1. Assimilated Inversion of NO x Emissions over East Asia using OMI NO 2 Column Measurements Chun Zhao and Yuhang Wang School of Earth and Atmospheric Science, Georgia Institute of Technology, Atlanta, Georgia 30332 EAS Graduate Student Symposium Nov. 14, 2008

2. Tropospheric NO x sources  Anthropogenic emissions Power Plant, Industry, Transportation, Residential,..….  Natural emissions Lightning and soil  Biomass burning emissions Fire

3. NO x Emissions Inventory  Bottom-up approach  Complications of emission statistics and source factors, e.g., fossil fuel source, emission factors developed for industry, domestic, transport and power plants [e.g., Streets et al., 2003].  Problems? In regions such as China, where emission statistics and characteristics are incomplete, the bottom-up inventory uncertainties could be large [e.g., Streets et al., 2003].

4. http://www.aero.jussieu.fr/projet/ACCENT/POET.php

5. NO x Emissions Inventory  Bottom-up approach  Complications of emission statistics and source factors. e.g., fossil fuel source, emission factors developed for industry, domestic, transport and power plants [e.g., Streets et al., 2003].  Problems? In regions such as China, where emission statistics and characteristics are incomplete, the bottom-up inventory uncertainties could be large [e.g., Streets et al., 2003].

6. Correlate coefficient R 2 = 0.40 Relative error = 60%

7. NO x Emissions Inventory  Top-down approach  Global tropospheric NO 2 distributions were measured by satellite instruments in the last decade.  Many studies showed that satellite measurements provide important top-down constraints for improving emission inventories [e.g., Martin et al., 2003 and 2006; Y.X. Wang et al., 2007].

8. http://www.temis.nl/airpollution/no2col/no2regioomimonth_col3.php

9. R 2 =0.61 for Case A and 0.53 for Case B RMSE= 1.27 for Case A and 1.69 for Case B (10 15 molecs/cm 2 )

10. NO x Emissions Inventory  Top-down approach  Global tropospheric NO 2 distributions were measured by satellite instruments in the last decade.  Many studies showed that satellite measurements provide important top-down constraints for improving emission inventories [e.g., Martin et al., 2003 and 2006; Y.X. Wang et al., 2007].

11. Top-down method [Martin et al., 2003] 21 OMI NO2 columns NRT data from KNMI/NASA [Boersma et al., 2007] and OMI STD data from NASA (GES-DISC) [Bucsela et al., 2006] Cloud fraction <30% REAM NO 2 column/NOx emissions 23 levels to 10 hpa, 70x70 km 2 WRF meteorological fields Fossil fuel combustion NO x [Streets 2006 and POET 2000] Lightning and soil NO x [Choi et al., 2008] No biomass burning NO x [~2%, Wang et al.,2007] A priori Error ~60% for surface emissions Fossil fuel combustion (~50%) Soil (300%, Wang et al, 2007) OMI top-down Error ~50% for top-down emissions 40% for retrieval NO 2 columns 30% for model error E apost : “a posteriori” E a : “a priori” Emissions E t : “top-down”

12. Inversion Methods Daily updated at OMI pass time~36% ~50% from last day~60% E apost Daily updated at OMI pass time EtEt E apost from last dayEaEa MODEL-NO 2 OMI pass time Monthly mean OMI-NO 2 Assimilated dailyMonthly-mean

14. Table 2. Correlation statistics between OMI retrieved and REAM simulated tropospheric NO 2 columns with different surface NO x emissions. A prioriMonthly a posterioriAssimilated a posteriori Case ACase BCase ACase BCase ACase B R2R2 0.530.490.810.760.90 RMSE (molecs/cm 2 ) 1.511.840.800.890.620.61 A prioriMonthly a posterioriAssimilated a posteriori Case ACase BCase ACase BCase ACase B R2R2 0.40.60.94 Emissions (Tg N/yr)11.611.111.29.811.010.6 Table 1. Correlation statistics between Scaled Streets and Scaled POET emissions.

15. Partitioning:  Least-squares regression to linearly partition the a posteriori emissions to the fossil fuel and soil emissions:  b=2.4-2.7 based on the regression regions  TgN/yr for July over East Asia, ~14% of the total a posteriori emissions.  Tg N/yr for July over East Asia.

17. http://pangjiaoming.blog.163.com/blog/static/2396449820074173639260/

18. Table 3. A priori and assimilated a posteriori fossil fuel NO x emissions over East Asia for 2007 (Tg N/yr). A priori Assimilated a posteriori China8.487.48 South Korea0.360.28 Japan0.670.68 Other1.401.03 Total10.919.47

19. Summary:  The new developed assimilated daily inversion method improved the top- down constraints of NO x emissions over East Asia based on OMI NO 2 measurements.  The iterative nature of the assimilated inversion accounts for the chemical feedbacks of NO x emission changes and reduces the dependence of the a posteriori emissions on the a priori emissions.  We find a relatively small contribution from soil emissions, ~1.6 Tg N/yr or ~14% of total in July.  Significant spatial distribution changes of fossil fuel emissions are found over East China. The a priori inventory tends to overestimate the emissions over the economically developed areas and underestimate over the underdeveloped areas in East China, likely reflecting fossil fuel NO x emission reductions resulting from the urban-centric air quality controls and enforcements in China.  The new developed assimilated daily inversion method improved the top- down constraints of NO x emissions over East Asia based on OMI NO 2 measurements.  The iterative nature of the assimilated inversion accounts for the chemical feedbacks of NO x emission changes and reduces the dependence of the a posteriori emissions on the a priori emissions.  We find a relatively small contribution from soil emissions, ~1.6 Tg N/yr or ~14% of total in July.  Significant spatial distribution changes of fossil fuel emissions are found over East China. The a priori inventory tends to overestimate the emissions over the economically developed areas and underestimate over the underdeveloped areas in East China, likely reflecting fossil fuel NO x emission reductions resulting from the urban-centric air quality controls and enforcements in China.