Optimization of the electrocoagulation process for the removal of lead from water using aluminium as electrode material

Bouguerra, Wided; Barhoumi, Afef; Ibrahim, Nesrine; Brahmi, Khaled; Limam, Aloui; Hamrouni, Béchir

doi:10.1080/19443994.2015.1015308

Cited by 30 publications

(10 citation statements)

References 49 publications

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“…This suggests that the release of OHions from water reduction reaction was higher than its consumption to form hydroxy complexes of Al. However, the pH change observed in the solution during the EC process was not substantial (1 to 2 unit) (Bouguerra et al, 2015;Maghanga JK et al, 2017). is amorphous in nature and forms sweep flocs with a large surface area (Ghernaout et al, 2009).…”

Section: Effect Of Phmentioning

confidence: 99%

Produced Water Treatment By Electrocoagulation Process: Experimental and Modelling Study

Agrawal

Nawaz

2022

Preprint

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Produced water (PW) is the largest by-product that comes out from wells during oil & gas (O&G) fields exploration. These waters contain high saline content along with other organic and inorganic composition. A mathematical model specifically for treatment of PW with electrocoagulation (EC) techniques has been developed. The mechanistic model considers the dominant Al species contribution to COD removal, multi-scale modelling of the EC reactor, the role of Al chloro complex species in impacting the COD removal and the development of mechanistic approach for the removal of COD by the Al complexes dominantly present in the system. The influence of experimental and model working parameters such as current density (10-20 mA/cm2), initial pH (3.1-8.6), interelectrode distance (1.35-4 cm), mixing speed (130-300 rpm) and scale up of EC reactor (0.3-1.5 L) on Al concentration and COD removal was investigated and modelled. The results showed that EC at the current density of 20 mA/cm2 enabled higher COD removal (78.3%) than at the current density of 10 mA/cm2 (68.3%) and 15 mA/cm2 (75%) and mathematical model prediction of COD removal fits well with the experimental data at 10 mA/cm2, and 15 mA/cm2 with R2 value of 0.96 and 0.97, respectively. The initial pH of 7.3 resulted in higher COD removal (95.85%) than the initial pH of 3.1 (64.5%), 6.1 (79.1%) and 8.6 (81.2%) and model reproduces a good fit at initial pH of 6.1, 7.3 and 8.6 with R2 value of 0.92, 0.96 and 0.98, respectively. The variation of constants involved in the model formulation was optimized according to the effect of model working parameters.

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Section: Effect Of Phmentioning

confidence: 99%

Produced Water Treatment By Electrocoagulation Process: Experimental and Modelling Study

Agrawal

Nawaz

2022

Preprint

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“…This result is obtained because the lead concentration in the solution is low enough, which is 10.92 mg.L -1 . On the other hand, lead ions can be precipitated at a low pH range of 1 to 5 as Pb(OH)2, PbCO3, and Pb3(CO3)2(OH)2 (Bouguerra et al 2015). It is suggested that in an acidic condition, the lead ion removal is due to the precipitation process, while in the alkaline condition, the lead ion removal is due to the EC process.…”

Section: The Effect Of Phmentioning

confidence: 99%

Copper and Lead Ions Removal by Electrocoagulation: Process Performance and Implications for Energy Consumption

Prasetyaningrum

Ariyanti

Widayat

et al. 2021

Int. J. Renew. Energy Dev.

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Electroplating wastewater contains high amount of heavy metals that can cause serious problems to humans and the environment. Therefore, it is necessary to remove heavy metals from electroplating wastewater. The aim of this research was to examine the electrocoagulation (EC) process for removing the copper (Cu) and lead (Pb) ions from wastewater using aluminum electrodes. It also analyzes the removal efficiency and energy requirement rate of the EC method for heavy metals removal from wastewater. Regarding this matter, the operational parameters of the EC process were varied, including time (20−40 min), current density (40−80 A/m2), pH (3−11), and initial concentration of heavy metals. The concentration of heavy metals ions was analyzed using the atomic absorption spectroscopy (AAS) method. The results showed that the concentration of lead and copper ions decreased with the increase in EC time. The current density was observed as a notable parameter. High current density has an effect on increasing energy consumption. On the other hand, the performance of the electrocoagulation process decreased at low pH. The higher initial concentration of heavy metals resulted in higher removal efficiency than the lower concentration. The removal efficiency of copper and lead ions was 89.88% and 98.76%, respectively, at 40 min with electrocoagulation treatment of 80 A/m2 current density and pH 9. At this condition, the speciﬁc amounts of dissolved electrodes were 0.2201 kg/m3, and the energy consumption was 21.6 kWh/m3. The kinetic study showed that the removal of the ions follows the first-order model.

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“…The increase of current intensity will improve the removal due to the increase of the anodes dissolution rate, and consequently, the increase of soluble and insoluble metal hydroxide species available to participate in fluoride retention (Mollah et al 2004). Moreover, the increase of the current intensity enhances the hydrogen bubbles production rate and the growth and size of the coagulant flocs, which can improve the removal efficiency (Bouguerra et al 2015). However, high current intensities lead to high energy consumption that, combined with a high anode dissolution rate, increases operating costs.…”

Section: Optimization Of the Cec Processmentioning

confidence: 99%

Modeling and optimization of a continuous electrocoagulation process using an artificial intelligence approach

2021

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An artificial neural network (ANN) with the topology 8-94-85-2 (input – hidden layer 1 - hidden layer 2 - output) was used to model the operation of the continuous electrocoagulation (CEC) process for the removal of fluoride from water. After the ANN training, the sum of the squared errors (MSE) and the determination coefficient (R2) of the testing set model predictions were 0.0088 and 0.999, respectively, showing a good generalization and model's predictive capacity. The optimization of the process cost using the genetic algorithm (GA) showed that the optimal conditions are highly dependent on the feed concentration and the fluoride removal requirements. For a 5 L of water containing 10 mg/L of fluoride, the optimal conditions to reduce the fluoride concentration below the permissible limit (1.5 mg/L) are 88.3 mA of current intensity, a flow rate of 73.6 mL/min, and the use of a series monopolar (SM) electrode configuration, corresponding to a fluoride removal of 85% and an operating cost of 0.05 €/L.

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Optimization of the electrocoagulation process for the removal of lead from water using aluminium as electrode material

Cited by 30 publications

References 49 publications

Produced Water Treatment By Electrocoagulation Process: Experimental and Modelling Study

Produced Water Treatment By Electrocoagulation Process: Experimental and Modelling Study

Copper and Lead Ions Removal by Electrocoagulation: Process Performance and Implications for Energy Consumption

Modeling and optimization of a continuous electrocoagulation process using an artificial intelligence approach

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