Folkert Boersma, D.J. Jacob, R.J. Park, R.C. Hudman – Harvard University H.J. Eskes, J.P. Veefkind, R.J. van der A, P.F. Levelt, E.J. Brinksma – KNMI A. Perring, R. Cohen, T. Bertram, P. Wooldridge – University of California E.J. Bucsela, J.F. Gleason – NASA GSFC A. Gilliland – NOAA/EPA Validation and interpretation of OMI tropospheric NO 2 observations during INTEX-B and comparison to SCIAMACHY

Integration of aircraft and satellite observations Sub-satellite spirals (0-12 km) for validation OMI trace gases Spiral 1 (down) Spiral 2 (up) Important goal INTEX-B: EOS-Aura Validation Criteria Cloud fraction < 20% Use all OMI pixels covered by spatial extent of spiral Use of KNMI analysed near-real time product (

DC8: molec. cm -2 OMI: 2.62 ± molec. cm -2 (n = 19) Berkeley TD/LIF Validation of OMI tropospheric NO 2 : 4 March 2006

All OMI validation spirals during March 2006 All spirals r = 0.89 n = 18 DC8-OMI: molec. cm -2 RMS: molec. cm -2 Mexico City Remote Gulf of Mexico

OMI vs. GEOS-Chem NO 2 with EPA NEI99 emissions OMI NEI99/BRAVO GEOS-Chem GEOS-Chem with NEI99 too high (+30%) over midwest too low over Mexico (up to -50%)

EPA emission reports OMI Studies by Richter et al. (2005) and van der A et al. (2006) also show negative trend in NO 2 columns Power plants Other Industry Mobile ~60%~20%

r 2 =0.87r 2 =0.86 Have emissions changed since 1999? Decompose OMI derived NOx emissions with SVD Decompose best guess of inferred emissions into underlying basis functions Basis functions: EPA (1999) source category patterns Total NO x emissions: -2.5% (March 1999 – March 2006) Power plants:-22%  15% Mobile: +31%  16% Other industry: +9%  29% Rest: -45%  45% Frost et al.: -20% ( )

How do SCIAMACHY and OMI compare? Method Grid SCIAMACHY and OMI NO2 observations on 0.5 x 0.5 grid Take only those grid cells that were cloud-free for both instruments Compute monthly averages SCIAMACHY: hrs local time OMI: hrs local time

r = 0.76 n = 1.9×10 6 OMI 10-40% lower than SCIAMACHY for most anthropogenic source regions OMI higher than SCIAMACHY for biomass burning regions

Simulating 10am to 1:30pm with GEOS-Chem ObservedGEOS-Chem US: -16% -28% EU: -6%-13% China: -26%-22% Relative decrease in NO2 column from 10am to 1:30 pm

Biomass burning mainly in afternoon Jun Wang Relative increase in NO 2 column from 10am to 1:30 pm ObservedGEOS-Chem Africa:+48% +16% Indon.:+60%+10% Brazil:+54%+13%

Conclusions 1. OMI NO 2 validation during INTEX-B: r=0.89, low bias Decreasing power plant NO x emissions (-20%, ) Evidence for increasing mobile emissions (+30%, ) 3. SCIAMACHY and OMI observe - photochemistry - diurnal emission patterns from space