Methodology for minimum nitrogen compounds removal efficiencies estimation and wastewater treatment systems pre-selection: a watershed approach
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | RBRH (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312019000100239 |
Resumo: | ABSTRACT Nitrogen is a very important parameter for water pollution control since nitrification implies in aquatic environment oxygen consumption and some nitrogen forms are toxic. In the present study, an optimization model was developed and applied aiming at simultaneous organic matter and nitrogen compounds minimum removal efficiencies determination. A water quality model and the Genetic Algorithm Metaheuristic were associated in order to solve the optimization problem. The estimated minimum efficiencies conditioned the sewage treatment systems pre-selection. The study area was the Pardo River watershed (Espírito Santo State, Brazil). The results indicate that the treatment systems need to be more efficient in ammonia removal when the treated effluents disposed in watercourses that present high pH values because ammonia toxicity increases with pH. Considering the boundary conditions assumed in this study, the pre-selection process indicated activated sludge systems, submerged aerated biofilter with nitrification, or with biological nitrogen removal, for Ibatiba city. Simpler systems such as primary treatment with septic tanks, stabilization ponds, UASB reactors and biological filters were pre-selected for Santíssima Trindade and Nossa Senhora das Graças towns. |
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Methodology for minimum nitrogen compounds removal efficiencies estimation and wastewater treatment systems pre-selection: a watershed approachNitrogenWater quality modelOptimizationGenetic algorithmSewage treatmentABSTRACT Nitrogen is a very important parameter for water pollution control since nitrification implies in aquatic environment oxygen consumption and some nitrogen forms are toxic. In the present study, an optimization model was developed and applied aiming at simultaneous organic matter and nitrogen compounds minimum removal efficiencies determination. A water quality model and the Genetic Algorithm Metaheuristic were associated in order to solve the optimization problem. The estimated minimum efficiencies conditioned the sewage treatment systems pre-selection. The study area was the Pardo River watershed (Espírito Santo State, Brazil). The results indicate that the treatment systems need to be more efficient in ammonia removal when the treated effluents disposed in watercourses that present high pH values because ammonia toxicity increases with pH. Considering the boundary conditions assumed in this study, the pre-selection process indicated activated sludge systems, submerged aerated biofilter with nitrification, or with biological nitrogen removal, for Ibatiba city. Simpler systems such as primary treatment with septic tanks, stabilization ponds, UASB reactors and biological filters were pre-selected for Santíssima Trindade and Nossa Senhora das Graças towns.Associação Brasileira de Recursos Hídricos2019-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312019000100239RBRH v.24 2019reponame:RBRH (Online)instname:Associação Brasileira de Recursos Hídricos (ABRH)instacron:ABRH10.1590/2318-0331.241920180173info:eu-repo/semantics/openAccessSá,Glaucia de Laia NascimentoReis,José Antonio Tosta dosMendonça,Antonio Sérgio FerreiraSilva,Fernando das Graças Braga daeng2019-10-15T00:00:00Zoai:scielo:S2318-03312019000100239Revistahttps://www.scielo.br/j/rbrh/https://old.scielo.br/oai/scielo-oai.php||rbrh@abrh.org.br2318-03311414-381Xopendoar:2019-10-15T00:00RBRH (Online) - Associação Brasileira de Recursos Hídricos (ABRH)false |
dc.title.none.fl_str_mv |
Methodology for minimum nitrogen compounds removal efficiencies estimation and wastewater treatment systems pre-selection: a watershed approach |
title |
Methodology for minimum nitrogen compounds removal efficiencies estimation and wastewater treatment systems pre-selection: a watershed approach |
spellingShingle |
Methodology for minimum nitrogen compounds removal efficiencies estimation and wastewater treatment systems pre-selection: a watershed approach Sá,Glaucia de Laia Nascimento Nitrogen Water quality model Optimization Genetic algorithm Sewage treatment |
title_short |
Methodology for minimum nitrogen compounds removal efficiencies estimation and wastewater treatment systems pre-selection: a watershed approach |
title_full |
Methodology for minimum nitrogen compounds removal efficiencies estimation and wastewater treatment systems pre-selection: a watershed approach |
title_fullStr |
Methodology for minimum nitrogen compounds removal efficiencies estimation and wastewater treatment systems pre-selection: a watershed approach |
title_full_unstemmed |
Methodology for minimum nitrogen compounds removal efficiencies estimation and wastewater treatment systems pre-selection: a watershed approach |
title_sort |
Methodology for minimum nitrogen compounds removal efficiencies estimation and wastewater treatment systems pre-selection: a watershed approach |
author |
Sá,Glaucia de Laia Nascimento |
author_facet |
Sá,Glaucia de Laia Nascimento Reis,José Antonio Tosta dos Mendonça,Antonio Sérgio Ferreira Silva,Fernando das Graças Braga da |
author_role |
author |
author2 |
Reis,José Antonio Tosta dos Mendonça,Antonio Sérgio Ferreira Silva,Fernando das Graças Braga da |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Sá,Glaucia de Laia Nascimento Reis,José Antonio Tosta dos Mendonça,Antonio Sérgio Ferreira Silva,Fernando das Graças Braga da |
dc.subject.por.fl_str_mv |
Nitrogen Water quality model Optimization Genetic algorithm Sewage treatment |
topic |
Nitrogen Water quality model Optimization Genetic algorithm Sewage treatment |
description |
ABSTRACT Nitrogen is a very important parameter for water pollution control since nitrification implies in aquatic environment oxygen consumption and some nitrogen forms are toxic. In the present study, an optimization model was developed and applied aiming at simultaneous organic matter and nitrogen compounds minimum removal efficiencies determination. A water quality model and the Genetic Algorithm Metaheuristic were associated in order to solve the optimization problem. The estimated minimum efficiencies conditioned the sewage treatment systems pre-selection. The study area was the Pardo River watershed (Espírito Santo State, Brazil). The results indicate that the treatment systems need to be more efficient in ammonia removal when the treated effluents disposed in watercourses that present high pH values because ammonia toxicity increases with pH. Considering the boundary conditions assumed in this study, the pre-selection process indicated activated sludge systems, submerged aerated biofilter with nitrification, or with biological nitrogen removal, for Ibatiba city. Simpler systems such as primary treatment with septic tanks, stabilization ponds, UASB reactors and biological filters were pre-selected for Santíssima Trindade and Nossa Senhora das Graças towns. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-01-01 |
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=S2318-03312019000100239 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312019000100239 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/2318-0331.241920180173 |
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 |
Associação Brasileira de Recursos Hídricos |
publisher.none.fl_str_mv |
Associação Brasileira de Recursos Hídricos |
dc.source.none.fl_str_mv |
RBRH v.24 2019 reponame:RBRH (Online) instname:Associação Brasileira de Recursos Hídricos (ABRH) instacron:ABRH |
instname_str |
Associação Brasileira de Recursos Hídricos (ABRH) |
instacron_str |
ABRH |
institution |
ABRH |
reponame_str |
RBRH (Online) |
collection |
RBRH (Online) |
repository.name.fl_str_mv |
RBRH (Online) - Associação Brasileira de Recursos Hídricos (ABRH) |
repository.mail.fl_str_mv |
||rbrh@abrh.org.br |
_version_ |
1754734701920124928 |