UNCERTAINTIES OF BACTERIAL INACTIVATION IN MARINE ENVIRONMENT

摘要

It is a common final disposal option to discharge treated or pre-treated domestic wastewaters utilizing marine outfall systems in coastal areas. The main parameters used to design a marine outfall system are: treatment level, effluent flow rate, length and depth of the outfall system, current velocity, bacterial inactivation rate and density of effluent and sea water. It is vital to put in practice the water quality standards especially in sensitive areas (such as aqua-culture and recreational) to protect public health against water borne diseases originated from pathogens. In this manner, it is very important to define the case specific bacterial inactivation rates and the time needed to inactive 90% of the bacteria (T_(90)) in design of marine outfall systems. According to Turkish Water Pollution Control Regulations, T_(90) values in summer and winter seasons are 1 and 3 hours respectively, for Mediterranean Sea at sea surface. Bacterial inactivation rate is affected by solar irradiation, salinity, temperature, pH, predation by other organisms and nutrient deficiencies. However, solar irradiation is the most effective environmental parameter affecting the bacterial inactivation process and T_(90) values increase dramatically during night-time or in darkness. Therefore, dynamic T_(90) values, which change with respect to varying light intensities and ambient conditions, should be used instead of constant values to obtain more reliable dilution and bacterial concentration predictions and to decrease uncertainty of the predicted parameters. In this study, uncertainties of bacterial inactivation process have been analyzed using Monte Carlo Simulation for Antalya Sea Outfall System. The required input data of hourly solar radiation has been obtained from State Meteorology Office of Antalya to determine hourly values of T_(90) parameter. Other required input data have been obtained from in-situ measurements. The obtained results show that bacterial inactivation process needs to be evaluated in a probabilistic approach to estimate bacteriological pollution risk from marine outfall systems.