Nitrous oxide (N₂O) has a high global warming potential and depletes stratospheric ozone. The U. S. Corn Belt plays an important role in the global anthropogenic N₂O budget. To date, studies on local surface N₂O emission and the atmospheric N₂O budget have commonly used Lagrangian models. In the present study, we used an Eulerian model – Weather Research and Forecasting Chemistry (WRF-Chem) model to investigate the relationships between N₂O emission in the Corn Belt and observed atmospheric N₂O mixing ratios. Modeled hourly N₂O mixing ratios were combined with continuous atmospheric N₂O measurements at the KCMP tall tower in Minnesota to constrain agricultural N₂O emissions. The modeled spatial patterns of atmospheric N₂O were validated against discrete observations at multiple tall towers in the NOAA flask network. After optimization of the surface flux, the model reproduced reasonably well the hourly N₂O mixing ratios monitored at the KCMP tower. Agricultural N₂O emissions in the EDGAR42 database needed to be scaled up by 19.0 to 28.1 fold to represent the true emission in the Corn Belt from June 1–20, 2010 – a peak emission period. Optimized total N₂O emissions were 3.00–4.38, 1.52–2.08, 0.61–0.81 and 0.56–0.75 nmol m^−2 s^−1 from June 1–20, August 1–20, October 1–20 and December 1–20, 2010, respectively. The simulated spatial patterns of atmospheric N₂O mixing ratios were in good agreement with the NOAA discrete observations during the strong emission peak in June. Such spatial patterns illustrate that the IPCC (Inter-governmental Panel on Climate Change) underestimate of emissions is not dependent on tower measurement location.