SOURCE APPORTIONMENT OF PRAGUE AEROSOL FROM COMBINED PARTICLE NUMBER SIZE DISTRIBUTION AND GASEOUS COMPOSITION DATA BY BILINEAR POSITIVE MATRIX FACTORIZATION Devraj Thimmaiah 1, Jan Hovorka 1 and Philip K. Hopke 2 1 Institute for Environmental Studies, Charles University in Prague, 12801, Prague, Czech Republic 2 Department of Chemical & Biomolecular Engineering, Clarkson Univ., Potsdam,13699,USA Identify and apportion the sources of ambient aerosols in the urban atmosphere of Prague, Czech Republic using bilinear Positive Matrix Factorization (PMF2) model. European Aerosol Conference (EAC), September 9-14, 2007, Salzburg, Austria To help in interpreting and in knowing the directionality of the sources, Conditional Probability Function plots (CPF) (Ashbaugh et al., 1985) were used. The CPF plots of contributing sources and overall wind profile is shown in Figure 2-7. PMF technique was first introduced by Paatero & Tapper in A similar study for modeling source contributions to submicron particle number concentrations in Rochester, NY is performed by Ogulei et al., Fpeak Analysis between -1 and +1 was performed and the lowest Q value was when the Fpeak was set to 0.0. (Figure 9). This work was supported by the Grant Agency, Czech Republic under GAUK Grant No. PřF/49707 / Objective 2. Experimental 3. Results & Discussion 5. Conclusion 6. Acknowledgement Figure 1. Location of sampling site Figure 2-7. Directionality of contributing sources and overall wind profile using CPF. Figure 8a,b. Wind roses for the sampling period Figure 10-15: Weekday and Weekend variations of 5 sources identified by PMF2. Sampling site Figure 16 and 17. Source profiles and contributions deduced from PMF2 analysis. Table 1. Summary of measured species MeasurementInstrument Original time resolution before averaging to 1 h. Particle sizeSMPS-3936L2510 min Size range: nm Meteorological dataVane type15 min WS, WD, Temp, RH Gaseous dataHoriba15 min CO, SO 2, NO X & O 3 Rain IntensityLNM Disdrometer1 min PMF2 has identified 5 factors. They are: traffic, ozone influenced secondary particles, residential heating and two unidentified mixed sources 1 & 2 with directionality from all the sides. Work is in progress to identify these two sources. One of the mixed sources maybe background or long range transport, not known due to lack of tracers. 7. References Ashbaugh, L.L., Malm, W.C. & Sadeh, W.Z. (1985). Atmospheric Environment, 19, Paatero, P., & Tapper, U. (1993). Chemometrics Intell. Lab Sys., 18: Ogulei, D., Hopke, P.K., Chalupa, D.C., & Utell, M.J. (2007). Aerosol Sci. Technol., 41, Figure 9. Fpeak analysis to find lowest Q value The source profiles and the contributions deduced from PMF2 analysis in Prague is depicted in Figure 16 and 17 respectively. A series of CPF plots (Figure 18-25) for the meteorological data recorded at the receptor site were drawn to help in identifying and naming the sources deduced by PMF2, Figure give the variation of Temp, RH, and Rain intensity recorded at the site. 4. Supplementary material Figure Variation of Temp., RH and Rain intensity recorded at receptor site. Sampling site: All the data were recorded at roof-top (at height 25m) station at the receptor site, University Botanic garden in the Prague city center (50 0 4`17.29”N, `46.52”E) (Figure 1). Apparatus: Particle number size concentrations, ambient gaseous concentrations, meteorological data and rain intensity measured at the receptor site, instrumentation used is summarized in Table 1. Sampling period: Feb 16-28, March and April 01-10, Data Analysis: All the data obtained were normalized and averaged to hourly concentrations and used in data matrix preparation