1. Source apportionment of submicron organic aerosols at an urban site by linear unmixing of aerosol mass spectra V. A. Lanz 1, M. R. Alfarra 2, U. Baltensperger 2, B. Buchmann 1, C. Hueglin 1, and A. S. H. Prévôt 2 [1] Empa, Swiss Federal Laboratories for Materials Testing and Research, Laboratory for Air Pollution and Environmental Technology, CH-8600 Duebendorf, Switzerland [2] PSI, Paul Scherrer Institute, Laboratory for Atmospheric Chemistry, CH- 5232 Villigen PSI, Switzerland submitted to ACPD

2. urban background site (Zurich - Kaserne) three-week measurement period in summer 2005 N www.mapsearch.ch Measurement campaign

3. Positive matrix factorization (PMF) X = G F - non-negativity of G and F - algorithm accounts for uncertainty in X (weighted least squares) X {n x m} = G {n x p} F { p x m} species j: 1…m samples in time i: 1…n Columns (scores) Rows (loadings or factors) number of p must be specified

4. Goodness of fit (R 2 ) of regressed scores vs. measured organics and rotational freedom as a function of the number of factors chosen in PMF. Number of factors p ?

5. Most important step in PMF analyses: interpretation of F (and G), i.e. the mathematical solutions (G and F matrices) must be linked to sources and aerosol components rows of F - factors: e.g check for spectral similarity with ~ AMS reference spectra columns of G - scores: e.g. look at correlation with other species (time series) (compare modelled emission/ratios with literature)

6. Interpretation of F factors spectral similarity to reference spectra R 2 : correlation of all m/z‘s R 2 m/z>44 : correlation of m/z > 44 m/z 29 m/z 44 m/z 18 m/z 43 factor [norm. int] Ref. MS [norm. int] similarity measure for AMS spectra ?

7. Interpretation of F factors example 1: 1 st factor is very similar to fulvic acid, (aged urban aerosol, …) (R 2 =0.96; R m/z>44 2 =0.83) interpretation as OOA (oxygenated organic aerosol) example 2: 3 rd factor is very close to fuel, (lubricant oil, diesel, …) (R 2 =0.99; R m/z>44 2 =0.99): interpretation as HOA (hydrocarbon-like organic aerosol)

9. correlation with other species -secondary processes: atm. oxidants (O 3 + NO 2 ) temperature particle-phase nitrate/sulfate -primary processes: carbon monoxide (CO) nitrogen oxides (NO x ) elemental carbon (EC) Interpretation of G - scores

10. emission ratio [ng m -3 /ppbv] Zürich- Kaserne Pittburgh (Zhang et al., 2005) New England (de Gouw et al., 2005) Tokyo (Takegawa et al., 2005) diesel trucks/light-duty vehicles (calculated from Kirchstetter et al., 1999) POA/CO10.44.39.411- HOA/NO x 15.942--11/16 AMS (PMF)AMS (2-fact. approach) total OA, gas- phase tracer AMS (2-fact. approach) tunnel studies modelled emission ratios

11. Main results

12. PM 1 (Zürich-Kaserne, Summer 2005) (avg. OM 6.58  g m -3 ) 10% wood burning 13% in Zürich, 2002 ( 14 C analysis, Szidat et al., 2006) SOA and POA estimation

13. Limitations of PMF PMF (and other multivariate receptor models) cannot resolve sources/components when (a) profiles are too similar (b) when sources/components show similar temporal variation (e.g. Zurich winter data set) → CMB approach (collinearity and multicollinearity of profiles might be a problem) → Hybrid model combining CMB and PMF features ?

14. Outlook: CMB - type approach (Zurich winter) Temporal variation of three mass tracers (m/z 44, m/z 57 and m/z 60) during the Zurich winter 2006 campaign

15. Outlook: CMB - type approach (Zurich winter)

16. calculated G factors average contribution (incl. uncertainty estimates) Outlook: CMB - type approach (Zurich winter) – preliminary !

18. Calculated factors and its interpretation Spectra of all PMF factors (interpreted as the denoted source profiles) calculated by 6-factorial PMF. Only for the minor source the full mass range up to 300 m/z is shown because it is the only source or component with significant features in the high mass region on the linear scale.

19. Measured AMS-sulphate and modelled aerosol from wood burning on the Swiss national holiday (1 August)