Statistical Indicators for Evaluating the Effect of Heavy Metals on Samaraa Drug Industry Water Exposed to the Sun and Freezing http://www.doi.org/10.26538/tjnpr/v6i12.12
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Abstract
Heavy metal poisoning is a worldwide problem caused by various human industrial activities such as battery and paint manufacturing, as well as occupational exposure of individuals working at petrol stations. Contaminated water and wastewater contain higher amounts of heavy metals such as chromium (Cr), aluminum (Al), copper (Cu), manganese (Mn), zinc (Zn), and iron (Fe), which may pose a risk to wastewater treatment plant workers. However, only a few studies have been conducted to assess the level of heavy metals and their subsequent effects. This study was therefore conducted to measure Samaraa pharmaceutical factory (SPF) work efficiency and predict the most important characteristics that affect water quality using the multiple linear regression (MLR) model. The case study location was the Samaraa Drug Industry, situated in Iraq. Water samples exposed to the sun and freezing were collected Pre and post factory operation. The concentrations (mg/L) of heavy metals (Cr, Al, Cu, Mn, Zn, and Fe) in the water samples were measured. Also, the influent, effluent, and samples exposed to sun and freezing were analyzed according to Iraqi standards for drinking water (ISL). The results show that the heavy metal data were normally distributed because the p-value was equal to 0.05 and the concentrations of substances in the river water were within the ISL acceptable limits. Meanwhile, Fe exceeded the ISL during the study period, but excellent results were obtained when the samples were exposed to the sun and freezing. Based on the coefficient of correlation, the MLR model (R2 of 91.4 %) proved efficient.
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