Underestimation of Elemental Carbon in PM: Reasons and Uncertainties in Modelling

1. Why do we underestimate Elemental Carbon in PM? Progress with MSC-W modelling of EC Presented by Svetlana Tsyro TFMM 7-th meeting, Helsinki, 10-12 May2006 Title

2. EC emissions, EMEP 2002 (Kt) (*) PM emission speciation based on Kupiainen, K. and Klimont (2004) Meteorologisk Instituttmet.no

3. EC concentrations Model calculated for 2002 Observed EMEP OC/EC campaign (July 2002-June 2003) 14 sites, 1 day a week Meteorologisk Instituttmet.no

4. Model vs. MeasurementsJuly 2002-March 2003 Bias=- 41% Corr= 0.84 Individual stations Bias: from -80% (PT01) to +7% (NO01) Temporal correlation:~ 0.54 from 0.12 (UK) to 0.73 (NL) Meteorologisk Instituttmet.no

5. Outline: Possible reasons for EC underestimation Missing emission sources Uncertainties in modelling of EC transport Uncertainties in anthropogenic emissions of EC/PM Meteorologisk Instituttmet.no

6. 1. Missing EC emission sources Wildland fires Monthly EC emissions from Global Fire Emission Database (GFED2) Meteorologisk Instituttmet.no

7. EC emissions in 2002 1. Wildland fires Anthropogenic Wildfires (GFED2) Units: tonnes/grid Meteorologisk Instituttmet.no

8. EC from wildfires in 2002 1. Wildland fires Contribution to total EC (%) Concentrations (ng/m3) Meteorologisk Instituttmet.no

9. 1. Wildland fires For the sites affected: Bias = - 39%  - 37% Corr = 0.85 Meteorologisk Instituttmet.no

10. 2. Uncertainties in modelling EC transport So far EC was assumed to be in internal mixture – hydrophilic Freshly emitted EC is mostly hydrophobic EC ”ageing” - getting coated with soluble material, becoming hydrophilic Meteorologisk Instituttmet.no

11. Hygroscopic properties of EC affect its removal 2. Uncertainties in modelling EC transport EC wet deposition No scavengingof hydrophobic EC from clouds EC dry deposition – Smaller dry deposition velocityof “fresh” EC (no hygroscopic growth of hydrophobic EC) Fresh EC is less efficiently removed that the aged EC More EC remains in the air Meteorologisk Instituttmet.no

12. Sensitivity tests on the effect of EC ageing: 2. Uncertainties in modelling EC transport 1.Internally mixed – hydrophilic Assume: 80% of emitted EC is hydrophobic 2.Ageing:hydrophobic  hydrophilic: turnover rate 2.5% h-1(e-time scale τ  1 day) (Cook and Wilson, JGR, 1996) variable turnover rate(Riemer et al. ACP, 2004) daytime summer, winter: τ = 8 h (below 250m) ---- # ---- # ---- #τ = 2 h (above 250m) night τ = 30 h (10 - 40 h) 3. Externally mixed – hydrophobic (no in-cloud scavenging) Meteorologisk Instituttmet.no

13. Effect of EC ageing 2. Uncertainties in modelling EC transport PHIL - hydrophilic EC AGEC - ageing EC with constant rate AGEV - ageing EC with variable rate, PHOB - hydrophobic EC Meteorologisk Instituttmet.no

14. Effect of EC ageing on results 2. Uncertainties in modelling EC transport UrbBG rural Near-city UrbBG Meteorologisk Instituttmet.no

15. 2. The effect of EC ageing Rather limited for the sites considered  However, the effect is expected to be larger in other regions with different pollution and precipitation regime  Even extreme case of hydrophobic EC yields a negative bias of 28% Even with no EC removal we still underestimate EC by 2% !!! Meteorologisk Instituttmet.no

16. EC emissions (EMEP, 2002) 3. Uncertainties in anthropogenic emissions Meteorologisk Instituttmet.no

17. Sensitivity tests for EC emissions 3. Uncertainties in anthropogenic emissions • EC emissions between 1 and 2.5 mkm • Underestimation of residential combustion emissions • Underestimation of traffic emissions Meteorologisk Instituttmet.no

18. Effect of EC properties 3. Uncertainties in anthropogenic emissions Near-city rural Urb BG Urb BG Meteorologisk Instituttmet.no

19. 3. Uncertainties in anthropogenic emissions Monthly series “Flat” underestimation Mixed Meteorologisk Instituttmet.no

20. 3. Uncertainties in anthropogenic emissions Underestimation -larger in winter Lager underestimation in summer Meteorologisk Instituttmet.no

21. 3. Uncertainties in anthropogenic emissions Underestimation larger in summer The EC underestimation is generally the same over the seasons, some places larger in summer than in winter Residential combustion cannot explain such underestimation (low emissions in summer) Results suggest: Emissions from mobile sources can be underestimated Meteorologisk Instituttmet.no

22. Conclusions: • Natural biomass burning emissions – arenot sufficiently widespread over Europe to explain the 40% underestimation of EC concentrations (improvements of bias by 2-10%) • EC hygroscopity ++ has a small effect over central European areas and does not provide a feasible explanation for the EC underestimation • The results suggest that anthropogenic EC/PM emissions are underestimated Meteorologisk Instituttmet.no

23. Conclusions: • EC emission underestimation++ analysis of temporal correlations results indicates that the underestimation is generally the same for different seasons. • This points out the importance of traffic and off-road mobile sources • Are emission factors for diesel underestimated? • Can these be re-evaluated (ref. US EPA) • Measurements needed ! Uncertainties in measured EC (analytical procedures) Meteorologisk Instituttmet.no

24. Thank you!