scholarly journals Source apportionment of fine particulate matter over the Eastern U.S. Part I: source sensitivity simulations using CMAQ with the Brute Force method

2011 ◽  
Vol 2 (3) ◽  
pp. 300-317 ◽  
Author(s):  
Michael J. Burr ◽  
Yang Zhang
Keyword(s):  
Particulate Matter ◽  
Source Apportionment ◽  
Fine Particulate Matter ◽  
Brute Force ◽  
Force Method ◽  
Fine Particulate ◽  
Brute Force Method

scholarly journals Fine particulate matter source apportionment using a hybrid chemical transport and receptor model approach

2013 ◽  
Vol 13 (10) ◽  
pp. 26657-26698
Author(s):  
Y. Hu ◽  
S. Balachandran ◽  
J. E. Pachon ◽  
J. Baek ◽  
C. Ivey ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Source Apportionment ◽  
Hybrid Method ◽  
Fine Particulate Matter ◽  
Hybrid Approach ◽  
Chemical Transport ◽  
Measurement Information ◽  
Analysis Tool ◽  
Receptor Model ◽  
Fine Particulate

Abstract. A hybrid fine particulate matter (PM2.5) source apportionment approach based on a receptor-model (RM) species balance and species specific source impacts from a chemical transport model (CTM) equipped with a sensitivity analysis tool is developed to provide physically- and chemically-consistent relationships between source emissions and receptor impacts. This hybrid approach enhances RM results by providing initial estimates of source impacts from a much larger number of sources than are typically used in RMs, and provides source-receptor relationships for secondary species. Further, the method addresses issues of source collinearities, and accounts for emissions uncertainties. Hybrid method results also provide information on the resulting source impact uncertainties. We apply this hybrid approach to conduct PM2.5 source apportionment at Chemical Speciation Network (CSN) sites across the US. Ambient PM2.5 concentrations at these receptor sites were apportioned to 33 separate sources. Hybrid method results led to large changes of impacts from CTM estimates for sources such as dust, woodstove, and other biomass burning sources, but limited changes to others. The refinements reduced the differences between CTM-simulated and observed concentrations of individual PM2.5 species by over 98% when using a weighted least squared error minimization. The rankings of source impacts changed from the initial estimates, revealing that CTM-only results should be evaluated with observations. Assessment with RM results at six US locations showed that the hybrid results differ somewhat from commonly resolved sources. The hybrid method also resolved sources that typical RM methods do not capture without extra measurement information on unique tracers. The method can be readily applied to large domains and long (such as multi-annual) time periods to provide source impact estimates for management- and health-related studies.

Source Apportionment of Airborne Fine Particulate Matter in an Underground Mine

2003 ◽  
Vol 53 (4) ◽  
pp. 386-395 ◽  
Author(s):  
Jacob D. McDonald ◽  
Barbara Zielinska ◽  
John C. Sagebiel ◽  
Mark R. McDaniel ◽  
Pierre Mousset-Jones
Keyword(s):  
Particulate Matter ◽  
Source Apportionment ◽  
Fine Particulate Matter ◽  
Underground Mine ◽  
Fine Particulate

Source apportionment of fine particulate matter organic carbon in Shenzhen, China by chemical mass balance and radiocarbon methods

2018 ◽  
Vol 240 ◽  
pp. 34-43 ◽  
Author(s):  
Ibrahim M. Al-Naiema ◽  
Subin Yoon ◽  
Yu-Qin Wang ◽  
Yuan-Xun Zhang ◽  
Rebecca J. Sheesley ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Organic Carbon ◽  
Mass Balance ◽  
Source Apportionment ◽  
Fine Particulate Matter ◽  
Chemical Mass Balance ◽  
Fine Particulate

scholarly journals Source apportionment of fine particulate matter in a Middle Eastern Metropolis, Tehran-Iran, using PMF with organic and inorganic markers

2020 ◽  
Vol 705 ◽  
pp. 135330 ◽  
Author(s):  
Sepideh Esmaeilirad ◽  
Alexandra Lai ◽  
Gülcin Abbaszade ◽  
Jürgen Schnelle-Kreis ◽  
Ralf Zimmermann ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Source Apportionment ◽  
Middle Eastern ◽  
Fine Particulate Matter ◽  
Fine Particulate
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