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    A Novel Experimental and Machine Learning Model to Remove COD in a Batch Reactor Equipped with Microalgae
    (Springer Science and Business Media Deutschland GmbH, 2023-07-01)
    By using microorganisms and the microalgae Chlorella vulgaris in conjunction with sequencing batch reactors (SBRs), the performance of a wastewater treatment facility was studied. For this purpose, the effect of pH, temperature, COD inlet , and air flowrate on COD removal rate and residual was investigated. A single-factorial optimization method is utilized to optimize the amount of COD removal, and the best result is obtained with a pH of 8, CODinlet=600mg/l , and an airflow rate of 55 l/min. Under optimal conditions, the amount of residual COD in the effluent reached 36 mg / l , showing an augmentation in the efficiency of the desired system. Moreover, empirical correlations are proposed for double-factorial optimization of residual COD and COD removal. Also, a multilayer perceptron artificial neural network is proposed to model the process and predict the residual COD concentration. The useful technique of hyperparameter tuning is utilized to obtain the best result for the predictions. All the effective parameters, including the number of hidden layers, neurons, epochs, and batch size, are adjusted. Data from the experiments agreed well with the artificial neural network modeling results. For this modeling, the values of the correlation coefficient (R2) and mean absolute error (MAE) were obtained as 0.98 and 2%, respectively.
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    Integrating microplastic management into a broader wastewater decision-making framework. Is activated granular sludge (AGS) a game changer?
    (Elsevier Ltd, 2025-01-01)
    Wastewater treatment plants (WWTPs) are not specifically designed to tackle microplastics (MPs), leaving them in aquatic ecosystems. The novelty of our study is a critical review of the effectiveness of conventional activated sludge (CAS), membrane bioreactors (MBRs), and activated granular sludge (AGS) in managing MPs within WWTPs. We bridge a gap in scientific literature by assessing MP removal and resilience to MPs. Our scope extends beyond MPs management, evaluating these technologies against environmental, economic, and social criteria. Findings show that MBR outperforms CAS and AGS in MP removal but faces challenges with smaller MPs due to fouling and secondary pollution. AGS shows similar removal rates to CAS but often superior resilience to MPs, given its higher decontamination capabilities. Environmentally, AGS may better reduce indirect greenhouse gas (GHG) emissions due to lower energy and chemical demands. Moreover, AGS exhibits higher resource recovery potential (e.g., biopolymers, phosphates). Socially, MBR excels in pathogen removal, reducing waterborne disease risks. Economically, AGS is the most cost-effective technology regarding both operational and capital expenditures. However, MPs can impact these criteria by reducing nutrient removal efficiency and increasing both direct and indirect GHGs. MPs create “plastisphere” habitats, reducing pathogen removal and compromising water safety. Moreover, MPs increase energy and chemical use, especially in MBR systems due to fouling concerns.
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