1. Inverse Modeling of Asian CO and NO x emissions Yuxuan Wang M.B. McElroy, T. Wang, and P. I. Palmer 2 nd GEOS-CHEM Users’ Meeting April 5, 2005

2. 2 Nested grid version of GEOS-CHEM 1  x1  4  x5  v5-07-08

3. 3 TRACE-P Aircraft and Chinese Stations Data Time frame: Jan – Apr., 2001 Hong Kong Lin An

4. 4 A priori Emissions of CO and NO x r Uncertainties: 154% for CO, 27% for NO x Source: Streets et al. [2003]

5. 5 Model Underestimates Aircraft Observations of CO and NO y

6. 6 Model Underestimates Surface Measurements CO NO y Lin An Hong Kong Lin An Hong Kong

7. 7 Tagged Tracer Simulation Assume the model concentration fields are linear combinations of contributions from tagged sources

8. 8 Tagged Tracer Simulation Assume the model concentration fields are linear combinations of contributions from tagged sources

9. 9 NO y Chemistry and Deposition Scheme 1. Model has no bias in simulating contributions of component NO y species to total NO y below 6km  no systematic bias in NO y chemistry and relative deposition rate in the model  no systematic bias in NO y chemistry and relative deposition rate in the model 2. Linear relationship between NO x emissions and NO y concentrations can thus be adopted. NO x /NO y HNO 3 /NO y PAN/NO y

10. 10 Error specification  RRE method for aircraft observations (spatially selected bins) [Palmer et al., 2003] RE = (modeled – observed ) / observed mean of RE due to bias in emissions; std. of RE due to total model error std. of RE due to total model error  Values of RRE for the aircraft data: 20% for CO and 30% for NO y  RRE method for station data (temporal selected bins) mean of RE due to bias in emissions; std. of RE due to total model error mean of RE due to bias in emissions; std. of RE due to total model error

11. 11 Treatment for the station data 1.average the observed and simulated concentrations of CO and NO y every 2 days (~76 data) 2.Errors: 7% (Feb) ~15% (Apr) for CO and NO y at Lin An; 14% ~ 7% for CO at HK, 47% ~ 24% for NO y at HK

12. 12 Uncertainties are from ensemble simulations

13. 13 ? Uncertainties are from ensemble simulations

14. 14 Microbial Sources of NO x and N 2 O Nitrification: NH 4 +  NO 2 -  NO 3 - Denitrification: NO 3 -  N 2 O  N 2 The weight of the evidence suggests that nitrification provides the dominant source of N 2 O. NH 2 OH N 2 O, NO O2O2 O2O2 Low levels of O 2 Aerobic denitr.

15. 15 Survey of Field and Laboratory Studies  Yield of N 2 O and NO increases with decreasing levels of O 2  So does the NO / N 2 O ratio

16. 16 N Processed through the Agriculture/Animal/Human Food Chain 226 Data from FAO 48 32 22

17. 17 N Processed through the Agriculture/Animal/Human Food Chain 226 TgN/yr * 2% = 4.4 TgN-N 2 O /yr NO x /N 2 O = 3 or 6% yield for NO x Central China: 30% of Chinese N  0.9 TgN-NO x /yr 226 48 32 22

18. 18 Biomass burning sources are excluded

19. 19 Future Work 1.Reconcile our results with previous top- down estimates of NO x emissions (e.g., GOME NO 2 column) 2.Seasonality of biological sources (relative abundance of NO 2 - and O 2 ) 3.Impact of biological sources of NO x on ozone and OH 4.3-D modeling of N 2 O