higher adsorption efficiencies.     

Speciation of mercury in South African coals

Total mercury (Hg_TOT) concentrations were determined by inductively coupled plasma mass spectrometry (ICP MS) for South African Highveld coals. The distribution of Hg in coals was investigated using a four-stage sequential leaching protocol and isotope dilution/gas chromatography coupled to ICP MS (ID-GC-ICP MS). The results show that Hg_TOT ranged from 144 to 303?µg?kg^?1 with a mean of 199?±?26?µg?kg^?1, while Hg_TOT leached from coals using different solvents ranged between 103 and 310?µg?kg^?1 (mean: 218?±?60?µg?kg^?1). Hg leaching rates of 53–78% were achieved in crushed coals. Hg⁰, Hg²⁺, and CH₃Hg⁺ were identified in all coals. CH₃Hg⁺ in studied coals ranged between 0.1 and 0.4 (mean: 0.2) µg?kg^?1. GC ICP MS chromatograms also showed unknown Hg peaks which were identified as other organomercury species such as ethylmercury. Modes of occurrence of Hg in coals were variable with the organic-bound (37–40%) and the sulfide-bound (37–39%) being the dominant mercury forms. Increasing the HCl concentration in the used protocol increased the amount of Hg leached (16%) during this step.     

Application of magnesite–bentonite clay composite as an alternative technology for removal of arsenic from industrial effluents

This study evaluated the feasibility of integrating amorphous magnesite and bentonite clay (composite) as an alternative technology for removing arsenic from industrial effluents. The removal of arsenic from industrial effluents by using magnesite–bentonite clay composite was carried out in batch mode. The effects of equilibration time, adsorbent dosage, adsorbate concentration, and pH on removal of arsenic were investigated. The experiments demonstrated that ≈100% arsenic removal is optimum at 30 minutes of agitation, 2 g of adsorbent dosage (2 g: 100 mL, S/L ratio), and 20 mg L^?1 of arsenic concentration. The adsorption data fitted well to both Langmuir and Freundlich adsorption models, hence proving monolayer and multilayer adsorption. The kinetic studies revealed that the data fitted better to a pseudo-second-order reaction than to a pseudo-first-order reaction, hence proving chemisorption. At optimized conditions, the composite was able to remove arsenic to below World Health Organization water quality guidelines, hence depicting that the composite is effective and efficient in removing arsenic from contaminated water. Based on that, this comparative study proves that the composite is a promising adsorbent with high adsorption capacity for arsenic and can be a suitable substitute for the conventional treatment methods.     

Sulfonated cross-linked polyethylenimine for selective removal of mercury from aqueous solutions

Polymeric materials are among the most promising, effective, and increasingly important adsorbents for the removal of toxic metals from wastewater. This study was dedicated to the development of an insoluble, modified chelating polymer for use as an adsorbent for abstraction of Hg from aqueous solutions. Cross-linked polyethylenimine (CPEI) was sulfonated by 3-chloropropanesulfonyl chloride for selective removal of Hg. The binding affinity of the sulfonated CPEI (SCPEI) to Hg was assessed as well as its ability to be regenerated for reuse. It exhibited high removal percentage for Hg up to 87% in synthetic solutions, with high selectivity even in the presence of competing ions: “Mn, Ni, Fe, Pb, Zn, and Cr.” The removal mechanism followed was observed to be adsorption and precipitation at pH 3 and 8, respectively. High adsorption capacities were also observed for wastewater to which the polymer was applied. The Freundlich isotherm was found to be the best fit describing the adsorption process of Hg onto the SCPEI. The pseudo second-order equation was found to better explain the adsorption kinetics, implying chemisorption. The thermodynamic study of the adsorption revealed high activation energies which confirmed the chemisorption as the mechanism of adsorption. The polymer exhibited up to 72% removal efficiency after regeneration, thus showing potential for re-use.     

Development and application of microwave assisted extraction (MAE) for the extraction of five polycyclic aromatic hydrocarbons in sediment samples in Johannesburg area, South Africa

A microwave-assisted extraction (MAE) method was verified and applied for the extraction of polycyclic aromatic hydrocarbons (PAHs) in sediment samples. Soxhlet extraction was used as the reference method. The optimum MAE was carried out with 20 mL of hexane/acetone (1:1, v/v) mixture in a 1-g sample at 250 W for 20 min. Soxhlet extraction was carried out with 250 mL of dichloromethane:hexane (1:1, v/v) mixture in a 15-g sample for 24 h in a water bath maintained at 60 °C. The collected extracts were both cleaned up, reduced to 1 mL under nitrogen and then injected into an HPLC fluorescence. To increase the sample throughput, simultaneous MAE was performed. The obtained percentage recoveries ranged from 61 to 93 and 88–98 for MAE and SE, respectively. The optimised MAE method was validated using certified reference material. It was then applied to real sediment samples from in and around the greater Johannesburg area. The sediments from Jukskei River were found to be the most polluted while Hartbeespoort Dam sediments were found to be least polluted. The overall order of concentrations for the studied PAHs per site was as follows: Jukskei River?>?Kempton Park?>?Centurion Dams?>?Natalspruit River (PIT)?>?Hartbeespoort Dam.     

Performance optimization of a membrane assisted passive sampler for monitoring of ionizable organic compounds in water

A thin-walled silicone rubber hollow fibre membrane has been developed as a passive sampler. The inside of the tube is filled with an aqueous solution at an appropriate pH. The tube is sealed at both ends and then immersed in a water sample. In order for the ionizable permeating compounds to be trapped in the aqueous receiving phase, the pH is adjusted such that the compounds are ionized and trapped. The major advantages are its simplicity, low cost and high selectivity, since only ionizable organic compounds are trapped. Additionally, the sampler uses no organic solvent. By adjusting the pH of the acceptor phase, it is possible to control the extraction process and whether the sampler is used in the kinetic or equilibrium regime. Since it is very selective, no further clean-up of the extract is required. The membrane assisted passive sampler has been tested for extraction of chlorophenols under laboratory conditions. The extraction process was found to be linear over a 72 h sampling period. Selectivity of the passive sampler in river water was demonstrated and the extraction process was independent of sample concentration, even at lower concentration levels of analytes. However, the sample matrix in some river water samples led to incomplete trapping, thereby reducing the amount trapped in the acceptor phase. Detection limits (three times signal to noise ratio) were dependant on sample matrix and type of detection system and ranged from 0.05 microg L(-1) to about 1 microg L(-1) with a UV photodiode detector in water samples from one river and 1.0 microg L(-1) to 20 microg L(-1) in another but with an ordinary UV detector. The enrichment factors in river water were 28 for 2-chlorophenol and 44 for 2,4-dichlorophenol over a 72 h sampling period. 4-chlorophenol was poorly extracted and its enrichment factor was 3.     

Determination of organochlorine pesticide residue in sediment and water from the Densu river basin, Ghana

The distribution of organochlorine pesticides in the aquatic ecosystem from the Densu river revealed varying levels of concentration in water and the sediment samples. Three locations were sampled along the river to evaluate the levels of organochlorine pesticide residue in the river. Sediment and surface water samples were extracted by soxhlet and liquid-liquid extraction respectively and analyzed using Gas Chromatograph coupled with electron capture detector. The detectable organochlorine pesticides were gamma-hexachlorocyclohexane (HCH), delta-hexachlorocyclohexane, heptachlor, aldrin and dieldrin. The other pesticides that were investigated are gamma-chlordane, alpha endosulfan, endosulfan sulfate, p,p′-DDT and its metabolite p,p′-DDE, methoxychlor, endrin and its metabolite endrin aldehyde and endrin ketone. The order of increasing frequency of detection of samples was higher in sediment than water. In sediment, the mean concentration ranged from 0.030 μg kg⁻¹ dry weight (endrin) to 10.98 μg kg⁻¹ dry weight (aldrin). The highest detected concentration of organochlorine in water was endosulfan sulfate with mean concentration of 0.185 μg L⁻¹. Analysis of variance indicated significant differences for most organochlorine pesticide residue in the sediment sampled from the various locations. Some of the levels of organochlorine pesticides detected in water were relatively high compared to guideline values set by World Health Organization and Australia and thus could be harmful if the trend is not checked.