Fine particle sources and cardiorespiratory morbidity: An application of chemical mass balance and factor analytical source-apportionment methods | Health & Environmental Research Online (HERO)

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Citation
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HERO ID

97972

Reference Type

Journal Article

Title

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

Author(s)

Sarnat, JA; Marmur, A; Klein, M; Kim, E; Russell, AG; Sarnat, SE; Mulholland, JA; Hopke, PK; Tolbert, PE

Year

2008

Is Peer Reviewed?

Yes

Journal

Environmental Health Perspectives
ISSN: 0091-6765
EISSN: 1552-9924

Volume

116

Issue

Page Numbers

459-466

Language

English

PMID

18414627

DOI

10.1289/ehp.10873

Web of Science Id

WOS:000254566500026

URL

http://www.ncbi.nlm.nih.gov/pmc/?term=10.1289/ehp.10873
Exit

Relationship(s)

is comment on/response to 759191 IQRs used in Sarnat et al. 2008 (EHP)

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.

Keywords

acute; Atlanta; cardiovascular; chemical mass balance; emergency department visits; fine particulate matter; positive matrix factorization; respiratory; source apportionment; tracer

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