Diagnostics for determining influential species in the chemical mass balance receptor model

Authors
Citation
Bm. Kim et Rc. Henry, Diagnostics for determining influential species in the chemical mass balance receptor model, J AIR WASTE, 49(12), 1999, pp. 1449-1455
Citations number
36
Categorie Soggetti
Environment/Ecology,"Environmental Engineering & Energy
Journal title
JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION
ISSN journal
10962247 → ACNP
Volume
49
Issue
12
Year of publication
1999
Pages
1449 - 1455
Database
ISI
SICI code
1096-2247(199912)49:12<1449:DFDISI>2.0.ZU;2-T
Abstract
The chemical mass balance (CMB) model can be applied to estimate the amount of airborne particulate matter (PM) coming from various sources given the ambient chemical composition of the particles measured at the receptor and the chemical composition of the source emissions. Of considerable practical importance is the identification of those chemical species that have a lar ge effect on either the source contributions or errors estimated by the CMB model. This paper details a study of a number of influential diagnostics f or application of the CMB software. Some of the diagnostics studied are sta ndard regression diagnostics based on single-row deletion diagnostics. A nu mber of new diagnostics were developed specifically for the CMB application , based on the pseudo-inverse of the source composition matrix anti called nondeletion diagnostics to distinguish them from the standard deletion diag nostics. Simulated data sets were generated to compare the diagnostics and their response to controlled amounts of random error. A particular diagnostic called a modified pseudoinverse matrix (MPIN), deve loped for this study, was found to be the best choice for CMB model applica tion. The MPIN diagnostic contains virtually all the information present in both deletion and nondeletion diagnostics. Since the MPIN diagnostic requi res only the source profiles, it can be used to identify influential specie s in advance without sampling the ambient data and to improve CMB results t hrough possible remedial actions for the influential species. Specific reco mmendations are given for interpretation and use of the MPIN diagnostic wit h the CMB model software. Elements with normalized MPIN absolute values of 1 to 0.5 are associated with influential elements. Noninfluential elements have normalized MPIN absolute values of 0.3 or less. Elements with absolute values between 0.3 and 0.5 are ambiguous but should generally be considere d noninfluential.