Literature DB >> 12661691

Source apportionment of Phoenix PM2.5 aerosol with the Unmix receptor model.

Charles W Lewis1, Gary A Norris, Teri L Conner, Ronald C Henry.   

Abstract

The multivariate receptor model Unmix has been used to analyze a 3-yr PM2.5 ambient aerosol data set collected in Phoenix, AZ, beginning in 1995. The analysis generated source profiles and overall average percentage source contribution estimates (SCEs) for five source categories:gasoline engines (33 +/- 4%), diesel engines (16 +/- 2%), secondary SO4(2-) (19 +/- 2%), crustal/soil (22 +/- 2%), and vegetative burning (10 +/- 2%). The Unmix analysis was supplemented with scanning electron microscopy (SEM) of a limited number of filter samples for information on possible additional low-strength sources. Except for the diesel engine source category, the Unmix SCEs were generally consistent with an earlier multivariate receptor analysis of essentially the same data using the Positive Matrix Factorization (PMF) model. This article provides the first demonstration for an urban area of the capability of the Unmix receptor model.

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Year:  2003        PMID: 12661691     DOI: 10.1080/10473289.2003.10466155

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


  11 in total

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Authors:  S Vedal; M P Hannigan; S J Dutton; S L Miller; J B Milford; N Rabinovitch; S-Y Kim; L Sheppard
Journal:  Atmos Environ (1994)       Date:  2008-12-24       Impact factor: 4.798

2.  UNMIX modeling of ambient PM(2.5) near an interstate highway in Cincinnati, OH, USA.

Authors:  Shaohua Hu; Rafael McDonald; Dainius Martuzevicius; Pratim Biswas; Sergey A Grinshpun; Anna Kelley; Tiina Reponen; James Lockey; Grace Lemasters
Journal:  Atmos Environ (1994)       Date:  2006       Impact factor: 4.798

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

Authors:  George D Thurston; Kazuhiko Ito; Ramona Lall
Journal:  Atmos Environ (1994)       Date:  2011-08       Impact factor: 4.798

4.  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

5.  An aerosol climatology for a rapidly growing arid region (southern Arizona): Major aerosol species and remotely sensed aerosol properties.

Authors:  Armin Sorooshian; Anna Wonaschütz; Elias G Jarjour; Bryce I Hashimoto; Bret A Schichtel; Eric A Betterton
Journal:  J Geophys Res Atmos       Date:  2011-10-01       Impact factor: 4.261

6.  Source apportionment of polycyclic aromatic hydrocarbons (PAHs) into Central Park Lake, New York City, over a century of deposition.

Authors:  Beizhan Yan; Richard F Bopp; Teofilo A Abrajano; Damon Chaky; Steven N Chillrud
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7.  Assessing the PM2.5 impact of biomass combustion in megacity Dhaka, Bangladesh.

Authors:  Md Mostafijur Rahman; Bilkis A Begum; Philip K Hopke; Kamrun Nahar; George D Thurston
Journal:  Environ Pollut       Date:  2020-05-13       Impact factor: 9.988

8.  Health effects of residential wood smoke particles: the importance of combustion conditions and physicochemical particle properties.

Authors:  Anette Kocbach Bølling; Joakim Pagels; Karl Espen Yttri; Lars Barregard; Gerd Sallsten; Per E Schwarze; Christoffer Boman
Journal:  Part Fibre Toxicol       Date:  2009-11-06       Impact factor: 9.400

9.  Particulate matter components and subclinical atherosclerosis: common approaches to estimating exposure in a Multi-Ethnic Study of Atherosclerosis cross-sectional study.

Authors:  Min Sun; Joel D Kaufman; Sun-Young Kim; Timothy V Larson; Timothy R Gould; Joseph F Polak; Matthew J Budoff; Ana V Diez Roux; Sverre Vedal
Journal:  Environ Health       Date:  2013-05-03       Impact factor: 5.984

10.  The effects of components of fine particulate air pollution on mortality in california: results from CALFINE.

Authors:  Bart Ostro; Wen-Ying Feng; Rachel Broadwin; Shelley Green; Michael Lipsett
Journal:  Environ Health Perspect       Date:  2007-01       Impact factor: 9.031

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