A pilot-scale mobile biofilter was developed where two types of wood chips (western cedar and 2 in. hardwood) were examined to treat odor emissions from a deep-pit swine finishing facility in central Iowa. The biofilters were operated continuously for 13 weeks at different air flow rates resulting in a variable empty bed residence time (EBRT) from 1.6 to 7.3 s. During this test period, solid-phase microextraction (SPME) PDMS/DVB 65 microm fibers were used to extract volatile organic compounds (VOCs) from both the control plenum and biofilter treatments. Analyses of VOCs were carried out using a multidimentional gas chromatography-mass spectrometry-olfactometry (MDGC-MS-O) system. Results indicated that both types of chips achieved significant reductions in p-cresol, phenol, indole and skatole which represent some of the most odorous and odor-defining compounds known for swine facilities. The results also showed that maintaining proper moisture content is critical to the success of wood-chip based biofilters and that this factor is more important than media depth and residence time.

It is a common practice in the midwestern United States to raise swine in buildings with under-floor slurry storage systems designed to store manure for up to one year. These so-called "deep-pit" systems are a concentrated source for the emissions of ammonia (NH 3 ), hydrogen sulfide (H 2 S), and odors. As part of a larger six-state research effort (U.S. Department of Agriculture-Initiative for Future Agriculture and Food Systems Project, "Aerial Pollutant Emissions from Confined Animal Buildings"), realtime NH 3 and H 2 S with incremental odor emission data were collected for two annual slurry removal events. For this study, two 1000-head deep-pit swine finishing facilities in central Iowa were monitored with one-year storage of slurry maintained in a 2.4 m-deep concrete pit (or holding tank) below the animal-occupied zone. Results show that the H 2 S emission, measured during four independent slurry removal events over two years, increased by an average of 61.9 times relative to the before-removal H 2 S emission levels. This increase persisted during the agitation process of the slurry that on average occurred over an 8-hr time period. At the conclusion of slurry agitation, the H 2 S emission decreased by an average of 10.4 times the before-removal emission level. NH 3 emission during agitation increased by an average of 4.6 times the before-removal emission level and increased by an average of 1.5 times the before-removal emission level after slurry removal was completed. Odor emission increased by a factor of 3.4 times the before-removal odor emission level and decreased after the slurry-removal event by a factor of 5.6 times the before-removal emission level. The results indicate that maintaining an adequate barn ventilation rate regardless of animal comfort demand is essential to keeping gas levels inside the barn below hazardous levels.

A pilot-scale biofilter was developed in which two types of wood chips (western cedar [WC] and 2-in. hardwood [HW]) were examined to treat odor emissions from a deep-pit swine finishing facility in central Iowa. The biofilters were operated continuously for 13 weeks at different airflow rates resulting in variable empty bed residence times (EBRTs) from 1.6 to 7.3 sec. The effects of three media moisture levels were also evaluated. A dynamic forced-choice olfactometer was used to evaluate odor concentrations from both the control (inlet) plenum and biofilter treatments (outlet). Hydrogen sulfide (H 2 S) and ammonia (NH 3 ) concentrations were also measured from these olfactometry samples. Solid-phase microextraction (SPME) polydimethylsiloxane (PDMS)/ divinylbenzene (DVB) 65-m fibers were used to extract volatile organic compounds from both the control plenum and biofilter treatments. Analyses of separated odors were carried out using a gas chromatographymass spectrometry-olfactometry (GC-MS-O) system. Static sample results indicated that both types of chips achieved significant reductions in odor (average 70.1 and 82.3% for HW and WC, respectively), H 2 S (average 81.8 and 88.6% for HW and WC, respectively) and NH 3 (average 43.4 and 74% for HW and WC, respectively) concentrations. GC-MS-O aromagram results showed both treatments reached high odor reduction efficiency (average 99.4 and 99.8% for HW and WC, respectively). The results also showed that maintaining proper moisture content and a minimum EBRT are critical to the success of wood chip-based biofilters.

It is vital to forecast gas and particle matter concentrations and emission rates (GPCER) from livestock production facilities to assess the impact of airborne pollutants on human health, ecological environment, and global warming. Modeling source air quality is a complex process because of abundant nonlinear interactions between GPCER and other factors. The objective of this study was to introduce statistical methods and radial basis function (RBF) neural network to predict daily source air quality in Iowa swine deep-pit finishing buildings. The results show that four variables (outdoor and indoor temperature, animal units, and ventilation rates) were identified as relative important model inputs using statistical methods. It can be further demonstrated that only two factors, the environment factor and the animal factor, were capable of explaining more than 94% of the total variability after performing principal component analysis. The introduction of fewer uncorrelated variables to the neural network would result in the reduction of the model structure complexity, minimize computation cost, and eliminate model overfitting problems. The obtained results of RBF network prediction were in good agreement with the actual measurements, with values of the correlation coefficient between 0.741 and 0.995 and very low values of systemic performance indexes for all the models. The good results indicated the RBF network could be trained to model these highly nonlinear relationships. Thus, the RBF neural network technology combined with multivariate statistical methods is a promising tool for air pollutant emissions modeling.

This paper describes techniques used to determine airflow rate in multiple emission point applications typical of animal housing. An accurate measurement of building airflow rate is critical to accurate emission rate estimates. Animal housing facilities rely almost exclusively on ventilation to control inside climate at desired conditions. This strategy results in building airflow rates that range from about three fresh-air changes per hour in cold weather to more than 100 fresh-air changes per hour in hot weather. Airflow rate measurement techniques used in a comprehensive six-state study could be classified in three general categories: fan indication methods, fan rotational methods, and airspeed measurement methods. Each technique is discussed and implementation plans are noted. A detailed error analysis is included that estimated the uncertainty in airflow rate between +/-5 and +/-6.1% of reading at a building operating static pressure, air temperature, relative humidity, and barometric pressure of 20 Pa, 25 degrees C, 50%, and 97,700 Pa, respectively.