Uncertainties in United States agricultural N2O emissions: comparing forward model simulations to atmospheric N2O data.

Monday, 15 December 2014: 9:15 AM
Cynthia D Nevison, INSTAAR/University of Colorado, Boulder, CO, United States, Eri Saikawa, Emory University, Atlanta, GA, United States, Edward J Dlugokencky, NOAA, Boulder, CO, United States, Arlyn E Andrews, NOAA Earth System Research Lab, Boulder, CO, United States and Colm Sweeney, Cooperative Institute for Research in Environmental Sciences, Boulder, CO, United States
Atmospheric N2O concentrations have increased from 275 ppb in the preindustrial to about 325 ppb in recent years, a ~20% increase with important implications for both anthropogenic greenhouse forcing and stratospheric ozone recovery. This increase has been driven largely by synthetic fertilizer production and other perturbations to the global nitrogen cycle associated with human agriculture. Several recent regional atmospheric inversion studies have quantified North American agricultural N2O emissions using top-down constraints based on atmospheric N2O data from the National Oceanic and Atmospheric Administration (NOAA) Global Greenhouse Gas Reference Network, including surface, aircraft and tall tower platforms. These studies have concluded that global N2O inventories such as EDGAR may be underestimating the true U.S. anthropogenic N2O source by a factor of 3 or more. However, simple back-of-the-envelope calculations show that emissions of this magnitude are difficult to reconcile with the basic constraints of the global N2O budget. Here, we explore some possible reasons why regional atmospheric inversions might overestimate the U.S. agricultural N2O source. First, the seasonality of N2O agricultural sources is not well known, but can have an important influence on inversion results, particularly when the inversions are based on data that are concentrated in the spring/summer growing season. Second, boundary conditions can strongly influence regional inversions but the boundary conditions used may not adequately account for remote influences on surface data such as the seasonal stratospheric influx of N2O-depleted air. We will present a set of forward model simulations, using the Community Land Model (CLM) and two atmospheric chemistry tracer transport models, MOZART and the Whole Atmosphere Community Climate Model (WACCM), that examine the influence of terrestrial emissions and atmospheric chemistry and dynamics on atmospheric variability in N2O at U.S. and global monitoring sites.