EMIS: Improve Emission Inventories of Environmentally Relevant Species

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

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

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)

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

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