Source apportionment of fine carbonaceous particles by positive matrix factorization at Gosan background site in East Asia

2008 ◽  
Vol 34 (5) ◽  
pp. 654-664 ◽  
Author(s):  
K.J. Moon ◽  
J.S. Han ◽  
Y.S. Ghim ◽  
Y.J. Kim
Keyword(s):  
East Asia ◽  
Source Apportionment ◽  
Matrix Factorization ◽  
Positive Matrix Factorization ◽  
Positive Matrix ◽  
Carbonaceous Particles ◽  
Background Site

scholarly journals Source apportionment of PM<sub>10</sub> in a North-Western Europe regional urban background site (Lens, France) using Positive Matrix Factorization and including primary biogenic emissions

2013 ◽  
Vol 13 (10) ◽  
pp. 25325-25385 ◽  
Author(s):  
A. Waked ◽  
O. Favez ◽  
L. Y. Alleman ◽  
C. Piot ◽  
J.-E. Petit ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Biomass Burning ◽  
Matrix Factorization ◽  
Iteration Process ◽  
Positive Matrix Factorization ◽  
Biogenic Emissions ◽  
Positive Matrix ◽  
Urban Background ◽  
Background Site ◽  
Urban Background Site

Abstract. In this work, the source of ambient particulate matter (PM10) collected over a one year period at an urban background site in Lens (France) were determined and investigated using a~Positive Matrix Factorization receptor model (US EPA PMF v3.0). In addition, a Potential Source Contribution Function (PSCF) was performed by means of the Hysplit v4.9 model to assess prevailing geographical origins of the identified sources. A selective iteration process was followed for the qualification of the more robust and meaningful PMF solution. Components measured and used in the PMF include inorganic and organic species: soluble ionic species, trace elements, elemental carbon (EC), sugars alcohols, sugar anhydride, and organic carbon (OC). The mean PM10 concentration measured from March 2011 to March 2012 was about 21 μg m−3 with typically OM, nitrate and sulfate contributing to most of the mass and accounting respectively for 5.8, 4.5 and 2.3 μg m−3 on a yearly basis. Accordingly, PMF outputs showed that the main emission sources were (in a decreasing order of contribution): secondary inorganic aerosols (28% of the total PM10 mass), aged marine emissions (19%), with probably predominant contribution of shipping activities, biomass burning (13%), mineral dust (13%), primary biogenic emissions (9%), fresh sea salts (8%), primary traffic emissions (6%) and heavy oil combustion (4%). Significant temporal variations were observed for most of the identified sources. In particular, biomass burning emissions were negligible in summer but responsible for about 25% of total PM10 and 50% of total OC at wintertime. Conversely, primary biogenic emissions were found to be negligible in winter but to represent about 20% of total PM10 and 40% of total OC in summer. The latter result calls for more investigations of primary biogenic aerosols using source apportionment studies, which quite usually disregards this type of sources. This study furthermore underlines the major influence of secondary processes during daily threshold exceedances. Finally, apparent discrepancies that could be generally observed between filter-based studies (such as the present one) and Aerosol Mass Spectrometer-based PMF analyses (organic fractions) are also discussed here.

scholarly journals Source apportionment of PM<sub>10</sub> in a north-western Europe regional urban background site (Lens, France) using positive matrix factorization and including primary biogenic emissions

2014 ◽  
Vol 14 (7) ◽  
pp. 3325-3346 ◽  
Author(s):  
A. Waked ◽  
O. Favez ◽  
L. Y. Alleman ◽  
C. Piot ◽  
J.-E. Petit ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Biomass Burning ◽  
Matrix Factorization ◽  
Iteration Process ◽  
Positive Matrix Factorization ◽  
Biogenic Emissions ◽  
Positive Matrix ◽  
Urban Background ◽  
Background Site ◽  
Urban Background Site

Abstract. In this work, the source of ambient particulate matter (PM10) collected over a one-year period at an urban background site in Lens (France) was determined and investigated using a positive matrix factorization receptor model (US EPA PMF v3.0). In addition, a potential source contribution function (PSCF) was performed by means of the Hybrid Single-Particle Lagrangian Integrated Trajectory (Hysplit) v4.9 model to assess prevailing geographical origins of the identified sources. A selective iteration process was followed for the qualification of the more robust and meaningful PMF solution. Components measured and used in the PMF included inorganic and organic species: soluble ionic species, trace elements, elemental carbon (EC), sugar alcohols, sugar anhydride, and organic carbon (OC). The mean PM10 concentration measured from March 2011 to March 2012 was about 21 μg m−3 with typically OM, nitrate and sulfate contributing to most of the mass and accounting respectively for 5.8, 4.5 and 2.3 μg m−3 on a yearly basis. Accordingly, PMF outputs showed that the main emission sources were (in decreasing order of contribution) secondary inorganic aerosols (28% of the total PM10 mass), aged marine emissions (19%), with probably predominant contribution of shipping activities, biomass burning (13%), mineral dust (13%), primary biogenic emissions (9%), fresh sea salts (8%), primary traffic emissions (6%) and heavy oil combustion (4%). Significant temporal variations were observed for most of the identified sources. In particular, biomass burning emissions were negligible in summer but responsible for about 25% of total PM10 and 50% of total OC in wintertime. Conversely, primary biogenic emissions were found to be negligible in winter but to represent about 20% of total PM10 and 40% of total OC in summer. The latter result calls for more investigations of primary biogenic aerosols using source apportionment studies, which quite usually disregard this type of source. This study further underlines the major influence of secondary processes during daily threshold exceedances. Finally, apparent discrepancies that could be generally observed between filter-based studies (such as the present one) and aerosol mass spectrometer-based PMF analyses (organic fractions) are also discussed.

scholarly journals Source apportionment using positive matrix factorization on daily measurements of inorganic and organic speciated PM2.5

2010 ◽  
Vol 44 (23) ◽  
pp. 2731-2741 ◽  
Author(s):  
Steven J. Dutton ◽  
Sverre Vedal ◽  
Ricardo Piedrahita ◽  
Jana B. Milford ◽  
Shelly L. Miller ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Matrix Factorization ◽  
Positive Matrix Factorization ◽  
Positive Matrix ◽  
Inorganic And Organic
Sign in / Sign up

Export Citation Format

Share Document