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- W2008723305 abstract "Abstract In the receptor modeling literature, the standard tool for solving the chemical mass balance (CMB) equations is the effective variance solution. Using pollution source profiles, profile uncertainties, and measurement error variances, the CMB model can be fit in order to partition the ambient pollutants measured at the receptor into a collection of source contributions. We discuss the use of the CMB model for the analysis of a multivariate time series of air quality measurements. We consider new multivariate extensions of the effective variance solution for temporally correlated observations. New estimation and inference procedures which account for the multiple sources of correlation in the data are presented. Using computer simulation, approaches are compared under various scenarios in which ambient measures are collected over time and in which other standard model assumptions are violated. Key Words: Chemical mass balanceReceptor modelMultivariate time seriesEffective variance solutionCorrelated errorsMathematics Subject Classification: 62P1262M10 Acknowledgments" @default.
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- W2008723305 date "2004-10-01" @default.
- W2008723305 modified "2023-10-16" @default.
- W2008723305 title "Estimating Pollution Source Contributions from Temporally Correlated Air Quality Observations" @default.
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- W2008723305 doi "https://doi.org/10.1081/sac-200040706" @default.
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