Ronaldo G. Maghirang

Assessment of Bioaerosols in Swine Barns by Filtration and Impaction

Bioaerosol concentrations inside one naturally ventilated and one mechanically ventilated swine finishing barn were assessed by sampling air using membrane filtration and impaction (six-stage Andersen sampler), and assayed by culture method. The barns, located on the same commercial farm in northeast Kansas, did not show any significant difference (p > 0.05) in concentrations of total and respirable airborne microorganisms. The overall mean total concentrations inside the two barns were 6.6 × 104 colony forming units (CFU)/m3 (SD = 3.8 × 104 CFU/m3) as measured by filtration and 8.6 × 104 CFU/m3 (SD = 5.1 × 104 CFU/m3) by impaction. The overall mean respirable concentrations were 9.0 × 103 CFU/m3 (SD = 4.1 × 103 CFU/m3) measured by filtration and 2.8 × 104 CFU/m3 (SD = 2.2 × 104 CFU/m3) by impaction. Total and respirable CFU concentrations measured by impaction were significantly (p < 0.05) higher than that by filtration. The persistent strains of microorganisms were various species of the following genera: Staphylococcus, Pseudomonas, Bacillus, Listeria, Enterococcus, Nocardia, Lactobacillus, and Penicillium. It appears that filtration sampling can be used for a qualitative survey of bioaerosols in swine barns while the Andersen sampler is suitable for both quantitative and qualitative assessments.

DYNAMIC AIR SAMPLING OF VOLATILE ORGANIC COMPOUNDS USING SOLID PHASE MICROEXTRACTION

A new dynamic air sampling system was devised and evaluated in conjunction with solid phase microextraction (SPME) fiber materials for extracting odor-causing volatile organic compounds (VOCs) present in swine building environments. Utilizing a standard solution consisting of 11 compounds (i.e., volatile fatty acids, indoles, and phenol), sampling times, volumes, and flow rates were adjusted to establish optimal extraction conditions. Results indicated that the sampling system was effective with the Carboxen/Polydimethylsiloxane (CAR/PDMS) fiber in extracting all 11 standard compounds. The best sampling conditions for the extraction were a 100-mL sampling vial subjected to a continuous flow of 100 mL/min for 60 min. The gas chromatographic analysis showed that the reproducibility was within acceptable ranges for all compounds (RSD=4.24–17.26% by peak areas). In addition, field tests revealed that the sampling system was capable of detecting over 60 VOCs in a swine house whose major components were identified by gas chromatography–mass spectrometry (GC–MS) and by their retention times as volatile fatty acids, phenols, indole, and skatole. The field tests also showed that considerably different levels of VOCs were present in various parts of the swine building.

Applications of Discrete Element Method in Modeling of Grain Postharvest Operations

Grain kernels are finite and discrete materials. Although flowing grain can behave like a continuum fluid at times, the discontinuous behavior exhibited by grain kernels cannot be simulated solely with conventional continuum-based computer modeling such as finite-element or finite-difference methods. The discrete element method (DEM) is a proven numerical method that can model discrete particles like grain kernels by tracking the motion of individual particles. DEM has been used extensively in the field of rock mechanics. Its application is gaining popularity in grain postharvest operations, but it has not been applied widely. This paper reviews existing applications of DEM in grain postharvest operations. Published literature that uses DEM to simulate postharvest processing is reviewed, as are applications in handling and processing of grain such as soybean, corn, wheat, rice, rapeseed, and the grain coproduct distillers dried grains with solubles (DDGS). Simulations of grain drying that involve particles in both free-flowing and confined-flow conditions are also included. Review of the existing literature indicates that DEM is a promising approach in the study of the behavior of deformable soft particulates such as grain and coproducts, and it could benefit from the development of improved particle models for these complex-shaped particles.

LABORATORY EVALUATION OF THE DUST-EMISSION POTENTIAL OF CATTLE FEEDLOT SURFACES

A laboratory apparatus was developed for measuring the dust-emission potential of cattle feedlot surfaces as affected by manure surface characteristics. A feedlot surface was simulated with a layer of dry, loose, sieved feedlot manure, either with or without a compacted soil layer underneath. The vertical action of the cattle hoof was reproduced by dropping a steel weight onto the manure surface. High-volume samplers for PM10 (particulate matter smaller than 10 .m aerodynamic equivalent diameter) were used to collect suspended PM10. The effects of kinetic energy of the falling weight, manure depth, manure moisture content, bulk density, and surface amendment (sawdust, wheat straw, and surface water application) were investigated. For each manure depth, PM10 emission was directly related to the kinetic energy of the falling weight. For each weight drop, PM10 emission did not differ significantly with manure depth. In addition, PM10 emission was inversely related to the manure moisture content. Compaction of the manure surface reduced PM10 emission. Increased amounts of water, sawdust, or wheat straw to the manure surface also significantly decreased PM10 emission in initial tests, but dislodging/displacement of wheat straw and penetration of the wetted surface crust by the falling weight increased the emission potential for subsequent tests. The weight drop test chamber developed is a simple and repeatable method that can be used to compare relative effectiveness of different dust abatement measures. While the measurements are reproducible, the vertical action of the cattle hoof is highly simplified; thus, the WDTC might not fully reproduce the actual vertical action of the cattle hoof on a feedlot surface. In addition, the resulting aerosol may not have similar physical characteristics as those of dust emitted from feedlots.

CHARACTERIZATION OF VOLATILE ORGANIC COMPOUNDS ON AIRBORNE DUST IN A SWINE FINISHING BARN

Three methods of extracting volatile organic compounds (VOCs) adsorbed on the airborne dust in a swine finishing building were investigated: solvent extraction using dichloromethane, solid-phase microextraction (SPME) using carboxen/ polydimethylsiloxane (CAR/PDMS) and PDMS fibers, and purge and trap. Airborne dust was first collected in pre-baked glass-fiber filters and analyzed using each of the three methods. Solvent extraction with dichloromethane extracted only some high-boiling point carboxylic acids. The SPME CAR/PDMS fiber extracted the low- to mid-boiling point VOCs such as the carboxylic acids, phenols, and indoles; while the PDMS fiber extracted more of the mid-boiling point compounds, specifically the aliphatic hydrocarbons, indoles, and some aldehydes. The purge and trap method extracted compounds with low- to mid- boiling points including volatile carboxylic acids, aldehydes, alcohols, ketones, indoles, and esters. Quantitative analysis of five selected VOCs (i.e., acetic acid, propionic acid, butyric acid, hexanal, and nonanal) using the purge and trap method showed acetic acid as generally the most abundant and nonanal as the least abundant.

Field comparison of inhalable and total dust samplers for assessing airborne dust in swine confinement barns

Inhalable and total dust sampling devices were compared for evaluating airborne dust in swine confinement buildings. Measurements from three swine facilities (n = 77 paired means) were obtained by area sampling using the IOM (Institute of Occupational Medicine, Edinburgh, U.K.) inhalable dust sampler and a 37-mm closed-face total (TCF) dust sampler. The overall geometric mean IOM concentration (1.18 mg/m(3), geometric standard deviation [GSD] = 2.00) was significantly greater (P < 0.05) than the overall geometric mean TCF concentration (1.08 mg/m(3), GSD = 1.98). Regression analysis with IOM and TCF values as independent and dependent variables, respectively, yielded a factor of 0.86 (+/-0.04 95% confidence interval), which can be used to estimate TCF values from the IOM measurements. Additional paired sampling data were obtained to compare the following pairs of dust samplers: (1) IOM sampler and conical inhalable sampler (CIS) (n = 20 paired means), (2) IOM and open-face total (TOF) dust samplers (n = 14), (3) CIS and TCF samplers (n = 19), and (4) TCF and TOF samplers (n = 8). Paired t-tests showed significantly (P < 0.05) higher IOM concentrations than the CIS sampler; no significant difference (P > 0.05) was found for the other three pairs compared. It may be necessary to establish work-specific conversion coefficients to obtain a reasonable estimate of worker exposure to total dust from measurements using other types of dust sampling devices.

Numerical simulation of airflow and particle collection by vegetative barriers

Abstract Vegetative barriers have the potential to mitigate particulate matter (PM) from open dust sources, including unpaved and paved roads, exposed storage piles, and agricultural sources; however, data on their effectiveness in capturing PM are limited. This study was conducted to predict the airflow and particle collection efficiency of vegetative barriers. The applicability of computational fluid dynamics (CFD) in modeling airflow around and through porous barriers was first evaluated by simulating airflow passing a porous fence (1.2 m high × 0.01 m thick, 50% porosity) using standard and realizable k -ε turbulence models in FLUENT. Predicted air velocities compared favorably with available experimental data. The CFD model was then applied to simulate airflow and particle collection by a row of trees (2.2 m high × 1.6 m wide) with characteristics similar to those of hawthorn trees. The Eulerian-Eulerian model was used to predict particle transport and collection by the tree elements. Predicted particle collection efficiencies for the trees agreed with available experimental data and ranged from less than 1% for 0.875-μm particles to approximately 32% for 15-μm particles. Results from this study indicated that numerical simulation with CFD can be used to predict particle collection efficiency of vegetative barriers and that this technique has the potential to advance research on vegetative barriers for dust control for open sources. Further work is investigating effects of the structure of vegetative barriers on particle collection.

Durability and Breakage of Feed Pellets during Repeated Elevator Handling

Pelleting of animal feeds is important for improved feeding efficiency and for convenience of handling. Pellet quality impacts the feeding benefits for the animals and pellet integrity during handling. To determine the effect of repeated handling on feed pellet breakage and durability, a 22.6-t (1000-bu) lot of feed pellets made from corn meal was transferred alternately between two storage bins in the USDA- ARS, Grain Marketing and Production Research Center research elevator at Manhattan, Kansas, at an average flow rate of 62.2 t/h. Samples from a diverter-type sampler were analyzed for particle size distribution (by sieving) and durability (by the tumbling box method). The apparent geometric mean diameter of samples decreased with repeated transfers, whereas the mass of accumulated broken pellets increased with repeated transfers. The percentage of broken pellets increased by an average of 4.0% with each transfer from an initial value of 17.5%, which was within the range of published values for shelled corn obtained from the same elevator. The pellet durability index averaged 92.9% (standard deviation=0.6%) and did not change significantly (p>0.05) during the transfers. The high pellet durability index indicates that the pellets can withstand repeated transfers in feed handling systems.

Size distribution and rate of dust generated during grain elevator handling

Dust generated during grain handling can pose a safety and health hazard and is an air pollutant. This study was conducted to characterize the particle size distribution (PSD) of dust generated during handling of wheat and shelled corn in the research elevator of the USDA Grain Marketing and Production Research Center and determine the effects of grain lot, repeated transfer, and grain types on the PSD. Dust samples were collected on glass fiber filters with high volume samplers from the lower and upper ducts upstream of the cyclone dust collectors. A laser diffraction analyzer was used to measure the PSD of the collected dust. For wheat, the size distribution of dust from the upper and lower ducts showed similar trends among grain lots but differed between the two ducts. The percentages of particulate matter (PM)-2.5, PM-4, and PM-10 were 5.19%, 9.81%, and 34.1% of the total wheat dust, respectively. The total dust mass flow rate was 0.94 g/s (equivalent to 64.6 g/t of wheat handled). For shelled corn, the size distributions of the dust samples from the upper and lower ducts also showed similar trends among transfers but differed between the two ducts. The percentages of PM-2.5, PM-4, and PM-10 were 7.45%, 9.98%, and 28.8% of the total shelled corn dust, respectively. The total dust mass flow rate was 2.91 g/s (equivalent to 185.1 g/t of corn handled). Overall, the corn and wheat differed significantly in the size distribution and the rate of total dust generated.

Particulate matter emission rates from beef cattle feedlots in Kansas—Reverse dispersion modeling

Open beef cattle feedlots emit various air pollutants, including particulate matter (PM) with equivalent aerodynamic diameter of 10 μm or less (PM10); however, limited research has quantified PM10 emission rates from feedlots. This research was conducted to determine emission rates of PM10 from large cattle feedlots in Kansas. Concentrations of PM10 at the downwind and upwind edges of two large cattle feedlots (KS1 and KS2) in Kansas were measured with tapered element oscillating microbalance (TEOM) PM10 monitors from January 2007 to December 2008. Weather conditions at the feedlots were also monitored. From measured PM10 concentrations and weather conditions, PM10 emission rates were determined using reverse modeling with the American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model (AERMOD). The two feedlots differed significantly in median PM10 emission flux (1.60 g/m2-day for KS1 vs. 1.10 g/m2-day for KS2) but not in PM10 emission factor (27 kg/1000 head-day for KS1 and 30 kg/1000 head-day KS2). These emission factors were smaller than published U.S. Environmental Protection Agency (EPA) emission factor for cattle feedlots. Implications This work determined PM10 emission rates from two large commercial cattle feedlots in Kansas based on extended measurement period for PM10 concentrations and weather conditions, and reverse dispersion modeling, providing baseline information on emission rates for cattle feedlots in the Great Plains that could be used for improving emissions estimates. Within the day, PM emission rates were generally highest during the afternoon period; PM emission rates also increased during early evening hours. In addition, PM emission rates were highest during warm season and prolonged dry periods. Particulate control measures should target those periods with high emission rates.