Dariusz Andraka, Lech Dzienis
This paper presents the results of research using Monte Carlo simulation, which aim was to assess various aspects of the risk associated with operation of the wastewater treatment plant. First part of the research included modeling of wastewater treatment plant effluent quality (using BOD5 as the example and assuming log-normal distribution of the variable) together with inspection results (check of compliance with fixed standards). Monte Carlo simulations of annual operational cycles of the plant allowed for creation of nomographs showing relations between coefficient of reliability (ratio of mean value of BOD to the fixed standard), coefficient of variation (ratio of standard deviation to mean value of variable) and reliability of the plant (expressed as probability of effluent concentration lower than fixed standard) as well as risk of the negative inspection result (probability that number of inspected samples that do not comply with required quality of the effluent is greater than fixed standard). Using such nomographs plant operator can evaluate for example the target mean value of effluent concentration to achieve required reliability and acceptable risk. Another part of the study included simulation of the water quality in the river after the discharge of wastewater. Using static model of pollutants budget in a mixed water (river + wastewater) and implementing random values of variables into the model (according to Monte Carlo simulation rules) the variations of river water quality were observed. It was found that although mean values of variables (among them quality and quantity of the discharge) result in good mixed river water quality, the probability of temporary degradation of river quality is significantly high. The results of simulation show that capacity of the river to accept pollutants load should be taken into account together with predicted variations in wastewater discharges, when establishing rules for water disposal in the river basin.
eksploatacja oczyszczalni; modelowanie ryzyka
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