Indication of aerosol aging by Aethalometer optical
absorption measurements
Luka Drinovec1, Griša Močnik1, Irena Ježek1, Jean-Eudes Petit2,3, Jean Sciare2, Olivier
Favez3, Peter Zotter4, Robert Wolf4, André S.H. Prévôt4, and Anthony D.A. Hansen1,5
1. Aerosol d.o.o., Kamniška 41, SI-1000 Ljubljana, Slovenia
2. LSCE (CEA-CNRS-UVSQ), Orme des Merisiers, Gif-sur-Yvette, France;
3. INERIS, Verneuil-en-Halatte, France
4. Paul Scherrer Institut, CH-5232 Villigen PSI, Switzerland
5. Magee Scientific, 1916A M.L. King Jr. Way, Berkeley, CA 94704, USA
Keywords: Aethalometer, source apportionment, ACSM, AMS, PSCF
Contact author email: luka.drinovec@aerosol.si
Presenting author email: irena.jezek@aerosol.si
ACCENT Symposium 2013, Urbino (Italy)
1. Introduction to BC measurements
dm=472 nm
Sources
- Combustion
dpp=20 nm
Note change in scale
Effects of black carbon (BC):
- Public health effects
- Climate change
How to reduce harmfull effects:
- Indentify sources: traffic vs household heating
- Indentify sources: local vs. regional
Analytical Instrument : Aethalometer™
Reference I0
BC
ATN = ln (I0 / I)
Light Detectors
Light Source
Filter with Sample
•
•
•
•
Sensing I

babs ~  ATN
Collect sample continuously.
Optical absorption ~ change in ATN.
Measure optical absorption continuously : λ = 370 to 950 nm.
Convert optical absorption to concentration of BC:
BC (t) = babs(t) / 
 - mass absorption crossection
• Real-time data: 1 s/1 minute
3
400
Tape advance
Tape advance
Filter loading effect
babs at 370 nm
raw data
compensated
babs (Mm-1)
300
200
100
0
0
100
200
300
t (min)
400
500
BC vs ATN analysis – ambient data
London Oct-Dec 2006
Roxbury Feb - June 1999
16000
1400
R2 = 0.90
14000
1200
Average BC in 1-ATN bin
Average BC in 1-ATN bin
k=0.005
k = 4.6
12000
10000
8000
Large loading
effect
6000
Average BC per 1 unit of ATN
4000
Linear fit
1000
R2 = 0.117
800
k = 1.4
k=0.001
600
Average BC
Linear fit
200
2000
0
Small loading
effect
400
0
0
5
10
15
20
25
30
35
40
45
50
0
5
10
15
ATN
20
25
30
35
40
ATN
BC (reported) = BC (zero loading) · { 1 - k · ATN }
Linear reduction of the instrumental response due to loading of the filter fiber.
Jump at the tape advance (similar to Virkkula (2007) model).
• ambient data – no dependence of BC on ATN
• slope k variable: site, source, aerosol age, composition
• 5need to determine it dynamically – do not assume, rather measure
45
Dual spot Aethalometer – AE33
Filter with Sample

Reference I0
BC1
Light Source
Sensing I1
Sensing I2
BC2
ATN1 = ln (I0 / I1)
ATN2 = ln (I0 / I2)
Light Detectors
Two parallel spots with different
flow, therefore ->
370 mn
470 nm
520 nm
590 nm
660 nm
880 nm
950 nm
0,010
From different loading and
attenuation loading compensation
parameter k(λ) is calculated.
0,008
k()
0,006
0,004
Absorption data is compensated:
6
babs=babs1/(1-k*ATN1)
0,002
Payerne Winter 2013
0,000
12.1.2013
19.1.2013
26.1.2013
time
2.2.2013
9.2.2013
BC source apportionment
• measure attenuation with the
Aethalometer
• absorption coefficient - babs
• for pure black carbon: babs ~1/λ
• generalize Angstrom exponent:
babs ~1/λα
diesel: α ≈ 1
wood-smoke: α ≈ 2 and higher
J. Sandradewi et al., A study of wood burning and traffic aerosols in an Alpine valley using a multi-wavelength
Aethalometer, Atmospheric Environment (2008) 101–112
7
BC source apportionment
b(λ) = bwb (λ,wood) + bff (λ,fossil)
λ = 470 nm, 950 nm
bi(470 nm) / bi (950 nm) = (470 nm / 950 nm) -
α = 1,0 ± 0,1 (fossil) Bond & Bergstrom 2004
α = 2,0 -0,5/+1,0 (wood) Kirchstetter 2004,
Day 2006,
Lewis 2008
BCwb
BCff
8
Sandradewi 2008
Measurement campaign
EMEP: summer 2012 & winter 2013
Paris site
- SIRTA Atmospheric Research Observatory
- located in a semi-urban environment
- 25 km south of the Paris city center
Payerne site
- Payerne aerological station
- Rural background site
- NW Swiss
Site
Campaign
BC (ng/m3)
Biomass burning (%)
Payerne
Winter 2013
789
29
Summer 2012
593
10
Winter 2013
968
25
Summer 2012
671
4
Paris
Back trajectory analysis
Back trajectory analysis using Potential Source Contribution Function (PSCF)
• Represents the probability that an air parcel may be responsible for high
concentrations observed at the receptor site
• 72h back trajectories calculated with Hysplit v4.9
• starting at 500m AGL
An example:
- PSCF analysis of BC
- Paris winter 2013
Indentification of source locations
- Angstrom exponent α obtained from AE33 spectral data
- PSCF (Back trajectory analysis using Potential Source Contribution Function)
α < 1.3 (traffic emissions)
α > 1.3 (biomass burning)
Paris – EMEP winter campaign 2013
Differentiation of fresh and aged aerosols
0,010
0,010
370 mn
470 nm
520 nm
590 nm
660 nm
880 nm
950 nm
0,008
370 nm
470 nm
520 nm
660 nm
880 nm
950 nm
0,008
0,006
k()
k()
0,006
Payerne summer
0,004
0,004
0,002
0,002
Payerne winter
0,000
12.1.2013
0,010
19.1.2013
26.1.2013
2.2.2013
Spectral fingerprint
0,000
16.6.2012
9.2.2013
24.6.2012
28.6.2012
2.7.2012
6.7.2012
winter
summer
0,009
0,008
Summer and winter aerosols have
different optical properties - k(λ)
0,007
Average k()
20.6.2012
0,006
0,005
For background locations with aged
aerosol loading effect at 880 nm (where
BC is measured) is small!
0,004
0,003
0,002
0,001
0,000
300
400
500
600
700
 (nm)
800
900
1000
Differentiation of fresh and aged
aerosols
- Compensation parameter k880nm obtained from AE33
- PSCF (Back trajectory analysis using Potential Source Contribution Function)
k880nm>0.002 (fresh aerosols)
k880nm<0.002 (aged aerosols)
Paris – EMEP summer campaign 2012
Particle coating hypotesis
Changes in k(λ) are caused by transparent coating
SMPS:
Fresh soot particle size = 20-50 nm
Aged particle size > 100 nm
Payerne Summer2013
Measurement
fit1
fit2
fit1 + fit2
1200
Particle number
1000
800
600
400
200
0
10
100
-Particle diameter
[nm]
1000
Particle coating hypotesis
Coating factor (CF) – ratio between the sum
of nonrefractory aerosol mass to BC:
CF = (Org + NH4 + SO4 +NO3)/BC
Aerosol mass spectrometers:
ACSM & AMS (Aerodyne)
-> Aerosol chemical composition is obtained
12
Org
NH4
Conc. (g/m3)
10
SO4
8
NO3
6
4
2
0
16.6.2012
23.6.2012
30.6.2012
7.7.2012
Particle coating hypotesis – summer data
-0,003
-0,002
AE33 compensation
parameter
-0,001
Paris Summer2012
campaign
0,001
0,002
0,003
0,004
0,005
30
(SO4 + NH4 + ORG) / BC
k880 nm
0,000
25
ACSM
20
15
10
5
0
13.6.2012 20.6.2012 27.6.2012 4.7.2012 11.7.2012
Compensation parameter
k880nm and coating factor
correlate well.
Summary
Spectral absorption data from Aethalometer AE33 was used for
BC source apportionment during EMEP campaigns in Paris
(France) and Payerne (Switzerland).
Back trajectory analysis using Potential Source Contribution
Function (PSCF) was used to determine fossil fuel and biomass
burning locations.
PSCF: Aged aerosols have small k880nm
Aethalometer and ACSM/AMS measurements were used for
calculation of the coating factor (CF): Big CF = Small k880nm
Acknowledgements
The work described herein was co-financed by the EUROSTARS grant E!4825 and JRKROP grant 3211-11-000519. Measurements performed at SIRTA (LSCE) were funded
by CNRS, CEA, the EU-FP7(2007-2013) 'ATRIS' project under grant agreement
n°262254, the Primequal Predit 'PREQUALIF' project (ADEME contract n°1132C0020),
and the DIM R2DS (AAP 2010) 'PARTICUL'AIR' project. Measurements in Payerne
were conducted by the Swiss Federal Office for the Environment (FOEN).
Thank you for your attention!