ABSTRACT
In this study, artificial neural network (ANN) tools were employed to forecast the adsorption capacity of Malachite green (MG) by baru fruit endocarp waste (B@FE) under diverse conditions, including pH, adsorbent dosage, initial dye concentration, contact time, and temperature. Enhanced adsorption efficiency was notably observed under alkaline pH conditions (pH 10). Kinetic analysis indicated that the adsorption process closely followed a pseudo-second-order model, while equilibrium studies revealed the Langmuir isotherm as the most suitable model, estimating a maximum adsorption capacity of 57.85 mg g-1. Furthermore, the chemical adsorption of MG by B@FE was confirmed using the Dubinin-Radushkevich isotherm. Thermodynamic analysis suggested that the adsorption is spontaneous and endothermic. Various ANN architectures were explored, employing different activation functions such as identity, logistic, tanh, and exponential. Based on evaluation metrics like the coefficient of determination (R2) and root mean square error (RMSE), the optimal network configuration was identified as a 5-11-1 architecture, consisting of five input neurons, eleven hidden neurons, and one output neuron. Notably, the logistic activation function was applied in both the hidden and output layers for this configuration. This study highlights the efficacy of B@FE as an efficient adsorbent for MG removal from aqueous solutions and demonstrates the potential of ANN models in predicting adsorption behavior across varying environmental conditions, emphasizing their utility in this field.
The innovative aspect of this study lies in the utilization of a new and effective adsorbent for the removal of Malachite Green (MG), derived from the fruit endocarp of baru (Dipteryx alata Vog.). The baru fruit endocarp, typically discarded as solid waste during processing, was found to possess favorable characteristics for adsorption processes and provides an adsorption capacity that exceeds that of most other similar adsorbents. Additionally, integrating Artificial Neural Networks (ANNs) enables accurate modeling of the adsorption process, eliminating the need for extensive laboratory experiments. This contributes significantly to wastewater treatment research, enhancing effectiveness and sustainability in unwanted dye removal.
ABSTRACT
Biodiesel is a clean renewable fuel used as alternative energy source to diesel and it is commercialized as a minor component in diesel blends. Similarly to diesel, biodiesel spill is a source of contamination for the ecosystem making necessary to provide effective remediation strategies. Bioremediation is a technology that has been applied with success to clean up hydrocarboncontaminated environments. In this study, fungal bioaugmentation strategy was compared with natural attenuation during bioremediation of a sandy soil contaminated with diesel, biodiesel and blends (B20 and B50). Respirometric assays simulating the contamination of soil were carried out in Bartha flasks used to measure microbial CO2 production. Penicillium sp. AV4 isolated from the wastewater of a biodiesel factory has the ability to degrade the fuels and was used in bioaugmentation. After 111 days, CO2 evolution demonstrated no significant difference in soil microbial activity between fungal augmentation and natural attenuation treatments for all fuels. The lack of influence of Penicillium sp. AV4 can be related to its inability to compete with soil microorganisms and/or increase its metabolic activity. During natural attenuation, B50 showed a higher CO2 production, followed by the B100, B20 and diesel, which is less biodegradable. Therefore, from a biodegradation perspective, biodiesel could be more beneficial than diesel during bioremediation spill.
Biodiesel é um combustível renovável utilizado como fonte energética alternativa ao diesel e é comercializado misturado a esse combustível. Assim como o diesel, derramamentos de biodiesel são fontes de contaminação dos ecossistemas, sendo necessário aplicar estratégias para a remediação. A biorremediação é uma tecnologia que vem sendo aplicada com sucesso para remediar ambientes contaminados com hidrocarbonetos. Neste trabalho, o bioenriquecimento fúngico foi comparado à atenuação natural durante a biorremediação de um solo arenoso contaminado com diesel, biodiesel e misturas (B20 e B50). Ensaios respirométricos foram efetuados, utilizando respirômetros de Bartha para avaliar a produção microbiana de CO2 no solo contaminado. Penicillium sp. AV4, isolado de efluentes de usina de biodiesel, possui a capacidade de degradar os combustíveis e foi usado no bioenriquecimento. Após 111 dias, a evolução de CO2 devido à atividade microbiana no solo não apresentou diferença estatística entre o bioenriquecimento fúngico e a atenuação natural, considerando todos os combustíveis. A ineficácia do fungo pode estar relacionada com sua incapacidade de competir com os microrganismos do solo e/ou expressar sua atividade metabólica degradadora. Durante a atenuação natural, B50 demonstrou maior produção de CO2, seguido por B100, B20 e diesel, o qual é menos biodegradável. Do ponto de vista da biodegradação, o biodiesel pode ser mais facilmente biorremediado do que o diesel.
ABSTRACT
ABSTRACT This study investigated the biosorption of the anionic textile dyes: Reactive Red 239 (RR239), Reactive Black B (RBB) and Direct Blue 85 (DB85) according to pH, biomass dosage, contact time and dye concentration onto waste beer yeast slurry. The kinetics and isotherm of the removal of dyes were also studied. The equilibrium of biosorption reaction was reached after 30 min for the reactive dyes and after 60 min for the direct dye. Optimum decolorization was observed at pH 2 and 0.63 g/L of biomass dosage. The kinetic data of the three dyes were better described by the pseudo second-order model. The adsorption process followed the Langmuir isotherm model and the biosorption capacity being estimated to be 152.9, 162.7 and 139.2 mg/g for RR239, RBB and DB85, respectively. Our findings indicated that the waste beer yeast slurry was an attractive low-cost biosorbent for the removal of anionic textile dyes from aqueous solution.
ABSTRACT
In this study, the potential for using an inoculum composed of a mixed-culture of bacteria and fungi, isolated from a landfarming at the Paulínia Oil Refinery, Brazil, to degrade oil residues generated in the process of petroleum refinement was investigated. The isolation of these microorganisms was carried out beforehand, assuming that they would be better adapted to petroleum hydrocarbons, as the landfarming consisted of an area impacted by the deposit of such compounds. The Bartha and Pramer respirometric test was used to measure the rate of biodegradation of the hydrocarbons by the mixed-culture of microorganisms via the evolution of CO2. The results obtained with respect to the efficiency of biodegradation showed no significant differences (P>0.05), indicating no increase in the biodegradation process using the inoculum. The addition of nutrients (N, P, K) also did not contribute to an increase in biodegradation of the oil residue studied.
Neste estudo foi investigado o potencial de um inóculo composto de cultura mista de bactérias e fungos, isolados do landfarming da Refinaria de Paulínia, Brasil, em degradar resíduos oleosos gerados no processo de refinamento de petróleo. O isolamento desses microrganismos foi realizado previamente, supondo-se que estejam melhor adaptados aos hidrocarbonetos de petróleo uma vez que o landfarming consiste em área impactada por deposição de tais compostos. Utilizou-se o teste respirométrico de Bartha e Pramer no intuito de verificar a taxa de biodegradação dos hidrocarbonetos pela cultura mista de microrganismos através da evolução de CO2. Os resultados obtidos para a eficiência da biodegradação não apresentaram diferença estatisticamente significativa (P>0.05) indicando que não houve aumento do processo de biodegradação com o uso do inóculo. A adição de nutrientes (N, P, K) tampouco contribuiu para aumentar a biodegradação do resíduo oleoso estudado.
