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EXAMINING THE TEMPORAL VARIABILITY OF AMMONIA AND NITRIC OXIDE EMISSIONS FROM AGRICULTURAL PROCESSES
Pierce Jr., T. E. AND L. W. Bender. EXAMINING THE TEMPORAL VARIABILITY OF AMMONIA AND NITRIC OXIDE EMISSIONS FROM AGRICULTURAL PROCESSES. Presented at AWMA/EPA Emission Inventory Conference, Raleigh, NC, October 26-28, 1999.
This paper examines the temporal variability of airborne emissions of ammonia from livestock operations and fertilizer application and nitric oxide from soils. In the United States, the livestock operations and fertilizer categories comprise the majority of the ammonia emissions inventory. Air quality modeling efforts for the most part have assumed annual-average ammonia emission factors. Based on a literature review, we have generated crude seasonal adjustments of ammonia emissions taking into account climatic factors, manure spreading, and fertilizer application schedules. Nitric oxide (NO) emissions from soils estimated with the Biogenic Emissions Inventory System (BEIS2) comprise about 10% of total annual nitric oxide emissions across the United States. BEIS2 distributes emissions by land use and modulates emissions based on hourly soil temperature, with the highest emissions arising from fertilized soils during warm conditions. A new algorithm has been developed that incorporates daily rainfall patterns, fertilizer application schedules, and plant canopy growth. Simulations with this new algorithm show more short-term variability and an over reduction in soil NO emissions compared to the BEIS2 algorithm, particularly in the Midwestern United States. The techniques introduced for estimating the temporal variability of ammonia and nitric oxide emissions from agricultural operations may help improve the accuracy of fine particulate and ozone models.
This paper has been reviewed in accordance with the U.S. Environmental Protection Agency's peer and administrative review policies and approved for presentation and publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.
To improve the accuracy of emissions and dry deposition algorithms in the Agency's regulatory air quality and multimedia simulation models. This effort requires developing process-oriented algorithms, assembling geographical data, evaluating algorithms against field data, and designing and collaborating on field experiments to collect the data needed to test these algorithms.
Record Details:Record Type: DOCUMENT (PRESENTATION/PAPER)
Organization:U.S. ENVIRONMENTAL PROTECTION AGENCY
OFFICE OF RESEARCH AND DEVELOPMENT
NATIONAL EXPOSURE RESEARCH LAB
ATMOSPHERIC MODELING DIVISION
MODELING SYSTEMS ANALYSIS BRANCH