heikki junninen, covadonga astorga-llorens, vittorio forcina, anne müller and bo larsen

14
1 Heikki Junninen, Covadonga Astorga- Llorens, Vittorio Forcina, Anne Müller and Bo Larsen Institute for Environment and Sustainability (IES) Ispra, Italy Emissions & Health Unit PARTICULATE MATTER AND POLYAROMATIC COMPOUNDS IN AIR OVER ATHENS DURING THE BOND SUMMER CAMPAIGN, JUNE 2003

Upload: gambhiri-naveen

Post on 02-Jan-2016

27 views

Category:

Documents


1 download

DESCRIPTION

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. - PowerPoint PPT Presentation

TRANSCRIPT

Page 1: Heikki Junninen, Covadonga Astorga-Llorens, Vittorio Forcina, Anne Müller and Bo Larsen

1

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

Institute for Environment and Sustainability (IES)Ispra, Italy

Emissions &Health Unit

PARTICULATE MATTER AND POLYAROMATIC COMPOUNDS IN AIR OVER ATHENS DURING THE BOND SUMMER

CAMPAIGN, JUNE 2003

Page 2: Heikki Junninen, Covadonga Astorga-Llorens, Vittorio Forcina, Anne Müller and Bo Larsen

2

14d (red) & 14n(blue)

24'

36' 4 8 ' 24

oE

1 2 '

40'

50'

38oN

10'

20'

Tatoi

Eleusina

Ellinko

Nea Philadelphia

Spata

10 m s-1

23d (red) & 23n(blue)

4 8 ' 24

oE

1 2 '

Tatoi

Eleusina

Ellinko

Nea Philadelphia

Spata

10 m s-1

Meteorological Conditions

14.06 Synoptic wind Land-breeze/sea-breeze 23.06

Page 3: Heikki Junninen, Covadonga Astorga-Llorens, Vittorio Forcina, Anne Müller and Bo Larsen

3

http://www.arl.noaa.gov/ready.html

Back trajectories14.06 Synoptic wind Land-breeze/sea-breeze 23.06

24'

36' 48' 24

oE

12'

40'

50'

38oN

10'

20'

Night

24'

36' 48' 24

oE

12'

40'

50'

38oN

10'

20'

Day

24'

36' 48' 24

oE

12'

40'

50'

38oN

10'

20'

Day

24'

36' 48' 24

oE

12'

40'

50'

38oN

10'

20'

Night

Page 4: Heikki Junninen, Covadonga Astorga-Llorens, Vittorio Forcina, Anne Müller and Bo Larsen

4

PM10 concentrations

EU 24h limit value

(50 g/m3)

0.0

20.0

40.0

60.0

80.0

100.0

120.0

night 12.06 day 12.06 night 13.06 day 13.06 night 14.06 day 14.06 night 15.06 day 15.06 night 16.06 day 16.06 night 17.06 day 17.06 night 18.06 day 18.06 night 19.06 day 19.06 night 20.06 day 20.06 night 21.06 day 21.06 night 22.06 day 22.06 night 23.06 day 23.06 night 24.06 day 24.06 night 25.06 day 25.06night 26.06day 26.06

Concentration [ug/m3]

Land/Sea breeze

Page 5: Heikki Junninen, Covadonga Astorga-Llorens, Vittorio Forcina, Anne Müller and Bo Larsen

5

Analytical procedure for atmospheric and emission profile samples

Page 6: Heikki Junninen, Covadonga Astorga-Llorens, Vittorio Forcina, Anne Müller and Bo Larsen

6

Polyaromatic hydrocarbons in Athens

0

10

20

30

40

50

60[ng/mg PM]

AcNylAcNFPhenAFlPB(a)AChrB(b)FlB(k)FlB(a)PInd(123cd)PdiB(ah)AB(ghi)Per

14N 14D 16N 16D 17N 17D 21N 21D 22N 22D 23N 23D 24N 24D 25N 25D0

10

20

30

40

50

60Background

City center

Page 7: Heikki Junninen, Covadonga Astorga-Llorens, Vittorio Forcina, Anne Müller and Bo Larsen

7

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:

Factor analysis

Multilinear Engine (ME2)

• Table-driven least squares program for solving multilinear problems

• PMF model was done using ME2 scripting language

Q =i+1

n

∑eij

2

sij2

j +1

m

∑ eij - estimated error for data value in sample i and compound j

sij - residual

• Estimated errors are iteratively re-evaluated

• Limits for high and low concentration outliers were used

Page 8: Heikki Junninen, Covadonga Astorga-Llorens, Vittorio Forcina, Anne Müller and Bo Larsen

8

Error estimation

Error for compound j in sample i for PMF model

ij

ijj C

ijs Φ+Λ= 2.0

Λj – Detection limit of compound jCij – Concentration of compound j in sample iΦij – Partition of compound j in particulate phase in sampling temperature of sample iKp – Temperature corrected partitioning coefficientCPM – Concentration of PMPLs

O – Temperature corrected subcooled liquid vapor pressurem, b – Constants (Fernández et al. Environ. Sci. Technol. 2002,36, 1162-1168)

Ts – Sampling temperature

bpmKp oLs += loglog

( )11loglog −−Δ −+= sRHo

LoLs TTpp( )PM

PM

KpCKpC+=Φ 1

Page 9: Heikki Junninen, Covadonga Astorga-Llorens, Vittorio Forcina, Anne Müller and Bo Larsen

9

Partitioning of PAH in sampling conditions

1 2 3 4 5 6 7 8 9 10 11 12 13 14 150

0.25

0.5

0.75

1Vehicle testingAtmospheric sampling 1. AcNyl

2. AcN 3. F 4. Phen 5. A 6. Fl 7. P 8. B(a)A 9. Chr10. B(b)Fl11. B(k)Fl12. B(a)P13. Ind(123cd)P14. diB(ah)A15. B(ghi)Per

Φ

Page 10: Heikki Junninen, Covadonga Astorga-Llorens, Vittorio Forcina, Anne Müller and Bo Larsen

10

14D 16D 17D 21D 22D 23D 24D 25D0

2

4

6

8

10

12

14

16

18

20[ng/mg PM]

Source contributions

Total PAH

B(a)A Chr B(b)Fl B(k)Fl B(a)P Ind(123cd)P diB(ah)A B(ghi)Per

Measured profiles

1 2 3

PMF factors

HD diesel LD gasol 1 LD gasol 2

Measured profiles

PMF Factors

Step 1: City center day samples, random initialization of profiles

Page 11: Heikki Junninen, Covadonga Astorga-Llorens, Vittorio Forcina, Anne Müller and Bo Larsen

11

Step 2: City center night samples, fixed initial profiles

14N 16N 17N 21N 22N 23N 24N 25N0

5

10

15

20

25

30

35

40

45

50 [ng/mg PM]

Source contributions

Total PAH

B(a)A Chr B(b)Fl B(k)Fl B(a)P Ind(123cd)P diB(ah)A B(ghi)Per

Measured profiles

1 2 3

PMF factors

Measured profiles

PMF Factors

HD diesel LD gasol 1 LD gasol 2

Page 12: Heikki Junninen, Covadonga Astorga-Llorens, Vittorio Forcina, Anne Müller and Bo Larsen

12

Step 3: City center night samples, 3 fixed and 1 random profile

14N 16N 17N 21N 22N 23N 24N 25N0

5

10

15

20

25

30

35

40

45

50 [ng/mg PM]

Source contributions

Total PAH

B(a)A Chr B(b)Fl B(k)Fl B(a)P Ind(123cd)P diB(ah)A B(ghi)Per

Measured profiles

1 2 3 4

PMF factors

Measured profiles

PMF Factors

HD diesel Gasol 1 Gasol 2 GasolMet

Page 13: Heikki Junninen, Covadonga Astorga-Llorens, Vittorio Forcina, Anne Müller and Bo Larsen

13

Source contributions

14N 14D 16N 16D 17N 17D 21N 21D 22N 22D 23N 23D 24N 24D 25N 25D0

10

20

30

40

50 [ng/mg PM]

14N 14D 16N 16D 17N 17D 21N 21D 22N 22D 23N 23D 24N 24D 25N 25D0

10

20

30

40

50 [ng/mg PM]

Source contribution in background

Total PAHDieselGasoline 1Gasoline 2Gasoline+Meteo

Source contribution in city site

Source contribution in background site

Land/Sea breeze

Page 14: Heikki Junninen, Covadonga Astorga-Llorens, Vittorio Forcina, Anne Müller and Bo Larsen

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