Data di Pubblicazione:
2008
Citazione:
Development of a dynamic model to predict PM10 emissions from swine houses / A. Haeussermann, A. Costa, J.M. Aerts, E. Hartung, T. Jungbluth, M. Guarino, D. Berckmans. - In: JOURNAL OF ENVIRONMENTAL QUALITY. - ISSN 0047-2425. - 37:2(2008), pp. 557-564.
Abstract:
Influences on dust emissions from livestock operations are
number, weight, and kind of animals and characteristics of
the housing system. Diff erences between facilities cannot be
explained solely by mechanistic input variables. Th e objective
of this study was to characterize the main input variables for
modeling emissions of particulate matter with a mass median
diameter ≤10 μm (PM10) from swine facilities using a databased
model. Investigations were performed in mechanically
ventilated facilities for weaning, growing-fi nishing, and sows
in Italy and Germany. Th e measurements included inside and
outside concentration of airborne PM10 particles (scatter light
photometry), ventilation rate (calibrated measuring fans), indoor
air climate at a measuring frequency of 60 s, feeding times, and
animal-related data such as weight and animal activity. Dust
concentration and emission were simulated using a dynamic
transfer function. Th e results indicated that the average PM10
emission rate was infl uenced considerably by housing system.
Th e simulation of the PM10 emission rate resulted in a mean
percentage error per data set of 21 to 39%, whereas the average
simulated and measured emission rate per data set diff ered by
about 4 to 19%. High prediction errors occurred especially
during situations in which the absolute level and spatial
location of the measured activity peaks did not correspond
with the measured dust peaks. Further recommendations of the
study were to improve continuous and accurate measurements
of input variables, such as the activity level in animal houses,
and to optimize the amount of measuring days in relation to the model accuracy.
Tipologia IRIS:
01 - Articolo su periodico
Elenco autori:
A. Haeussermann, A. Costa, J.M. Aerts, E. Hartung, T. Jungbluth, M. Guarino, D. Berckmans
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