Adjoint inversion of Global NOx emissions with SCIAMACHY NO 2 Changsub Shim, Qinbin Li, Daven Henze, Aaron van Donkellaar, Randall Martin, Kevin Bowman,

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Adjoint inversion of Global NOx emissions with SCIAMACHY NO 2 Changsub Shim, Qinbin Li, Daven Henze, Aaron van Donkellaar, Randall Martin, Kevin Bowman, Monika Kopacz, and Annmarie Eldering 4 th GEOS-Chem User’s Meeting Apr. 08, 2009

Global NOx emissions in GEOS-Chem NOx emissions NOx emissions2005 (a priori) 2001 (a)2005 (b)% Industry/urban 23.6 (1998) GEIA (2000) EDGAR 56 ~ 62 Biofuel 2.02 (1995) (2000)4.5 ~ 5 Soil/fertilizer 5.06 (c) ~13 Biomass Burning 6.7 (Climatological) 6.5 (d) 5.41 (GFEDV2) 10 ~16 Lightning/aircraft 4.2 (f)4.74.5~10 Total (Tg/yr) 42 (v6)4345 (v7)100 (a): adapted from Park et al., (2004) (b): GEOS-Chem v (1998): GEIA anthropogenic emission inventory for year 1985 scaled to 1998 by CO2 emission trends [Bey et al., 2001; Marland et al., 1999]. (2000): EDGAR anthropogenic emission inventory based on (c): Based on Yienger and Levy et al., (1995). (d): Climatological monthly biomass burning data (Duncan et al., 2003). (e): Monthly GFEDv2 biomass burning data. (f): Based on Wang et al., (1998)

Objective Objective Inversion of NOx emissions with consideration of physiochemical feedbacks with direct computing of parameter’s sensitivityInversion of NOx emissions with consideration of physiochemical feedbacks with direct computing of parameter’s sensitivity Comparison with “top-down” emissions estimates (or mass balance approach) derived from satellite observations (e.g., Martin et al., 2003; 2006)Comparison with “top-down” emissions estimates (or mass balance approach) derived from satellite observations (e.g., Martin et al., 2003; 2006) Advantage Advantage Can consider the chemical and physical feedbacks during optimizationCan consider the chemical and physical feedbacks during optimization  quantifying the parameter’s sensitivity w.r.t. model predictions  quantifying the parameter’s sensitivity w.r.t. model predictions Optimization controlOptimization control Disadvantage Disadvantage Still computationally expensiveStill computationally expensive Ex) 64 Intel Itanium2 processors (SGI architecture with LINUX) Ex) 64 Intel Itanium2 processors (SGI architecture with LINUX) 1.5 GHz clock speed with 1MB Cache + 1GB RAM1.5 GHz clock speed with 1MB Cache + 1GB RAM With parallel computing (8 CPUs)With parallel computing (8 CPUs)  Each iteration for one month time window (2°x2.5°, globally) takes 44 hours. Adjoint Inversion Changsub ShimGEOS-Chem User’s meeting

SCIAMACHY NO 2 from Dalhousie Univ (reprocessed data), filtered cloud fraction > 40%. SCIAMACHY NO 2 from Dalhousie Univ (reprocessed data), filtered cloud fraction > 40%. Adjoint of GEOS-Chem v6-2-5 & GEOS-4 & full chemistry (by D. Henze) with 2°x2.5° horizontal resolution Adjoint of GEOS-Chem v6-2-5 & GEOS-4 & full chemistry (by D. Henze) with 2°x2.5° horizontal resolution Time window: one month (Nov. 2005)  a week x 4 Time window: one month (Nov. 2005)  a week x 4 Emissions (NOx) Emissions (NOx) GEIA anthropogenic NOx emission (scaled to 1998)GEIA anthropogenic NOx emission (scaled to 1998) Climatological Biomass Burning(Duncan et al., 2003)Climatological Biomass Burning(Duncan et al., 2003) Biofuel emissions (Yevich et al., 2003)Biofuel emissions (Yevich et al., 2003) Soil NOx (Yienger and Levy(1995) & Wang(1998))Soil NOx (Yienger and Levy(1995) & Wang(1998)) Lightning NOx (Cloud Top Height; Price and Rind(1998) & Pickering (1998)): only consider the total emissions for opt.Lightning NOx (Cloud Top Height; Price and Rind(1998) & Pickering (1998)): only consider the total emissions for opt. Data (Nov. 2005) Data (Nov. 2005) Changsub ShimGEOS-Chem User’s meeting

N.AmE.U.Asia S.Am. Africa R.W Ind Ind Light Soil BB BF State vector errors (%) Observation error = e1 + e2 + e3 * e1: retrieval error from SCIAMACHY * e2: representation error : ~0.7 of e1 (~4.0x10 13 molec/cm 2 ) * e3: model transport error (from Jones et al., 2003)  ~0.8 of e1 (~4.5x10 13 molec/cm 2 ) total obs. error is about factor of ~2.5 of instrumental (retrieval) error  Same quantity of errors were applied to mass-balance approach Error Specification Relative instrument errors (%)

Iteration Norm of grad. Cost func. ratio D D D D D D D D Cost function from obs. Vs from a priori = ~10: 1 Now cost function reached ~ 0.40 of initial value after 7 th iteration Gradient Inversion Results Cost Function

Initial (a priori)8 th iteration (a posteriori) SCIA SCIAMACHY CTM CTM-SCIA Inversion Results (A priori vs A posteriori) Unit: molecules/cm 2 Nov. 2005

Inversion Results : NOx emissions ratio ( a posteriori / a priori)

Unit: Gg N/ month Total NOx emissions (by adjoint method, Nov 2005) Large reductions in N. Ame, Europe, and India Moderate reductions in Africa and S. Ame China shows mixed features

N.AmE.U.E.AsiaIndiaS.AmeAfricaAus.R.W.TotalIND1430(209)220(154)384(342)95.4(50.)74.3(58)103(64)12.6(13.6)165(123) 1484 (1013) IND2176(85)202(136) (8.)9.7(10.2)32(18) 442 (261) Light.21.8(21.1)10(10)5.3(5.2)1.6(1.4)62.3(40)53.4(36)12.3(12.4)23.3(21.4) 190 (147) Soil33.4(30)15.4(15.3)11.8(11.6)34.1(25.2)98.8(85)142(115)38.7(39.2)24.8(24) 399 (345) BB5.8(5.6)5.1(5.1)22.3(19.2)3.7(3.)126(77)276(173)94.2(89.4)45(42) 578 (413) BF7.5(6.9)18.5(18.2)51.8(50.0)33.3(25)14.6(13.4)31.5(27.7)0.66(0.65)24(23) 182 (164) Total682(364)490(357)535(481)202(130)391(286)652(451)169(166)338(273) 3456 (2507)  Global NOx emissions are lower by ~28% (Nov 2005): Annual proj. (42 vs 31 Tg N/yr)  N.Ame (~48%) and Europe (~30%) have significant reduction in industrial NOx emissions (2005 vs 1998)  A posteriori BB emissions are well matched with GFEDv2 (global total) A priori / A posteriori (unit: Gg N/ month; Nov 2005)

Some over-reduction over N. Ame and Europe less reduction over S. Ame, Africa, and India Less increase over China and Australia No latitudinal correlations (Lifetime?) Comparison with Mass Balance emissions estimate Based on Martin et al., (2003)

a Priori Mass- Balance Adjoint N. Ame (-38%) 364 (-47%) Europe (-16%) 357 (-27%) E. Asia (+28%) 481 (-10%) India (-38%) 130 (-36%) S. Ame (-36%) 286 (-27%) Africa (-30%) 451 (-31%) Aus (+40%) 166 (-2%) Global (-19%) 2507 (-28%) A priori / Mass-Balance / Adjoint (unit: Gg N/ month; Nov 2005) Changsub ShimGEOS-Chem User’s meeting

SCIAMACHY NO 2 columns (Nov 2005) from Dalhousie Univ Previous versionReprocessed (currently used) Previous - reprocessed Reprocessed SCIAMACHY Improved in solar measurements, and cloud fields for signal fitting and AMF calculation (10 15 Molecules/cm 2)

Conclusions According to the adjoint inversion, the N.Ame and European anthropogenic NOx emissions are greatly reduced by 48% and 30% (1998 vs 2005) According to the adjoint inversion, the N.Ame and European anthropogenic NOx emissions are greatly reduced by 48% and 30% (1998 vs 2005) Large increase in Chinese industrial NOx emissions is evident by SCIAMACHY, but the adjoint inversion does not represent enough enhancements Large increase in Chinese industrial NOx emissions is evident by SCIAMACHY, but the adjoint inversion does not represent enough enhancements Natural a priori NOx emissions overestimated (Nov. 2005) and a posteriori biomass burning emission is closer to GFEDv2 in global total Natural a priori NOx emissions overestimated (Nov. 2005) and a posteriori biomass burning emission is closer to GFEDv2 in global total More.. Comparison with recent emissions inventory for specific regions (EPA, EMEP, Streets, etc..) will be continued. Comparison with recent emissions inventory for specific regions (EPA, EMEP, Streets, etc..) will be continued. Changsub ShimGEOS-Chem User’s meeting