1. EMIS: Improve Emission Inventories of Environmentally Relevant Species

2. Agenda 11:00 Introduction – Randall Martin
11:10 ICARTT briefing – Daniel Jacob
11:25 Emission inventory assessment – David Parrish
11:40 Bottom-up inventory development – Ted Russell
12:00 lunch
1:30 NRT SCIAMACHY retrievals – Andreas Heckel
1:45 SAO retrievals – Kelly Chance
2:00 Preliminary SCIAMACHY/in situ comparison – Chris Sioris
2:15 VOC emissions – Paul Palmer
2:30 Action items – Randall Martin
2:40 Discussion
4 Adjourn

3. Weight by relative uncertainty
What Is Needed To Use Satellite Observations to Improve Emission Inventories?
Top-down emissions & uncertainty
Include in model
Optimized inventory & uncertainty
Test with correlative in situ obs
Weight by relative uncertainty
Bottom-up emissions & uncertainty
O3, NO, NO2, PAN, HNO3, HCHO, …
Quantified uncertainty in top-down inventory
Quantified uncertainty in bottom-up inventory
Ideally, attribution of differences to source type

4. Calculate Top-Down NOx Emissions from GOME/SCIAMACHY/OMI SCIAMACHY Tropospheric NO2
May 2004
Short NOx lifetime and dominance of NO2 near surface simplify calculation (top-down NOx emissions) Et =  t (satellite NO2 column observation) Calculate  locally with model as Ea/a (iterate if nonlinear)
Quantify uncertainty in satellite obs (validation and error propagation)
Quantify uncertainty in model chemistry (and transport)

5. How Can Different Source Types Be Isolated
How Can Different Source Types Be Isolated? By Day of the Week Variation
Friday Saturday Sunday
1015molec/cm2
Beirle et al., ACP, 2003

6. How Can Different Source Types Be Isolated
How Can Different Source Types Be Isolated? By Residual: Soils Contribute 40% of Surface NOx Emissions from Africa
Jaeglé, Martin, et al., JGR, in press