Modelagem dinâmica em estações de tratamento de efluentes utilizando os modelos: ASAL1 para lodo ativado e ADM1 para reatores UASB visando análise de comportamento dos sistemas - Morais, Thiago Augusto de (2018)
Sanitary effluents pressure water resources regarding irregular and untreated dumps. This subject is based on the importance of new technologies development, capable of optimizing this process. Thus, the dynamic modelling of Activated Sludge Model 1 (ASAL1) for the activated sludge systems and Anaerobic Digestion Model 1 (ADM1) for the Upflow Anaerobic Sludge Blanket reactors (UASB) present applicability in the prediction of sewage treatment plants’ behaviour, using the Sewage Treatment Optimization and Analysis over Time (STOAT) software. It is proposed to observe the behaviour of the system composed of UASB reactors in scenarios represented in STOAT, according to the mathematical model ADM1, as well as to analyse the ASAL1 model for activated sludge, both focused on Biochemical Oxygen Demand (BOD) removal. In order to do so, it was used monitoring data from an activated sludge station on a pilot scale, and data from a UASB reactors plant serving a city in Paraná. Then, the effluent profile data and the characteristics of the treatment methods used were calibrated and replicated in the STOAT for analysis considering the efficiency of the ASAL1 model and simulation of six possible scenarios with hydraulic retention times (HRT) of 7 and 12 hours, where the flow and concentration of pollutants in the UASB system varied. The calibration of the activated sludge system showed a variation of 7 mg/l for total BOD and 4 mg/l for the filtered BOD, while the parameter with the greatest variation was suspended solids with 30 mg/l. Regarding the calibration of the ADM1 model, the program is, on average, 10,64% less efficient than the actual treatment in removing pollutants. The scenarios studied would fit within the current legislation of treated sewage standards, except for ammoniacal nitrogen. To sum up, it was found that the software has a limited number of parameters that can be evaluated and, in addition, there was no significant difference between the HRTs. In this way, STOAT presents great potential of wastewater treatment optimization by dynamic models’ utilization.