Henna and walnut tree bark are widely used by Libyan women as cosmetics. They may contain lead (Pb), cadmium (Cd) and arsenic (As), which, in turn, pose a high risk to their health. This study aims to determine the levels of Pb, Cd and As in henna and walnut tree bark products sold in Libyan markets. The products were analyzed for their Pb, Cd and As content by using inductively coupled plasma mass spectrometry (ICP-MS) after a microwave acid digestion. The results showed a significant difference between the henna and walnut tree bark samples in terms of their heavy metals content (p < 0.05). The highest heavy metal concentrations were observed in the walnut tree bark samples whereas the lowest was observed in the henna samples. In addition, 60% of the henna and 90% of the walnut tree bark samples contained Pb levels and approximately 80% of the henna and 90% the walnut tree bark samples contained Cd levels, which are much higher than the tolerance limit. However, As concentrations in all the samples were lower. The results indicated that such cosmetics expose consumers to high levels of Pb and Cd and hence, to potential health risks. Thus, studying the sources and effects of heavy metals in such cosmetics is strongly recommended.

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In this research, three water quality (WQ) indexes, namely dissolved oxygen (DO), biochemical oxygen demand (BOD), and chemical oxygen demand (COD), in Selangor River of peninsular Malaysia were simulated using a stochastic model based on vector autoregression (VAR). The simulation was adopted based on three modeling scenarios of inputs as predictor: (i) related WQ parameters, (ii) WQ parameters and river flow data, and (iii) WQ parameters and rainfall data. The WQ parameters as input were determined based on the correlation analysis. The numerical analyses revealed that the prediction accuracy of VAR model substantially increases with the increase in input number. The model provided better accuracy in predictions of WQ indexes (root mean square error ≈ 0.11 and mean absolute error ≈ 0.26) when all environmental, hydrological, and climatological variables were considered. Further improvement in model performance (root mean square error ≈ 0.0248 and mean absolute error ≈ 0.1259) can be achieved if physiochemical parameters like suspended solid material and the turbidity are used as additional inputs.

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Coal-fired power plants and industrial waste (IW) incinerators increasingly dispose large amounts of fly ash that cause environmental contamination by toxic heavy metals. This study aimed to investigate the concentration of heavy metals and measure the specific activity of naturally occurring radioactive materials (NORM) that remain in the fly ash of coal power plants and industrial incinerators. Ash samples were collected from the Kapar and Jana Manjung coal-fired power plants and the Kualiti Alam industrial incinerator in Malaysia. The concentrations of As,