STATISTICAL OPTIMIZATION OF ETTRINGITE PRECIPITATION IN LANDFILL LEACHATE
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , |
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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Brazilian Journal of Chemical Engineering |
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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 |
_version_ |
1754213175977312256 |