Identification of the risk factors for high airborne particle concentrations in broiler buildings using statistical modelling
Article
Article Title | Identification of the risk factors for high airborne particle concentrations in broiler buildings using statistical modelling |
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ERA Journal ID | 3455 |
Article Category | Article |
Authors | Banhazi, T. M. (Author), Seedorf, J. (Author), Laffrique, M. (Author) and Rutley, D. L. (Author) |
Journal Title | Biosystems Engineering |
Journal Citation | 101 (1), pp. 100-110 |
Number of Pages | 11 |
Year | 2008 |
Publisher | Elsevier |
Place of Publication | London, UK |
ISSN | 1537-5110 |
1537-5129 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.biosystemseng.2008.06.007 |
Abstract | High concentrations of airborne particles in poultry building can affect the environmental sustainability of the operation, production efficiency, and the health and welfare of the birds. In addition, sub-optimal air quality can create occupational health and safety (OH&S) risks for farm workers. It was hypothesised that a systematic study of the relationship between air quality and housing features could identify practical ways of reducing the concentration of airborne pollutants found in poultry buildings. To achieve this aim the concentration of total viable (airborne bacteria), inhalable and respirable particles were measured in the airspace of 17 commercial broiler buildings between October 2001 and January 2002. The overall mean total viable, inhalable and respirable particle concentrations measured were 5.27 × 105 cfu m−3, 4.32 mg m−3, 0.84 mg m−3, respectively. The characteristics of the buildings surveyed were documented at the time of sampling and a multi-factorial general linear modelling approach was used to identify the statistically significant factors influencing the concentration of airborne particles. The viable airborne particle concentration was influenced by the cleaning regime (p = 0.067), ventilation type (p = 0.006), age of buildings (p = 0.006), bedding type (p = 0.075) and temperature (p = 0.002). The type of ventilation (p = 0.008), bedding (p = 0.045), temperature (p = 0.023) and building age (p = 0.04) had significant effects on inhalable particle concentrations. Four factors were identified as having a significant affect on respirable particle concentrations in broiler buildings. These were cleaning or not cleaning between batches of birds (p = 0.055), biological loading (kg birds per building airspace) of buildings (p = 0.008), ventilation levels (p = 0.005) and humidity (p = 0.016). The positive effects of cleaning and tunnel ventilation were clearly identified during the study and the fact that older buildings appear to have reduced airborne particle concentrations is also noteworthy. Further refinement and implementation of these aspects of broiler building management would lead to innovative airborne particle reduction opportunities. In turn, an improvement in air quality within poultry buildings should enhance production efficiency, the health of birds and could potentially reduce OH&S related health problems in humans. |
Keywords | air pollution; air quality; concentration (process); environmental protection; industrial hygiene; occupational risks; risk assessment; airborne bacteria; airborne particles; airborne pollutants; environmental sustainability; farm workers; high concentrations; occupational health and safety; particle concentrations; production efficiencies; respirable particles |
ANZSRC Field of Research 2020 | 490501. Applied statistics |
300302. Animal management | |
410404. Environmental management | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | University of Adelaide |
University of Applied Sciences Oldenburger, Germany | |
Agrocampus Rennes, France | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q0q49/identification-of-the-risk-factors-for-high-airborne-particle-concentrations-in-broiler-buildings-using-statistical-modelling
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