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Studies on the correlation of some aggregate parameters in the drains of a service facility
Abstract
Real composite samples from industrial waste drains were obtained from four different worksites in an oil company waste management facility, Warri Nigeria. The sites include: Recycle Waste Deport drain, Petroleum
Chemistry Laboratory drain, Tubo Scope Yard drain and Fuel Filling station drain. For each sample, four aggregate water quality parameter: Turbidity, Total Dissolved Solids (TDS), Chemical Oxygen Demand (COD) and 5-day
Biochemical Oxygen Demand (BOD5), were determined weekly, and monthly averages were taken over a period of seven months. TDS and Turbidity were well correlated in each case and Pearson’s correlation coefficient for the seven months for each of the drain samples were respectively: -0.78, - 0.24, 0.58 and 0.42. BOD5 was also well
correlated with COD and Pearson’s correlation coefficient for each drain sample for the period was respectively: 0.97, 0.90, 0.49 and 0.93. Regression analysis gave equations of a straight line: y = a b + c for the eight plots. In each case the Pearson’s coefficient of determination, R2, shows that each regression model is adequate for future prediction of
one water quality parameter regarded as the dependent variable from another, a determined independent variable.
Chemistry Laboratory drain, Tubo Scope Yard drain and Fuel Filling station drain. For each sample, four aggregate water quality parameter: Turbidity, Total Dissolved Solids (TDS), Chemical Oxygen Demand (COD) and 5-day
Biochemical Oxygen Demand (BOD5), were determined weekly, and monthly averages were taken over a period of seven months. TDS and Turbidity were well correlated in each case and Pearson’s correlation coefficient for the seven months for each of the drain samples were respectively: -0.78, - 0.24, 0.58 and 0.42. BOD5 was also well
correlated with COD and Pearson’s correlation coefficient for each drain sample for the period was respectively: 0.97, 0.90, 0.49 and 0.93. Regression analysis gave equations of a straight line: y = a b + c for the eight plots. In each case the Pearson’s coefficient of determination, R2, shows that each regression model is adequate for future prediction of
one water quality parameter regarded as the dependent variable from another, a determined independent variable.