STATISTICAL DETERMINATION OF STEADY-STATE CONDITION IN BIOREMEDIATIONTESTS

Linear regression and two newly developed statistical techniques were used to determine steady states in the dependent y-variables (effluent concentration or removal rate of pollutants) using correlation coeffi cients (r) for the relationship between the independent x-variables (r eactor operating or treatment time) and the dependent y-variables. The statistical technique applied to chlorophenol bioremediation using a varying number of data points for linear regression analysis was more useful in determining a steady state for six general data patterns fro m bioremediation tests than the statistical technique using a fixed nu mber of data points for linear regression analysis.