Prevalence of multidrug-resistant,coagulase-positive Staphylococcus aureus in nasal carriage,food, wastewater and paper currency in Jalandhar city (north-western), an Indian state of Punjab

Eighteen sites impacted by abandoned mine drainage (AMD) in Pennsylvania were sampled and measured for pH, acidity, alkalinity, metal ions, and sulfate. This study compared the accuracy of four acidity calculation methods with measured hot peroxide acidity and identified the most accurate calculation method for each site as a function of pH and sulfate concentration. Method E1 was the sum of proton and acidity based on total metal concentrations; method E2 added alkalinity; method E3 also accounted for aluminum speciation and temperature effects; and method E4 accounted for sulfate speciation. To evaluate errors between measured and predicted acidity, the Nash-Sutcliffe efficiency (NSE), the coefficient of determination (R ²), and the root mean square error to standard deviation ratio (RSR) methods were applied. The error evaluation results show that E1, E2, E3, and E4 sites were most accurate at 0, 9, 4, and 5 of the sites, respectively. Sites where E2 was most accurate had pH greater than 4.0 and less than 400 mg/L of sulfate. Sites where E3 was most accurate had pH greater than 4.0 and sulfate greater than 400 mg/L with two exceptions. Sites where E4 was most accurate had pH less than 4.0 and more than 400 mg/L sulfate with one exception. The results indicate that acidity in AMD-affected streams can be accurately predicted by using pH, alkalinity, sulfate, Fe(II), Mn(II), and Al(III) concentrations in one or more of the identified equations, and that the appropriate equation for prediction can be selected based on pH and sulfate concentration.