Characterization of gaseous pollutant and particulate matter emission rates from a commercial broiler operation part II: Correlated emission rates |
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| Authors: | Taylor S Roumeliotis Brad J Dixon Bill J Van Heyst |
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| Institution: | 1. Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN 47907, USA;2. Department of Agricultural and Biosystems Engineering, Iowa State University, Ames, IA 50011, USA;3. Pacific Northwest National Laboratory, Richland, WA 99352, USA;4. Department of Agricultural Systems Management, University of Missouri, Columbia, MO 65211, USA;1. Biological Engineering, University of Saskatchewan, 57 Campus Drive, Saskatoon, SK, S7N 5A9, Canada;2. Mechanical Engineering, University of Saskatchewan, 57 Campus Drive, Saskatoon, SK, S7N 5A9, Canada;1. Polytechnic Institute of Viseu, Agrarian School of Viseu, CI&DETS, Quinta da Alagoa, 3500-606 Viseu, Portugal;2. University of Trás-os-Montes and Alto Douro, CITAB, Quinta de Prados, 5000-801 Vila Real, Portugal;1. Dept. of Agricultural, Food and Environmental Sciences, University of Perugia;2. ARPA Umbria |
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| Abstract: | Emission rates of ammonia, acid gases, inorganic aerosols, methane, and size fractionated particulate matter were measured from a commercial broiler facility. This paper discusses the statistically influential parameters on numerous pollutants’ emission from a broiler chicken facility and generates emission correlations to fill data gaps and develop averaged emission factors.Live mass of the birds was commonly a significant variable to each pollutant’s emission. Some variables significantly impacted the pollutants’ emissions, such as litter moisture content, but were measured discretely and cannot be used for filling in data gaps.House parameter correlations were, therefore, developed using parameters measured at the facility, such as indoor temperature, relative humidity, and the live mass of the birds, and relied on the mutual behaviour of discretely measured explanatory parameters and continuously monitored confounding variables. The live mass and the difference in the indoor temperature and the house set-point temperature were the most significant variables in each pollutant’s correlation.The correlations predicted each pollutants emission to within 20% (total mass basis) over most broiler production cycles. Their validation on independent datasets also successfully estimated the flocks’ emissions to within 3%.Emission factors (EFs) were developed for methane, ammonia, and size fractionated particulate matter using measured data and correlated emissions to fill in data gaps. PM10 (particulate matter ≤10 microns) EFs were estimated to be 4.6 and 5.9 g d?1 Animal Unit, AU]?1 for five and six week production cycles, respectively. PM2.5 (PM ≤ 2.5 microns) EFs were 0.8 and 1.4 g d?1 AU?1 for five and six week cycles, respectively. Ammonia and methane emission factors were estimated at 120.8 and 197.0 g d?1 AU?1, respectively for a five week production cycle. |
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