Characterization of gaseous pollutant and particulate matter emission rates from a commercial broiler operation part I: Observed trends in emissions

This paper characterizes the emission rates of size fractionated particulate matter, inorganic aerosols, acid gases, ammonia and methane measured over four flocks at a commercial broiler chicken facility. Mean emission rates of each pollutant, along with sampling notes, were reported in this paper, the first in a series of two. Sampling notes were needed because inherent gaps in data may bias the mean emission rates. an emission rates of PM10 and PM2.5 were 5.0 and 0.78 g day−1 [Animal Unit, AU]−1, respectively, while inorganic aerosols mean emission rates ranged from 0.15 to 0.46 g day−1 AU−1 depending on the season. The average total acid gas emission rate was 0.43 g day−1 AU−1 with the greatest contribution from nitrous and nitric acids and little contribution from sulfuric acid (as SO2). a emissions were seasonally dependent, with a mean emission rate of 66.0 g day−1 AU−1 in the cooler seasons and 94.5 g day−1 AU−1 during the warmer seasons. Methane emissions were relatively consistent with a mean emission rate of 208 g day−1 AU−1. urnal pattern in each pollutant’s emission rate was relatively consistent after normalizing the hourly emissions according to each daily mean emission rate. Over the duration of a production cycle, all the measured pollutants’ emissions increased proportionally to the total live mass of birds in the house, with the exception of ammonia. elationships between pollutants provide evidence of mutually dependent release mechanisms, which suggests that it may be possible to fill data gaps with minimal data requirements. In the second paper (Roumeliotis, T.S., Dixon, B.J., Van Heyst, B.J. Characterization of gaseous pollutants and particulate matter emission rates from a commercial broiler operation part II: correlated emission rates. Atmospheric Environment, 2010.), regression correlations are developed to estimate daily mean emission rates for data gaps and, using the normalized hourly diurnal patterns from this paper, emission factors were generated for each pollutant.