Modeling phosphorus adsorption onto polyaluminium chloride water treatment residuals

Beneficial reuse and appropriate disposal of water treatment residuals (WTRs) are of great concern for sustainable drinking water treatment. Using WTRs to remove phosphorus (P) is widely regarded as a feasible approach. However, the information is still limited on air-dried WTRs containing polyalumi...

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Autores principales:	Runbin Duan, Clifford B. Fedler
Formato:	article
Lenguaje:	EN
Publicado:	IWA Publishing 2021
Materias:	anionic polyacrylamide artificial neural network index of model performance polyaluminium chloride wtrs Water supply for domestic and industrial purposes TD201-500 River, lake, and water-supply engineering (General) TC401-506
Acceso en línea:	https://doaj.org/article/70fe7929213e45f28f36b50c8fc55e38
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id	oai:doaj.org-article:70fe7929213e45f28f36b50c8fc55e38
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spelling	oai:doaj.org-article:70fe7929213e45f28f36b50c8fc55e382021-11-06T07:05:03ZModeling phosphorus adsorption onto polyaluminium chloride water treatment residuals1606-97491607-079810.2166/ws.2020.322https://doaj.org/article/70fe7929213e45f28f36b50c8fc55e382021-02-01T00:00:00Zhttp://ws.iwaponline.com/content/21/1/458https://doaj.org/toc/1606-9749https://doaj.org/toc/1607-0798Beneficial reuse and appropriate disposal of water treatment residuals (WTRs) are of great concern for sustainable drinking water treatment. Using WTRs to remove phosphorus (P) is widely regarded as a feasible approach. However, the information is still limited on air-dried WTRs containing polyaluminium chloride (PAC) and anionic polyacrylamide (APAM) used to adsorb P. The objectives of this study were to construct artificial neural network (ANN) models for P adsorption onto WTRs from distilled de-ionized (DDI) water solution and stormwater, to investigate the performance of ANN in predicting phosphorous adsorption, and to model isotherm adsorption, kinetics, and thermodynamics by using the index of model performance. Batch experiments were performed with different WTRs dosage, pH, initial P concentration, temperature, and time. ANN models accurately predicted the P concentration at equilibrium. Non-linearized Langmuir model fitted the isotherm data best. Pseudo second-order kinetic model provided a better fit to experimental data. The adsorption process may be at least simultaneously controlled by surface adsorption and intraparticle diffusion. The P adsorption is a homogenous monolayer adsorption that is spontaneous, endothermic, and entropy production process. WTRs were found to be favorable and effective in removing P, but the P removals had significant differences in both solutions.Runbin DuanClifford B. FedlerIWA Publishingarticleanionic polyacrylamideartificial neural networkindex of model performancepolyaluminium chloridewtrsWater supply for domestic and industrial purposesTD201-500River, lake, and water-supply engineering (General)TC401-506ENWater Supply, Vol 21, Iss 1, Pp 458-469 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	anionic polyacrylamide artificial neural network index of model performance polyaluminium chloride wtrs Water supply for domestic and industrial purposes TD201-500 River, lake, and water-supply engineering (General) TC401-506
spellingShingle	anionic polyacrylamide artificial neural network index of model performance polyaluminium chloride wtrs Water supply for domestic and industrial purposes TD201-500 River, lake, and water-supply engineering (General) TC401-506 Runbin Duan Clifford B. Fedler Modeling phosphorus adsorption onto polyaluminium chloride water treatment residuals
description	Beneficial reuse and appropriate disposal of water treatment residuals (WTRs) are of great concern for sustainable drinking water treatment. Using WTRs to remove phosphorus (P) is widely regarded as a feasible approach. However, the information is still limited on air-dried WTRs containing polyaluminium chloride (PAC) and anionic polyacrylamide (APAM) used to adsorb P. The objectives of this study were to construct artificial neural network (ANN) models for P adsorption onto WTRs from distilled de-ionized (DDI) water solution and stormwater, to investigate the performance of ANN in predicting phosphorous adsorption, and to model isotherm adsorption, kinetics, and thermodynamics by using the index of model performance. Batch experiments were performed with different WTRs dosage, pH, initial P concentration, temperature, and time. ANN models accurately predicted the P concentration at equilibrium. Non-linearized Langmuir model fitted the isotherm data best. Pseudo second-order kinetic model provided a better fit to experimental data. The adsorption process may be at least simultaneously controlled by surface adsorption and intraparticle diffusion. The P adsorption is a homogenous monolayer adsorption that is spontaneous, endothermic, and entropy production process. WTRs were found to be favorable and effective in removing P, but the P removals had significant differences in both solutions.
format	article
author	Runbin Duan Clifford B. Fedler
author_facet	Runbin Duan Clifford B. Fedler
author_sort	Runbin Duan
title	Modeling phosphorus adsorption onto polyaluminium chloride water treatment residuals
title_short	Modeling phosphorus adsorption onto polyaluminium chloride water treatment residuals
title_full	Modeling phosphorus adsorption onto polyaluminium chloride water treatment residuals
title_fullStr	Modeling phosphorus adsorption onto polyaluminium chloride water treatment residuals
title_full_unstemmed	Modeling phosphorus adsorption onto polyaluminium chloride water treatment residuals
title_sort	modeling phosphorus adsorption onto polyaluminium chloride water treatment residuals
publisher	IWA Publishing
publishDate	2021
url	https://doaj.org/article/70fe7929213e45f28f36b50c8fc55e38
work_keys_str_mv	AT runbinduan modelingphosphorusadsorptionontopolyaluminiumchloridewatertreatmentresiduals AT cliffordbfedler modelingphosphorusadsorptionontopolyaluminiumchloridewatertreatmentresiduals
_version_	1718443859688554496

Modeling phosphorus adsorption onto polyaluminium chloride water treatment residuals

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