Methodology for minimum nitrogen compounds removal efficiencies estimation and wastewater treatment systems pre-selection: a watershed approach

Abstract

Nitrogen is a very important parameter for water pollution control since nitrification implies in aquatic environment oxygen consumption and some nitrogen forms are toxic. In the present study, an optimization model was developed and applied aiming at simultaneous organic matter and nitrogen compounds minimum removal efficiencies determination. A water quality model and the Genetic Algorithm Metaheuristic were associated in order to solve the optimization problem. The estimated minimum efficiencies conditioned the sewage treatment systems pre-selection. The study area was the Pardo River watershed (Espírito Santo State, Brazil). The results indicate that the treatment systems need to be more efficient in ammonia removal when the treated effluents disposed in watercourses that present high pH values because ammonia toxicity increases with pH. Considering the boundary conditions assumed in this study, the pre-selection process indicated activated sludge systems, submerged aerated biofilter with nitrification, or with biological nitrogen removal, for Ibatiba city. Simpler systems such as primary treatment with septic tanks, stabilization ponds, UASB reactors and biological filters were pre-selected for Santíssima Trindade and Nossa Senhora das Graças towns.

Prospects for reducing the contribution of organic load in a water basin with significant urban occupation

“…Organic loads and removal percentages per water quality simulation scenario of the Poti River -results associated with the use of Optimization Model 2.treatment efforts to remove organic loads were reduced. A similar behavior was observed byBringer, Reis and Mendonça (2018),Rocha et al (2021),Sá et al (2019) andValory, Reis and Mendonça (2016) when evaluating the final disposal of domestic effluents in the Pardo and Santa Maria da…”

“…Examples of works that use the association between water quality modeling and optimization techniques are Aghasian et al (2019), Almeida et al (2022, Bringer, Reis and Mendonça (2018), Fantin, Reis and Mendonça (2017), Rocha et al (2021, Sá et al (2019) and Santoro, Reis and Mendonça (2016). The optimization models suggested by these authors were built through the combination of different objective functions and sets of constraints.…”