Literature DB >> 17608008

Source apportionment of fine particulate matter in Phoenix, AZ, using positive matrix factorization.

Steven G Brown1, Anna Frankel, Sean M Raffuse, Paul T Roberts, Hilary R Hafner, Darcy J Anderson.   

Abstract

Speciated particulate matter (PM)2.5 data collected as part of the Interagency Monitoring of Protected Visual Environments (IMPROVE) program in Phoenix, AZ, from April 2001 through October 2003 were analyzed using the multivariate receptor model, positive matrix factorization (PMF). Over 250 samples and 24 species were used, including the organic carbon and elemental carbon analytical temperature fractions from the thermal optical reflectance method. A two-step approach was used. First, the species excluding the carbon fractions were used, and initially eight factors were identified; non-soil potassium was calculated and included to better refine the burning factor. Next, the mass associated with the burning factor was removed, and the data set rerun with the carbon fractions. Results were very similar (i.e., within a few percent), but this step enabled a separation of the mobile factor into gasoline and diesel vehicle emissions. The identified factors were burning (on average 2% of the mass), secondary transport (7%), regional power generation (13%), dust (25%), nitrate (9%), industrial As/Pb/Se (2%), Cu/Ni/V (7%), diesel (9%), and general mobile (26%). The overall contribution from mobile sources also increased, as some mass (OC and nitrate) from the nitrate and regional power generation factors were apportioned with the mobile factors. This approach allowed better apportionment of carbon as well as total mass. Additionally, the use of multiple supporting analyses, including air mass trajectories, activity trends, and emission inventory information, helped increase confidence in factor identification.

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Year:  2007        PMID: 17608008     DOI: 10.3155/1047-3289.57.6.741

Source DB:  PubMed          Journal:  J Air Waste Manag Assoc        ISSN: 1096-2247            Impact factor:   2.235


  9 in total

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2.  Simulation of airborne trace metals in fine particulate matter over North America.

Authors:  Jun-Wei Xu; Randall V Martin; Barron H Henderson; Jun Meng; Burak Oztaner; Jenny L Hand; Amir Hakami; Madeleine Strum; Sharon B Phillips
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3.  PM2.5 pollution from household solid fuel burning practices in Central India: 2. Application of receptor models for source apportionment.

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4.  A Source Apportionment of U.S. Fine Particulate Matter Air Pollution.

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6.  Chemical characteristics and source apportionment of PM2.5 using PCA/APCS, UNMIX, and PMF at an urban site of Delhi, India.

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Journal:  Environ Sci Pollut Res Int       Date:  2017-04-28       Impact factor: 4.223

7.  A Bayesian Multivariate Receptor Model for Estimating Source Contributions to Particulate Matter Pollution using National Databases.

Authors:  Amber J Hackstadt; Roger D Peng
Journal:  Environmetrics       Date:  2014-11-01       Impact factor: 1.900

8.  Unmix Optimum analysis of PAH sediment sources.

Authors:  Gary A Norris; Ronald C Henry
Journal:  Sci Total Environ       Date:  2019-03-19       Impact factor: 7.963

9.  Symptoms and medication use in children with asthma and traffic-related sources of fine particle pollution.

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  9 in total

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