Satellite and Aircraft Based Constraints on NO X Emissions Randall Martin Chris Sioris Kelly Chance Tom Ryerson Andy Neuman Ron Cohen UC Berkeley Aaron Swanson Frank Flocke NCAR CIRES

Air Mass Factor Calculation in SCIAMACHY Retrieval Needs External Info on Shape of Vertical Profile d()d() IoIo IBIB EARTH SURFACE RADIATIVE TRANSFER MODEL Scattering weight ATMOSPHERIC CHEMISTRY MODEL Shape factor Calculate w(  ) as function of: solar and viewing zenith angle surface albedo, pressure cloud pressure, frac aerosol profile, type Individual SCIAMACHY Scenes NO 2 mixing ratio C NO2 (  ) norm. by column Ω NO2  (  ) is temperature dependent cross-section sigma (  )

Increased NO x Emissions from Midlatitude Improves GEOS-CHEM Simulation of NO 2 Profiles Used in Retrieval Remaining Discrepancy In Vertical Profile of NOx Emissions (i.e. importance of cloud-cloud flashes) Midlatitude lightningMean Bias in AMF: 0.4 Tg N yr -1 12%9%3% 1.6 Tg N yr -1 1%5%3% In Situ 0.4 Tg N yr Tg N yr -1

Enhanced Midlatitude Lightning Reduces Discrepancy with SCIAMACHY over North Atlantic Profile of NOx Emissions (lifetime) May Explain Remaining Discrepancy May-Oct 2004 SCIAMACHY NO 2 (10 15 molec cm -2 ) GEOS-Chem NO 2 (10 15 molec cm -2 ) 1.6 Tg N in Midlat GEOS-Chem NO 2 (10 15 molec cm -2 ) 0.4 Tg N in Midlat

Significant Agreement Between Coincident Cloud-Filtered SCIAMACHY and In-Situ Measurements r = 0.79 slope = 0.8 1:1 line Ryerson NO 2 Cohen NO 2 Chris Sioris Coincident measurements Cloud-radiance fraction < 0.5 In-situ measurements below 1 km & above 3 km Assume constant mixing ratio below lowest measurement Add upper tropospheric profile from mean obs Horizontal bars show 17 th & 83 rd percentiles

Cloud-filtered Tropospheric NO 2 Columns Retrieved from SCIAMACHY May-Oct 2004 detection limit

Error weighting Conduct a Chemical Inversion & Combine Top-Down and Bottom-up Inventories with Error Weighting A posteriori emissions Top-Down Emissions molec cm -2 A Priori NOx Emissions SCIAMACHY NO 2 Columns molec N cm -2 s -1 GEOS-CHEM model

May-Oct 2004 Global Optimal Emission Inventory Reveals Major Discrepancy in NOx Emissions from Megacities r 2 =0.83 vs a priori

A Posteriori NOx Emissions from East Asia Exceed Those from Either North America or Europe A priori (Tg N yr -1 ) A posteriori (Tg N yr -1 ) East Asia North America Europe Africa SE Asia & India South America Australia Total

Large Change in NOx Emissions Near New York City atoms N cm -2 s -1  atoms N cm -2 s -1 A prioriA posteriori A posteriori – A priori 7.8 Tg N 0.6 Tg N r 2 = 0.92 Evaluate Each Inventory By Conducting GEOS-CHEM Simulation & Sampling Model Along Aircraft Flight Tracks  NO x (pptv) Simulation with A Posteriori – Simulation with A Priori  HNO 3 (pptv) 7.2 Tg N  PAN (pptv)

In Situ Airborne Measurements Support A Posteriori Inventory In Situ GEOS-CHEM (A priori) GEOS-CHEM (A posteriori) New England New England + Gulf P-3 Measurements from Tom Ryerson (NOAA) Aaron Swanson Andy Neuman Frank Flocke (NCAR) (CIRES/NOAA) Horizontal bars show 17th & 83rd percentiles

Conclusions Growing confidence in top-down constraint on NOx emissions Underestimate in NOx emissions from megacities North American lightning NOx emissions underestimated