Identifying and quantifying secondhand smoke in source and receptor rooms: logistic regression and chemical mass balance approaches.
Indoor Air
; 24(1): 59-70, 2014 Feb.
Article
em En
| MEDLINE
| ID: mdl-23631597
ABSTRACT
Identifying and quantifying secondhand tobacco smoke (SHS) that drifts between multiunit homes is critical to assessing exposure. Twenty-three different gaseous and particulate measurements were taken during controlled emissions from smoked cigarettes and six other common indoor source types in 60 single-room and 13 two-room experiments. We used measurements from the 60 single-room experiments for (i) the fitting of logistic regression models to predict the likelihood of SHS and (ii) the creation of source profiles for chemical mass balance (CMB) analysis to estimate source apportionment. We then applied these regression models and source profiles to the independent data set of 13 two-room experiments. Several logistic regression models correctly predicted the presence of cigarette smoke more than 80% of the time in both source and receptor rooms, with one model correct in 100% of applicable cases. CMB analysis of the source room provided significant PM2.5 concentration estimates of all true sources in 9 of 13 experiments and was half-correct (i.e., included an erroneous source or missed a true source) in the remaining four. In the receptor room, CMB provided significant estimates of all true sources in 9 of 13 experiments and was half-correct in another two.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Poluição por Fumaça de Tabaco
/
Poluição do Ar em Ambientes Fechados
/
Material Particulado
/
Compostos Orgânicos Voláteis
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
País/Região como assunto:
America do norte
Idioma:
En
Revista:
Indoor Air
Assunto da revista:
SAUDE AMBIENTAL
Ano de publicação:
2014
Tipo de documento:
Article
País de afiliação:
Estados Unidos