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Heikki Junninen, Covadonga Astorga-Llorens, Vittorio Forcina, Anne Müller and Bo Larsen

Emissions & Health Unit. PARTICULATE MATTER AND POLYAROMATIC COMPOUNDS IN AIR OVER ATHENS DURING THE BOND SUMMER CAMPAIGN, JUNE 2003. Heikki Junninen, Covadonga Astorga-Llorens, Vittorio Forcina, Anne Müller and Bo Larsen Institute for Environment and Sustainability (IES) Ispra, Italy.

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Heikki Junninen, Covadonga Astorga-Llorens, Vittorio Forcina, Anne Müller and Bo Larsen

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  1. Emissions & Health Unit PARTICULATE MATTER AND POLYAROMATIC COMPOUNDS IN AIROVER ATHENS DURING THE BOND SUMMER CAMPAIGN,JUNE 2003 Heikki Junninen, Covadonga Astorga-Llorens, Vittorio Forcina, Anne Müller and Bo Larsen Institute for Environment and Sustainability (IES) Ispra, Italy

  2. Meteorological Conditions 1 4 d ( r e d ) & 1 4 n ( b l u e ) 2 3 d ( r e d ) & 2 3 n ( b l u e ) 2 0 ' 1 0 ' T a t o i T a t o i E l e u s i n a N e a P h i l a d e l p h i a E l e u s i n a N e a P h i l a d e l p h i a o 3 8 N S p a t a S p a t a E l l i n k o E l l i n k o 5 0 ' 1 2 ' 1 2 ' - 1 - 1 4 0 ' 1 0 m s 1 0 m s 2 4 ' o o 2 4 E 2 4 E 3 6 ' 4 8 ' 4 8 ' 14.06 Synoptic wind Land-breeze/sea-breeze 23.06

  3. Back trajectories 20' 20' Night Night 10' 10' o o 38 N 38 N 50' 50' 12' 12' 40' 40' 24' 24' o o 24 E 24 E 36' 48' 36' 48' Day 20' 20' Day 10' 10' o o 38 N 38 N 50' 50' 12' 12' 40' 40' 24' 24' o o 24 E 24 E 36' 36' 48' 48' 14.06 Synoptic wind Land-breeze/sea-breeze 23.06 http://www.arl.noaa.gov/ready.html

  4. PM10 concentrations EU 24h limit value (50 g/m3) Land/Sea breeze

  5. Analytical procedure for atmospheric and emission profile samples

  6. Polyaromatic hydrocarbons in Athens City center 6 0 [ n g / m g P M ] 5 0 4 0 3 0 A c N y l A c N 2 0 F P h e n 1 0 A F l 0 P B ( a ) A C h r Background B ( b ) F l B ( k ) F l 6 0 B ( a ) P I n d ( 1 2 3 c d ) P 5 0 d i B ( a h ) A B ( g h i ) P e r 4 0 3 0 2 0 1 0 0 1 4 N 1 4 D 1 6 N 1 6 D 1 7 N 1 7 D 2 1 N 2 1 D 2 2 N 2 2 D 2 3 N 2 3 D 2 4 N 2 4 D 2 5 N 2 5 D

  7. Factor analysis eij - estimated error for data value in sample i and compound j sij - residual • Positive Matrix Factorization • First paper by Paatero in 1994 and most resent 2004 • X = GF + E, X - data matrix, G - scores, F - loadings, E - unexplained part of X • Point-by-point least square fit of components so that the non-negative constraint and weighting of the data points are used. • Correlation matrix is not used • Objective is to minimise Q: • Estimated errors are iteratively re-evaluated • Limits for high and low concentration outliers were used • Multilinear Engine (ME2) • Table-driven least squares program for solving multilinear problems • PMF model was done using ME2 scripting language

  8. Error estimation Error for compound j in sample i for PMF model j – Detection limit of compound j Cij – Concentration of compound j in sample i ij – Partition of compound j in particulate phase in sampling temperature of sample i Kp – Temperature correctedpartitioning coefficient CPM– Concentration of PM PLsO – Temperature corrected subcooled liquid vapor pressure m, b – Constants (Fernández et al. Environ. Sci. Technol. 2002,36, 1162-1168) Ts – Sampling temperature

  9. Partitioning of PAH in sampling conditions 1. AcNyl 2. AcN 3. F 4. Phen 5. A 6. Fl 7. P 8. B(a)A 9. Chr 10. B(b)Fl 11. B(k)Fl 12. B(a)P 13. Ind(123cd)P 14. diB(ah)A 15. B(ghi)Per 

  10. Step 1: City center day samples, random initialization of profiles S o u r c e c o n t r i b u t i o n s 2 0 Measured profiles M e a s u r e d p r o f i l e s [ n g / m g P M ] T o t a l P A H 1 8 1 6 1 4 1 2 HD diesel LD gasol 1 LD gasol 2 1 0 PMF Factors P M F f a c t o r s 8 6 4 2 0 1 4 D 1 6 D 1 7 D 2 1 D 2 2 D 2 3 D 2 4 D 2 5 D 1 2 3 B ( a ) A C h r B ( b ) F l B ( k ) F l B ( a ) P I n d ( 1 2 3 c d ) P d i B ( a h ) A B ( g h i ) P e r

  11. Step 2: City center night samples, fixed initial profiles S o u r c e c o n t r i b u t i o n s Measured profiles M e a s u r e d p r o f i l e s [ n g / m g P M ] T o t a l P A H 5 0 4 5 4 0 3 5 3 0 HD diesel LD gasol 1 LD gasol 2 2 5 PMF Factors P M F f a c t o r s 2 0 1 5 1 0 5 0 1 4 N 1 6 N 1 7 N 2 1 N 2 2 N 2 3 N 2 4 N 2 5 N 1 2 3 B ( a ) A C h r B ( b ) F l B ( k ) F l B ( a ) P I n d ( 1 2 3 c d ) P d i B ( a h ) A B ( g h i ) P e r

  12. Step 3: City center night samples, 3 fixed and 1 random profile S o u r c e c o n t r i b u t i o n s Measured profiles M e a s u r e d p r o f i l e s [ n g / m g P M ] T o t a l P A H 5 0 4 5 4 0 3 5 3 0 HD diesel Gasol 1 Gasol 2 GasolMet 2 5 PMF Factors P M F f a c t o r s 2 0 1 5 1 0 5 0 1 4 N 1 6 N 1 7 N 2 1 N 2 2 N 2 3 N 2 4 N 2 5 N 1 2 3 4 B ( a ) A C h r B ( b ) F l B ( k ) F l B ( a ) P I n d ( 1 2 3 c d ) P d i B ( a h ) A B ( g h i ) P e r

  13. Source contributions Source contribution in city site 5 0 [ n g / m g P M ] Total PAH Diesel Gasoline 1 Gasoline 2 Gasoline+Meteo 4 0 3 0 2 0 1 0 0 1 4 N 1 4 D 1 6 N 1 6 D 1 7 N 1 7 D 2 1 N 2 1 D 2 2 N 2 2 D 2 3 N 2 3 D 2 4 N 2 4 D 2 5 N 2 5 D Source contribution in background site S o u r c e c o n t r i b u t i o n i n b a c k g r o u n d 5 0 [ n g / m g P M ] 4 0 Land/Sea breeze 3 0 2 0 1 0 0 2 2 N 2 2 D 2 3 N 2 3 D 2 4 N 2 4 D 2 5 N 2 5 D 1 4 N 1 4 D 1 6 N 1 6 D 1 7 N 1 7 D 2 1 N 2 1 D

  14. Summary • Particulate phase PAHs over the city of Athens are mostly traffic related. • Gasoline powered vehicles dominating the distribution, but their influence might be over estimated because of the higher portion of heavy PAH in their emissions. • Sampling conditions for environmental and source profile sampling should be closer to each other. • PMF is a powerful tool for source apportionment with capability of capturing profile changes caused by meteorology or chemistry

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