The use of response surface methodology for modelling and analysis of water and wastewater treatment processes: a review

In recent years, response surface methodology (RSM) has been used for modelling and optimising a variety of water and wastewater treatment processes. RSM is a collection of mathematical and statistical techniques for building models, evaluating the effects of several variables, and obtaining the val...

Full description

Saved in:
Bibliographic Details
Published in:Water science and technology 2014-01, Vol.69 (3), p.464-478
Main Authors: NAIR, Abhilash T, MAKWANA, Abhipsa R, MANSOOR AHAMMED, M
Format: Article
Language:English
Subjects:
Adsorption
Applied sciences
Disinfection
Electrochemical Techniques
Exact sciences and technology
Flocculation
General purification processes
Mathematical models
Modelling
Models, Theoretical
Oxidation
Oxidation-Reduction
Pollution
Process variables
Response surface methodology
Statistical analysis
Wastewater
Wastewater treatment
Wastewaters
Water analysis
Water Purification
Water treatment
Water treatment and pollution
Citations: Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In recent years, response surface methodology (RSM) has been used for modelling and optimising a variety of water and wastewater treatment processes. RSM is a collection of mathematical and statistical techniques for building models, evaluating the effects of several variables, and obtaining the values of process variables that produce desirable values of the response. This paper reviews the recent information on the use of RSM in different water and wastewater treatment processes. The theoretical principles and steps for its application are first described. The recent investigations on its application in coagulation-flocculation, adsorption, advanced oxidation processes, electro-chemical processes and disinfection are reviewed. The limitations of the methodology are highlighted. Attempts made to improve the RSM by combining it with other modelling techniques are also described.
ISSN:0273-1223
1996-9732
DOI:10.2166/wst.2013.733