Removal of arsenic from water by supported nano zero-valent iron on activated carbon

Zhu, Huijie; Jia, Yongfeng; Wu, Xing; Wang, He

doi:10.1016/j.jhazmat.2009.08.031

Cited by 623 publications

(231 citation statements)

References 35 publications

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“…The relationship of the electrostatic force between As(V) ions and α-Fe 2 O 3 explains the influence of pH on As(V) sorption. This has been well described in previous studies concerning As(V) sorption on other adsorbents (Zhu et al, 2009;Chang et al, 2010;Sheng et al, 2012). …”

Section: Effect Of Phsupporting

confidence: 86%

“…5b. As the solution pH increases from an acidic region to an alkaline region, As(V) ions in solution exist mainly as H 3 AsO 4 at pH<2.2 (pK a1 ), H 2 AsO 4 − at pH 2.2-6.98 (pK a2 ), HAsO 4 2− at pH 6.98-11.5 (pK a3 ), and AsO 4 3− at pH>11.5 (Zhu et al, 2009;Chang et al, 2010). When the pH is below the isoelectric point of α-Fe 2 O 3 , the surface of α-Fe 2 O 3 will be positively charged and favorable for As(V) sorption.…”

Section: Effect Of Phmentioning

confidence: 99%

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Synthesis of flower-like α-Fe2O3 and its application in wastewater treatment

Xie

Wang

Liu

et al. 2014

J. Zhejiang Univ. Sci. A

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Abstract:The removal of arsenic from aqueous solution is crucial to human health and environmental pollution. Herein, flower-like α-Fe 2 O 3 nanostructures were synthesized via a template-free microwave-assisted solvothermal technique, and were applied as adsorbents for the removal of arsenic (As(V)) from aqueous solutions. The results indicated that the synthesized flower-like α-Fe 2 O 3 showed excellent sorption properties and had a maximum sorption capacity of 47.64 mg/g for As(V). Meanwhile, the experimental results of photodegradation of methylene blue (MB) indicated that the as-synthesized flower-like α-Fe 2 O 3 exhibited very high photocatalytic performance for the photodegradation of MB and that the as-obtained flower-like α-Fe 2 O 3 nanostructures were suitable materials in wastewater treatment.

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Section: Effect Of Phsupporting

confidence: 86%

Section: Effect Of Phmentioning

confidence: 99%

Synthesis of flower-like α-Fe2O3 and its application in wastewater treatment

Xie

Wang

Liu

et al. 2014

J. Zhejiang Univ. Sci. A

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“…Although most of the adsorbents mentioned above are considered good adsorbents, CNWs offer higher adsorption capacity and performance due to high specific surface areas and a high reactive group density on the surface (Eyley and Thielemans, 2014). In addition to acting as an adsorbent, the cellulose-derived material has also showed potential as a support for a primary adsorbent (activated carbon) in wastewater treatment, or also served as a backbone structure upon which the main adsorbent is attached (Zhu et al, 2009) is a further example for the use of modified CNWs as an adsorbent to remove pollutants from water.…”

Section: Introductionmentioning

confidence: 99%

Predicting the capability of carboxylated cellulose nanowhiskers for the remediation of copper from water using response surface methodology (RSM) and artificial neural network (ANN) models

Hamid

Jenidi

Thielemans

et al. 2016

Industrial Crops and Products

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This study observed the influence of temperature, initial Cu(II) ion concentration, and sorbent dosage on the Cu(II) removal from the water matrix using surface-oxidized cellulose nanowhiskers (CNWs) bearing carboxylate functionalities. In addition, this study focused on the actual conditions in a wastewater treatment plant. Conductometric titration of CNWs suspensions showed a surface charge of 54 and 410 mmol/kg for the unmodified and modified CNWs, respectively, which indicated that the modified CNWs provide a relatively high surface area per unit mass than the unmodified CNWs. In addition, the stability of the modified CNWs was tested under different conditions and proved that the functional groups were permanent and not degraded. Response surface methodology (RSM) and artificial neural network (ANN) models were employed in order to optimize the system and to create a predictive model to evaluate the Cu(II) removal performance of the modified CNWs. The performance of the ANN and RSM models were statistically evaluated in terms of the coefficient of determination (R 2 ), 2 absolute average deviation (AAD), and the root mean squared error (RMSE) on predicted experiment outcomes. Moreover, to confirm the model suitability, unseen experiments were conducted for 14 new trials not belonging to the training data set and located both inside and outside of the training set boundaries. Result showed that the ANN model (R 2 =0.9925, AAD = 1.15%, RMSE = 1.66) outperformed the RSM model (R 2 =0.9541, AAD = 7.07%, RMSE = 3.99) in terms of the R 2 , AAD, and RMSE when predicting the Cu (II) removal and is thus more reliable. The Langmuir and Freundlich isotherm models were applied to the equilibrium data and the results revealed that Langmuir isotherm (R 2 = 0.9998) had better correlation than the Freundlich isotherm (R 2 = 0.9461). Experimental data were also tested in terms of kinetics studies using pseudo-first order and pseudo-second order kinetic models. The results showed that the pseudo-second-order model accurately described the kinetics of adsorption.

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“…It has been proven that nZVIs are efficient for the degradation of halogenated hydrocarbons (Wang et al, 2012), polychlorinated biphenyls (PCBs) (Petersen et al, 2012) or metals (Zhu et al, 2009), but information about their reactivity with pharmaceutical products (PPs) is scarce. PPs have been massively used and are considered emergent contaminants because they have been introduced in soils and waters through (i) human excretions in sewage collectors (especially from hospital effluents (Heberer, 2002)), (ii) disposal of unwanted, unused or expired products in the toilet or sink, and (iii) land application of animal manure (O'Connor and Aga, 2007) and treated sewage sludge (Kinney et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Application of green zero-valent iron nanoparticles to the remediation of soils contaminated with ibuprofen

Machado

Stawiński

Slonina

et al. 2013

Science of The Total Environment

174

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Zero-valent iron nanoparticles (nZVIs) are often used in environmental remediation. Their high surface area that is associated with their high reactivity makes them an excellent agent capable of transforming/degrading contaminants in soils and waters. Due to the recent development of green methods for the production of nZVIs, the use of this material became even more attractive. However, the knowledge of its capacity to de-grade distinct types of contaminants is still scarce. The present work describes the study of the application of green nZVIs to the remediation of soils contami-nated with a common antiinflammatory drug, ibuprofen. The main objectives of this work were to produce nZVIs using extracts of grape marc, black tea and vine leaves, to verify the degradation of ibuprofen in aque-ous solutions by the nZVIs, to study the remediation process of a sandy soil contaminated with ibuprofen using the nZVIs, and to compare the experiments with other common chemical oxidants. The produced nZVIs had nanometric sizes and were able to degrade ibuprofen (54 to 66% of the initial amount) in aqueous solutions. Similar remediation efficiencies were obtained in sandy soils. In this case the remediation could be enhanced (achieving degradation efficiencies above 95%) through the complemen-tation of the process with a catalyzed nZVI Fenton-like reaction. These results indicate that this remediation technology represents a good alternative to traditional and more aggressive technologies.

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Removal of arsenic from water by supported nano zero-valent iron on activated carbon

Cited by 623 publications

References 35 publications

Synthesis of flower-like α-Fe2O3 and its application in wastewater treatment

Synthesis of flower-like α-Fe2O3 and its application in wastewater treatment

Predicting the capability of carboxylated cellulose nanowhiskers for the remediation of copper from water using response surface methodology (RSM) and artificial neural network (ANN) models

Application of green zero-valent iron nanoparticles to the remediation of soils contaminated with ibuprofen

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