Atmospheric Ammonia Emissions from the Livestock Sector: Development and Evaluation of a Process-based Modeling ApproachEPA Grant Number: RD834549
Title: Atmospheric Ammonia Emissions from the Livestock Sector: Development and Evaluation of a Process-based Modeling Approach
Investigators: Adams, Peter
Institution: Carnegie Mellon University
EPA Project Officer: Chung, Serena
Project Period: May 1, 2010 through April 30, 2014 (Extended to November 30, 2015)
Project Amount: $483,827
RFA: Novel Approaches to Improving Air Pollution Emissions Information (2009) RFA Text | Recipients Lists
Research Category: Air Quality and Air Toxics , Air
We propose multi-faceted research to enhance our understanding of NH3 emissions from livestock feeding operations. A process-based emissions modeling approach will be used, and we will investigate ammonia emissions from the scale of the individual farm out to impacts on regional nitrogen deposition and particulate matter formation. Proposed tasks are: (a) develop FEMs and NPMs for beef cows, swine, and chickens; (b) evaluate the FEMs against unprecedented emissions measurements made during the NAEMS study; (c) use the FEMs and NPMs to generate a process-based NH3 emissions inventory for the United States; (d) incorporate revised livestock emissions into the CMU Ammonia Emissions Inventory; (e) evaluate the performance of the revised inventory in a CTM against a suite of ambient observations; (f) perform policy-relevant chemical transport modeling to understand the sensitivity of inorganic PM2.5 to SO2, NOx, and NH3 under current and future regulatory regimes; and (g) disseminate the revised inventory to the public via the world wide web.
The objective of this work is to develop a set of emissions modeling tools that predict the seasonality and amount of ammonia emissions from livestock operations. These emissions contribute to ambient PM2.5 concentrations when ammonia reacts with nitric acid gas to form ammonium nitrate particulate matter. Ammonia emissions are highly variable in space and time depending on local climate conditions and farming practices. Ammonia emissions models should adequately account for the major regional and seasonal variations in livestock emission factors.
A set of farm emissions modules (FEMs) will be developed to predict ammonia emissions at livestock operations. The FEMs will be based on mass balances for reduced nitrogen and on mass transfer principles. FEMs will be developed for the following major livestock types: beef cows, swine, and chickens. Each FEM will predict emissions from animal housing and/or grazing as well as subsequent manure management (manure storage and/or spreading). FEM predictions will account for variations in local climate and farming practices. The FEM predictions will be scaled up into a national ammonia emissions inventory for livestock (with monthly and county level resolution) by repeatedly running the FEMs to simulate the major types of farming practices in each county and month. The resulting ammonia emissions will be evaluated by using them as inputs to a chemical transport model (PMCAMx) and comparing predicted NH3/NH4+ concentrations and deposition against available observations.
A major result will be a set of emissions modeling tools that predict the timing and amount of ammonia emitted by livestock operations nationwide. These predictions will be evaluated against data, including from the National Air Emisions Monitoring Study (NAEMS), so that they may be used with confidence. Predicted ammonia emissions are an important input for chemical transport modeling of fine particulate matter (PM2.5), and the seasonal cycle of ammonia emissions will enhance our capabilities to predict PM2.5 levels nationwide. As emissions control strategies depend on such modeling, this work will support better decision-making tools for controlling PM2.5 levels and protecting human health. Additionally, ammonia deposition contributes to eutrophication, so this work will contribute to better policy-making for protecting ecosystems.