Methane liquid-gas phase distribution during anaerobic sludge digestion: A thermodynamic approach.

Anaerobic digestion is certainly one of the options that can help solve the dilemma of energy demand, waste management and climate crisis mitigation mainly. Under ideal conditions, it is expected that all biomethane will be transferred from the liquid to the gaseous phase, ensuring maximum recovery. However, for concentrated wastewater or complex organic waste blends composed of functional groups with different sizes, the molecular interactions become important since the system is not only biphasic. Since the formation and transfer of a gas is related to the equilibrium condition, a thermodynamic approach could help to estimate the degree of variation of biomethane between the liquid and gaseous phases. Therefore, this investigation aimed to obtain the distribution between liquid and gaseous phases of the biomethane produced in the sewage sludge anaerobic digestion considering the substrate as a non-ideal solution. The nonlinear differential equations of the ADM1 were integrated with Aspen Plus® to verify the equilibrium conditions and the model was calibrated with data obtained through experiments conducted in a lab scale sequence batch reactor (SBR) fed with synthetic substrate (1500 mgCOD.L-1) and inoculated with flocculent sludge (500 mgSSV.L-1) from a full-scale UASB reactor. Considering the thermodynamic approach, the percentage of dissolved biomethane remains below the 2.97% percentage estimated by using the ADM1. It is possible to state that the principle of ideality is maintained in the system. On the other hand, CO2 phase distribution was considerably affected by the species defined in the equilibrium reactions. Therefore, it can be stated that Henry's Law simplification in ADM1 model is valid to represent the phenomenon investigated.

Diagnosis of patients with blood cell count for COVID-19: An explainable artificial intelligence approach / Diagnóstico de pacientes com hemograma para COVID-19: Uma abordagem com inteligência artificial explicável / Diagnóstico de pacientes con hemograma para COVID-19: un enfoque explicable de inteligencia artificial

Objective: Present an explainable artificial intelligence (AI) approach for COVID-19 diagnosis with blood cell count. Methods: Five AI algorithms were evaluated: Logistic Regression, Random Forest, Support Vector Machine, Gradient Boosting and eXtreme Gradient Boosting. A Bayesian optimization with 5-Fold cross-validation was used to hyper-parameters tuning. The model selection evaluated three results: cross validation performance, test set prediction performance and a backtest: performance on identifying patients negative for COVID-19, but positive for others respiratory pathologies. Shapley Additive explanations (SHAP) was used to explain the chosen model. Results: A Random Forest model was obtained with 77.7% F1-Score (IC95%:57.1;92.3), 85.9% AUC (IC95%:73.7;95.9), 74.4% Sensitivity (IC95%:50.0;92.1) and 97.5% Specificity (IC95%:93.6;100.0). The main features were leukocytes, platelets and eosinophils. Conclusion: The research highlights the importance of model interpretability, demonstrating blood cell count as a possibility for COVID-19 diagnosis. The methodological structure developed, using TRIPOD's guidelines, can be extrapolated to other pathologies.

Objetivo: Propor uma abordagem com inteligência artificial explicável para diagnóstico de COVID-19 com hemograma. Métodos: Cinco algoritmos de IA foram testados: Regressão Logística, Florestas Aleatórias, Máquina de Vetores de Suporte, Gradient Boosting e eXtreme Gradient Boosting. Os hiper-parâmetros foram definidos através da otimização bayesiana com validação cruzada 5-Fold. A seleção de modelo utilizou três resultados de desempenho para definir o melhor modelo: validação cruzada, conjunto de teste e rendimento na identificação de pacientes negativos para COVID-19, porém positivos para outras patologias respiratórias (backtest). Ao final, Shapley Additive explanations (SHAP) foi utilizado para explicar o modelo escolhido. Resultados: Obteve-se um modelo Random Forest com F1-Score de 77.7% (IC95%:57.1;92.3), AUC de 85.9% (IC95%:73.7;95.9), Sensibilidade de 74.4% (IC95%:50.0;92.1) e Especificidade de 97.5% (IC95%:93.6;100.0). As principais variáveis foram leucócitos, plaquetas e eosinófilos. Conclusão: A pesquisa destaca a importância da interpretabilidade do modelo, demonstrando o hemograma como uma possibilidade para diagnosticar COVID-19. A estrutura metodológica desenvolvida no estudo, utilizando as diretrizes do TRIPOD, pode ser extrapolada para detecção de outras patologias.

Objetivo: Proponer un enfoque explicable de inteligencia artificial (IA) para el diagnóstico de COVID-19 con el uso de hemograma. Métodos: Cinco modelos de IA fueron evaluados: Logistic Regression, Random Forest, Support Vector Machine, Gradient Boosting e eXtreme Gradient Boosting. Los hiper-parámetros fueron definidos a través de optimización bayesiana con validación cruzada 5-Folds. La selección del modelo se utilizó tres resultados: rendimiento del validación cruzada, rendimento en conjunto de pruebas y el análisis de desempeño en identificación de pacientes negativos para COVID-19, pero positivos para otras patologías respiratorias (backtest). Shapley Additive explanations (SHAP) fue utilizado para explicar el modelo elegido. Resultados: Se obtuvo un modelo Random Forest con F1-Score de 77.7% (IC95%:57.1;92.3), AUC de 85.9% (IC95%:73.7;95.9), Sensibilidad de 74.4% (IC95%:50.0;92.1) y Especificidad de 97.5% (IC95%:93.6;100.0). Las principales variables fueron leucocitos, plaquetas y eosinófilos. Conclusión: La investigación presenta la importancia de la interpretabilidad del modelo, demostrando el uso de hemograma como posibilidad para diagnosticar COVID-19. La estructura elaborada, siguiendo las directrices de TRIPOD, puede ser extrapolar para otras patologías.

Coalescence process to treat produced water: an updated overview and environmental outlook.

Produced water is the largest liquid effluent in volume generated in petroleum production. It originates from natural wells or from water that was previously injected during the exploration process. The composition of produced water is complex, containing high salt concentration, emulsified oil, suspended solids, chemical additives used in the various stages of oil production, heavy metals, and other contaminants. Several technologies can be used in the treatment of produced water in order to meet the conditions specified in local legislations and the most used are phase separators, decanters, cyclones, and filters. The separation process mechanism of oil emulsions by coalescence in fibrous media has excellent results, though it is not fully understood and is frequently based on empirical, as well as on experimental, observations. This article presents a general overview on produced water, including origin, production, composition, environmental impact, treatment techniques, disposal, and legislation, as well as an updated discussion utilizing recent literature regarding the unit operation of coalescence: general aspects, kinetics, mechanisms, and factors that influence the coalescence process.

Avaliação de parâmetros operacionais de um sistema de membranas para tratamento de efluentes oleosos / Evaluation of a membrane system's operational parameters for oily effluent treatment

RESUMO O objetivo deste trabalho foi discutir os principais parâmetros de controle de um sistema de membranas de microfiltração para remoção de óleo de efluentes com base em ensaios experimentais. Os ensaios utilizaram efluentes sintéticos com diâmetros de gotas de óleo entre 4 e 8 µm. As membranas usadas foram do tipo fibra oca com módulo submerso. Foram testados os seguintes parâmetros: concentrações de óleos e graxas na alimentação das membranas (O&Gam) entre 100 e 260 mg.L-1; taxas de recuperação de água (Rec) de 0,75 e 0,90; e pressões através das membranas (Δp) de -0,20 e -0,30 bar. Os resultados mostraram que as membranas produzem um permeado com uma qualidade boa a ponto de possibilitar o seu reúso em atividades industriais diversas. Foi também observado que a elevação da O&Gam e da Rec acentuam o declínio de fluxo com o tempo e que a elevação da Δp aumenta o valor do fluxo no tempo de seis horas.

ABSTRACT The aim of this paper is to discuss the main control parameters of a microfiltration membranes system for oil removal from effluent on experimental bases. The experiments were conducted by using synthetic effluent with oil droplets diameter ranging from 4 to 8 microns. The membranes used were hollow fiber-type which were assembled in a submerged module. The following parameters were tested: Oil and grease concentration in the feed stream (O&Gf ) of 100 and 200 mg.L-1, Water recovery rates (WRR) of 0.75 and 0.90, and Transmembrane pressure (TMP) of -0.20 and -0.30 bar. The results showed that the membranes produced a permeate with a good quality to the point of enabling their reuse in several industrial activities. It was also observed that the elevation of O&Gf and WRR increase the flux decline over time and that the increase of TMP increases the flow value in time of 6 hours.

Importance of legislation on the treatment of chemical effluents as a way to avoid environmental pollution: the use of numerical technique to simulate the sedimentation of chemical effluents.

Environmental pollution analysis should be present in scientific research. The more organized the environmental laws of a particular place, the smaller the risks imputed to the ecosystem. The environmental damages that irregular waste from industrial effluents can cause are notorious. However, Brazil lacks extensive legal regulation, which is an embryonic legal matter. There is no specific law regulating a National Industrial Effluent Policy, dealing with the treatment and final disposal of these chemical compounds. Until a solid legal structure has been formalized on the treatment and final disposal of industrial effluents in Brazil, it is necessary that scientific researches optimize techniques capable of causing lower environmental impacts, so as to avoid possible pollution to the bodies of water. This article defends the argument that it is possible to elaborate legislation on the treatment and final disposal of industrial effluents in Brazil, through the application of engineering techniques, specifically through numerical simulation, by using the discrete elements method or particles method. The present case study is the Camaçari Petrochemical Pole, state of Bahia, which is the largest integrated industrial complex in the Southern Hemisphere, composed of more than 90 companies in the chemical and petrochemical areas. All the effluents from this locality are treated by CETREL (Liquid Effluent Treatment Plant). Particle analysis was performed in CETREL tanks to illustrate how numerical simulations can be applied to investigate the treatment of industrial effluents and, consequently, to affirm the importance of developing procedures and norms for this matter. It is believed that this article brings relevant information to support a future law that regulates a Brazilian National Policy of Industrial Effluents.

Metodologia TECLIM para uso racional de água na indústria: o banco de ideias no contexto da metodologia front-end loading / TECLIM method for rational water use in industry: the bank of ideas in the context of the front-end loading methodology

RESUMO O banco de ideias (BI) é uma ferramenta da metodologia TECLIM para otimização ambiental de processos industriais. Está conceitualmente associado com a metodologia front-end loading (FEL), a qual considera que forte atenção nas etapas iniciais de identificação e seleção de alternativas aumenta as chances de sucesso de um projeto, evitando que recursos sejam desperdiçados ou mal alocados. O BI abrange a etapa FEL 1, na qual é feito o levantamento de ideias, e segue até parte da etapa FEL 2, na qual as oportunidades selecionadas são desenvolvidas a projetos conceituais. O método para priorização de oportunidades no BI é apresentado demonstrando-se a sinergia com a FEL. A aplicação do BI permitiu o cadastro e processamento de 500 ideias com potencial de redução do consumo de água em 1,4 x 103 t.h-1 e de efluentes em pelo menos 0,5 x 103 t.h-1. O BI direciona recursos para projetos conceituais mais atrativos e sustentáveis.

ABSTRACT The bank of ideas (BI) is a TECLIM tool for environmental optimization of industrial processes. It is conceptually associated with the front-end loading (FEL) methodology, which pays particular attention to the initial stage of identification and selection of alternatives of water use, increasing the chances of a project´s success, avoiding wasted or badly allocated resources. The BI covers FEL 1 stage, in which the ideas are invited, followed by stage FEL 2, in which the opportunities selected are developed into conceptual projects. The method of giving priorities to the opportunities in the BI is presented, showing the synergy with FEL. The application of the BI enabled the register and process of 500 ideas with the potential to reduce water consumption by 1.4 x 103 t.h-1 and effluents by at least 0.5 x 103 t.h-1. The BI tool helps to identify the most attractive and sustainable conceptual projects.

Modeling simultaneous carbon and nitrogen removal (SCNR) in anaerobic/anoxic reactor treating domestic wastewater.

This paper presents a mathematical model based on the Anaerobic Digestion Model No. 1 (ADM1) to simulate the effects of nitrate concentration and hydraulic retention time (HRT) on the simultaneous carbon and nitrogen removal (SCNR) in anaerobic/anoxic reactor treating domestic wastewater. The model was calibrated using previously published experimental data obtained from anaerobic batch tests for different COD/ [Formula: see text] ratios. Model simulations were performed to predict the SCNR in a completely mixed reactor (CSTR) operating under mesophilic conditions (35 °C). Six different scenarios were evaluated to investigate the performance of the SCNR based on typical influent characteristics of domestic wastewater. The variables analyzed were chemical oxygen demand (COD) removal, nitrate concentration, methane production, nitrogen gas, volatile fatty acids (VFA) concentration, pH and percentage of COD used by the denitrifying and methanogenic microorganisms. The HRT was decreased stepwise from 15 to 4 h. The results indicate that Scenario (S5) with a COD/ [Formula: see text] ratio equal to 10 and an HRT equal to 15 h ensures the occurrence of the stable SCNR. Furthermore, the accumulation of denitrification intermediates and a significant reduction in the biogas production when the organic matter is limited was verified.

Utilização de coalescedor com leito de resinas de trocas catiônicas para pré-tratamento de óleo emulsionado em efluentes líquidos / Use of coalescer with a bed made of cationic exchange resins for pre-treatment of emulsified oil from oily wastewater

O tratamento de efluentes com coalescedor de leito consiste em induzir o aumento das gotas de óleo, pela passagem da emulsão por um leito poroso, para que elas possam, posteriormente, flotar por processo de separação gravitacional. O objetivo deste artigo foi apresentar considerações técnicas e experimentais sobre o uso do coalescedor de leito granular, com leito constituído por resinas de trocas catiônicas, visando o pré-tratamento de óleo emulsionado em efluentes líquidos. Os testes ocorreram em uma unidade em escala de bancada alimentada com emulsão óleo em água (O/A) com um teor de óleos e graxas (TOG) entre 200 e 400 mg.L-1 e diâmetro de gotas entre 3 a 8 μm. As velocidades do fluido (v) testadas foram entre 4,4 e 17,4 m.h-1. A altura do leito do coalescedor foi fixada em 5 cm. Os parâmetros usados para avaliar a eficiência dos testes foram eficiência de remoção de óleo (%E), pressão diferencial através do leito (Δp) e permeabilidade do leito (ko). Os resultados mostraram que o processo operou em estado estacionário e que os valores de TOG testados influenciaram no processo, bem como as velocidades do fluido, cuja elevação reduziu a eficiência significativamente. Os valores aproximados de %E obtidos foram 50 e 20-30%, para valores de v de 4,4 e 17,4 m.h-1, respectivamente.

The wastewater treatment with a bed coalescer consists of inducing the increase of oil droplets by passing the emulsion through a porous bed, so they can flote by gravitational separation process. The objective of this paper is to present technical and experimental considerations on the use of a granular bed coalescer, with a bed made of cationic exchange resins, for pre-treatment of emulsified oil from oily wastewater. Tests were conducted on a bench scale unit, which was fed with oil in water emulsion with oil and grease concentration (O & G) between 200 and 400 mg.L-1 and oil droplet diameter between 3 and 8 μm. The fluid velocities (v) tested were between 4.4 and 17.4 m.h-1. The coalescer bed height was fixed at 5 cm. The parameters used for assessing the tests efficiency were oil removal efficiency percentage (%E), differential pressure across the bed and, bed permeability. Results showed that the process operates in a steady-state condition and that the influent O&G affected the process efficiency, as well as the fluid velocities which reduced the efficiency significantly, with its increasing. The %E values obtained ​​were between 50 and 20-30% to v between 4.4 and 17.4 m.h-1, respectively.

Application of Anaerobic Digestion Model No. 1 for simulating anaerobic mesophilic sludge digestion.

Improving anaerobic digestion of sewage sludge by monitoring common indicators such as volatile fatty acids (VFAs), gas composition and pH is a suitable solution for better sludge management. Modeling is an important tool to assess and to predict process performance. The present study focuses on the application of the Anaerobic Digestion Model No. 1 (ADM1) to simulate the dynamic behavior of a reactor fed with sewage sludge under mesophilic conditions. Parametric sensitivity analysis is used to select the most sensitive ADM1 parameters for estimation using a numerical procedure while other parameters are applied without any modification to the original values presented in the ADM1 report. The results indicate that the ADM1 model after parameter estimation was able to predict the experimental results of effluent acetate, propionate, composites and biogas flows and pH with reasonable accuracy. The simulation of the effect of organic shock loading clearly showed that an organic shock loading rate above of 35kg/m(3) day affects the performance of the reactor. The results demonstrate that simulations can be helpful to support decisions on predicting the anaerobic digestion process of sewage sludge.

Tratamento de água produzida de petróleo para remoção de óleo por processos de separação por membranas: revisão / Produced water treatment for oil removal by membrane separation process: review

O gerenciamento da água produzida (AP) de petróleo se constitui em um enorme desafio para as empresas petrolíferas. As alternativas usualmente adotadas para o seu destino são o descarte, injeção e o reúso. Em todos os casos é necessário tratamento da AP, a fim de evitar danos ao meio ambiente e às instalações de produção ou a fim de permitir o seu reúso sem causar prejuízos aos processos nos quais a AP será utilizada. Os processos de separação por membranas (PSM) têm se mostrado capazes de tratar efluentes que apresentam elevados teores de óleo em emulsão e de partículas com tamanhos médios e pequenos, competindo, assim, com tecnologias de tratamento mais complexas, tais como flotação. O objetivo deste artigo foi apresentar uma revisão sobre o tratamento de AP utilizando os PSM discutindo os principais aspectos da AP e os aspectos conceituais dos PSM, com ênfase para sua aplicação para remoção de óleo da AP.

The management of oil produced water (PW) constitutes a major challenge to oil companies. The options usually adopted for PW are disposal, injection and reuse. In all cases, a PW treatment is required in order to avoid damages to the environment and to production facilities or to allow its reuse without causing damage to processes in which the PW is used. The membrane separation processes (MSP) has been shown to be capable of treating effluent with high content of emulsified oil and with medium and small sizes particle, competing well with more complex treatment technologies such as flotation. The aim of this paper was to present a review of the PW treatment by MSP, discussing the main aspects of the PW and the conceptual aspects of the MSP, with emphasis on their application for removal of oil from the PW.

Oral administration of an anti-inflammatory does not compromise the efficacy of intra-testicular injection of zinc gluconate as a contraceptive for dogs.

The objective was to determine whether the efficacy of zinc gluconate (Testoblock(®)) as a chemical contraceptive in male dogs was compromised in the presence of metamizole sodium (a nonsteroidal antiinflammatory/analgesic agent). Ten sexually mature mongrel dogs were assigned to two groups, a control group (n = 5) and a treated group (n = 5). Testoblock(®), a proprietary zinc-gluconate (13.1 mg zinc/ml) solution in a physiological vehicle, was injected into each testis (0.2-1.0 ml/testis, based on testis width). Half of the dogs (treated group) were also given metamizole sodium (also known as sodium dipyrone) orally (25mg/kg three times a day for 2 days), starting 2-3 h after testis injection. A physical examination and assessment of testis width, hematology, clinical chemistry (hepatic and renal function) and semen characteristics, were done immediately after treatment and then every 2 months for 180 days. There was no post-treatment scrotal biting or licking, although there was transient testicular swelling in both control and treated dogs during the first 3 days after injection. At 60 days after injection, all dogs were azoospermic. At 120 and 180 days, seven dogs had azoospermia and the remaining three (two control and one treated) had apparent aspermia (no ejaculate could be collected). There were no significant differences between groups for clinical findings or any aspect of hematology, renal, or hepatic function. In conclusion, giving metamizole sodium concurrent with an intra-testicular injection of a zinc-based solution did not interfere with chemical sterilization and it improved animal welfare.

Redes neurais artificiais aplicadas ao processo de coagulação / Artificial neural networks applied to the coagulation process

A coagulação é uma etapa de tratamento da água, e para tal são realizados ensaios de teste de jarro que permitem determinar a dose necessária dos agentes coagulante e químico de ajuste de pH no processo de coagulação. Contudo, esses ensaios demoram a ser executados, não respondendo em tempo real às mudanças da qualidade da água bruta. Para superar tal limitação, redes neurais artificiais multicamadas foram construídas (e seus pesos sinápticos ajustados), validadas e testadas para predizer a dosagem do hidróxido de sódio e do sulfato de alumínio - utilizados como agentes químico de ajuste de pH e coagulante, respectivamente. Os resultados dos modelos obtidos são compatíveis com os dados experimentais tendo em vista que as incertezas das estimativas estão na mesma ordem de grandeza das faixas indicadas pelos ensaios realizados de testes de jarro ao longo de quase seis anos.

Coagulation is a stage in water treatment and, for this, jar tests are performed, which allows determining the optimal coagulant and alkalizer doses in coagulation process. However, these tests are time-consuming and do not enable real-time responses to changes in raw water quality. To overcome these limitations, artificial multilayer perceptron neural networks were built, trained, validated and tested to predict the aluminum and sodium hydroxide doses - used as coagulant and alkalizer, respectively. The results of these models are encouraging to consider that the estimated uncertainties have the same order of the variation limits magnitude indicated by the jar tests for almost a six-year period.

Simulation of aerated lagoon using artificial neural networks and multivariate regression techniques.

The aim of this study was to develop an empirical model that provides accurate predictions of the biochemical oxygen demand of the output stream from the aerated lagoon at International Paper of Brazil, one of the major pulp and paper plants in Brazil. Predictive models were calculated from functional link neural networks (FLNNs), multiple linear regression, principal components regression, and partial least-squares regression (PLSR). Improvement in FLNN modeling capability was observed when the data were preprocessed using the PLSR technique. PLSR also proved to be a powerful linear regression technique for this problem, which presents operational data limitations.