Estimation of NH3 bi-directional flux from managed agricultural soils

The Community Multi-Scale Air Quality model (CMAQ) is used to assess regional air quality conditions for a wide range of chemical species throughout the United States (U.S.). CMAQ representation of the regional nitrogen budget is limited by its treatment of ammonia (NH3) soil emission from, and deposition to underlying surfaces as independent rather than tightly coupled processes, and by its reliance on soil emission estimates that do not respond to variable meteorology and ambient chemical conditions. The present study identifies an approach that addresses these limitations, lends itself to regional application, and will better position CMAQ to meet future assessment challenges. These goals were met through the integration of the resistance-based flux model of Nemitz et al. (2001) with elements of the United States Department of Agriculture EPIC (Environmental Policy Integrated Climate) model. Model integration centers on the estimation of ammonium and hydrogen ion concentrations in the soil required to estimate soil NH3 flux. The EPIC model was calibrated using data collected during an intensive 2007 field study in Lillington, North Carolina. A simplified process model based on the nitrification portion of EPIC was developed and evaluated. It was then combined with the Nemitz et al. (2001) model and measurements of near-surface NH3 concentrations to simulate soil NH3 flux at the field site. Finally, the integrated flux (emission) results were scaled upward and compared to recent national ammonia emission inventory estimates. The integrated model results are shown to be more temporally resolved (daily), while maintaining good agreement with established soil emission estimates at longer time-scales (monthly). Although results are presented for a single field study, the process-based nature of this approach and NEI comparison suggest that inclusion of this flux model in a regional application should produce useful assessment results if nationally consistent sources of driving soil and agricultural management information are identified. Published by Elsevier Ltd.