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Fine particle sources and cardiorespiratory morbidity: an application of chemical mass balance and factor analytical source-apportionment methods.

Sarnat JA, Marmur A, Klein M, Kim E, Russell AG, Sarnat SE, Mulholland JA, Hopke PK, Tolbert PE - Environ. Health Perspect. (2008)

Bottom Line: Few epidemiologic studies, however, have included source-apportionment estimates in their examinations of PM health effects.We estimated the risk ratio (RR) associated with same day PM concentrations using Poisson generalized linear models.Generally, the epidemiologic results were robust to the selection of source-apportionment method, with strong agreement between the RR estimates from the PMF and CMB-LGO models, as well as with results from models using single-species tracers as surrogates of the source-apportioned PM(2.5) values.

View Article: PubMed Central - PubMed

Affiliation: Rollins School of Public Health of Emory University, Department of Environmental and Occupational Health, 1518 Clifton Rd., Room 260, Atlanta, GA 30322, USA. jsarnat@sph.emory.edu

ABSTRACT

Background: Interest in the health effects of particulate matter (PM) has focused on identifying sources of PM, including biomass burning, power plants, and gasoline and diesel emissions that may be associated with adverse health risks. Few epidemiologic studies, however, have included source-apportionment estimates in their examinations of PM health effects. We analyzed a time-series of chemically speciated PM measurements in Atlanta, Georgia, and conducted an epidemiologic analysis using data from three distinct source-apportionment methods.

Objective: The key objective of this analysis was to compare epidemiologic findings generated using both factor analysis and mass balance source-apportionment methods.

Methods: We analyzed data collected between November 1998 and December 2002 using positive-matrix factorization (PMF), modified chemical mass balance (CMB-LGO), and a tracer approach. Emergency department (ED) visits for a combined cardiovascular (CVD) and respiratory disease (RD) group were assessed as end points. We estimated the risk ratio (RR) associated with same day PM concentrations using Poisson generalized linear models.

Results: There were significant, positive associations between same-day PM(2.5) (PM with aero-dynamic diameter

Conclusions: Despite differences among the source-apportionment methods, these findings suggest that modeled source-apportioned data can produce robust estimates of acute health risk. In Atlanta, there were consistent associations across methods between PM(2.5) from mobile sources and biomass burning with both cardiovascular and respiratory ED visits, and between sulfate-rich secondary PM(2.5) with respiratory visits.

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Related in: MedlinePlus

Agreement of estimated RRs (0-day lag) for all RD and CVD between (A) CMB and PMF (R2 = 0.87), (B) CMB and single-species tracers (R2 = 0.76), and (C) PMF and single-species tracers (R2 = 0.87). Observations are taken from the comparable source categories.
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f4-ehp0116-000459: Agreement of estimated RRs (0-day lag) for all RD and CVD between (A) CMB and PMF (R2 = 0.87), (B) CMB and single-species tracers (R2 = 0.76), and (C) PMF and single-species tracers (R2 = 0.87). Observations are taken from the comparable source categories.

Mentions: Analyses comparing the observed RR estimates for source categories identified by all three methods indicated strong agreement among the three source-apportionment methods. Scatterplots of the RR values from CMB-LGO predicting the RR values from PMF, the RR values from PMF predicting the RR values from the tracer method, and the RR values from CMB-LGO predicting the RR values from the tracer method showed approximate one-to-one associations (Figure 4). Variability in observed RR estimates within the CMB-LGO model output, for example, explained 87% of the corresponding variability in the PMF-based RRs.


Fine particle sources and cardiorespiratory morbidity: an application of chemical mass balance and factor analytical source-apportionment methods.

Sarnat JA, Marmur A, Klein M, Kim E, Russell AG, Sarnat SE, Mulholland JA, Hopke PK, Tolbert PE - Environ. Health Perspect. (2008)

Agreement of estimated RRs (0-day lag) for all RD and CVD between (A) CMB and PMF (R2 = 0.87), (B) CMB and single-species tracers (R2 = 0.76), and (C) PMF and single-species tracers (R2 = 0.87). Observations are taken from the comparable source categories.
© Copyright Policy - public-domain
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2290994&req=5

f4-ehp0116-000459: Agreement of estimated RRs (0-day lag) for all RD and CVD between (A) CMB and PMF (R2 = 0.87), (B) CMB and single-species tracers (R2 = 0.76), and (C) PMF and single-species tracers (R2 = 0.87). Observations are taken from the comparable source categories.
Mentions: Analyses comparing the observed RR estimates for source categories identified by all three methods indicated strong agreement among the three source-apportionment methods. Scatterplots of the RR values from CMB-LGO predicting the RR values from PMF, the RR values from PMF predicting the RR values from the tracer method, and the RR values from CMB-LGO predicting the RR values from the tracer method showed approximate one-to-one associations (Figure 4). Variability in observed RR estimates within the CMB-LGO model output, for example, explained 87% of the corresponding variability in the PMF-based RRs.

Bottom Line: Few epidemiologic studies, however, have included source-apportionment estimates in their examinations of PM health effects.We estimated the risk ratio (RR) associated with same day PM concentrations using Poisson generalized linear models.Generally, the epidemiologic results were robust to the selection of source-apportionment method, with strong agreement between the RR estimates from the PMF and CMB-LGO models, as well as with results from models using single-species tracers as surrogates of the source-apportioned PM(2.5) values.

View Article: PubMed Central - PubMed

Affiliation: Rollins School of Public Health of Emory University, Department of Environmental and Occupational Health, 1518 Clifton Rd., Room 260, Atlanta, GA 30322, USA. jsarnat@sph.emory.edu

ABSTRACT

Background: Interest in the health effects of particulate matter (PM) has focused on identifying sources of PM, including biomass burning, power plants, and gasoline and diesel emissions that may be associated with adverse health risks. Few epidemiologic studies, however, have included source-apportionment estimates in their examinations of PM health effects. We analyzed a time-series of chemically speciated PM measurements in Atlanta, Georgia, and conducted an epidemiologic analysis using data from three distinct source-apportionment methods.

Objective: The key objective of this analysis was to compare epidemiologic findings generated using both factor analysis and mass balance source-apportionment methods.

Methods: We analyzed data collected between November 1998 and December 2002 using positive-matrix factorization (PMF), modified chemical mass balance (CMB-LGO), and a tracer approach. Emergency department (ED) visits for a combined cardiovascular (CVD) and respiratory disease (RD) group were assessed as end points. We estimated the risk ratio (RR) associated with same day PM concentrations using Poisson generalized linear models.

Results: There were significant, positive associations between same-day PM(2.5) (PM with aero-dynamic diameter

Conclusions: Despite differences among the source-apportionment methods, these findings suggest that modeled source-apportioned data can produce robust estimates of acute health risk. In Atlanta, there were consistent associations across methods between PM(2.5) from mobile sources and biomass burning with both cardiovascular and respiratory ED visits, and between sulfate-rich secondary PM(2.5) with respiratory visits.

Show MeSH
Related in: MedlinePlus