Abstract

Adsorption plays an important role in water and wastewater treatment. The analysis and design of processes that involve adsorption rely on the availability of isotherms that describe these adsorption processes. Adsorption isotherms are usually estimated empirically from measurements of the adsorption process variables. Unfortunately, these measurements are usually contaminated with errors that degrade the accuracy of estimated isotherms. Therefore, these errors need to be filtered for improved isotherm estimation accuracy. Multiscale wavelet based filtering has been shown to be a powerful filtering tool. In this work, multiscale filtering is utilized to improve the estimation accuracy of the Freundlich adsorption isotherm in the presence of measurement noise in the data by developing a multiscale algorithm for the estimation of Freundlich isotherm parameters. The idea behind the algorithm is to use multiscale filtering to filter the data at different scales, use the filtered data from all scales to construct multiple isotherms and then select among all scales the isotherm that best represents the data based on a cross validation mean squares error criterion. The developed multiscale isotherm estimation algorithm is shown to outperform the conventional time-domain estimation method through a simulated example.

Original languageEnglish
Pages (from-to)509-518
Number of pages10
JournalInternational Journal of Environmental Science and Technology
Volume7
Issue number3
Publication statusPublished - 2010

Fingerprint

Adsorption isotherms
Adsorption
Isotherms
adsorption
isotherm
Water Purification
Waste Water
water treatment
wastewater treatment
Water treatment
Wastewater treatment
Mean square error
estimation method
Availability
wavelet
filter

Keywords

  • Freundlich isotherm
  • Multiscale representation
  • Noise filtering
  • Parameter estimation

ASJC Scopus subject areas

  • Environmental Engineering
  • Environmental Chemistry
  • Agricultural and Biological Sciences(all)

Cite this

@article{53f672cda4364d3ab593e99d2dd28958,
title = "Multiscale estimation of the freundlich adsorption isotherm",
abstract = "Adsorption plays an important role in water and wastewater treatment. The analysis and design of processes that involve adsorption rely on the availability of isotherms that describe these adsorption processes. Adsorption isotherms are usually estimated empirically from measurements of the adsorption process variables. Unfortunately, these measurements are usually contaminated with errors that degrade the accuracy of estimated isotherms. Therefore, these errors need to be filtered for improved isotherm estimation accuracy. Multiscale wavelet based filtering has been shown to be a powerful filtering tool. In this work, multiscale filtering is utilized to improve the estimation accuracy of the Freundlich adsorption isotherm in the presence of measurement noise in the data by developing a multiscale algorithm for the estimation of Freundlich isotherm parameters. The idea behind the algorithm is to use multiscale filtering to filter the data at different scales, use the filtered data from all scales to construct multiple isotherms and then select among all scales the isotherm that best represents the data based on a cross validation mean squares error criterion. The developed multiscale isotherm estimation algorithm is shown to outperform the conventional time-domain estimation method through a simulated example.",
keywords = "Freundlich isotherm, Multiscale representation, Noise filtering, Parameter estimation",
author = "Mohamed Nounou and Hazem Nounou",
year = "2010",
language = "English",
volume = "7",
pages = "509--518",
journal = "International Journal of Environmental Science and Technology",
issn = "1735-1472",
publisher = "CEERS",
number = "3",

}

TY - JOUR

T1 - Multiscale estimation of the freundlich adsorption isotherm

AU - Nounou, Mohamed

AU - Nounou, Hazem

PY - 2010

Y1 - 2010

N2 - Adsorption plays an important role in water and wastewater treatment. The analysis and design of processes that involve adsorption rely on the availability of isotherms that describe these adsorption processes. Adsorption isotherms are usually estimated empirically from measurements of the adsorption process variables. Unfortunately, these measurements are usually contaminated with errors that degrade the accuracy of estimated isotherms. Therefore, these errors need to be filtered for improved isotherm estimation accuracy. Multiscale wavelet based filtering has been shown to be a powerful filtering tool. In this work, multiscale filtering is utilized to improve the estimation accuracy of the Freundlich adsorption isotherm in the presence of measurement noise in the data by developing a multiscale algorithm for the estimation of Freundlich isotherm parameters. The idea behind the algorithm is to use multiscale filtering to filter the data at different scales, use the filtered data from all scales to construct multiple isotherms and then select among all scales the isotherm that best represents the data based on a cross validation mean squares error criterion. The developed multiscale isotherm estimation algorithm is shown to outperform the conventional time-domain estimation method through a simulated example.

AB - Adsorption plays an important role in water and wastewater treatment. The analysis and design of processes that involve adsorption rely on the availability of isotherms that describe these adsorption processes. Adsorption isotherms are usually estimated empirically from measurements of the adsorption process variables. Unfortunately, these measurements are usually contaminated with errors that degrade the accuracy of estimated isotherms. Therefore, these errors need to be filtered for improved isotherm estimation accuracy. Multiscale wavelet based filtering has been shown to be a powerful filtering tool. In this work, multiscale filtering is utilized to improve the estimation accuracy of the Freundlich adsorption isotherm in the presence of measurement noise in the data by developing a multiscale algorithm for the estimation of Freundlich isotherm parameters. The idea behind the algorithm is to use multiscale filtering to filter the data at different scales, use the filtered data from all scales to construct multiple isotherms and then select among all scales the isotherm that best represents the data based on a cross validation mean squares error criterion. The developed multiscale isotherm estimation algorithm is shown to outperform the conventional time-domain estimation method through a simulated example.

KW - Freundlich isotherm

KW - Multiscale representation

KW - Noise filtering

KW - Parameter estimation

UR - http://www.scopus.com/inward/record.url?scp=77953547631&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77953547631&partnerID=8YFLogxK

M3 - Article

VL - 7

SP - 509

EP - 518

JO - International Journal of Environmental Science and Technology

JF - International Journal of Environmental Science and Technology

SN - 1735-1472

IS - 3

ER -