Particle Matter in Po Valley (Source Apportionment)

1European Commission - JRC Institute for Environment and Sustainability, Ispra, Italy2Université Libre de Bruxelles, Brussels, Belgium

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

JRC-ISPRA 28 April 2011 1


Is there any influence of photochemistry on PM2.5 concentration in the Po valley?


Limito di Pioltello and the Po valley, Italy

Po Valley

Limito di PioltelloMilano

Large agricultural areas Industrial area Large residential area ~ 30.000 inhabitants

Site of the field campaign:Limito di Pioltello

Limito di Pioltello is located in the Po valleynear the city of Milan

Date: 17-20 Jun 2009 08-17 July 2009


4-hour experimental time resolution

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)


Results


What causes the PM2.5, PM10 summer EPISODE?

15-16 July 2009

NO input ?

increase of O3 levels

less polluted

EPISODE

EPISODE


Ions (PM2.5) correlated with absolute humidity

Night-early morning: NO3- and NH4

+

Evening:SO4- -

EPISODE


NO3- and SO4

-- are balanced by NH4+

4NH

-24SO-3NO

Seinfeld, J. H., and S. N. Pandis (2006), John Wiley & Sons, Inc.Vecchi, R., et al. (2009), Environ. Monit. and Assess., 154(1-4), 283-300Zhang, K., et al. (2007), Atmos. Res., 84, 67-77

particles(secondary inorganic aerosols, SIA)

less polluted

EPISODE


Secondary Inorganic Aerosols (SIA)

OH

)(l2OH)(3 g2(g) NONO

42SOH

3HNO

3(g)NH

2(g)SO

34NONH44 )HSO(NH424 SO)(NH

Seinfeld, J. H., and S. N. Pandis (2006), John Wiley & Sons, Inc.Zhang, K., et al. (2007), Atmos. Res., 84, 67-77Dickerson, R. R. (2003), Nat. Atmos. Dep Progr. Ammonia WorkshopFinlayson-Pitts, B. J., and J. N. Pitts, (2000), Academic Press: San DiegoKaragulian, F., and M. J. Rossi, (2005), 7(17), Phys. Chem. Chem. Phys. 3150-3162

SIAAerosolformation

Aqueous phase photochemistry of SO2 and NO2

Heterogeneousprocesses

)(l2OH

3(g)SO

)(5 g2ON

photochemistry

nighttime


NH3 in the Po Valley: 7-19 July 2009satellite observation in the boundary layer

Large reservoir of NH3 in the Po valley (Italy)

major NH3 sources: fertilizers animal waste

major NH3 sinks: wet and dry deposition

Po Valley

Limito di PioltelloMilano

Averaged NH3 total column from 7 to 17 July 2009

(data are provided by IASI on the MetOp-A Meteorological payload)

The aerial background photographs are © 2008 Google-Imagery © 2008 Terrametrics (http://maps.google.com)Clarisse, L., et al. (2009), Nature Geoscience, 2(7), 479-483

volatilization: temperature relative humidity - - - > nucleation


PM2.5 dominated by SIA during the EPISODE

OM = 1.4 x OCLess polluted8th July 2009

EPISODE16th July 2009

Turpin, B. J., and H. J. Lim (2001), Aerosol Science and Technology, 35(1), 602-610Vecchi, R., et al. (2009), Environ. Monit. and Assess., 154(1-4), 283-300

OM = 1.6 x OC

OM = 2.0 x OC

Si, Fe, Al, Zn, Na, contributed for less than 1% to the total PM2.5 mass


Fine particles dominate the EPISODE

Coarse-crustal (transport, re-suspension)

(2.0-15.0 µm)

Fine particles(0.25-0.58 µm)

even

ing

nigh

t

* Data are from ARPA Lombardia (Italy)


Wind direction coherent with trends for wind speed

Fine particles during nighttime (local)

00-04h 04-08h 08-12h 16-20h12-16h 20-24h

Coarse particles during afternoon

(advection + traffic)


Photochemical formation of carbonyls during the EPISODE

AldehydesVOCsO3

OH

Sampling on air!

Photochemical smogdaytime

Atkinson, R., et al. (1984), Journal of Physical Chemistry, 88(6), 1210-1215Donahue, N. M., et al. (2009), Atmos. Environ., 43(1), 94-106

O3

vehicle exhausts gasoline vapor

Lau, A. K. H. et al. (2010), 408(19), Science of the Total Environment 4138-4149.

O3

formation

OHROHVOCs 2


The most volatile OC fraction of PM2.5 correlates with photochemical oxidation products

(OC1)oxygenated

organic compounds

Correlation: r2 ~ 0.7

Matuschek, G., et al. (2007), Environmental Science and Technology, 41(24), 8406Streibel, T., et al. (2006), Analytical Chemistry, 78(15), 5354

RT Quartz temperature protocolfor OC/EC thermal desorption

Oxygenated organic compounds

EPISODE


Comparison between EPA PMF 3.0 andMultilinear Engine (ME-2)


Source apportionment and receptor models

p

1kkjikij fgx

Mass conservation principle….

i = 1,2,….m (samples) j = 1,2,….n (species) uij is the measured uncertainty

Concentration of the jth specie in the ith sample

Concentration of the ith specie in the kth source

Contribution of the kth source in the jth sample

When both gik and fkj are unknown, the Positive matrix Factorization (PMF) model is used (EPA PMF 3.0)

best fit

2

n

1i

m

1j ij

p

1kkjikij

main

u

fgx

Q

object function

f)(x,Qmin main

f

two way model


Multilinear Engine ME-2

We can also use a PMF which includes constraints and pulling equations

Introducing the Multilinear Engine ME-2 auxmain QQQ

V

lv

V

lv

2v

2pjv

auxv

aux /s)f(aQQ

softness of the pullingpulling value


Source Contribution Estimation to PM2.5

Viana, M., et al. (2008), Journal of Aerosol Science, 39(10), 827-849

EU Report, Regione Lombardia (under revision)

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

Amato, F. et al., (2009), 43(17), Atmospheric Environment, 2770-2780


Wind direction factors for each source

Sulfate Traffic Nitrate

Uniformly distributed around the receptor site

Enhanced ME-2 2-way model with constraints

and pulling equations

Po Valley

Predominant from Po Valley

Predominant from Milano area

MilanoLimito


Higlights

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

Diurnal Trend Analysis


PM2.5 diurnal profiles


Conlusions

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)

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


Thanks for your attentionThanks for your attention

Acknowledgment Data: Michel Gerboles, Sinan Yatkin, Bo LarsenProgramming: Luca Spano’General Support: all my friends

Particle Matter in Po Valley (Source Apportionment)

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