Abstract
Removal of arsenic from water is of utmost priorities on a global scenario due to its ill effects. Therefore, in the present study, aluminium oxide nano-particles (nano-alumina) were synthesised via solution combustion method, which is self-propagating and eco-friendly in nature. Synthesised nano-alumina was further employed for arsenate removal from water. Usually, pre-oxidation of arsenite is performed for better removal of arsenic in its pentavalent form. Thus, arsenate removal as a function of influencing parameters such as initial concentration, dose, pH, temperature, and competing anions was the prime objective of the present study. The speciation analysis showed that H2AsO4– and HAsO42− were co-existing anions between pH 6 and 8, as a result of which higher removal was observed. Freundlich isotherm model was well suited for data on adsorption. At optimal temperature of 298 K, maximum monolayer adsorption capacity was found as 1401.90 μg/g. The kinetic data showed film diffusion step was the controlling mechanism. In addition, competing anions like nitrate, bicarbonate, and chloride had no major effect on arsenate removal efficiency, while phosphate and sulphate significantly reduced the removal efficiency. The negative values of thermodynamic parameters ΔH° (− 23.15 kJ/mol) established the exothermic nature of adsorption, whereas the negative values of ΔG° (− 7.05, − 6.51, − 5.97, and − 5.43 kJ/mol at 298, 308, 318, and 328 K respectively) indicated the spontaneous nature of the process. The best-fitted isotherm was used to design a batch adsorber to estimate the required amount of aluminium oxide nano-particles for achieving the desired equilibrium arsenate concentration. Nano-alumina was also applied to treat the collected arsenic-contaminated groundwater from actual field. Experimental data were used to develop a neural network–based model for the effective prediction of removal efficiency without carrying out any extra experimentation.
Similar content being viewed by others
References
Abu Tarboush BJ, Chouman A, Jonderian A, Ahmad M, Hmadeh M, Al-Ghoul M (2018) Metal–organic framework-74 for ultratrace arsenic removal from water: experimental and density functional theory studies. ACS Applied Nano Mater 1(7):3283–3292
Afkhami A, Saber-Tehrani M, Bagheri H (2010) Simultaneous removal of heavy-metal ions in wastewater samples using nano-alumina modified with 2,4-dinitrophenylhydrazine. J Hazard Mater 181(1–3):836–844
Ahmadi MH, Mohseni-Gharyehsafa B, Farzaneh-Gord M, Jilte RD, Kumar R, Chau KW (2019) Applicability of connectionist methods to predict dynamic viscosity of silver/water nanofluid by using ANN-MLP, MARS and MPR algorithms. Eng Appl Comput Fluid Mech 13(1):220–228
Ali I, Gupta VK, Khan TA, Asim M (2012) Removal of arsenate from aqueous solution by electro-coagulation method using Al-Fe electrodes. Int J Electrochem Sci 7:1898–1907
Ali I, Al-Othman ZA, Alwarthan A, Asim M, Khan TA (2014) Removal of arsenic species from water by batch and column operations on bagasse fly ash. Environ Sci Pollut Res 21(5):3218–3229
Alizadeh MJ, Nodoushan EJ, Kalarestaghi N, Chau KW (2017) Toward multi-day-ahead forecasting of suspended sediment concentration using ensemble models. Environ Sci Pollut Res 24(36):28017–28025
Allen SJ, Mckay G, Porter JF (2004) Adsorption isotherm models for basic dye adsorption by peat in single and binary component systems. J Colloid Interface Sci 280(2):322–333
AlOmar MK, Alsaadi MA, Hayyan M, Akib S, Hashim MA (2016) Functionalization of CNTs surface with phosphonuim based deep eutectic solvents for arsenic removal from water. Appl Surf Sci 389:216–226
APHA (2012) Standards for examination of water and waste water. American Public Health Association, America Water Works Association, 22nd edn. Water Environment Federation, Washington DC
Awual MR, Hossain MA, Shenashen MA, Yaita T, Suzuki S, Jyo A (2013) Evaluating of arsenic (V) removal from water by weak-base anion exchange adsorbents. Environ Sci Pollut Res 20(1):421–430
Baghban A, Jalali A, Shafiee M, Ahmadi MH, Chau KW (2019) Developing an ANFIS-based swarm concept model for estimating the relative viscosity of nanofluids. Eng Appl Computat Fluid Mech 13(1):26–39
Banerjee S, Dubey S, Gautam RK, Chattopadhyaya MC, Sharma YC (2019) Adsorption characteristics of alumina nanoparticles for the removal of hazardous dye, orange G from aqueous solutions. Arab J Chem 12(8):5339–5354
Bentahar Y, Hurel C, Draoui K, Khairoun S, Marmier N (2016) Adsorptive properties of Moroccan clays for the removal of arsenic (V) from aqueous solution. Appl Clay Sci 119:385–392
Bissen M, Frimmel FH (2003) Arsenic—a review. Part I: occurrence, toxicity, speciation, mobility. Acta Hydrochim Hydrobiol 31(1):9–18
Bhatnagar A, Kumar E, Sillanpää M (2010) Nitrate removal from water by nano-alumina: Characterization and sorption studies. Chem Eng J 163(3):317–323
Boyd GE, Adamson AW, Myers LS Jr (1947) The exchange adsorption of ions from aqueous solutions by organic zeolites. II. Kinetics1. J Am Chem Soc 69(11):2836–2848
Carlin DJ, Naujokas MF, Bradham KD, Cowden J, Heacock M, Henry HF et al (2015) Arsenic and environmental health: state of the science and future research opportunities. Environ Health Perspect 124(7):890–899
Chaudhry SA, Ahmed M, Siddiqui SI, Ahmed S (2016) Fe (III)–Sn (IV) mixed binary oxide-coated sand preparation and its use for the removal of arsenite and arsenate from water: application of isotherm, kinetic and thermodynamics. J Mol Liq 224:431–441
Chen XY, Chau KW (2019) Uncertainty analysis on hybrid double feedforward neural network model for sediment load estimation with LUBE method. Water Resour Manag 33(10):3563–3577
Cho DW, Chon CM, Yang H, Tsang YF, Song H (2018) Effect of Mn substitution on the oxidation/adsorption abilities of iron (III) oxyhydroxides. Clean Techn Environ Policy 20(10):2201–2208
Darban AK, Kianinia Y, Taheri-Nassaj E (2013) Synthesis of nano-alumina powder from impure kaolin and its application for arsenite removal from aqueous solutions. J Environ Health Sci Eng 11(1):19
Dubey SP, Nguyen TT, Kwon YN, Lee C (2015) Synthesis and characterization of metal-doped reduced graphene oxide composites, and their application in removal of Escherichia coli, arsenic and 4-nitrophenol. J Ind Eng Chem 29:282–288
EPA (2000). “Regulations on the Disposal of Arsenic Residuals from Drinking Water Treatment Plants”. Office of Research and Development, U.S. EPA, EPA/600/R-00/ 025. May .http://www.epa.gov/ORD/WebPubs/residuals/index.htm
Foroutan R, Mohammadi R, Adeleye AS, Farjadfard S, Esvandi Z, Arfaeinia H, Sahebi S (2019) Efficient arsenic (V) removal from contaminated water using natural clay and clay composite adsorbents. Environ Sci Pollut Res 26(29):29748–29762
Ghosh S, Prabhakar R, Samadder SR (2019) Performance of γ-aluminium oxide nanoparticles for arsenic removal from groundwater. Clean Techn Environ Policy 21(1):121–138
Giles DE, Mohapatra M, Issa TB, Anand S, Singh P (2011) Iron and aluminium based adsorption strategies for removing arsenic from water. J Environ Manag 92(12):3011–3022
Hajahmadi Z, Younesi H, Bahramifar N, Khakpour H, Pirzadeh K (2015) Multicomponent isotherm for biosorption of Zn (II), CO (II) and cd (II) from ternary mixture onto pretreated dried Aspergillus niger biomass. Water Resour Ind 11:71–80
Han C, Pu H, Li H, Deng L, Huang S, He S, Luo Y (2013) The optimization of As (V) removal over mesoporous alumina by using response surface methodology and adsorption mechanism. J Hazard Mater 254:301–309
Ho YS, McKay G (1998) The kinetics of sorption of basic dyes from aqueous solution by sphagnum moss peat. Can J Chem Eng 76(4):822–827
Hughes MF, Del Razo LM, Kenyon EM (2000) Dose-dependent effects on tissue distribution and metabolism of dimethylarsinic acid in the mouse after intravenous administration. Toxicology 143(2):155–166
Khan TA, Chaudhry SA, Ali I (2013) Thermodynamic and kinetic studies of arsenate removal from water by zirconium oxide-coated marine sand. Environ Sci Pollut Res 20(8):5425–5440
Lata S, Samadder SR (2016) Removal of arsenic from water using nano adsorbents and challenges: a review. J Environ Manag 166:387–406
Lata S, Prabhakar R, Adak A, Samadder SR (2019) As (V) removal using biochar produced from an agricultural waste and prediction of removal efficiency using multiple regression analysis. Environ Sci Pollut Res 26(31):32175–32188
Lunge S, Singh S, Sinha A (2014) Magnetic iron oxide (Fe3O4) nanoparticles from tea waste for arsenic removal. J Magn Magn Mater 356:21–31
Majumder A, Ramrakhiani L, Mukherjee D, Mishra U, Halder A, Mandal AK, Ghosh S (2019) Green synthesis of iron oxide nanoparticles for arsenic remediation in water and sludge utilization. Clean Techn Environ Policy 21(4):795–813
Mazumder DG (2008) Chronic arsenic toxicity & human health. Indian J Med Res 128(4):436–447
Mishra T, Mahato DK (2016) A comparative study on enhanced arsenic (V) and arsenic (III) removal by iron oxide and manganese oxide pillared clays from ground water. J Environ Chem Eng 4(1):1224–1230
Murcott S (2012) Arsenic contamination in the world. IWA publishing
Nassar MY, Khatab M (2016) Cobalt ferrite nanoparticles via a template-free hydrothermal route as an efficient nano-adsorbent for potential textile dye removal. RSC Adv 6(83):79688–79705
Nassar MY, Mohamed TY, Ahmed IS, Samir I (2017) MgO nanostructure via a sol-gel combustion synthesis method using different fuels: an efficient nano-adsorbent for the removal of some anionic textile dyes. J Mol Liq 225:730–740
Powers M, Yracheta J, Harvey D, O’Leary M, Best LG, Bear AB, Morgan C (2019) Arsenic in groundwater in private wells in rural North Dakota and South Dakota: water quality assessment for an intervention trial. Environ Res 168:41–47
Pintor AM, Vieira BR, Santos SC, Boaventura RA, Botelho CM (2018) Arsenate and arsenite adsorption onto iron-coated cork granulates. Sci Total Environ 642:1075–1089
Prabhakar R, Samadder SR (2018) Low cost and easy synthesis of aluminium oxide nanoparticles for arsenite removal from groundwater: a complete batch study. J Mol Liq 250:192–201
Razavi R, Sabaghmoghadam A, Bemani A, Baghban A, Chau KW, Salwana E (2019) Application of ANFIS and LSSVM strategies for estimating thermal conductivity enhancement of metal and metal oxide based nanofluids. Eng Appl Comput Fluid Mech 13(1):560–578
Roy PK, Majumder A, Banerjee G, Roy MB, Pal S, Mazumdar A (2015) Removal of arsenic from drinking water using dual treatment process. Clean Techn Environ Policy 17(4):1065–1076
Samiey B, Cheng CH, Wu J (2014) Organic-inorganic hybrid polymers as adsorbents for removal of heavy metal ions from solutions: a review. Materials 7(2):673–726
Sarkar A, Paul B (2016) The global menace of arsenic and its conventional remediation-a critical review. Chemosphere 158:37–49
Sharma YC, Srivastava V, Singh VK, Kaul SN, Weng CH (2009) Nano-adsorbents for the removal of metallic pollutants from water and wastewater. Environ Technol 30(6):583–609
Shamshirband S, Jafari Nodoushan E, Adolf JE, Abdul Manaf A, Mosavi A, Chau KW (2019) Ensemble models with uncertainty analysis for multi-day ahead forecasting of chlorophyll a concentration in coastal waters. Eng Appl Comput Fluid Mech 13(1):91–101
Shih MC (2005) An overview of arsenic removal by pressure-drivenmembrane processes. Desalination 172(1):85–97
Taşar Ş, Kaya F, Özer A (2014) Biosorption of lead (II) ions from aqueous solution by peanut shells: equilibrium, thermodynamic and kinetic studies. J Environ Chem Eng 2(2):1018–1026
Temkin MJ, Pyzhev V (1940) Recent modifications to Langmuir isotherms. Acta Phys -Chim Sin 12:217–222
Thanh DN, Bastl Z, Černá K, Ulbrich P, Lederer J (2016) Amorphous nanosized Al–Ti–Mn trimetal hydrous oxides: synthesis, characterization and enhanced performance in arsenic removal. RSC Adv 6(103):100732–100742
Vaclavikova M, Gallios GP, Hredzak S, Jakabsky S (2008) Removal of arsenic from water streams: an overview of available techniques. Clean Techn Environ Policy 10(1):89–95
W.U.J.W. Supply (2014) S.M. Programme progress on drinking water and sanitation: 2014 update, World Health Organization,
Weber WJ, Morris JC (1963) Kinetics of adsorption on carbon from solution. J Sanit Eng Div 89(2):31–60
Weber TW, Chakravorti RK (1974) Pore and solid diffusion models for fixed-bed adsorbers. AICHE J 20(2):228–238
Youngran J, FAN M, Van Leeuwen J, Belczyk JF (2007) Effect of competing solutes on arsenic(V) adsorption using iron and aluminum oxides. J Environ Sci 19(8):910–919
Acknowledgements
The authors acknowledge the Department of Environmental Science & Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad, for providing experimental facilities.
Funding
This study was financially supported by the Science & Engineering Research Board (A Statutory body of Department of Science and Technology, Govt. of India) (Project No. SB/EMEQ-010/2014).
Author information
Authors and Affiliations
Corresponding author
Additional information
Responsible Editor: Tito Roberto Cadaval Jr.
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
ESM 1
(DOCX 20 kb)
Rights and permissions
About this article
Cite this article
Prabhakar, R., Samadder, S.R. Use of adsorption-influencing parameters for designing the batch adsorber and neural network–based prediction modelling for the aqueous arsenate removal using combustion synthesised nano-alumina. Environ Sci Pollut Res 27, 26367–26384 (2020). https://doi.org/10.1007/s11356-020-08975-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11356-020-08975-y