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Biomass Smoke Aerosol: Spatial and Temporal Pattern over the US

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

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Biomass Smoke Aerosol: Spatial and Temporal Pattern over the US

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  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: DEC/DOC = 0.08 DPM25/DOC = 1.5 Smoke Excess OC – EC Calibration of Smoke Composition EC/OC Ratio DPM25 DEC DOC • Smoke (excess) PM25, EC and OC yields calibration • Ratios for Kansas, Big Bend and Quebec smoke are similar • Good news for OC apportionment

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

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

  7. OCS, OCNS and PM25 Seasonal PatternAverage over 2000-2004 period PM25Mass OCS Smoke Agricultural Smoke Mexican Smoke OCNS NonSmoke Day of Year Urban NonSmoke Carbon

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

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

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

  11. Example OC ‘Smoke’ Events Smoke Events

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

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

  14. Monthly Maps of Fire Pixels NOAA HMS – S. Falke Kansas Ag Smoke No Smoke Jan Feb Mar Apr May Jun Jul Aug Smoke Sep Oct Nov Dec • Fire pixels are necessary but not sufficient • Some Fire pixels produce more smoke aerosol than others …by at least factor of 5

  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

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