Development of an Agricultural Fertilizer Modeling System for Bi-directional Ammonia Fluxes in the Community Multiscale Air Quality (CMAQ) Model Limei Ran 1, Ellen Cooter 2, Verel Benson 3, Qun He 1 1 Institute for the Environment, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA 2 Atmospheric Modeling and Analysis Division, U.S. EPA, Research Triangle Park, NC 27711, USA 3 Verel W. Benson, Benson Consulting, 200 Haywood Ct, Columbia, MO 65203, USA

Outline of the Presentation Agricultural Fertilizer Modeling System Environmental Policy Integrated Climate (EPIC) Tools to Connect EPIC and CMAQ Fertilizer Emission Scenario Tool for CMAQ (FEST-C) Interface Related Research and Future Work Acknowledgements

Background Atmospheric ammonia (NH 3 ) plays a very important role in –Ammonium, nitrate and sulfate aerosol formation –Ammonia and ammonium deposition The annual National Emission Inventory (NEI) is currently used by USEPA to estimate NH 3 emissions –Most of ammonia emissions come from agricultural practices (>75%) –Animal operations (~51%, NEI 2002af) –Agricultural soil commercial inorganic N fertilizer applications (~35%) Problem : Accurate estimation of ammonia emissions in space and time has always been a challenge –Fertilizer applications vary in the time, amount, method by crop types and locations Solution : Development of an agricultural fertilizer modeling system for use with a newly developed ammonia bi- directional flux model in CMAQ

Agricultural Fertilizer Modeling System for CMAQ N Deposition Environmental Policy Integrated Climate (EPIC) Bi-directional NH 3 Flux modeling CMAQ Spatial Allocator Tools Java-base Fertilizer Tool (FEST-C) Interface Non-Fertilizer NEI Emission Inventories WRF Fertilizer N BELD4 (NLCD/MODIS, FIA, NASS) Meteorology Crops Focus on USEPA extended CONUS 12km CMAQ domain

Environmental Policy Integrated Climate (EPIC) A cropping simulation system, developed during the 1980’s to estimate soil productivity as affected by erosion –Formerly called the Erosion-Productivity Impact Calculator Designed to simulate drainage areas that are characterized by: –Homogeneous weather, soil, landscape, crop rotation, and management Enhanced continuously to simulate: –Water quality, climate change, the effect of atmospheric CO 2 concentration, and C/N cycling A field/site scale, daily time step model Has been applied across the continental U.S. and around the world from field to national scale

EPIC contains processes: Weather (simulated or actual) Hydrology (runoff, evapotranspiration, percolation) Erosion (wind and water) Crop growth (N & P uptake, stresses, yields, N-fixation) Fertilization (application, runoff, leaching, mineralization, denitrification, volatilization, nitrification) Tillage Irrigation and furrow diking Drainage Pesticide (application, movement, degradation) Grazing Manure application Crop rotations, inter-cropping, weed competition

Modified EPIC Modeling for the Extended EPA CONUS CMAQ 12km Domain Grids Environmental Policy Integrated Climate (EPIC) WRF CMAQ BELD4: Grid Crop Data (NLCD/MODIS, NASS) Site (12km grid with crop/pasture) Data elevation, slope, lat and long GIS Data Country, State, County, HUC8, DEM, 10 regions Site Weather N Deposition Data historical NRI sample point data (350,000 points) Baumer soil database (280,000 soils, 23,000 EPIC soils) Crop management data from NASS, FSA/FAPRI CRP assessment, CEAP, and RCA analytical database 8-digit HUC Soil Data Site crop Management Data All other existing EPIC data sets (e.g. monthly climatology data, parameters) 10-yr biogeochemical spin-up

Total Grids = 299 * 459 = 137,241 Grids with Crop/Pasture: 70,169 EPIC sites: US: 45,950 CAN: 17,900 MEX: 6,265 BAH: 54

38 NASS Crops to Be Modeled Climatology-Based Irrigated Grain Corn Planting Date 22 Hay 23 Hay_ir 24 Alfalfa 25 Alfalfa_ir 26 Other_Grass 27 Other_Grass_ir 28 Barley 29 Barley_ir 30 BeansEdible 31 BeansEdible_ir 32 CornGrain 33 CornGrain_ir 34 CornSilage 35 CornSilage_ir 36 Cotton 37 Cotton_ir 38 Oats 39 Oats_ir 40 Peanuts 41 Peanuts_ir 42 Potatoes 43 Potatoes_ir 44 Rice 45 Rice_ir 46 Rye 47 Rye_ir 48 SorghumGrain 49 SorghumGrain_ir 50 SorghumSilage 51 SorghumSilage_ir 52 Soybeans 53 Soybeans_ir 54 Wheat_Spring 55 Wheat_Spring_ir 56 Wheat_Winter 57 Wheat_Winter_ir 58 Other_Crop 59 Other_Crop_ir Climatology-Based Rainfed Grain Corn Planting Date

Tools to Connect EPIC and CMAQ MCIP/CMAQ to EPIC tool: –Radiation (MJ m^2, daily total) –Tmax, Tmin (C, daily) –Precipitation (mm, daily total) –Relative humidity (fraction, daily average) –Windspeed (m s^-1, daily average) –Dry N from CMAQ (g/ha, daily total) –Wet N from CMAQ (g/ha, daily total) EPIC to CMAQ tool to create three NetCDF files for EPIC sites: –Soil property output e.g., bulk density, wilting point… –Time step output e.g. NO 3 loss, denitrification, N-volatilized, Fertilize-NH 3, LAI, crop height… –Fertilizer application output e.g. Application-Date, Application-Depth, mineral and organic N and P

EPIC Site Weather June 14, 2002

Rainfed Grain Corn Leaf Area Index (LAI) January FebruaryMarch April May June JulyAugustSeptember

Java-based FEST-C Interface Provides integrated capabilities of running EPIC model, Spatial Allocator Raster Tools, and VERDI visualization for input and output NetCDF Contains five components: –Process MCIP and CMAQ N deposition data for EPIC modeling –Modify management scenario and EPIC run files –Run the EPIC model –Process EPIC output data into the CMAQ ready format –Visualize input and output data using VERDI

Related Research Estimation of NH 3 Bi-directional Flux from Managed Agricultural Soils (Cooter et al., 2010, Atmospheric Environment) Estimation of In-Canopy Ammonia Sources and Sinks in a Fertilized Zea Mays Field (Bash et al., 2010, ES&T) Development and Evaluation of an Ammonia Bi- Directional Flux Model for Air Quality Models (Pleim et al., 2010, ITM 31)

Future Work Complete and evaluate current modeling system for all 38 crops (fertilizer rates, dates, yield) Update crop and soil management files when BELD4 is complete (under development) Improve soil and management scenarios for Canada, Mexico, and Bahamas Complete and enhance options in FEST-C interface Enhance soil and crop management programs for other domains with different grid resolutions Develop and model crop rotation and biofuel scenarios Prepare for climate change applications (e.g., multi-year time slices) Integrate with the coupled WRF-CMAQ for climate, air quality, and agricultural productivity studies

Acknowledgements This project is fully funded by US EPA under the Contract No. EP-W “Operation of the Center for Community Air Quality Modeling and Analysis” and EP-D We gratefully acknowledge the support of Jonathan Pleim, William Benjey, and Robin Dennis from US EPA