Spectral deconvolution associated to the Gaussian fit as a tool for the optimization of photovoltaic electrocoagulation applied in the treatment of textile dyes.

The objective of this study was to investigate the color removal in a binary mixture of azo dyes from the photovoltaic electrocoagulation (EC) technique, using spectral deconvolution and the Gaussian fit for qualitative and quantitative determination of the physical color parameter. Initially, a conventional energy source was used to feed the EC reactor and the experimental design was conducted according to the Rotational Central Compound Design (RCCD). The spectral deconvolution method associated to the Gaussian fit aided in the description of the composition of the sample matrix, In the first step, through the Analysis of Variance, the RCCD and the three-dimensional surface response graphs, the optimized operating conditions were identified, which corresponded to 1320 A m-2 with an reaction time of 16.6 min, and an expected removal of 98.40% for Scarlet Red (SR) dye and 1160 A m-2 with a run time of 15.7 min and 97.9% removal for Turquoise Blue (TB) dye. Using the photovoltaic module as the power source of the EC reactor, a maximum removal of 97 ± 0.43% for TB dye and 98% ± 0.81 for SR was obtained. The results encourage the applicability of photovoltaic module-fed EC technology as a promising alternative for the treatment of effluents containing textile dyes, as well as the use of the spectral deconvolution method associated with the Gaussian fit, for the reliability and precision of the results.

A simple, rapid and low cost reversed-phase dispersive liquid-liquid microextraction for the determination of Na, K, Ca and Mg in biodiesel.

In this work a method based on reversed-phase dispersive liquid-liquid microextraction (RP-DLLME) as sample preparation for the extraction and preconcentration of Na, K, Ca and Mg in biodiesel samples was developed. The analytes determination was performed by flame atomic absorption spectrometry (FAAS), operating in emission mode for Na and K and in absorption mode for Ca and Mg. The extraction/preconcentration step of the analytes was performed by using a mixture of dispersant and extractant solvents (isopropanol and HNO3, respectively) and the aqueous phase containing the analytes was separated by centrifugation. Some parameters such as sample mass, type and volume of dispersant and extractant solutions, HNO3 concentration (extraction solution), use of ultrasound, centrifugation time and temperature were evaluated. During the optimization of RP-DLLME, biodiesel samples were spiked with a multi-element biodiesel B100 (Conostan®) with final concentration of 1.0 µg g-1 of the analytes. Analytes determination was performed by FAAS using external calibration with aqueous reference solutions. The limits of quantification (LOQ) for Na, K, Ca and Mg were 0.04; 0.02; 0.05 and 0.08 µg kg respectively. The accuracy was evaluated by recovery tests, which ranged from 93.9% to 108.1%, with relative standard deviation lower than 3% for all analytes. Then, the proposed method was applied for analytes determination in five biodiesel samples produced from different raw materials. Comparing to conventional methods for elements determination in biodiesel (e.g., dilution with organic solvent, sample digestion, etc.), RP-DLLME combined to FAAS is simple, low cost, low reagents consumption and provides LOQs values significantly below compared to the limits established in the legislation for these elements in biodiesel.

Optimization of the nitrification process of wastewater resulting from cassava starch production.

The present study has the objective of optimizing operational conditions of an aerated reactor applied to the removal of ammoniacal nitrogen from wastewater resulting from the production of cassava starch. An aerated reactor with a usable volume of 4 L and aeration control by rotameter was used. The airflow and cycle time parameters were controlled and their effects on the removal of ammoniacal nitrogen and the conversion to nitrate were evaluated. The highest ammoniacal nitrogen removal, of 96.62%, occurred under conditions of 24 h and 0.15 L min-1 Lreactor-1. The highest nitrate conversion, of 24.81%, occurred under conditions of 40.92 h and 0.15 L min-1 Lreactor-1. The remaining value of ammoniacal nitrogen was converted primarily into nitrite, energy, hydrogen and water. The optimal operational values of the aerated reactor are 29.25 h and 0.22 L min-1 Lreactor-1. The mathematical models representative of the process satisfactorily describe ammoniacal nitrogen removal efficiency and nitrate conversion, presenting errors of 2.87% and 3.70%, respectively.

Optimization of the pretreatment of wastewater from a slaughterhouse and packing plant through electrocoagulation in a batch reactor.

The purpose of this study is to evaluate the removal of chemical oxygen demand (COD), turbidity and color of wastewater from a pig slaughterhouse and packing plant through the electrochemical technique and to optimize the ΔV (electric potential difference) and HRT (hydraulic retention time) variables in an electrocoagulation batch reactor using aluminum electrodes. The experimental design used was rotatable central composite design. For turbidity, the values for removal efficiency obtained varied from 92.85% to 99.28%; for color, they varied from 81.34% to 98.93% and for COD, they varied from 58.61% to 81.01%. The best optimized conditions of treatment were at 25 min for the HRT and 25 V for the ΔV, which correspond to electrical current of 1.08 A and a current density of 21.6 mA cm-2. The aluminum residue varied from 15.254 to 54.291 mg L-1 and the cost of the treatment was US$4.288 m-3. The novelty of the work was the simultaneous optimization of three response variables using the desirability function applied to the treatment of wastewater from slaughterhouses.

Gráfico de controle da média móvel exponencialmente ponderada: aplicação na operação e monitoramento de uma estação de tratamento de esgoto / Exponentially weighted moving average control chart: application in the operation and monitoring of a sewage treatment plant

RESUMO Este trabalho teve por objetivo avaliar o desempenho de uma estação de tratamento de esgoto através de cartas de controle de qualidade estatística da média móvel exponencialmente ponderada (MMEP). A estação de tratamento de esgoto estudada localiza-se no Município de Cascavel, Paraná, Os parâmetros avaliados foram o potencial hidrogeniônico (pH), sólidos sedimentáveis (SSed), sólidos suspensos totais (SST), demanda química de oxigênio (DQO) e a demanda bioquímica de oxigênio (DBO). As cartas MMEP acusaram que estação de tratamento de esgoto apresentou bom desempenho estatístico para o pH, sólidos suspensos totais, DQO e DBO e falhas para os sólidos sedimentáveis. As cartas de controle MMEP se apresentam como uma boa alternativa no monitoramento de estações de tratamento de esgoto.

ABSTRACT This work was intended to assess the performance of a sewage treatment plant through letters of statistical quality control of exponentially weighted moving average. The sewage treatment plant is located in the municipality studied of Cascavel, Paraná, the parameters measured were the hydrogenionic potential (pH), settleable solids (SetS), total suspended solids (TSS), chemical oxygen demand (COD), biochemical oxygen demand (BOD). The EWMA letters accused that sewage treatment station has good statistical performance for the pH, total suspended solids, COD and BOD and failures for settleable solids. The EWMA control letters are presented as a good alternative in monitoring of sewage treatment plants.

Neural network based control of an absorption column in the process of bioethanol production

Gaseous ethanol may be recovered from the effluent gas mixture of the sugar cane fermentation process using a staged absorption column. In the present work, the development of a nonlinear controller, based on a neural network inverse model (ANN controller), was proposed and tested to manipulate the absorbent flow rate in order to control the residual ethanol concentration in the effluent gas phase. Simulation studies were carried out, in which a noise was applied to the ethanol concentration signals from the rigorous model. The ANN controller outperformed the dynamic matrix control (DMC) when step disturbances were imposed to the gas mixture composition. A security device, based on a conventional feedback algorithm, and a digital filter were added to the proposed strategy to improve the system robustness when unforeseen operating and environmental conditions occured. The results demonstrated that ANN controller was a robust and reliable tool to control the absorption column.

Deseja-se recuperar o etanol perdido por evaporação durante o processo de fermentação da cana-de-açúcar. Para tanto, faz-se uso de uma coluna de absorção. O controle da concentração de etanol no efluente gasoso da coluna é realizado pela manipulação da vazão de solvente, sendo esta determinada pelo controlador não linear proposto, baseado em um modelo inverso de redes neurais (controlador ANN). Foram feitas simulações adicionando-se um sinal de ruído a medida de concentração de etanol na fase gasosa. Quando perturbações degrau foram inseridas na mistura gasosa afluente, o controlador ANN demonstrou desempenho superior ao controle por matriz dinâmica (DMC). Um dispositivo de segurança, baseado em um controlador feedback convencional, e um filtro digital foram implementados à estratégia de controle proposta para agregar robustez no tratamento de distúrbios ocorridos no ambiente operacional. Os resultados demonstraram que o controlador ANN é uma ferramenta robusta e confiável no controle de uma coluna de absorção.