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 dpp=20 nm Note change in scale dm=472 nm Sources - Combustion 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™ ATN = ln (I0 / I) Reference I0 Sensing I BC Light Source Filter with Sample Light Detectors  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

Filter loading effect

BC vs ATN analysis – ambient data k=0.005 k=0.001 Large loading effect Small loading effect 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 need to determine it dynamically – do not assume, rather measure

Dual spot Aethalometer – AE33 ATN1 = ln (I0 / I1) Reference I0 Sensing I1 BC1 Light Source Filter with Sample Light Detectors  Sensing I2 ATN2 = ln (I0 / I2) BC2 Two parallel spots with different flow, therefore -> From different loading and attenuation loading compensation parameter k(λ) is calculated. Absorption data is compensated: babs=babs1/(1-k*ATN1) Payerne Winter 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

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 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 Paris 968 25 671 4

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 Payerne summer Payerne winter Spectral fingerprint Summer and winter aerosols have different optical properties - k(λ) For background locations with aged aerosol loading effect at 880 nm (where BC is measured) is small!

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 Particle diameter [nm]

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

Particle coating hypotesis – summer data AE33 compensation parameter Paris Summer2012 campaign ACSM 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

Thank you for your attention! Acknowledgements The work described herein was co-financed by the EUROSTARS grant E!4825 and JR-KROP 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!