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Recent developments in receptor modeling
Author(s) -
Hopke Philip K.
Publication year - 2003
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.796
Subject(s) - identification (biology) , computer science , air pollution , particulates , high resolution , air pollutants , data mining , environmental science , data science , biochemical engineering , chemistry , remote sensing , geography , engineering , botany , organic chemistry , biology
Receptor modeling is the application of data analysis methods to elicit information on the sources of air pollutants. Typically, it employs methods of solving the mixture resolution problem using chemical composition data for airborne particulate matter samples. In such cases, the outcome is the identification of the pollution source types and estimates of the contribution of each source type to the observed concentrations. It can also involve efforts to identify the locations of the sources through the use of ensembles of air parcel back trajectories. In recent years, there have been improvements in the factor analysis methods that are applied in receptor modeling as well as easier application of trajectory methods. These developments are reviewed. Copyright © 2003 John Wiley & Sons, Ltd.