Premium
Bilinear estimation of pollution source profiles and amounts by using multivariate receptor models
Author(s) -
Sug Park Eun,
Spiegelman Clifford H.,
Henry Ronald C.
Publication year - 2002
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/env.557
Subject(s) - identifiability , multivariate statistics , context (archaeology) , estimator , econometrics , bilinear interpolation , estimation , pollution , estimation theory , statistics , computer science , mathematics , geography , engineering , biology , ecology , archaeology , systems engineering
Multivariate receptor models aim to identify the pollution sources based on multivariate air pollution data. This article is concerned with estimation of the source profiles (pollution recipes) and their contributions (amounts of pollution). The estimation procedures are based on constrained nonlinear least squares methods with the constraints given by nonnegativity and identifiability conditions of the model parameters. We investigate several identifiability conditions that are appropriate in the context of receptor models, and also present new sets of identifiability conditions, which are often reasonable in practice when the other traditional identifiability conditions fail. The resulting estimators are consistent under appropriate identifiability conditions, and standard errors for the estimators are also provided. Simulation and application to real air pollution data illustrate the results. Copyright © 2002 John Wiley & Sons, Ltd.