Environment

 Industry Partners


Prairie Swine Centre is an affiliate of the University of Saskatchewan


Prairie Swine Centre is grateful for the assistance of the George Morris Centre in developing the economics portion of Pork Insight.

Financial support for the Enterprise Model Project and Pork Insight has been provided by:



How can I Control Hydrogen Sulphide in my Barn?

Posted in: Environment by admin on January 1, 2004 | No Comments

Hydrogen sulphide (H2S) is a life threatening gas produced by the anaerobic breakdown of liquid manure. H2S can be released while performing common tasks that involve manure flow or mixing. Short and long-term effects of exposure can have impacts on the health and well being of the exposed person. 100-ppm exposure is immediately dangerous to life or health. Pit pulling can generate up to 1000 ppm. Research is being done to improve building design and manure management systems to minimize H2S exposure in hog barns. The goal is to develop low cost systems that will prevent or reduce worker exposure to high H2S concentration during pit pulling. The first stage is to develop a pit pulling system to allow plugs to be pled from a remote location and prevents backflow of manure or gases when the plugs are put back in. The second stage is to determine reduction of H2S gas when tap water is sprinkled. The third stage is to design and develop a pit scraper system to remove swine manure from the barn on a daily basis and to evaluate the reduction of H2S. A pit puller system has already been developed that is low cost, easy to install/use, and is safe. This system involves a winch in the hallway to mechanically pull the plugs from outside the room. A laboratory apparatus was designed to simulate H2S peak concentrations observed during pit pulling events in barns. This was put in a tank, which was equipped with a nozzle port to spray water solution while the H2S was injected. At this time, both the remote puller and the sprinkling systems look promising to control the H2S exposure of workers at a low cost.

Effects of Duration and Intensity of Aeration on Solids Decomposition in Pig Slurry for Odour Control

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A 30 day laboratory scale experiment was carried out using three different aeration rates, i.e. +35mV
oxidation–reduction potential (ORP: standard hydrogen electrode), 10, and 30 mg[O2] l1, to achieve solids decomposition and odour control in pig slurry with total solids (TS) levels from 05 to 40%. Changes during the aeration process were characterised by TS, total volatile solids (TVS), total suspended solids (TSS), and total volatile suspended solids (TVSS), all expressed as w/w. The measurement of volatile fatty acids (VFAs), expressed as w/v, was used to evaluate the potential odour generation in the aerated slurry. The TS removal efficiencies from 60 to 449, 186 to 503, and 423 to 564% were observed for the three different aeration levels, with reductions from 66 to 489, 260 to 611, and 573 to 699% for the slurry TVS. The ratios of TVS/ TS, TSS/TS, and TVSS/TS in slurry over the experimental duration were found to increase with increased TS levels in the 30 day aeration under the three aeration intensities. Reductions in the 5 day biological oxygen
demand (BOD5) reached 785–920, 794–960, and 912–970%, while reductions of VFAs reached 127–990, 717–990%, and 878–993%. The biodegradation of solids, BOD5, and VFAs was effectively enhanced when aeration time and intensity were increased. A low level of solids in slurry promoted aerobic decompositions of solids, BOD5, and VFAs. Changes of state in the solids being aerated and changes in the BOD5 levels can be used to distinctly characterise the potential of odour generation from the slurry. Batch aeration of 5–10 days under intensities of 10 to 30 mg[O2] l1 is recommended for odour control at farm level.

Dust Control for Livestock Buildings

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The majority of agricultural safety groups considers dust an occupational hazard and confined livestock buildings have a lot of it. There are two kinds of dust: inhalable, which is >20ìm, and respirable, which is >5ìm. About 80-90% of dust in swine and poultry buildings is the respirable type, which can be inhaled deeply into the lungs. This can lead to health problems such as bronchitis, chronic farmer lung disease, occupational asthma and organic dust toxic syndrome (ODTS).
Factors affecting dust concentration in confined livestock buildings are temperature, relative humidity, ventilation systems, feeding practices, stocking density, cleanliness of the buildings, bedding materials and animal activity. Minimizing the occurrence of fine particles, preventing these particles from forming dust clouds, removing airborne dust using air cleaning devices and having workers use dust masks can reduce dust hazards. Dust control methods include proper and timely maintenance of feeding equipment, having a good ventilation system, sprinkling oil on the ground or in the pens, misting the air to increase the relative humidity and ionization to accelerate and remove dust.

Single-component Modelling of Pig Farm Odour with Statistical Methods and Neural Networks

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Pork farm odour has become an increasingly important problem for the pork industry because non-farming
rural residents object to the odours coming from pig facilities and insist that it disrupts enjoyment of their properties. The pork industry has thus faced strong opposition to farm expansion or the creation of new pork farms. Reducing pork farm odour requires an understanding of what causes the odour and the ability to measure the odour. The pork industry and researchers have attempted to model pork farm odour using single-component odour indicators, such as ammonia and hydrogen sulphide, with statistical models. Single component analysis refers to only one odour indicator being used to predict odour levels. In this paper, a neural network approach to the pork farm odour using single-component analysis with the consideration of other relevant factors, such as measurement location is proposed. Neural network models and statistical models for pork farm odour have been developed and compared for single-component models to determine which method produces superior results. In general, the use of neural networks to model the pork farm odour yields more accurate and precise odour intensity predictions than the statistical models. The measurement location for the pork farm odour was considered in several model comparisons. The neural network models significantly outperformed the statistical models in this comparison because the statistical models are not able to consider the measurement location. This indicates that measurement location is a relevant factor for modelling pork farm odour. This also demonstrates that factors other than odour components should be considered during modelling. It is hypothesised that a multiple-component (odour components) and multiplefactor
(environmental conditions and other human expert knowledge) analysis approach to the modelling of
pork farm odour using neural networks and other intelligent systems techniques will yield increased accuracy for odour prediction and a thorough understanding of this significant problem.

Capturing Carbon Credits through Manure Digestion

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The issue of capturing Green House Gas (GHG) emissions and the sequestering of carbon credits is a new and emerging field for the agricultural sector. One of the biggest incentives on the horizon appears to be the sale of carbon credits. In 2001, BioGem Power Systems Inc. obtained the rights to an anaerobic digestion process that was being used in Europe to capture methane generated from manure from intensive livestock operations. One of these digesters was built in East Central Alberta. This reduces GHG emissions and has the potential for a carbon credit value that will allow producers to received financial gain from new technology. The benefits of this system include using the heat generated by the system in the barn and passing the processed manure through a water treatment plant to in turn be used by the producer in the barn. Costs of a facility like the one in Alberta would be in the range of $2.5 million and would include the cost of the water treatment facility. The plants can be customized to the producers’ specific needs and conditions. A control system such as the ISO system used in many other industries will likely be developed to be the basis for measuring, quantifying, auditing and reporting GHG emissions and subsequent carbon credits.

 
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