Literature DB >> 22168104

PM2.5 source apportionment: reconciling receptor models for U.S. nonurban and urban long-term networks.

L W Antony Chen1, John G Watson, Judith C Chow, Dave W DuBois, Lisa Herschberger.   

Abstract

Chemical mass balance (CMB) and trajectory receptor models were applied to speciated particulate matter with aerodynamic diameter < or =2.5 microm (PM2.5) measurements from Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]) and Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring network across the state of Minnesota as part of the Minnesota PM2.5 Source Apportionment Study (MPSAS). CMB equations were solved by the Unmix, positive matrix factorization (PMF), and effective variance (EV) methods, giving collective source contribution and uncertainty estimates. Geological source profiles developed from local dust materials were either incorporated into the EV-CMB model or used to verify factors derived from Unmix and PMF. Common sources include soil dust, calcium (Ca)-rich dust, diesel and gasoline vehicle exhausts, biomass burning, secondary sulfate, and secondary nitrate. Secondary sulfate and nitrate aerosols dominate PM2.5 mass (50-69%). Mobile sources outweigh area sources at urban sites, and vice versa at rural sites due to traffic emissions. Gasoline and diesel contributions can be separated using data from the STN, despite significant uncertainties. Major differences between MPSAS and earlier studies on similar environments appear to be the type and magnitude of stationary sources, but these sources are generally minor (<7%) in this and other studies. Ensemble back-trajectory analysis shows that the lower Midwestern states are the predominant source region for secondary ammoniated sulfate in Minnesota. It also suggests substantial contributions of biomass burning and soil dust from out-of-state on occasions, although a quantitative separation of local and regional contributions was not achieved in the current study. Supplemental materials are available for this article. Go to the publisher's online edition of the Journal of the Air & Waste Management Association for a summary of input data, Unmix and PMF factor profiles, and additional maps.

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Year:  2011        PMID: 22168104     DOI: 10.1080/10473289.2011.619082

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


  5 in total

1.  PM2.5 pollution from household solid fuel burning practices in Central India: 2. Application of receptor models for source apportionment.

Authors:  Jeevan Lal Matawle; Shamsh Pervez; Manas Kanti Deb; Anjali Shrivastava; Suresh Tiwari
Journal:  Environ Geochem Health       Date:  2016-11-02       Impact factor: 4.609

2.  Positive matrix factorization of PM2.5 - eliminating the effects of gas/particle partitioning of semivolatile organic compounds.

Authors:  M Xie; K C Barsanti; M P Hannigan; S J Dutton; S Vedal
Journal:  Atmos Chem Phys       Date:  2013       Impact factor: 6.133

3.  Positive matrix factorization of a 32-month series of daily PM2.5 speciation data with incorporation of temperature stratification.

Authors:  Mingjie Xie; Ricardo Piedrahita; Steven J Dutton; Jana B Milford; Joshua G Hemann; Jennifer L Peel; Shelly L Miller; Sun-Young Kim; Sverre Vedal; Lianne Sheppard; Michael P Hannigan
Journal:  Atmos Environ (1994)       Date:  2013-02-01       Impact factor: 4.798

4.  Personal exposure to fine particulate air pollution while commuting: An examination of six transport modes on an urban arterial roadway.

Authors:  Robert A Chaney; Chantel D Sloan; Victoria C Cooper; Daniel R Robinson; Nathan R Hendrickson; Tyler A McCord; James D Johnston
Journal:  PLoS One       Date:  2017-11-09       Impact factor: 3.240

5.  A Two-Stage Method to Estimate the Contribution of Road Traffic to PM₂.₅ Concentrations in Beijing, China.

Authors:  Xin Fang; Runkui Li; Qun Xu; Matteo Bottai; Fang Fang; Yang Cao
Journal:  Int J Environ Res Public Health       Date:  2016-01-13       Impact factor: 3.390

  5 in total

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