Utilization of Alyssum mucilage as a natural coagulant in oily-saline wastewater treatment

Fard, Moein Besharati; Hamidi, Donya; Yetilmezsoy, Kaan; Alavi, Javad; Hosseinpour, Fatemeh

doi:10.1016/j.jwpe.2020.101763

Cited by 48 publications

(14 citation statements)

References 85 publications

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“…The optimal ANN structure was determined based on three performance measures MAPE, NRMSE, and R. Some authors have applied coagulation-flocculation as a primary treatment and used Machine Learning (ML) algorithms to estimate some efficiencies of the treatment. Beshrati [16], used Alyssum mucilage and Polyaluminium chloride as coagulants on oily-saline wastewater and applied ANN and Adaptive Neuro Fuzzy Inference System (ANFIS), to predict COD removal efficiency based on input parameters (pH, coagulant dose and contact time), obtaining high accuracy in both models for predicting COD removal. Adaobi [17] used Picralima Nitida Extract (PNE) on landfill leachate and applied Response Surface Methodology (RMS) and ANN using coagulation-flocculation variables like pH, PNE dosage, and time as inputs to estimate the COD reduction process, obtaining superior accuracy on ANN.…”

Section: Discussionmentioning

confidence: 99%

Machine Learning Techniques in the Dosage of Biopolymers and Coagulants for Leachate Treatment

Matovelle¹,

Quinteros²,

Heras³

2023

Preprint

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The leachate discharges generated in sanitary landfills contain many pollutants that are harmful to the environment; treatments are scarce and should be carried out better. The use of coagulation-flocculation processes has been one of the most widely used, but that; Due to the complexity of the characterization of the leachate, the dosing strategy of coagulants and biopolymers needs to be clarified. Therefore, the present study is carried out to determine the doses of coagulants and biopolymers suitable for coagulation-flocculation processes in the treatment of leachates by using computational models of machine learning techniques such as Artificial Neural Networks (ANN); these allow to decrease the operations of the tests of jars in the laboratory; optimizing resources. Through laboratory experimentation, there are real results of the effectiveness of applying biopolymers in leachate treatments at different concentration levels. The laboratory results were taken as input variables for the algorithms used; after the validation and calibration process, we proceeded to estimate predicted data with the computational model, obtaining predictions of optimal doses for treatment with high statistical adjustment indicators. It is verified that the applied coagulation-flocculation treatments reduce the turbidity values in the leachate and contaminants associated with suspended solids. In this way, the jar tests are optimized so that the operational costs decrease without affecting the results of adequate dosing.

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Section: Discussionmentioning

confidence: 99%

Machine Learning Techniques in the Dosage of Biopolymers and Coagulants for Leachate Treatment

Matovelle¹,

Quinteros²,

Heras³

2023

Preprint

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“…Gravity (Caplan et al, 2000), flotation (Hanafy & Nabih, 2007), and filtration (Ahmad et al, 2018; Tomaszewska et al, 2005) methods were used as physical separation methods. Coagulation (Fard et al, 2021; Hamidi et al, 2021), Fenton oxidation (Öz & Çetin, 2021), membrane distillation (Gryta, 2020), and photocatalysis (Cazoir et al, 2012) methods were used as chemical treatment methods. Anaerobic treatment (Emadian et al, 2015), biofilms (Vyrides et al, 2018), and aerobic treatment (Nisenbaum et al, 2020) methods were used as biological treatment methods.…”

Section: Introductionmentioning

confidence: 99%

The investigation of parameters affecting the treatment of synthetic bilge water by continuous electrooxidation/flotation process

Akbarzadeh Yazdi,

Yilmaz,

Güler

et al. 2024

Water & Environment J

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This study addresses the pressing issue of bilge water pollution from ships, a highly oily and hazardous wastewater source. The research employs the electrooxidation/flotation process, known for its effectiveness in organic matter removal. Key parameters, such as initial pH, current density and flow rate, were investigated for their impact on the removal of chemical oxygen demand (COD) and oil‐grease (OG) from bilge water. Initial pH showed minimal effects on COD and OG removal, while current density significantly enhanced removal efficiency by influencing anodic electrochemical reactions. Conversely, higher flow rates reduced residence time and lowered removal efficiency. Optimal conditions, with a current density of 10 mA/cm2, pH 7.5 and a flow rate of 20 ml/min, achieved impressive results, removing approximately 80% of COD and 99% of OG from bilge water. These findings highlight the potential of this method for effective bilge water purification.

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“…The principle of coagulation is the destabilization of suspended particles by reducing the repulsive forces between the particles by adding the coagulant. Destabilized particles then collide with each other to form a large size of floc which easily precipitates [3,4]. The effectiveness of coagulation depends on several factors, for example, temperature, pH, coagulant type and dose, and mixing conditions.…”

Section: Introductionmentioning

confidence: 99%

Effect of Rapid-Mixing Duration on Floc Growth in the Coagulation of Peat Water with Sesbania grandiflora Seed as Measured by DinoCapture 2.0

Putra¹,

Fitria²

2023

Atlantis Highlights in Chemistry and Pharmaceutical Sciences

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The coagulation treatment was applied to the synthetic peat water using Sesbania grandiflora seed. One of the factors to enhance coagulation is rapid and slow mixing. Rapid mixing is crucial to promote the interaction of coagulant with suspended particles and the formation of micro flocs. While slow mixing is crucial to promote aggregation between microflocs. In this study, rapid mixing was varied from 5 to 10 and 15 min during the coagulation process. Microscopic method analysis was used to obtain the data using a camera and computer. Flocs formed are captured by DinoCapture 2.0 software equipped with a Dino-Lite handheld digital microscope resulting in microscopic images of the flocs. Afterward, direct measurement of a magnified floc image is applied by using a calibrated scale on the floc image, so a large number of floc sizes can be obtained. Image analysis results from DinoCapture 2.0 showed that the longer duration of the rapid-mixing time, the larger size of floc formed, but in contrast, the number of flocs decreased. The optimum time for rapid mixing was 5 min and 30 min for slow mixing, according to the highest number of flocs formed, with the floc size spread evenly under 0.2 mm. Rapid-mixing time of 5/30 min was applied to the coagulation of peat water so that the floc could grow well and coagulation could be carried out optimally. This is because a mixing time that is too short can reduce floc formation, but a very long mixing time can cause floc breakage.

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Utilization of Alyssum mucilage as a natural coagulant in oily-saline wastewater treatment

Cited by 48 publications

References 85 publications

Machine Learning Techniques in the Dosage of Biopolymers and Coagulants for Leachate Treatment

Machine Learning Techniques in the Dosage of Biopolymers and Coagulants for Leachate Treatment

The investigation of parameters affecting the treatment of synthetic bilge water by continuous electrooxidation/flotation process

Effect of Rapid-Mixing Duration on Floc Growth in the Coagulation of Peat Water with Sesbania grandiflora Seed as Measured by DinoCapture 2.0

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