GEOS-Chem meeting, 12 April 2007 Preliminary results for the year-to-year variation in satellite-derived NOx sources S. Koumoutsaris 1, I. Bey 1, N. Moore 3, A. van Donkelaar 3, R. Martin 3,4, L. Jaeglé 2 1 Laboratoire de Modélisation de la Chimie Atmosphérique, Lausanne, Switzerland 2 Department of Atmospheric Sciences, University of Washington, Seattle, (WA) USA. 3 Department of Physics and Atmospheric Science, Dalhousie University, Halifax (NS), Canada 4 Harvard-Smithsonian Centre of Astrophysics, Cambridge (MA), USA. GEOS-Chem meeting, 12 April 2007

Objectives Use GOME satellite data to derive multi-year inventory of NOx sources ( ). Use GOME satellite data to derive multi-year inventory of NOx sources ( ). Examine the trends in fossil fuel NOx emissions. Examine the trends in fossil fuel NOx emissions. Implement the new inventory into GEOS- Chem, examine the effects in O 3 and compare with the standard simulation and with observations. Implement the new inventory into GEOS- Chem, examine the effects in O 3 and compare with the standard simulation and with observations.

GEOS-Chem NO 2 column/NO x emissions  v  30 levels, 2°x2.5°, 50 tracers, from 1995 to 2000  GEOS-4 meteorological fields  Biomass burning emissions IAV using AATSR Fire [Generoso et al., 2003]  Anthropogenic emissions: fixed for 1995  Lightning NOx emissions: TgN/yr GOME NO 2 column (data from Aaron van Donkelaar, Dalhousie University)  Improved filtering  Accounts for meridional changes in stratospheric column  Only when clouds contribute <50% of the backscattered radiation GOME Error (data from Aaron van Donkelaar, Dalhousie University ) GEOS-Chem Error  Fossil fuel+biofuel errors: using EDGAR2000 emissions  Biomass burning error: using RETRO emissions  Soil error = ±200% Method: inversion [Martin et al., 2003] E apost : “a posteriori” E a : “a priori” NO x emissions E t : “top-down”

Method: global partitioning [Jaeglé et al., 2005] We obtain “a posteriori” NO x inventories for : a)Biomass burning emissions b)Fossil fuel and biofuel emissions c)Soil emissions YESNO or >0=0 ATSR/VIRS firecounts of boxes with fires=0

NO x emissions over the biomass burning regions (1) BB “a priori” error = ±200% CCD TOMS Control simulation S0 Simulation with “a posteriori” emissions Tropical tropospheric ozone column (DU) a posteriori a priori Total NO x emissions (TgN) November DU 46 DU

Does GOME see the diurnal variations of the fires? How does that affect the NO 2 column over the fire regions? a posteriori a priori IAV BB “a priori” error = BB “a priori” emissions BB “RETRO” emissions NO x emissions over the biomass burning regions (2)

South America: -8% | 39% | Mediterranean Europe: +100% | 107% | Russia-Siberia: -6% | 34% | region: mean% |max%| Biomass burning NOx emissions (TgN/month): “a priori” vs. “a posteriori” a posteriori a priori

Soil NOx emissions (TgN/month): “a priori” vs. “a posteriori” USA: +46% | 78% | South Africa: +20% | 154% | Australia: +42% | 138% | region: mean% |max%| a posteriori a priori

Fossil fuel/biofuel NOx emissions (TgN/month): “a priori” vs. “a posteriori” Middle East: -14% | 19% | Australia: +5% | 30% | region: mean% |max%| a posteriori a priori Mediterranean Europe: +2% | 15% |

“a posteriori” FF+BF trends North Europe : %/yr China/Japan : +1.4 %/yr Australia : +1.3 %/yr Mediterranean Europe : +0.7 %/yr <0.5%/yr

“a posteriori” FF+BF trends North Europe : %/yr China :+1.4 %/yr Australia : +1.3 %/yr Mediterranean Europe : +0.7 %/yr China/Japan:+1.4 %/yr Bottom-up: 1996 to 2005: 74% (~8.2%/yr) & 1998 to 2005: 71% (~10.1%/yr) [Streets, personnal communication] No trend in FF+BF in our “a priori” Slowdown of increase during the late ’90s

NO x emissions / NO 2 column trend Control Run: 0.67 % / yr NOx emissions / NO 2 column (Tg N) China/Japan Control Run  30 levels, 4°x5°, 24 tracers  GEOS-4 Top-down using GOME NO 2 column: 1996 to 2002: 50% (~8.3%/yr) [Irie et al., 2005; Richter et al., 2005]

NO x emissions / NO 2 column trend Control Run: 0.67 % / yr Meteorology fixed in 1988 : 0.83 % / yr Anthropogenic emissions fixed in 1988 : ~ 0.0 % /yr Lightning emissions fixed (6TgN/yr) : 0.73 % /yr NOx emissions / NO 2 column (Tg N) China/Japan Control Run  30 levels, 4°x5°, 24 tracers  GEOS-4 Top-down using GOME NO 2 column: 1996 to 2002: 50% (~8.3%/yr) [Irie et al., 2005; Richter et al., 2005]

North AmericaSouth America North Europe China/Japan Australia Mediterannean Europe India-Indonesia-SEAsia South Africa “a posteriori” FF+BF seasonal trends

Preliminary conclusions Issue with the NO 2 column in GOME over fire regions. Issue with the NO 2 column in GOME over fire regions. The “a posteriori” soil NOx emissions show higher interannual and seasonal variation and are found to be globally 16% higher than the “a priori”. The “a posteriori” soil NOx emissions show higher interannual and seasonal variation and are found to be globally 16% higher than the “a priori”. Positive trends have been found in the “a posteriori” fossil fuel+biofuel inventory over China, Australia and the Mediterranean Europe. Positive trends have been found in the “a posteriori” fossil fuel+biofuel inventory over China, Australia and the Mediterranean Europe. Positive trend in the simulated NO X emissions/NO 2 column ratio which prevents from using directly NO 2 column to derive trends in emissions. Positive trend in the simulated NO X emissions/NO 2 column ratio which prevents from using directly NO 2 column to derive trends in emissions.

Additional slides

The change in bb error changes the total and the bb (ff & soil unaffected) The change in bb error changes the total and the bb (ff & soil unaffected) 1997: bb error=31997: bb error=using RETRO

NO x emissions / NO 2 trend RUN 2x2.5 China, E NOx /[NO 2 ]: % / yr NOx emissions / NO 2 (Tg N)