Evaluation Of PM2.5 In Chicago By
Chemical Mass Balance And Positive Matrix
Factorization Models
Author(s)
P. Scheff & M. Rizzo
Abstract
Chemical Mass Balance (CMB) and Positive Matrix Factorization (PMF) models
were used to analyze fine particulate matter data from two sites within the city of
Chicago. Measurements of metals, organic and elemental carbon, sulfate, nitrate,
and gaseous criteria pollutants from the PM2.5 speciation network were
evaluated. CMB and PMF results were both strongly influenced by the
measurement uncertainty. Variables with a high percentage of measurements
below the detection limit were heavily down-weighted so that the models would
not be overly influenced by low or unknown concentrations. Variables that were
usually above the detection limit were weighted by the root mean square average
of 10 % of the measured concentration and the corresponding detection limit.
The analysis yielded a nine
Keywords
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