Influence of Particles Size on NIR Spectroscopic Estimations of Charcoal Properties
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Floresta e Ambiente |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872019005000113 |
Resumo: | ABSTRACT The objective of this study was to evaluate the influence of particle size of charcoal samples on the predictive model statistics of charcoal chemical composition based on the NIR spectroscopy. Spectra of Acacia and of Eucalyptus charcoal were collected in the 100, 60 and 40 mesh granulometry, besides the powder remaining at the bottom of the sieves sets. They were subjected to principal component analysis and partial least square regression in order to estimate of volatile material (VMC), ash (AC) and fixed carbon content (FCC) values. The estimation of the FCC, VMC and AC of Eucalyptus based on NIR was more accurate using spectra of lower-particle-size powder. The models for Acacia charcoal were better using spectra measured at 40 mesh to predict FCC, 100 mesh for AC, and smaller size for VMC. NIR spectroscopy was efficient in estimating the immediate chemical composition of charcoal, except for AC. |
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Floresta e Ambiente |
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Influence of Particles Size on NIR Spectroscopic Estimations of Charcoal Propertieswood pyrolysisNIRproximate chemical analysisforest biomassABSTRACT The objective of this study was to evaluate the influence of particle size of charcoal samples on the predictive model statistics of charcoal chemical composition based on the NIR spectroscopy. Spectra of Acacia and of Eucalyptus charcoal were collected in the 100, 60 and 40 mesh granulometry, besides the powder remaining at the bottom of the sieves sets. They were subjected to principal component analysis and partial least square regression in order to estimate of volatile material (VMC), ash (AC) and fixed carbon content (FCC) values. The estimation of the FCC, VMC and AC of Eucalyptus based on NIR was more accurate using spectra of lower-particle-size powder. The models for Acacia charcoal were better using spectra measured at 40 mesh to predict FCC, 100 mesh for AC, and smaller size for VMC. NIR spectroscopy was efficient in estimating the immediate chemical composition of charcoal, except for AC.Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro2019-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872019005000113Floresta e Ambiente v.26 n.spe1 2019reponame:Floresta e Ambienteinstname:Universidade Federal do Rio de Janeiro (UFRJ)instacron:UFRJ10.1590/2179-8087.039718info:eu-repo/semantics/openAccessRamalho,Fernanda Maria GuedesSimetti,RodrigoArriel,Taiana GuimarãesLoureiro,Breno AssisHein,Paulo Ricardo Gherardieng2021-03-19T00:00:00Zoai:scielo:S2179-80872019005000113Revistahttps://www.floram.org/PUBhttps://old.scielo.br/oai/scielo-oai.phpfloramjournal@gmail.com||floram@ufrrj.br||2179-80871415-0980opendoar:2021-03-19T00:00Floresta e Ambiente - Universidade Federal do Rio de Janeiro (UFRJ)false |
dc.title.none.fl_str_mv |
Influence of Particles Size on NIR Spectroscopic Estimations of Charcoal Properties |
title |
Influence of Particles Size on NIR Spectroscopic Estimations of Charcoal Properties |
spellingShingle |
Influence of Particles Size on NIR Spectroscopic Estimations of Charcoal Properties Ramalho,Fernanda Maria Guedes wood pyrolysis NIR proximate chemical analysis forest biomass |
title_short |
Influence of Particles Size on NIR Spectroscopic Estimations of Charcoal Properties |
title_full |
Influence of Particles Size on NIR Spectroscopic Estimations of Charcoal Properties |
title_fullStr |
Influence of Particles Size on NIR Spectroscopic Estimations of Charcoal Properties |
title_full_unstemmed |
Influence of Particles Size on NIR Spectroscopic Estimations of Charcoal Properties |
title_sort |
Influence of Particles Size on NIR Spectroscopic Estimations of Charcoal Properties |
author |
Ramalho,Fernanda Maria Guedes |
author_facet |
Ramalho,Fernanda Maria Guedes Simetti,Rodrigo Arriel,Taiana Guimarães Loureiro,Breno Assis Hein,Paulo Ricardo Gherardi |
author_role |
author |
author2 |
Simetti,Rodrigo Arriel,Taiana Guimarães Loureiro,Breno Assis Hein,Paulo Ricardo Gherardi |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Ramalho,Fernanda Maria Guedes Simetti,Rodrigo Arriel,Taiana Guimarães Loureiro,Breno Assis Hein,Paulo Ricardo Gherardi |
dc.subject.por.fl_str_mv |
wood pyrolysis NIR proximate chemical analysis forest biomass |
topic |
wood pyrolysis NIR proximate chemical analysis forest biomass |
description |
ABSTRACT The objective of this study was to evaluate the influence of particle size of charcoal samples on the predictive model statistics of charcoal chemical composition based on the NIR spectroscopy. Spectra of Acacia and of Eucalyptus charcoal were collected in the 100, 60 and 40 mesh granulometry, besides the powder remaining at the bottom of the sieves sets. They were subjected to principal component analysis and partial least square regression in order to estimate of volatile material (VMC), ash (AC) and fixed carbon content (FCC) values. The estimation of the FCC, VMC and AC of Eucalyptus based on NIR was more accurate using spectra of lower-particle-size powder. The models for Acacia charcoal were better using spectra measured at 40 mesh to predict FCC, 100 mesh for AC, and smaller size for VMC. NIR spectroscopy was efficient in estimating the immediate chemical composition of charcoal, except for AC. |
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=S2179-80872019005000113 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872019005000113 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/2179-8087.039718 |
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 |
Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro |
publisher.none.fl_str_mv |
Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro |
dc.source.none.fl_str_mv |
Floresta e Ambiente v.26 n.spe1 2019 reponame:Floresta e Ambiente instname:Universidade Federal do Rio de Janeiro (UFRJ) instacron:UFRJ |
instname_str |
Universidade Federal do Rio de Janeiro (UFRJ) |
instacron_str |
UFRJ |
institution |
UFRJ |
reponame_str |
Floresta e Ambiente |
collection |
Floresta e Ambiente |
repository.name.fl_str_mv |
Floresta e Ambiente - Universidade Federal do Rio de Janeiro (UFRJ) |
repository.mail.fl_str_mv |
floramjournal@gmail.com||floram@ufrrj.br|| |
_version_ |
1750128143237120000 |