Space-based insight into the global sources of nitrogen oxides with implications for tropical tropospheric ozone Randall Martin Dalhousie University With contributions from Bastien Sauvage, Neil Moore, Thomas Walker: Dalhousie University Christopher Sioris: Environment Canada Christopher Boone and Peter Bernath: University of Waterloo Jerry Ziemke: NASA Goddard Lyatt Jaegle: University of Washington Xiong Liu, Kelly Chance: Harvard-Smithsonian Center for Astrophysics

Tropospheric Ozone is a Key Species in Climate and Air Quality Tropopause Stratopause Major greenhouse gas Largely controls atmospheric oxidation Primary constituent of smog Stratosphere Troposphere Ozone layer Mesosphere Half of all Americans live in regions that exceed the surface ozone standard

FiresBiosphereHuman activity Nitrogen oxides (NO x ) CO, Volatile Organic Compounds (VOCs) Ozone (O 3 ) Hydroxyl (OH) Global Budget of Tropospheric Ozone Driven By Production in the Troposphere hvhv,H 2 O Ozone Production is Largely NOx-Limited

Bottom-up Estimates for Global NOx Emissions (Range) in Tg N yr -1 for 2000 Fossil Fuel 24 (20-33) Biomass Burning 6 (3-13) Soils 7 (4-21) Lightning 6 (1-20) How Do We Evaluate and Improve A Priori Bottom-up Inventories?

Top-Down Information from Satellite Observations Nadir-viewing solar backscatter instruments including ultraviolet and visible wavelengths GOME Spatial resolution 320x40 km 2 Global coverage in 3 days SCIAMACHY 2002-present Spatial resolution 60x30 km 2 Global coverage in 6 days OMI 2004-present Spatial resolution up to 13x24 km 2 Daily global coverage GOME present Spatial resolution up to 40x80 km 2 Daily global coverage

Retrieve NO 2 Columns To Map Surface NO x Emissions Emission NO NO 2 HNO 3 lifetime <1 day NITROGEN OXIDES (NO x ) BOUNDARY LAYER NO / NO2   W ALTITUDE Tropospheric NO 2 column ~ E NOx O3O3 hv NOx = NO + NO 2

Spectral Fit of NO 2 Scattering by Earth surface and by atmosphere Backscattered intensity I B Solar I o Distinct NO 2 Spectrum Nonlinear least-squares fitting Ozone NO 2 O 2 -O 2 Albedo A Martin et al., JGR, 2002, 2006 Fitting Uncertainty 5-10x10 14 molec cm -2

Total NO 2 Slant Columns Observed from SCIAMACHY Dominant stratospheric background (where NO 2 is produced from N 2 O oxidation) Also see tropospheric hot spots (fossil fuel and biomass burning) May-October 2004 Uncertainty in Stratospheric Removal 2-10x10 14 molec cm -2

Perform an Air Mass Factor (AMF) Calculation to Account for Viewing Geometry and Scattering  RcRc RoRo I B,o I B,c PcPc RsRs GOMECAT (Kurosu) & FRESCO Clouds Fields [Koelemeijer et al., 2002] Surface Reflectivity [Koelemeijer et al., 2003] LIDORT Radiative Transfer Model [Spurr et al., 2002] GEOS-CHEM NO 2 & aerosol profiles dd IoIo Martin et al., JGR, 2002, 2003, 2006 Cloud Radiance Fraction I B,c / (I B,o + I B,c ) AMF Uncertainty 40%

Cloud-filtered Tropospheric NO 2 Columns Retrieved from SCIAMACHY May 2004 – Apr 2005 Martin et al., JGR, 2006 Mean Uncertainty ±(5x %) NO / NO2   W ALTITUDE

ICARTT Campaign Over and Downwind of Eastern North America in Summer 2004 Aircraft Flight Tracks and Validation Locations Overlaid on SCIAMACHY Tropospheric NO 2 Columns NASA DC-8NOAA WP-3D

GEOS-Chem Chemical Transport Model Assimilated Meteorology (NASA GMAO) 2 o x2.5 o horizontal resolution, 30 vertical layers O 3 -NO x -VOC chemistry SO NO 3 - -NH 4 + -H 2 O, dust, sea-salt, organic & elemental carbon aerosols Interactive aerosol-chemistry Solve continuity equation for individual gridboxes Accumulation Transport flux divergence Sources: - emissions - chemical prod. Sinks: - chemical loss - deposition  x ~ 200 km  z ~ 1 km 41 tracers ~90 species 300 reactions

Air Mass Factor Calculation in SCIAMACHY Retrieval Needs External Info on Shape of Vertical Profile Increased Lightning NO x Emissions Improves GEOS-CHEM Simulation of Midlatitude NO 2 Profiles Remaining Discrepancy In Vertical Profile of NOx Emissions 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 Martin et al., JGR, 2006

Enhanced Midlatitude Lightning Reduces Discrepancy with SCIAMACHY over North Atlantic Profile of NOx Emissions (lifetime) Contributes to 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 Martin et al., JGR, 2006

Significant Agreement Between Coincident Cloud-Filtered SCIAMACHY and In-Situ Measurements r = 0.77 slope = :1 line Ryerson (WP-3D) Cohen (DC-8) 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 Martin et al., JGR, 2006

Error weighting Conduct a Chemical Inversion For NOx Emissions A posteriori emissions x Top-Down Emissions molec N cm -2 A Priori NOx Emissions (x a ) SCIAMACHY NO 2 Columns (y) molec N cm -2 s -1 GEOS-CHEM model F(x) min cost function SySy SaSa

Significant Agreement Between A Priori and A Posteriori Largest Discrepancy in East Asia and Major Urban Centers r 2 =0.82 Martin et al., JGR, 2006 (2000)

A Posteriori NOx Emissions from East Asia Exceed Those from Either North America or Europe Implications for North American Air Quality A posteriori (46 Tg N/yr) A priori (38 Tg N/yr) Martin et al., JGR, 2006

Thomas Walker INTEX-B: Long-Range Transport to North America Average over April – May 2006 standard No lightning No Asian NOx Whistler, BC Ozone Column(Dobson Units) Δ Ozone Column (Dobson Units) Δ Ozone (ppbv) Sensitivity at 750 hPa to PAN Sensitivity to Asian EmissionsSensitivity to Lightning

Liu et al., JGR, 2006 Direct Retrieval of Tropospheric Ozone from GOME Using Optimal Estimation in Ultraviolet with TOMS V8 a priori GOMEGEOS-CHEM Tropospheric Ozone Column (Dobson Units)

In Situ Data Used for Tropical Evaluation 1.MOZAIC programme MOZAIC & SHADOZ sites used for model evaluation 2.SHADOZ ozone sonde network ( Thompson et al., 2003a;b ) : > 9000 vertical profiles within the Tropics (30°N-30°S)

Northern Tropics Remain a Challenge for Satellites and Models Scan-Angle Method (Kim et al., 2005) UV Method That Best Captures In Situ Seasonal Variation Liu et al., JGR, 2006 GOMEGEOS-CHEM RBiasR Caracas Dakar Tel Aviv Bangkok Comparison with MOZAIC Ozone Measurements

Biomass Burning 2. Spatiotemporal distribution of fires used to separate BB/soil VIRS/ATSR fire counts Soils No fires + background 2 Algorithm for partitioning top-down NO x inventory (2000) Algorithm tested using synthetic retrieval GOME NO x emissions Fuel Combustion 1. Spatial location of FF- dominated regions in a priori (>90%) 1 Jaeglé et al.,

Speciated Inventory for Soil emissions A posteriori 70% larger than a priori! A priori A posteriori Largest soil emissions: seasonally dry tropical + fertilized cropland ecosystems (±200%) (±90%) r 2 = 0.62 Soils Onset of rainy season: Pulsing of soil NO x ! North Eq. Africa Jaeglé et al., 2005 Soils East Asia

Improved Bottom-up Inventory for Soil NOx Emissions Developments of soil temp/soil moisture, pulsing, fertilizer application Change in NOx EmissionsSoil NOx Emissions Δ Global Total = +1.9 Tg N/yrGlobal Total = 7.8 Tg N/yr molec cm -2 s -1 Δ molec cm -2 s -1 Neil Moore

GOMEModel originalModel constrained NO 2 Column (10 15 molec cm -2) Top-down Constraint on Biomass Burning NOx Emissions DJF MAM Improved simulation of lower tropospheric O 3 versus aircraft measurements Pressure (hPa) O 3 Mixing Ratio (ppbv) Sauvage et al., ACP, 2007 Bottom-up Top-down Observed

Global Lightning NOx Source Remains Uncertain Constrain with Top-down Satellite Observations SCIAMACHY Tropospheric NO 2 Columns ACE-FTS Limb HNO 3 Measurements in the Upper Troposphere OMI & MLS Tropospheric O 3 Flashes km -2 min year Mean Flash Rate from the OTD & LIS Satellite Instruments Global rate 44±5 flash/sec [Christian et al. 2003] 30 – 500 moles NO per flash

Current Estimate of Annual Global NOx Sources As Used In GEOS-Chem molecules N cm -2 s -1 Lightning Global: 6.0 Tg N yr -1 Tropics: 4.4 Tg N yr -1 Other NOx sources: (fossil fuel, biofuel, biomass burning, soils) 39 Tg N yr -1

Simplified Chemistry of Nitrogen Oxides Exploit Longer Lifetimes in Upper Troposphere NO NO 2 NOx lifetime < day Nitrogen Oxides (NO x ) Boundary Layer NO / NO2   with altitude hv NO NO 2 O 3, RO 2 hv HNO 3 NOx lifetime ~ week lifetime ~ weeks Ozone (O 3 ) lifetime ~ month Upper Troposphere Ozone (O 3 ) lifetime ~ days HNO 3 O 3, RO 2

Strategy 1) Use GEOS-Chem model to identify species, regions, and time periods dominated by the effects of lightning NOx production 2) Constrain lightning NOx source by interpreting satellite observations in those regions and time periods

Simulated Monthly Contribution of Lightning, Soils, and Biomass Burning to NO 2 Column

Tropospheric NO 2 (10 14 molec cm -2 ) Annual Mean NO 2 Column at Locations & Months with >60% from Lightning, 60% from Lightning, <25% from Surface Sources Meridional Average SCIAMACHY (Uses 15% of Tropical Observations) GEOS-Chem with Lightning (8% bias, r=0.75) GEOS-Chem without Lightning (-60% bias) NO 2 Retrieval Error ~ 5x10 14 molec cm -2 GEOS-Chem with Lightning (6±2 Tg N yr -1 ) SCIAMACHY GEOS-Chem without Lightning Martin et al., 2007

ACE HNO 3 over hPa for Feb 2004 – Feb 2006 HNO 3 Mixing Ratio (pptv) Data from Boone et al., 2005

GEOS-Chem Calculation of Contribution of Lightning to HNO 3 HNO 3 from LightningFraction from Lightning Focus on hPa HNO 3 With Lightning (6±2 Tg N yr -1 ) No Lightning Fraction of HNO 3 from Lightning Jan Jul

Annual Mean HNO 3 Over hPa at Locations & Months with > 60% of HNO 3 from Lightning Meridional Average ACE (Uses 83% of Tropical Measurements) GEOS-Chem with Lightning (-12% bias, r=0.75) GEOS-Chem without Lightning (-80% bias) HNO 3 Mixing Ratio (pptv) ACE-FTS GEOS-Chem with Lightning (6±2 Tg N yr -1 ) GEOS-Chem without Lightning HNO 3 Retrieval Error ~35 pptv Martin et al., 2007

OMI/MLS Tropospheric Ozone Column Jan Jul Data from Ziemke et al. (2006)

Calculated Monthly Contribution of Lightning to O 3 Column O 3 Column from LightningColumn Fraction from Lightning Martin et al., 2007

Annual Mean Tropospheric O 3 Columns at Locations & Months with > 40% of Column from Lightning Meridional Average OMI/MLS (Uses 15% of Tropical Measurements) GEOS-Chem with Lightning (-1% bias, r=0.85) GEOS-Chem without Lightning (-45% bias) Tropospheric O 3 (Dobson Units) OMI/MLS GEOS-Chem with Lightning (6±2 Tg N yr -1 ) GEOS-Chem without Lightning O 3 Retrieval Error < 5 Dobson Units Martin et al., 2007

Scaled version Original version Same intensity: 6 Tg N yr -1 Spatial Distribution of GEOS-Chem Lightning NOx Source DJF JJA Lightning NOx emissions (10 9 molec N cm -2 s) Sauvage et al., ACP, 2007 Local Scaling to Match 10-year HRAC Seasonal OTD-LIS Climatology

Ozone Sensitivity to Spatial Distribution of Lightning NOx -O 3 highly sensitive in the MT-UT -O 3 simulations improved by 5-15 ppbv versus In situ -Main influence near subsidence areas: South America; Middle East; Atlantic Pressure (hPa) O 3 (ppbv) Original Modified In situ Snapshot of the model evaluation Sauvage et al., ACP, 2007 Scaled

Ozone sensitivity to Lightning NOx 4 TgN/yr; 6 TgN/yr; 8 TgN/yr Evaluation for the Tropics 8Tg N/yr  O 3 over estimation 4Tg N/yr  O 3 under estimation 6±2Tg N/yr  general agreement Pressure (hPa) O 3 (ppbv) Sauvage et al., ACP, 2007 Scaled

Lightning NOx Dominant Source for Tropical Tropospheric Ozone Sensitivity to decreasing NOx emissions by 1% for each source ΔDU DJF MAM JJA SON Lightning Ozone Production Efficiency = 3 times OPE of each surface source Sauvage et al., JGR, in press 6 Tg N/yr Atmospheric Oxidation Largely Controlled by Lightning NOx Source

Simulated Annual Mean Characteristics O3O3 ppb NO x ppb 3/O 3 production during transport and subsidence over South Atlantic basin 1/Surface emissions of O 3 precursors S. Am.Africa 2/Injection of NOx (mostly from lightning) into the upper troposphere Sauvage et al., JGR, in press

Conclusions Growing confidence in top-down constraints on NOx emissions South Atlantic Maximum largely results from lightning NOx due to high ozone production efficiency Global lightning NOx source likely between 4 – 8 Tg N / yr 6 Tg N / yr is a best estimate Further refinement of lightning source will require - stronger constraints on midlatitude source - improved satellite retrieval accuracy (e.g. NO 2 ) - more observations (e.g. HNO 3 ) - model development to better represent processes (e.g. lightning NOx representation, vertical transport) Acknowledgements Supported by NASA, CFCAS, and NSERC