The goal of this project is to integrate observations and bottom-up as well as top-down modeling in an interdisciplinary way to address uncertainties in N2O modeling. For soil emissions, the research employs the Community Land Model with prognostic Carbon and Nitrogen (CLM-CN) created at NCAR with a N2O emissions module (CLMCN-N2O) added at MIT, in combination with a global chemical transport model, Community Atmosphere Model version 3 (CAM3). In addition to a land model that is able to represent terrestrial water, and carbon and nitrogen balances, CLMCN-N2O includes process-level biogeochemistry to estimate global soil N2O emissions. Using the N2O emissions obtained from the process model combined with N2O observations from NOAA, the Advanced Global Atmospheric Gases Experiment (AGAGE) and other available international networks (e.g., National Institute for Environmental Studies in Japan),the estimate of global and regional annual N2O emissions for 5 different sources over the last 15 years with CAM3 will be refined. Incorporating a variety of projections simulated in the MIT Integrated Global System Model (IGSM), the impact of potential future climate on soil N2O emissions, and how potential future land use change (especially that from managed bio-energy/agricultural land) and the extent of anthropogenic combustion-related activities (mobile and stationary sources) may affect these emissions will be assessed. In doing so, the response of terrestrial biogeochemical system will be explored and various mitigation pathways assessed. Furthermore, analyzing the stratospheric loss rate of N2O by O(1D) will enable the calculation of current and possible future stratospheric ozone loss due to the predicted N2O emissions, which will lead to an improved understanding of the impact of N2O emissions not only on nitrogen cycle, but also on climate and on stratospheric O3. In addition, work will be undertaken with Dr. Cindy Nevison to run a regional chemical transport model WRF-Chem as well as a global model CAM-WACCM to assess the difference between regional and global models, and to analyze the effect of chemical mechanisms on model results.