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Inverse Modeling of Asian CO and NO x emissions

This study focuses on the inverse modeling of CO and NOx emissions in Asia using data from the TRACE-P Aircraft and Chinese Stations. It analyzes the uncertainties in CO and NOx emissions, as well as the linear relationship between NOx emissions and NOy concentrations. The study also explores the microbial sources of NOx and N2O, the processing of N through the agriculture/animal/human food chain, and future implications and research areas.

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Inverse Modeling of Asian CO and NO x emissions

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  1. Inverse Modeling of Asian CO and NOx emissions Yuxuan Wang M.B. McElroy, T. Wang, and P. I. Palmer 2nd GEOS-CHEM Users’ Meeting April 5, 2005

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

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

  4. A priori Emissions of CO and NOx Uncertainties: 154% for CO, 27% for NOx Source: Streets et al. [2003] r

  5. Model Underestimates Aircraft Observations of CO and NOy

  6. Model Underestimates Surface Measurements Lin An CO Hong Kong Lin An NOy Hong Kong

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

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

  9. 1. Model has no bias in simulating contributions of component NOy species to total NOy below 6km  no systematic bias in NOy chemistry and relative deposition rate in the model 2. Linear relationship between NOx emissions and NOy concentrations can thus be adopted. NOy Chemistry and Deposition Scheme NOx/NOy HNO3/NOy PAN/NOy

  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 • Values of RRE for the aircraft data: 20% for CO and 30% for NOy • RRE method for station data (temporal selected bins) mean of RE due to bias in emissions; std. of RE due to total model error

  11. Treatment for the station data • average the observed and simulated concentrations of CO and NOy every 2 days (~76 data) • Errors: 7% (Feb) ~15% (Apr) for CO and NOy at Lin An; 14% ~ 7% for CO at HK, 47% ~ 24% for NOy at HK

  12. Uncertainties are from ensemble simulations

  13. Uncertainties are from ensemble simulations ?

  14. Microbial Sources of NOx and N2O O2 O2 Nitrification: NH4+ NO2-  NO3- Denitrification: NO3- N2O  N2 The weight of the evidence suggests that nitrification provides the dominant source of N2O. NH2OH Low levels of O2 Aerobic denitr. N2O, NO N2O, NO

  15. Survey of Field and Laboratory Studies • Yield of N2O and NO increases with decreasing levels of O2 • So does the NO / N2O ratio

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

  17. N Processed through the Agriculture/Animal/Human Food Chain 226 48 32 22 22 226 TgN/yr * 2% = 4.4 TgN-N2O /yr NOx/N2O = 3 or 6% yield for NOx Central China: 30% of Chinese N  0.9 TgN-NOx/yr

  18. Biomass burning sources are excluded

  19. Future Work • Reconcile our results with previous top-down estimates of NOx emissions (e.g., GOME NO2 column) • Seasonality of biological sources (relative abundance of NO2- and O2) • Impact of biological sources of NOx on ozone and OH • 3-D modeling of N2O

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