Heavy metals in soil, plants, and associated risk on grazing ruminants in the vicinity of Cu-Ni mine in Selebi-Phikwe, Botswana

Toxicological analysis of metals content in agro-food wastes as possible supplement in animal feed

The agro-food surplus is considered the most abundant renewable resource, interesting for the economic and environmental impact, with a possible employment in different productive fields such as supplement in animal feed. For a safe and effective enhancement of agro-food wastes it is needed a toxicological analysis before of their employment, to avoid potential risks to animals, humans and environment. The purpose of this study was to evaluate the metals content (Cu, Fe, Zn, Mg, Na, K, Ca, Mn, Se, Zn, Co, Ni, V, Sb, Mo, Cr and Pb, Cd, As, Ba), in agro-food wastes through ICP-MS analysis. The results obtained showed the presence of metals analysed with a significant content of essential micro and macro-elements; with regard to toxic metals, only strawberries and fennel samples showed Pb levels above the MRL. These data confirm, from the toxicological point of view, a possible and safe reuse of the most of all agro-food wastes, as raw material at low cost and rich of essential nutrients and particularly as supplement in animal feed.

Investigating metal pollution in the food chain surrounding a lead-zinc mine (Northwestern Iran); an evaluation of health risks to humans and animals

The current study aims to evaluate the health risk of heavy metals for humans and animals in the Angouran mining complex (northwest of Iran). Twenty-five plant species and their corresponding soils (natural soils) were collected along with mine tailings samples. The carcinogenic and non-carcinogenic risks of heavy metals (Zn, Pb, Cd, Cr, and Co) for humans using the hazard quotient (HQ) and hazard index (HI) were evaluated. Moreover, the health risk caused by forage feeding to grazing ruminants (cow and sheep) and the risk associated with animal products consumption by humans in the soil-plant-animal transfer system were assessed. The value of HI in natural soils (rangeland use) was less than one (HI < 1), while regarding tailings, the HQ via oral ingestion and the HI were greater than one (HI & HQ > 1). The range of total carcinogenesis risk in natural soils exceeded the target risk (Risk < 10-6) and for tailings, it showed the probability of cancer risk, 1 person per 3636 populations, which is much higher than the acceptable or tolerable range (10-4 < Risk < 10-6). Regarding the animal health risk, the content of Pb and Cd in most of the animal organs was higher than the control values. In turn, dietary exposure to Pb and Cd is worrying for residents due to exceeding the provisional tolerable weekly intake (PTWI). This comprehensive study suggests the necessity of risk assessment of mining sites in Iran and immediate control measures to diminish pollutants.

Contaminant Binding and Bioaccessibility in the Dust From the Ni-Cu Mining/Smelting District of Selebi-Phikwe (Botswana)

We studied the dust fractions of the smelting slag, mine tailings, and soil from the former Ni-Cu mining and processing district in Selebi-Phikwe (eastern Botswana). Multi-method chemical and mineralogical investigations were combined with oral bioaccessibility testing of the fine dust fractions (<48  and <10 μm) in a simulated gastric fluid to assess the potential risk of the intake of metal(loid)s contaminants. The total concentrations of the major contaminants varied significantly (Cu: 301-9,600 mg/kg, Ni: 850-7,000 mg/kg, Co: 48-791 mg/kg) but were generally higher in the finer dust fractions. The highest bioaccessible concentrations of Co, Cu, and Ni were found in the slag and mine tailing dusts, where these metals were mostly bound in sulfides (pentlandite, pyrrhotite, chalcopyrite). On the contrary, the soil dusts exhibited substantially lower bioaccessible fractions of these metals due to their binding in less soluble spinel-group oxides. The results indicate that slag dusts are assumed to be risk materials, especially when children are considered as a target group. Still, this exposure scenario seems unrealistic due to (a) the fencing of the former mine area and its inaccessibility to the local community and (b) the low proportion of the fine particles in the granulated slag dump and improbability of their transport by wind. The human health risk related to the incidental ingestion of the soil dust, the most accessible to the local population, seems to be quite limited in the Selebi-Phikwe area, even when a higher dust ingestion rate (280 mg/d) is considered.

Prediction of nickel concentration in peri-urban and urban soils using hybridized empirical bayesian kriging and support vector machine regression

Soil pollution is a big issue caused by anthropogenic activities. The spatial distribution of potentially toxic elements (PTEs) varies in most urban and peri-urban areas. As a result, spatially predicting the PTEs content in such soil is difficult. A total number of 115 samples were obtained from Frydek Mistek in the Czech Republic. Calcium (Ca), magnesium (Mg), potassium (K), and nickel (Ni) concentrations were determined using Inductively Coupled Plasma Optical Emission Spectroscopy. The response variable was Ni, while the predictors were Ca, Mg, and K. The correlation matrix between the response variable and the predictors revealed a satisfactory correlation between the elements. The prediction results indicated that support vector machine regression (SVMR) performed well, although its estimated root mean square error (RMSE) (235.974 mg/kg) and mean absolute error (MAE) (166.946 mg/kg) were higher when compared with the other methods applied. The hybridized model of empirical bayesian kriging-multiple linear regression (EBK-MLR) performed poorly, as evidenced by a coefficient of determination value of less than 0.1. The empirical bayesian kriging-support vector machine regression (EBK-SVMR) model was the optimal model, with low RMSE (95.479 mg/kg) and MAE (77.368 mg/kg) values and a high coefficient of determination (R² = 0.637). EBK-SVMR modelling technique output was visualized using a self-organizing map. The clustered neurons of the hybridized model CakMg-EBK-SVMR component plane showed a diverse colour pattern predicting the concentration of Ni in the urban and peri-urban soil. The results proved that combining EBK and SVMR is an effective technique for predicting Ni concentrations in urban and peri-urban soil.