Linked Life Data

18234404

Source:http://linkedlifedata.com/resource/pubmed/id/18234404

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2008-9-8
pubmed:abstractText
Identifying the sources of volatile organic compounds (VOCs) is key to reducing ground-level ozone and secondary organic aerosols (SOAs). Several receptor models have been developed to apportion sources, but an intercomparison of these models had not been performed for VOCs in China. In the present study, we compared VOC sources based on chemical mass balance (CMB), UNMIX, and positive matrix factorization (PMF) models. Gasoline-related sources, petrochemical production, and liquefied petroleum gas (LPG) were identified by all three models as the major contributors, with UNMIX and PMF producing quite similar results. The contributions of gasoline-related sources and LPG estimated by the CMB model were higher, and petrochemical emissions were lower than in the UNMIX and PMF results, possibly because the VOC profiles used in the CMB model were for fresh emissions and the profiles extracted from ambient measurements by the two-factor analysis models were "aged".
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
1873-6424
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
156
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
174-83
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
Comparison of receptor models for source apportionment of volatile organic compounds in Beijing, China.
pubmed:affiliation
Department of Environmental Sciences, Peking University, Beijing 100871, China.
pubmed:publicationType
Journal Article, Comparative Study, Research Support, Non-U.S. Gov't