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Fertilizer NH3 Emission Estimates for 2017 National Emissions Inventory Using an Agricultural Ecosystem Model and an Air Quality Model
Citation:
Bash, J., V. Rao, AND Keith Appel. Fertilizer NH3 Emission Estimates for 2017 National Emissions Inventory Using an Agricultural Ecosystem Model and an Air Quality Model. 2019 International Emissions Inventory Conference, Dallas, TX, July 29 - August 02, 2019.
Impact/Purpose:
A methodology in estimating NH3 emissions from fertilizer using an agricultural and air quality model than can incorporate state submitted data has been developed for the 2017 National Emissions Inventory. CMAQ v5.3 model estimates of NH3 emissions from fertilizer will be evaluated against 2014 and 2011 U.S. EPA NEI estimates. Preliminary results from this modeling system indicate that these new parameterizations can capture the magnitude of measured ammonia fluxes well however annual ambient concentrations when simulated with CMAQ are lower than observations. The limitations of using nutrient demands from a plant growth model in EPIC will be discussed. Techniques to reduce these limitations by using USDA survey and state submitted data to modify CMAQ inputs will be presented.
Description:
The Community Multiscale Air Quality (CMAQ) model v5.3 includes a new land use specific dry deposition scheme that has been developed to improve linkages with ecosystem models and to estimate fertilizer NH3 emissions when coupled to the USDA’s Environmental Policy Integrated Climate model (EPIC). A model resistance framework that parameterizes air-surface exchange as a gradient process and is consistent between bidirectional exchange and dry deposition will be introduced. NH3 fluxes and ambient concentrations will be evaluated against field scale measurements and ambient NH3 measurements from monitoring networks and satellite observations respectively. CMAQ v5.3 model estimates of NH3 emissions from fertilizer will be evaluated against 2014 and 2011 U.S. EPA NEI estimates. The seasonality and annual emission factors of NH3 emissions estimated in this modeling system will be discussed. Preliminary results from this modeling system indicate that these new parameterizations can capture the magnitude of measured ammonia fluxes well however annual ambient concentrations when simulated with CMAQ are lower than observations. The limitations of using nutrient demands from a plant growth model in EPIC will be discussed. Techniques to reduce these limitations by using USDA survey and state submitted data to modify CMAQ inputs will be presented.