STATISTICAL OPTIMIZATION OF ETTRINGITE PRECIPITATION IN LANDFILL LEACHATE

Detalhes bibliográficos
Autor(a) principal: Aygun,Ahmet
Data de Publicação: 2018
Outros Autores: Dogan,Selim, Argun,Mehmet Emin
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Brazilian Journal of Chemical Engineering
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322018000300969
Resumo: Abstract In the present study, experiments were conducted to optimize sulfate removal efficiency with ettringite precipitation from landfill leachate using Response Surface Methodology (RSM) and Central Composite Design (CCD). The statistical analysis of the results showed that the operating parameters such as molar rates of Ca/SO4 and Al/SO4, and pH had a significant effect on sulfate removal efficiency. Aluminum hydroxide and calcium hydroxide were used for external sources of aluminum and calcium. The goodness of the model was checked by different criteria including the coefficient of determination (R2 = 0.94), p value (<0.0001), adequate precision (14.78), and coefficient of variance (7.30). The RSM results indicated that the fitted model could be appropriate to predict sulfate removal efficiency. A 55.7% maximum sulfate removal efficiency was obtained at pH 11.95 for 2.29 Ca/SO4 and 0.74 Al/SO4 molar ratios. Sulfate inhibition effects on treatment methods such as the anaerobic process decreased with increasing COD/SO4 ratio from 14:1 to 25:1 by ettringite precipitation.
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spelling STATISTICAL OPTIMIZATION OF ETTRINGITE PRECIPITATION IN LANDFILL LEACHATEEttringite PrecipitationLandfillLeachateResponse Surface Methodology (RSM)Sulphate RemovalAbstract In the present study, experiments were conducted to optimize sulfate removal efficiency with ettringite precipitation from landfill leachate using Response Surface Methodology (RSM) and Central Composite Design (CCD). The statistical analysis of the results showed that the operating parameters such as molar rates of Ca/SO4 and Al/SO4, and pH had a significant effect on sulfate removal efficiency. Aluminum hydroxide and calcium hydroxide were used for external sources of aluminum and calcium. The goodness of the model was checked by different criteria including the coefficient of determination (R2 = 0.94), p value (<0.0001), adequate precision (14.78), and coefficient of variance (7.30). The RSM results indicated that the fitted model could be appropriate to predict sulfate removal efficiency. A 55.7% maximum sulfate removal efficiency was obtained at pH 11.95 for 2.29 Ca/SO4 and 0.74 Al/SO4 molar ratios. Sulfate inhibition effects on treatment methods such as the anaerobic process decreased with increasing COD/SO4 ratio from 14:1 to 25:1 by ettringite precipitation.Brazilian Society of Chemical Engineering2018-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322018000300969Brazilian Journal of Chemical Engineering v.35 n.3 2018reponame:Brazilian Journal of Chemical Engineeringinstname:Associação Brasileira de Engenharia Química (ABEQ)instacron:ABEQ10.1590/0104-6632.20180353s20170528info:eu-repo/semantics/openAccessAygun,AhmetDogan,SelimArgun,Mehmet Emineng2019-01-15T00:00:00Zoai:scielo:S0104-66322018000300969Revistahttps://www.scielo.br/j/bjce/https://old.scielo.br/oai/scielo-oai.phprgiudici@usp.br||rgiudici@usp.br1678-43830104-6632opendoar:2019-01-15T00:00Brazilian Journal of Chemical Engineering - Associação Brasileira de Engenharia Química (ABEQ)false
dc.title.none.fl_str_mv STATISTICAL OPTIMIZATION OF ETTRINGITE PRECIPITATION IN LANDFILL LEACHATE
title STATISTICAL OPTIMIZATION OF ETTRINGITE PRECIPITATION IN LANDFILL LEACHATE
spellingShingle STATISTICAL OPTIMIZATION OF ETTRINGITE PRECIPITATION IN LANDFILL LEACHATE
Aygun,Ahmet
Ettringite Precipitation
Landfill
Leachate
Response Surface Methodology (RSM)
Sulphate Removal
title_short STATISTICAL OPTIMIZATION OF ETTRINGITE PRECIPITATION IN LANDFILL LEACHATE
title_full STATISTICAL OPTIMIZATION OF ETTRINGITE PRECIPITATION IN LANDFILL LEACHATE
title_fullStr STATISTICAL OPTIMIZATION OF ETTRINGITE PRECIPITATION IN LANDFILL LEACHATE
title_full_unstemmed STATISTICAL OPTIMIZATION OF ETTRINGITE PRECIPITATION IN LANDFILL LEACHATE
title_sort STATISTICAL OPTIMIZATION OF ETTRINGITE PRECIPITATION IN LANDFILL LEACHATE
author Aygun,Ahmet
author_facet Aygun,Ahmet
Dogan,Selim
Argun,Mehmet Emin
author_role author
author2 Dogan,Selim
Argun,Mehmet Emin
author2_role author
author
dc.contributor.author.fl_str_mv Aygun,Ahmet
Dogan,Selim
Argun,Mehmet Emin
dc.subject.por.fl_str_mv Ettringite Precipitation
Landfill
Leachate
Response Surface Methodology (RSM)
Sulphate Removal
topic Ettringite Precipitation
Landfill
Leachate
Response Surface Methodology (RSM)
Sulphate Removal
description Abstract In the present study, experiments were conducted to optimize sulfate removal efficiency with ettringite precipitation from landfill leachate using Response Surface Methodology (RSM) and Central Composite Design (CCD). The statistical analysis of the results showed that the operating parameters such as molar rates of Ca/SO4 and Al/SO4, and pH had a significant effect on sulfate removal efficiency. Aluminum hydroxide and calcium hydroxide were used for external sources of aluminum and calcium. The goodness of the model was checked by different criteria including the coefficient of determination (R2 = 0.94), p value (<0.0001), adequate precision (14.78), and coefficient of variance (7.30). The RSM results indicated that the fitted model could be appropriate to predict sulfate removal efficiency. A 55.7% maximum sulfate removal efficiency was obtained at pH 11.95 for 2.29 Ca/SO4 and 0.74 Al/SO4 molar ratios. Sulfate inhibition effects on treatment methods such as the anaerobic process decreased with increasing COD/SO4 ratio from 14:1 to 25:1 by ettringite precipitation.
publishDate 2018
dc.date.none.fl_str_mv 2018-09-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322018000300969
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322018000300969
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0104-6632.20180353s20170528
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Brazilian Society of Chemical Engineering
publisher.none.fl_str_mv Brazilian Society of Chemical Engineering
dc.source.none.fl_str_mv Brazilian Journal of Chemical Engineering v.35 n.3 2018
reponame:Brazilian Journal of Chemical Engineering
instname:Associação Brasileira de Engenharia Química (ABEQ)
instacron:ABEQ
instname_str Associação Brasileira de Engenharia Química (ABEQ)
instacron_str ABEQ
institution ABEQ
reponame_str Brazilian Journal of Chemical Engineering
collection Brazilian Journal of Chemical Engineering
repository.name.fl_str_mv Brazilian Journal of Chemical Engineering - Associação Brasileira de Engenharia Química (ABEQ)
repository.mail.fl_str_mv rgiudici@usp.br||rgiudici@usp.br
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