RESUMO

Wastewater Treatment Plants (WWTPs) present complex biochemical processes of high variability and difficult prediction. This study presents an innovative approach using Machine Learning (ML) models to predict wastewater quality parameters. In particular, the models are applied to datasets from both a simulated wastewater treatment plant (WWTP), using DHI WEST software (WEST WWTP), and a real-world WWTP database from Santa Catarina Brewery AMBEV, located in Lages/SC - Brazil (AMBEV WWTP). A distinctive aspect is the evaluation of predictive performance in continuous data scenarios and the impact of changes in WWTP operations on predictive model performance, including changes in plant layout. For both plants, three different scenarios were addressed, and the quality of predictions by random forest (RF), support vector machine (SVM), and multilayer perceptron (MLP) models were evaluated. The prediction quality by the MLP model reached an R2 of 0.72 for TN prediction in the WEST WWTP output, and the RF model better adapted to the real data of the AMBEV WWTP, despite the significant discrepancy observed between the real and the predicted data. Techniques such as Partial Dependence Plots (PDP) and Permutation Importance (PI) were used to assess the importance of features, particularly in the simulated WEST tool scenario, showing a strong correlation of prediction results with influent parameters related to nitrogen content. The results of this study highlight the importance of collecting and storing high-quality data and the need for information on changes in WWTP operation for predictive model performance. These contributions advance the understanding of predictive modeling for wastewater quality and provide valuable insights for future practice in wastewater treatment.

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RESUMO

This study deals with the photochemical degradation of the model compound tetracycline, an aqueous pollutant derived from the degradation of the bactericide oxytetracycline (OTC), in the innovative photoreactor FluHelik, designed to promote pollutant abatement in liquid phase through H2O2/UVC and UVC processes. Computational fluid dynamics (CFD) simulations were performed to predict the behavior of the photoreactor in the laboratory scale. The simulations revealed a well-defined helicoidal flow pattern around the UVC lamp in the photoreactor, and the effect of different operational conditions (e.g., flow rate and light intensity) on the reactor's performance was evaluated, allowing to optimize the equipment.

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RESUMO

In this work, the performance of microreactors irradiated with conventional (fluorescent) and UV-LED light was evaluated. For this purpose, a microfluidic reactor with an equivalent diameter of 133.5 µm was used. In addition, the effect of scale variation on the performance of photochemical reactors was assessed using reactors with three internal diameters (600, 1200, and 2300 µm), 2 residence times (30 and 60 s), and two sources of UVA radiation (A with irradiance of 115 W m-2 and B with irradiance of 44 W m-2). Also, the relationship between the configuration of the photocatalyst film and the effect of the scale on the performance of photochemical reactors was experimentally and theoretically investigated. For both cases, methylene blue dye was used as a model pollutant and titanium dioxide (TiO2) as a photocatalyst deposited on the inner wall of the photocatalytic reactors. For the residence time of 30 s, the smaller the reactor diameter, the greater was the degradation (22, 18, and 6%, respectively, for lamp A and 17, 16, and 8 %, respectively, for lamp B). The influence of the diameter of the reactor was also observed for the residence time of 60 s, but only for the reactor with a 2300-µm internal diameter. The reactors with diameters 600 and 1200 µm only showed different results when illuminated with lamp B (33 and 28% of methylene blue conversion, respectively). Moreover, computational simulation results suggested higher efficiency as the reactor's diameter is decreased and an optimum thickness of photocatalyst film to maximize the performance of devices in which photocatalytic reactions are carried out.

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RESUMO

A 2D CFD model was implemented for the numerical simulation of NOx abatement in a photocatalytic reactor, considering the effect of relative humidity (10-60%), light intensity (0.3-13 W⋅m-2) and inlet NO concentration (0.1-1.0 ppm). Significant differences of NOx concentration at the catalytic surface and bulk gas were found (Δmax of ∼12% and ∼16% for NO and NO2, respectively) and corrections were proposed to achieve intrinsic rate laws from a model available in the literature. An analysis of the reactor performance was conducted and a nonlinear behavior was observed when the channel height (H) was varied. A point of maximum for the integral rate of NO and NO2 consumption as a function of H was found (ΔNO of ∼2% and ∼-1% for H→2H→4H; [Formula: see text] of ∼46% and -8.5% for H→2H→4H). Additionally, the NO conversion decreased from ∼29% to ∼7% and the selectivity decreased from ∼85% to ∼80% (passing through a point of minimum at 2H) when the height was varied in the range H-4H. When comparing the results from the CFD simulations and the predictions of a plug flow model, deviations for NO conversion and selectivity increased with H (Δmax of ∼2% and ∼45%, respectively).

RESUMO

Groundwater contamination is becoming a serious problem in many Brazilian regions. European countries started to deal with this issue in the 1980s, mainly caused by the extensive usage of nitrogenous fertilizers and the absence of domestic wastewater treatment. Due to its high solubility, nitrate readily passes through the soil and reaches the aquifer. Thereafter, this ion moves, following groundwater flow, and can be found several kilometers from the area where the pollution occurred. Concern about nitrate contamination is due to the link found between this contaminant and various human health diseases, such as methemoglobin and cancer. Studies carried out in France enabled the design and implementation of several biological denitrification plants throughout the country, in order to remove nitrate from its contaminated groundwater. Heterotrophic denitrification facilities shown to be adequate to treat high water flows with satisfactory nitrate removal efficiency, especially when static media supports are employed. The objective of this research was to evaluate the existence of denitrifying microorganisms in bamboo (Bambusa tuldóides) and verify the feasibility of their use to inoculate a pilot-scale fixed-bed bioreactor. The support material selected to fill the bioreactor bed was commercial polypropylene Pall rings, since such support has a high porosity associated with a wide superficial area. The bioreactor was able to produce and retain a large amount of cells. Using ethanol as carbon source, nitrate (N-NO3(-)) removal efficiency of the bioreactor stood around 80 % for a maximum nitrogen loading rate of approximately 6.5 mg N-NO3 (-) L(-1) h(-1).

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