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Steven G. Brown
Researcher at Colorado State University
Publications - 35
Citations - 1699
Steven G. Brown is an academic researcher from Colorado State University. The author has contributed to research in topics: Air quality index & Particulates. The author has an hindex of 16, co-authored 35 publications receiving 1353 citations.
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Journal ArticleDOI
Methods for estimating uncertainty in PMF solutions: Examples with ambient air and water quality data and guidance on reporting PMF results
TL;DR: BS-DISP and BS are found useful in understanding the uncertainty of factor profiles; they also suggest if the data are over-fitted by specifying too many factors, and recommendations for reporting PMF results.
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Methods for estimating uncertainty in factor analytic solutions
TL;DR: In this article, the authors present three methods for estimating uncertainty in factor analytic models: classical bootstrap (BS), displacement of factor elements (DISP), and bootstrap enhanced by displacement of element (BS-DISP).
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Source apportionment of VOCs in the Los Angeles area using positive matrix factorization
TL;DR: In this article, the multivariate receptor model positive matrix factorization (PMF) was used to identify five and six factors at Azusa and Hawthorne, respectively, with a good comparison between predicted and measured mass.
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Source apportionment of volatile organic compounds measured in Edmonton, Alberta
TL;DR: In this paper, the United States Environmental Protection Agency's positive matrix factorization receptor model (EPA PMF) was used to apportion ambient concentrations of VOCs into eleven factors, which were associated with emissions sources.
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Characterization of organic aerosol in Big Bend National Park, Texas
Steven G. Brown,Pierre Herckes,Lowell L. Ashbaugh,Michael P. Hannigan,Sonia M. Kreidenweis,Jeffrey L. Collett +5 more
TL;DR: The Big Bend Regional Aerosol and Visibility Observational (BRAVO) study was conducted in Big Bend National Park, Texas, July through October 1999 as mentioned in this paper, and a total of 12 composites, each containing 3-10 daily samples, were analyzed.