BACKGROUND

Livestock and poultry producers are becoming concerned over the odors that are generated from their operations. The impact of odors, not only for their neighbors, but also for their own family and employees, are forcing some producers to consider odor control technologies. However, little research and on-farm odor level data exists to assist in the decision making process. At the same time, county and other local units of government are being asked to make land use decisions to reduce the impact of odors from livestock and poultry operation, but have little or no scientific information on which to base their decisions.

In reaction to these concerns, a Livestock Odor Task Force (LOTF) was appointed by the Feedlot Manure Management Advisory Committee (FMMAC) to provide a strategy to address the odor problems associated with animal agriculture. At the core of LOTF recommendations is a system to ìrateî odor emissions from livestock and poultry facilities and manure storages. The LOTF also recommended that the so called "odor rating system," in combination with standardized total emission/separation distance curves, be used by producers, county staff, and others as a resource and guideline for reducing the impact of odors from animal production units.

This preliminary project is a first attempt at establishing an odor rating system for a particular livestock housing system. As indicated in the progress report for this initial project, we are more concerned about the process on how to develop such a system than with specific results.

MATERIALS AND METHODS

The approach taken in this project was to select two pig nursery production operations and collect odor plume measurements from these two housing systems. Several existing prediction models were used with inputs from the existing farms. The experimental results were compared to the outputs of prediction models to determine how well they can predict odor levels near the pig production sites.

The two pig nursery facilities selected had mechanically ventilated buildings. One of the sites stored manure in deep pits under the barns and the other stored manure in an earthen basin. Pig numbers and ages were obtained for each of the sites. Airflow capacities of the exhaust fans (ratings) were obtained so an emission rate could be obtained from that source. The size and approximate loading rate of the outside manure storage unit was also collected.

Plume monitoring was accomplished by bringing seven individuals, trained to determine odor intensity in ambient air, to the site to measure the odor plume dispersion. Measuring the plume dispersion uses a method developed in Germany and is currently being used in similar studies in both Germany and Switzerland. (ILES, 1997). Distances of 50, 100, and 200 meters were measured off from the odor sources of either buildings and/or manure storage units. At these locations, a line was established with sniffers located about 10 meters apart so the plume width would be covered by the seven individuals. The sniffers were provided with stop watches, charcoal filtered masks, and a clip board with a data sheet. At a given time the sniffers began smelling the air every 10 seconds for a 10 minute period, for a total of 60 data points. The numbers were recorded as odor intensity levels on a 0 (no odor) to 5 (very strong odor) scale. Between smelling times (every 10 seconds) the individual put their masks on to prevent fatigue to their olfactory systems.

While the individual sniffers were taking readings at the three distances from the odor sources, individual air samples were collected from the exhaust air from the barns and/or surface of the manure storage units. A portable weather station was always set on the farm site to continuously record temperature, humidity, wind speed, and direction.

RESULTS

The data collected by the odor plume measurements are summarized in Table 1 and shown graphically in Figures 1-3.

Date	6/17	6/18	6/25	6/25 North
Start time (military time)	17:37	7:07	16:52	18:08
Wind direction average (degrees)	277	338	287	303
Wind speed (m/s)	4.5	5.4	5.8	3.6
RH (%)	35	62	45	53
Radiant energy w/m2	1990	1883	2646	1495
Temperature (°C)	31	17	24	23
Ventilation wall fan (m3/s)	10.73	0	22720	0
Ventation pit fan (m3/s)	4.46	4.46	4.46	4.46
Odor units wall (ou)	872	ñ	305	ñ
Odor units pit (ou)	1331	670	764	905
H2S pit fan (ppb)	ñ	400	710	1100

Table 1. Sampling Data for Farm 1. Numbers are averages over the sampling period. Two barns on the site. Each barn has capacity for 1200 nursery pigs. Each barn is approximately 360 square meters.

Figure 1. Odor plume readings taken from Farm #1 on June 17 at 50, 100, and 200 m.

Figure 2. Odor plume recordings taken from Farm #1 on June 18 at 50, 100, and 200 m.

Figure 3. Odor plume recordings taken from Farm #1 on June 25 at 50, 100, and 200 m.

The figures indicate northwest (315°) to west winds (270°) existed when plume measurements were made on the three days in June. Data was collected in the evening or early morning when wind speeds were low (< 13 mph) and atmospheric conditions relatively stable. The numerical values listed in the figures are a function of the intensity values (0 to 5) recorded by the individual sniffers and the lines drawn are of equal odor values. As seen in Figure 1, the direction and width of the odor plume from the south nursery barn seem to have been identified by the measurements taken. Odor values of slightly more than 200 were measured at 50 and 100 meters from the barn while at 200 meters the odor value was reduced to a maximum of 100. Plume measurements taken during June 18 and 25 were not as successful in defining the exact location of the odor plume as it left the barn sources. Part of the reason for the difficulty in doing this was the fact that at such close distances there were actually two odor sources, the south and the north barns. Some evidence of that is seen in Figure 2, which shows a high odor value at the north end of the 100 and 200 meters distances, and in Figure 3, which shows more odor at the south end of these same measurement lines.

Figures 1-3 all show a consistent reduction in odor, as measured by dilution threshold, as one moves away from the odor source. The plume seems to be identifiable at the 50 m and even at the 100 m distances but is a little more difficult to locate at 200 m because of dispersion. It does seem logical, as described in the German studies, that these distances are appropriate for this type of field odor collection.

Date	6/17	6/18	6/26	6/26
Start time (military time)	19:22	5:34	6:15	6:59
Wind direction average (degrees)	320	348	255	256
Wind speed (m/s)	4.0	4.0	2.2	2.7
RH (%)	39	69	47	47
Radiant energy w/m2	301	247	3658	3593
Temperature (°C)	25	16	18	17
Ventilation wall fan (m3/s)	12.7	10.9	10.9	10.9
Odor units wall (ou)	538	1226	549	549
Odor units basin (ou)	134	754	302	302
H2S wall fan (ppb)	30	280	ñ	ñ
H2S basin (ppb)	15	ñ	ñ	ñ

Table 2. Sampling Data for Farm 2. Numbers are averages over the sampling period. One nursery barn on site with 9 rooms, each room has the capacity for 450 pigs. Barn size is approximately 1200 square meters. Manure is drained (pull plug) to a 4500 m² earthen basin.

Figure 4. Odor plume data taken from Farm #2 on June 17 at 50, 100, and 200 m.

Figure 5. Odor plume data taken from Farm #2 on June 18 at 50, 100, and 200 m.

Figure 6. Odor plume data taken from Farm #2 on June 26 at 50, 100, and 200 m.

The odor plume average field data is summarized in Table 2 and shown graphically in Figures 4-6 for Farm #2. Again, the figures show that defining the odor direction and magnitude is a difficult task. Figure 4 does show quite well the location and magnitude of odors from the outside manure storage travel under the conditions of a fairly low wind from the west-northwest. Slightly better dispersion of odors were found on following day (June 18), shown in Figure 5, but the main odor plume from the manure basin may have gone south of the sniffer's location while some of the building's odors may have been picked up at the north end of the sensing lines. The characteristics of an odor plume from a combined odor source (building and manure storage) are shown in Figure 6, where a southwest wind resulted in an odor plume from both sources. Results from this sampling again show dispersion of odors as one moves away from the odor sources although there is evidence of another source at the northern end of the 200 meter measurement line which may have been off-farm.

Prediction Models

Minimum Distance Separation II (MDS II)

The Ontario Ministry of Agriculture, Food and Rural Affairs has published a guideline for recommended separation distances between a new livestock facility and residential land use. The calculation of the so-called Minimum Distance Separation (MDS) involves the use of four factors which are determined by using tables in the publication. The first factor, "A," represents the barn odor potential. For swine operations, "A" is 1.0 and for a free stall dairy facility, "A" is 0.7. The second factor, "B," makes adjustments for the number of livestock units on the farm site. The third factor, "C," is based on the percentage increase of livestock units on the farm (assumes expansion of an existing livestock operation). For an expansion of 50% or less (based on animal units), "C" is 0.70 and gradually increases up to 1.14 for either a 700% increase or a new operation. The final input factor, "D," is determined by the fundamental type of manure handling system used. Factor "D" is either 0.8 for a liquid system or 0.7 for a solid manure system. The numerical values of the four input factors are simply multiplied together to generate a building base distance, "F." The values for "F" can then be used to determine the separation distances, "S," for both the buildings and the manure storage units by using a different table in the publication.

If the MDS II system is used on the two sites monitored for this study, the results for Farm #1 nursery (deep pit manure storage) are:

A: 1.0 B: 245 C: 1.14 D: 0.8 F: 224 S: 224

The values are then used to recommend the separation distance for the following situations for this farm site.

Nearest neighbor's dwelling: 224 m

Urban residential area: 448 m

Nearest side or rear lot line: 45 m

Nearest road: 56 m

The MDS II results for Farm #2 nursery (earthen basin storage) are:

A: 1.0 B: 253 C: 1.14 D: 0.8 F: 230 S: 408

The values generate two different separation distances due to the earthen basin storage structure system.

Barn Manure Storage Basin

Nearest neighbor's dwelling: 224 m 408 m

Urban residential area: 448 m 816 m

Nearest side or rear lot line: 45 m 82 m

Nearest road: 56 m 102 m

Mathematical Model

Plume prediction was also done using a simple Gaussian dispersion model by a computer program called Pig-E2. This software was obtained from Clemson University (Chastain, personal communications). The inputs needed to run the model include weather, topography, and source odor units. There are eight weather stability class choices, which include time of day, sky conditions, and season of the year. Wind speed and direction are also other required weather inputs. The topography or terrain input is one of two choices which includes either open-flat or closed-trees. Source odor units assumes that the farm is a point source of odor emission and is some measure of the strength and quantity of odor emitted from the farm.

Pig-E2 was run on both of the farms in this preliminary project in order to determine if experimental data could be predicted from the model. For both farms, the chosen stability class was a sunny summer day with a solar altitude of 15-35^o and open-flat terrain. The wind during the observation at Farm #1 was 12 mph NW. In order to generate a plume which was similar to what we observed, 6700 source odor units (ou) was implemented. These inputs produced a plume which was approaching background odor unit levels at 200 m from the pig nursery building, but was still detectable out to 300 m.

The stability class and terrain for the Farm #2 pig nursery site was the same for the previous farm, although the average wind had dropped to 8 mph NW. The source odor units which produced a similar plume to what was observed had to be increased to 18,000 ou to be above the detection level at 200 m, and continued until nearly 400 m.

Determination of the source odor units is difficult to relate to those collected from the earthen basin (Farm #2) and from several rooms and pit fans (Farms #1 & #2). Data from more observations would be needed in order to develop a relationship between the odor units that were measured and those used in the Pig-E2 model. If relationships could be established not only for the odor source inputs but also the weather and other model inputs, this plume model or any model would become a valuable resource.

DISCUSSION

At this preliminary stage of the project, it is premature to compare the prediction models with the experimental data collected. A fair comparison cannot be done until the relative odor values used in the models and recorded by the sniffers for the plume measurements can be correlated. Even among the prediction models, the different odor scales used must be standardized to be able to compare models and then correlated with something that relates to the numbers recorded by the plume sniffers.

Even though little can be said on the distances needed to disperse odors from livestock production units, the process to develop these relationships seems to be possible through comparing prediction results with measurements taken from the field. The experimental data collected reveals that odor plumes can be defined by direction and location from sources by the use of odor sniffers and support equipment like a portable weather station and other materials, if care is taken in during field measurements.

It is important to note that the purpose of the odor rating system is not to recommend setback distances for livestock facilities but rather predict the impact these facilities will have on a community. Therefore, the project's objective is to predict the separation distance from a facility where the community will begin to recognize the odor from the facility. This distance is dependent on both the odor emissions from the facility and the current climatic conditions. Dispersion of odors during very stable climatic conditions is minimal, therefore the odors during those times will maximize the separation distance for a facility. The number of ìstableî conditions throughout the year is difficult to predict; however, this value can be estimated based on past meteorological records for a given geographic location. It is anticipated that there will be approximately four to six different curves on the final separation curves graph per manure handling system, each of them representing a unique climatic condition (Figure 7). It would be the responsibility of the local zoning authority to determine the frequency of odor events that is tolerable for the community.

Because of the limited time frame of this initial project, very little can be said about the impact of nursery barns on the surrounding community. Instead, this project gave us some good practical experience on the important factors to consider in developing an odor rating system. The following ìConceptual Methodology for an Odor Rating System,î is a first attempt at defining the steps necessary to estimate the total emissions from a facility and estimate the odor impact on the surrounding community. This conceptual model is based on information gathered in this project and some brainstorming on how this information could be applied to actual situations. This model will be developed more fully with the current odor rating project funded through the Minnesota State Legislature.

STEP 1. Determine, from Table 1 and Table 2, the Odor Reference Number (ORN) for each odor source. (These odor reference numbers would have been determined through a series of odor measurements at existing facilities.) The odor reference number is a value based on odor units and odor intensity.

Odor Source	Odor Reference Number	Area	Maximum Ventilation Rate	Management Factor	Other Factor
source #1	25
source #2	50
source #3	75

STEP 2. Determine the area in square feet or maximum ventilation rate in cubic feet per minute for each odor source on the site. Area measurements must be made on open manure storages, open feedlots and naturally ventilated buildings. (Area determinations should be made on naturally ventilated, deep pit barns.) The maximum ventilation rates should be determined for each fan. These measurements should be summed for wall fans and pit fans.

Odor Source	Odor Reference Number	Area (sq ft)	Maximum Ventilation Rate (cfm)	Management Factor	Other Factor
source #1	25	45,000
source #2	50		28,000
source #3	75		20,000

STEP 3. Determine a level of manure management between one and five, (one = average management, five = bad management). (It is unclear at this time how much impact this number would have on the estimated total emissions from the farm.) Factors to consider may be spilled feed, saturated bedding, manure buildup in corners, etc.

Odor Source	Odor Reference Number (ORN)	Area (sq ft) (A)	Maximum Ventilation Rate (cfm) (MVR)	Management Factor (MF)	Odor Control Factor (OCF)
source #1	25	45,000		1
source #2	50		28,000	1
source #3	75		20,000	2

Step 4. Determine the odor control factor for any odor control technologies implemented. These technologies are listed in Table 3. If no odor control technologies are implemented put, a 1 in the column.

Odor Source	Odor Reference Number (ORN)	Area (sq ft) (A)	Maximum Ventilation Rate (cfm) (MVR)	Management Factor (MF)	Odor Control Factor (OCF)
source #1	25	45,000		1	1
source #2	50		28,000	1	0.5
source #3	75		20,000	2	1

STEP 5. Determine the odor emission factor for each odor source by using the following equation. Note surface emissions use a different equation than mechanically ventilated odor sources.

Odor Emission Factor (OEF)= (ORN x A x MF x OCF) / 1000

source #1 = (25 x 45,000 x 1) / 1000 = 1125

Odor emission factor (OEF)= (ORN x MVR x MF x OCF) / 1000

source #2 = (50 x 28,000 x 1 x 0.5) /1000 = 700

source #3 = (75 x 20,000 x 2 x 1) /1000 = 3000

STEP 6. Determine the minimum width and length that encompasses all odor sources. It is anticipated that the impact on the community will be related to the width of the odor plume. However, it is also understood that a narrower plume with the same odor total emissions may be more concentrated and therefore move farther from the source. Therefore, this is one of the other ìmissing piecesî to be filled in with further study.

Table 1. Estimated Odor Reference Number (ORN) for Livestock Facilities

(Note: Odor Reference Numbers will be determined through extensive on farm

evaluation of existing systems.)

Type of Facility	Technology	Odor Number
Nursery Barn	Deep Pitted, MV	0-100
	Pull Plug, MV	0-100
Farrowing	Deep Pitted, MV	0-100
	Pull Plug, MV	0-100
Finishing	Deep Pitted MV	0-100
	Deep Pitted, NV	0-100
	Hoop House, NV	0-100
Dairy Freestall	Sand Bedding, scrape, NV	0-100
	Mattress, scrape, NV	0-100
	Mattress, flush, NV	0-100
etc.
etc.

MV= mechanically ventilated

NV= naturally ventilated

Table 2. Estimated Odor Reference Number (ORN) for Manure Storages

(Note: Odor Reference Numbers will be determined through extensive on farm

evaluation of existing systems.)

Type of Livestock	Manure Storage	Odor Number
Nursery	Earthen Basin	0-100
	Above ground tank	0-100
	In ground tank	0-100
	Lagoon	0-100
Farrowing	Earthen Basin	0-100
	Above ground tank	0-100
	In ground tank	0-100
	Lagoon	0-100
Finishing	Earthen Basin	0-100
	Above ground tank	0-100
	In ground tank	0-100
	Lagoon	0-100
Dairy	Earthen Basin, crusted	0-100
	Earthen basin, not crusted	0-100
	Above ground tank	0-100
	In ground tank	0-100
	Lagoon	0-100
etc.
etc.

Table 3. Estimated Odor Control Factor (OCF)

(Note: Odor Control Factor will be determined by extensive control and farm

measurements of odor control technologies.)

Odor Source	Odor Control Technology	Odor Reduction (0-1)
Manure Storages	covers	0-1
	aeration	0-1
	solid separation	0-1
	pit additives	0-1
	ì	ì
	ì	ì
Buildings	biofilters	0-1
	spraying oil	0-1
	feed additives	0-1
	ì	ì
	ì	ì

Figure 7. Odor Number vs. Distance to Odor Recognition

(NOTE: Different lines represent some percent of the time that odors are recognized at various climatic conditions. Odor dispersion, hence odor recognition at some distance from the source, is dependent on climatic conditions. It is anticipated that there will be approximately four to six different curves on the graph, each of them representing a unique climatic condition. A frequency of an odor event at specific distances and at specific odor emission factors could then be determined by reviewing the frequency of stability classes for a particular region.)