Particle Matter in Po Valley (Source Apportionment)
- 1. JRC-ISPRA 28 April 2011 1 F. KARAGULIAN1, L. Clarisse2, F. Lagler1, M. Barbiere1, R. Connolly1 and, C. A. Belis1 PM formation during a photochemical episode in the Po Valley: measurements, mechanisms and source apportionment European Commission - JRC Institute for Environment and Sustainability, Ispra, Italy 2 Université Libre de Bruxelles, Brussels, Belgium 1
- 2. JRC-ISPRA 28 April 2011 Is there any influence of photochemistry on PM2.5 concentration in the Po valley? 2
- 3. Limito di Pioltello and the Po valley, Italy JRC-ISPRA 28 April 2011 3 Site of the field campaign: Limito di Pioltello Milano Limito di Pioltello Date: 17-20 Jun 2009 08-17 July 2009 Po Valley Limito di Pioltello is located in the Po valley near the city of Milan Large agricultural areas Industrial area Large residential area ~ 30.000 inhabitants
- 4. 4-hour experimental time resolution JRC-ISPRA 28 April 2011 4 Sequential samplers (FAI Instruments and Leckel SEQ47/50) for gravimetric measurements of PM1 (24h) PM2.5 (4h, 24h) and PM10 (24h), respectively Sampling: quartz filter for ion chromatography and offline carbon analysis, Teflon® filter, (PTFE) for gravimetric and elemental analysis, on-line semi-continuous OC/EC analyzer Sunset (on hourly basis) VOCs sampled on air for 24 hours with CARBOPACK tubes made of activated charcoal cartridges and analyzed with GC-MS Carbonyls groups sampled with 2,4-Dinitrophenylhydrazine-coated (DNPH) cartridges and analyzed with HPLC Size distribution of particles were also collected with an optical particle counter (OPC, Grimm)
- 5. JRC-ISPRA 28 April 2011 5 Results
- 6. What causes the PM2.5, PM10 summer EPISODE? JRC-ISPRA 28 April 2011 6 EPISODE 15-16 July 2009 less polluted NO input ? increase of O3 levels EPISODE
- 7. Ions (PM2.5) correlated with absolute humidity JRC-ISPRA 28 April 2011 7 EPISODE Night-early morning: NO3- and NH4+ Evening:SO4- -
- 8. NO3- and SO4-- are balanced by NH4+ JRC-ISPRA 28 April 2011 8 EPISODE less polluted SO 24 3 NO NH 4+ particles (secondary inorganic aerosols, SIA) Seinfeld, J. H., and S. N. Pandis (2006), John Wiley & Sons, Inc. Vecchi, R., et al. (2009), Environ. Monit. and Assess., 154(1-4), 283-300 Zhang, K., et al. (2007), Atmos. Res., 84, 67-77
- 9. Secondary Inorganic Aerosols (SIA) JRC-ISPRA 28 April 2011 9 Aqueous phase photochemistry of SO2 and NO2 photochemistry SO2(g) NO2(g) + NO3( g ) nighttime OH • SO3(g) N 2O5( g ) H 2O(l ) H 2O(l ) H 2 SO4 HNO3 Aerosol formation Heterogeneous processes NH 3(g) Seinfeld, J. H., and S. N. Pandis (2006), John Wiley & Sons, Inc. Zhang, K., et al. (2007), Atmos. Res., 84, 67-77 Dickerson, R. R. (2003), Nat. Atmos. Dep Progr. Ammonia Workshop Finlayson-Pitts, B. J., and J. N. Pitts, (2000), Academic Press: San Diego Karagulian, F., and M. J. Rossi, (2005), 7(17), Phys. Chem. Chem. Phys. 3150-3162 SIA (NH 4 )2 SO4 (NH 4 )HSO4 NH 4 NO3
- 10. NH3 in the Po Valley: 7-19 July 2009 satellite observation in the boundary layer JRC-ISPRA 28 April 2011 10 Large reservoir of NH3 in the Po valley (Italy) Milano major NH3 sources: fertilizers animal waste Limito di Pioltello Po Valley major NH3 sinks: wet and dry deposition volatilization: temperature relative humidity - - - > nucleation Averaged NH3 total column from 7 to 17 July 2009 (data are provided by IASI on the MetOp-A Meteorological payload) Clarisse, L., et al. (2009), Nature Geoscience, 2(7), 479-483 The aerial background photographs are © 2008 Google-Imagery © 2008 Terrametrics (http://maps.google.com)
- 11. PM2.5 dominated by SIA during the EPISODE JRC-ISPRA 28 April 2011 11 Si, Fe, Al, Zn, Na, contributed for less than 1% to the total PM2.5 mass OM = 1.6 x OC EPISODE 16th July 2009 Less OM = 1.4 x OC polluted 8th July 2009 OM = 2.0 x OC Turpin, B. J., and H. J. Lim (2001), Aerosol Science and Technology, 35(1), 602-610 Vecchi, R., et al. (2009), Environ. Monit. and Assess., 154(1-4), 283-300
- 12. Fine particles dominate the EPISODE JRC-ISPRA 28 April 2011 12 Fine particles Coarse-crustal (transport, re-suspension) (2.0-15.0 µm) ev en ing n ig ht (0.25-0.58 µm) * Data are from ARPA Lombardia (Italy)
- 13. Wind direction coherent with trends for wind speed JRC-ISPRA 28 April 2011 13 Coarse particles during afternoon (advection + traffic) Fine particles during nighttime (local) 00-04h 04-08h 08-12h 12-16h 16-20h 20-24h
- 14. Photochemical formation of carbonyls during the EPISODE JRC-ISPRA 28 April 2011 14 O3 O3 OH • formation Sampling on air! O3 + VOCs → Aldehydes vehicle exhausts gasoline vapor • VOCs + OH → R + H 2O Lau, A. K. H. et al. (2010), 408(19), Science of the Total Environment 4138-4149. Photochemical smog daytime Atkinson, R., et al. (1984), Journal of Physical Chemistry, 88(6), 1210-1215 Donahue, N. M., et al. (2009), Atmos. Environ., 43(1), 94-106
- 15. The most volatile OC fraction of PM2.5 correlates with photochemical oxidation products JRC-ISPRA 28 April 2011 15 EPISODE Oxygenated organic compounds RT Quartz temperature protocol for OC/EC thermal desorption (OC1) oxygenated organic compounds Correlation: r2 ~ 0.7 Matuschek, G., et al. (2007), Environmental Science and Technology, 41(24), 8406 Streibel, T., et al. (2006), Analytical Chemistry, 78(15), 5354
- 16. JRC-ISPRA 28 April 2011 Comparison between EPA PMF 3.0 and Multilinear Engine (ME-2) 16
- 17. Source apportionment and receptor models JRC-ISPRA 28 April 2011 17 Contribution of the kth source in the jth sample Mass conservation principle…. p xij = ∑g ik f kj two way model k =1 Concentration of the jth specie in the ith sample i = 1,2,….m (samples) Concentration of the ith specie in the kth source j = 1,2,….n (species) uij is the measured uncertainty When both gik and fkj are unknown, the Positive matrix Factorization (PMF) model is used (EPA PMF 3.0) Q main = n ∑∑ i =1 object function p xij − g ik f kj m k =1 u ij j =1 ∑ 2 min Q main (x, f) f best fit
- 18. Multilinear Engine ME-2 JRC-ISPRA 28 April 2011 18 We can also use a PMF which includes constraints and pulling equations Introducing the Multilinear Engine ME-2 Q = Q main + Q aux Q aux V = ∑ v =l aux Qv V = ∑ 2 (av − f pj )2 /sv v =l softness of the pulling pulling value
- 19. Source Contribution Estimation to PM2.5 JRC-ISPRA 28 April 2011 19 Factors Measured Local Source Profiles Autopull ME-2 2-way model with constraints and pulling equations Paatero and Hopke, PMF-CD, 2010. YP-Tekniikka Ky Rikalantie 6 FI-00970 Helsinki FINLAND EU Report, Regione Lombardia (under revision) Amato, F. et al., (2009), 43(17), Atmospheric Environment, 2770-2780 Viana, M., et al. (2008), Journal of Aerosol Science, 39(10), 827-849
- 20. Wind direction factors for each source JRC-ISPRA 28 April 2011 20 Nitrate Sulfate Traffic Predominant from Po Valley Predominant from Milano area Limito Milano Enhanced ME-2 2-way model with constraints and pulling equations Po Valley Uniformly distributed around the receptor site
- 21. Higlights JRC-ISPRA 28 April 2011 21 Diurnal Trend Analysis Night: Low wind speed from East with high RH High concentration of sec. nitrate Local nucleation and heterogeneous reactions Afternoon-evening: Breeze mainly form South-East Traffic re-suspension PM likely advected from rural areas Traffic: Maximum values during rush hours
- 22. PM2.5 diurnal profiles JRC-ISPRA 28 April 2011 22
- 23. Conlusions JRC-ISPRA 28 April 2011 23 Photochemistry mainly occurs during the EPISODE Multilinear Engine with constraints, pulling equation and, wind direction analysis resulted to be an efficient approach for data processing ME-2 factors resemble source profile more than PMF factors The constraints did not lead to a significant increase in Q ME-2 factors more coherent with advection and particle properties (size distribution)
- 24. JRC-ISPRA 28 April 2011 Thanks for your attention Acknowledgment Data: Michel Gerboles, Sinan Yatkin, Bo Larsen Programming: Luca Spano’ General Support: all my friends 24