1. Biomass Smoke Aerosol: Spatial and Temporal Pattern over the US October 2005 rhusar@me.wustl.edu

2. Estimation of Smoke Mass The estimation of smoke mass from speciated aerosol data has eluded full quantification for many years CIRA, Poirot and others have While full quantification is still not in hand, a proposed approximate approach yields reasonably consistent results The smoke quantification consists of two steps: –Step 1: Carbon apportionment into Smoke and NonSmoke parts –Step 2: Applying factors to turn OCSmoke and OCNonSmoke into Mass

3. Smoke Quantification using Chemical Data –Step 1: Carbon apportionment into Smoke and NonSmoke parts Carbon (OC & EC) is assumed to have only two forms: smoke and non-smoke OC = OCS (Smoke) + OCNS (NonSmoke) EC = ECS (Smoke) + ECNS (NonSmoke) In each form, the EC/OC ratio is assumed to be constant ECS/OCS = rs (In smoke, EC/OC ratio rs =0.08) ECNS/OCNS = rns (In non-smoke, EC/OC ratio rns = 0.4) With thes four equations, the value of the four unknowns can be calcualted OCS = (rns*OC –EC)/(rns-rs) = (0.4*OC – EC)/0.32 OCNS = OC-OCS ECS = 0.088*OCS ECNS = 0.4*OCNS –Step2: Apply a factor to turn OC into Mass The smoke and non-smoke OC is scaled by a factor to estimate the mass OCSmokeMass = OCS*1.5 OCNonSmokeMass = OCNS*2.4

4. Smoke Excess OC – EC Calibration of Smoke Composition Smoke (excess) PM25, EC and OC yields calibration Ratios for Kansas, Big Bend and Quebec smoke are similar Good news for OC apportionment  PM25  EC  OC Smoke:  EC/  OC = 0.08  PM25/  OC = 1.5 EC/OC Ratio

5. OC–EC Non-Smoke Calibration by Iteration Non-smoke ratios are more difficult EC/OC of about 0.2-0.4 is reasonable Outside this range is not EC/OC Non-Smoke = 0.15 EC/OC Non-Smoke = 0.2 EC/OC Non-Smoke = 1EC/OC Non-Smoke = 0.4 Negative Smoke – not PossibleMaybe?? Too little non-smoke too much smoke Smoke OC Non Smoke OC

6. Measured and Reconstructed PM25 Mass Regional ‘calibration’ constants we applied to OC and Soil

7. OCS, OCNS and PM25 Seasonal Pattern Average over 2000-2004 period PM25 Mass OCS Smoke OCNS NonSmoke Day of Year Mexican Smoke Agricultural Smoke Urban NonSmoke Carbon

8. OC Smoke Spatial Pattern Dec Jan Feb Sep Oct Nov Mar Apr May Jun Jul Aug

9. EC NonSmoke Dec Jan Feb Sep Oct Nov Mar Apr May Jun Jul Aug

10. PM2.5 (blue) and ‘SmokeMass’ (red) Smoke Events Kansas Ag Smoke

11. Example OC ‘Smoke’ Events Smoke Events

12. Seasonality of OC Percentiles IMPROVE/STN Inconsistencies Not shown here Great Smoky Mtn: Episodic OC in the Fall season Chattanooga:: Elevated and Persistent OC

13. GRSM Seasonal Pattern of Percentiles PM25 OC SO4 Soil Episodic OC in Fall dominates episodicity - Smoke Organics?

14. Monthly Maps of Fire Pixels Fire pixels are necessary but not sufficient Some Fire pixels produce more smoke aerosol than others …by at least factor of 5 NOAA HMS – S. Falke JanFebMarApr AugJunJulMay SepOctNovDec Smoke Kansas Ag Smoke No Smoke

15. Summary Developments (CIRA, Poirot, others) OC and EC can be reasonably apportioned between Smoke and NonSmoke components The reconstructed mass can be matched to the measured PM25 Problems of OC Apportionment Need to incorporate biogenic OC! IMPROVE and STN OC don’t match Some coefficients may need regional/seasonal calibration