Inter-comparison of receptor models for PM source apportionment: Case study in an industrial area
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Other documents of the author: Viana, Marcelo; Pandolfi, Monica; Minguillón Bengochea, María Cruz; Querol, Xavier; Alastuey, Andres; Monfort, Eliseo; Celades López, Irina
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comunitat-uji-handle2:10234/7033
comunitat-uji-handle3:10234/8618
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http://dx.doi.org/10.1016/j.atmosenv.2007.12.056 |
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Title
Inter-comparison of receptor models for PM source apportionment: Case study in an industrial areaAuthor (s)
Date
2008Publisher
ElsevierISSN
1352-2310Bibliographic citation
Atmospheric environment (2008), 42, 16, p. 3820-3832Type
info:eu-repo/semantics/articlePublisher version
http://www.sciencedirect.com/science/journal/13522310Subject
Abstract
Receptor modelling techniques are used to identify and quantify the contributions from emission sources to the levels
and major and trace components of ambient particulate matter (PM). A wide variety of receptor ... [+]
Receptor modelling techniques are used to identify and quantify the contributions from emission sources to the levels
and major and trace components of ambient particulate matter (PM). A wide variety of receptor models are currently
available, and consequently the comparability between models should be evaluated if source apportionment data are to be
used as input in health effects studies or mitigation plans. Three of the most widespread receptor models (principal
component analysis, PCA; positive matrix factorization, PMF; chemical mass balance, CMB) were applied to a single
PM10 data set (n ¼ 328 samples, 2002–2005) obtained from an industrial area in NE Spain, dedicated to ceramic
production. Sensitivity and temporal trend analyses (using the Mann–Kendall test) were applied. Results evidenced the
good overall performance of the three models (r240.83 and a40.91 between modelled and measured PM10 mass), with a
good agreement regarding source identification and high correlations between input (CMB) and output (PCA, PMF)
source profiles. Larger differences were obtained regarding the quantification of source contributions (up to a factor of 4 in
some cases). The combined application of different types of receptor models would solve the limitations of each of the
models, by constructing a more robust solution based on their strengths. The authors suggest the combined use of factor
analysis techniques (PCA, PMF) to identify and interpret emission sources, and to obtain a first quantification of their
contributions to the PM mass, and the subsequent application of CMB. Further research is needed to ensure that source
apportionment methods are robust enough for application to PM health effects assessments [-]
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