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a USDA-ARS, National Swine Research Center, Ames, IA 50011
b Dep. of Microbiology, Iowa State University, Ames, IA 50011
c Dep. of Psychology, Iowa State University, Ames, IA 50011
d USDA-ARS, National Soil Tilth Lab., Ames, IA 50011
Corresponding author (zahn{at}nsric.ars.usda.gov)
Received for publication March 16, 2000.
| ABSTRACT |
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Abbreviations: VOC, volatile organic compound CAFO, concentrated animal feeding operation
| INTRODUCTION |
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Efforts to remediate odor from swine production facilities have been impeded by the lack of instruments capable of high-throughput, objective odor measurements. The desire to develop high-throughput, inexpensive methods of odor quantification has been the impetus for several recent investigations that have focused on defining relationships between gas concentration of odorants emitted from animal manure and odor intensity measured by olfactory methods (Hobbs et al., 1995; Jacobson et al., 1997a,b; Obrock-Hegel, 1997; Pain et al., 1990; Zahn et al., 2001). Obrock-Hegel (1997) found that nutritional manipulation of amino acid intake reduced NH3, cresols, and indoles measured in air samples from production environments. However, no reduction in odor concentration was observed between control and treatment samples. Schulte et al. (1985) and Hobbs et al. (1995) linked high levels of NH3 to odor. Unfortunately, the latter authors noted that the relationship between NH3 and odor could not be universally applied to all farms, especially when they differed in the type of manure management system used. The use of H2S as a surrogate of livestock waste odor has also proven to be a formidable challenge. Jacobson et al. (1997b) evaluated odor and H2S concentration in air from approximately 60 different pig, dairy, beef, and poultry manure storage units on farms in Minnesota. Low correlation was observed between H2S and odor concentration for manure storages based on a species comparison and for production systems grouped according to manure management system type (pit, basin, and lagoon). The study further suggested the possibility that chemical odorants other than H2S (i.e., VOCs) were responsible for swine odor. In support of these findings, Powers et al. (1999) recently demonstrated that solution-phase concentrations of several VOCs present in anaerobic digester effluent were positively correlated with odor intensity. However, the solution-phase concentration of VOCs did not predict odor intensities well enough to suggest that human panels should be eliminated. Data quality in the latter study were probably adversely influenced by the fact that odor responses were correlated to solution-phase concentrations of odorants, rather than to direct measurements of odorants present in air samples presented to panelists. Previous studies have established the importance of using air-phase concentrations of odorants when performing correlations to odor concentration, since VOC volatilization rates are highly matrix dependent (Hobbs et al., 1995; MacIntyre et al., 1995; Zahn et al., 1997). Problems associated with matrix-dependent odorant volatilization were recently overcome by performing direct multicomponent analyses of air samples that were simultaneously evaluated for odor intensity by human panels (Zahn et al., 2001). By using this sampling approach, it was shown that odor intensity from 29 swine production facilities correlated strongly
to the concentration of 19 volatile organic compounds present in ambient air samples. While this study provided evidence that direct multicomponent analysis of VOCs may be useful in monitoring odor from swine production, several important details concerning olfactory properties of key VOC odorants and the behavior of these compounds in complex mixtures were not addressed in this study.
The aims of this study are similar to that of Zahn et al. (2001) in our desire to develop an instrument-based odor quantification method for CAFOs that is based on the air concentration of specific odorants. In addition to this aim, there is currently a need to define olfactory properties of odorant reference standards that were previously described by Zahn et al. (2001). The objectives of this study were to (i) validate the selection of odorants present in synthetic swine odor by comparing the chemical profile of the synthetic mixture with the chemical profile of stored swine manure samples; (ii) construct and validate an emission chamber for reproducible delivery of an air stream containing the indicator odorants to an absorbent tube or to a nose cone for chemical and olfactory evaluation, respectively; (iii) define organoleptic properties of the odorant mixture at different delivery concentrations; and (iv) define potential synergistic and antagonistic olfactory activities for this group of odorants.
| MATERIALS AND METHODS |
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The reference stimulus solution was produced by diluting synthetic swine odor solution Z2 in an equal volume of ddH2O. Odorant solutions were formulated within 1 h of human evaluation to reduce variation due to loss of the odorants through volatilization or chemical decomposition, and were maintained at 21.0 ± 1.1°C during all procedures. Two series of experimental stimuli were formulated for olfactory studies. First, the effect of odorant concentration on olfactory responses was evaluated by preparing by six dilutions (83, 67, 50, 33, 17, and 1%) of synthetic swine odor solution Z2 in ddH2O. Second, the effect of synergistic or antagonistic interactions between odorants was investigated by doubling the concentration of individual odorants present in synthetic swine odor Z2, while maintaining the remaining 18 odorants at concentrations equivalent to the reference stimulus solution. The latter odorant solutions were diluted over the same concentration range (100, 83, 67, 50, 33, 17, and 1%) that was used in the first series of experiments.
The dilutions used in this study were assigned empirically based on the olfactory responses of panelists to the various dilutions of the synthetic swine odor solution. Physiological responses ranged from barely detectable to an overwhelming or unbearable olfactory response. There were five dilutions equally scattered between the two stimuli to provide data needed for fitting of olfactory response models. Statistical analysis of data shows that the dilutions employed in these experiments fitted well to established olfactory response models.
Emission Chamber Design and Operational Parameters
Olfactory and chemical quantification of VOC odorants was performed on the gas stream emitted from the dynamic emission chamber shown in Fig. 1
. Compressed air from a cylinder (ultra-high purity) was passed over activated carbon (#24,226-8; Aldrich Chemical Co.) and then was introduced to the dynamic emission chamber at a height of 10 cm above the odorant solution. Olfactory and chemical controls performed on chambers containing ddH2O showed that the emission chamber, flow path, and air source had no detectable odor or VOCs in the absence of odorant solutions. The flow of clean air was maintained at 1000 mL min-1 (±1.2%) using a thermal mass flow controller (Series 810, Sierra Instruments, Monterey, CA). The flow of air through the chamber proceeded downward toward the surface of the odorant solution and then exited the emission chamber through a glass transfer tube that was positioned 1 cm from the surface of the odorant solution. The odorant-containg gas was forced up the transfer tube to a nose cone and sampling tee for olfactory and chemical analyses, respectively. The sampling tee was positioned at the base of the nose cone to eliminate potential discrepancies between olfactory and chemical measurements due to non-equivalent flow paths.
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. The diameter of the emission chamber was 3.50 cm and the active surface area for the odorant solution was 9.62 cm2. Upon startup of the dynamic emission chamber, the initial 5 min (
5 L of odorant-containing gas) of operation were dedicated to equilibrating the flow path to odorants present in the gas stream. During this equilibration period the exhaust fan was operated to remove odorants from the cabinet. After the equilibration period, the fan was shut off and the air stream was sampled by human panelists or by chemical methods. Chemical and human olfactory analyses were conducted separately in order to minimize potential interferences with human olfactory evaluations. Olfactory evaluations of odorant air streams were conducted using full air flow through the dynamic emission chamber (1000 mL min-1). The exhaust fan was operated for 1 min after each evaluation to remove residual odorants from the sampling area. Air temperature and relative humidity in the evaluation area were maintained at 21.0 ± 1.1°C and 62 ± 7% RH, respectively. Comparisons between the reference stimulus and experimental stimuli were performed by placing a second dynamic emission chamber in the evaluation cabinet at a distance of 0.35 m from the reference stimulus. The second chamber is referred to as the experimental stimulus. Volatile organic compounds in the air stream from the emission chamber were trapped on adsorbent resins at the sampling tee using a flow rate of 950 mL min-1. The remaining balance of the gas flow (50 mL min-1) was expelled through the unoccupied nose cone. The adsorbent resins consisted of a multibed combination of Tenax TA and Carboxen-569 (Supelco, Bellefonte, PA) as previously described by Zahn et al. (1997). Compounds captured on the adsorbent tubes were transferred to a gas chromatograph by thermal desorption, separated on a HewlettPackard (Palo Alto, CA) Innowax cross-lined polyethylene glycol capillary column (30 m x 0.25 mm), and detected by flame ionization or by a mass selective detector as previously described by Zahn et al. (1997).
Scale Development and Sensory Panel Design
Development of a scale to measure the effects of odorant concentration was completed using Steven's magnitude estimation technique with 14 human panelists (Stevens, 1957, 1961, 1962). Subjects were presented with an odorant air stream from an emission chamber containing the reference stimulus solution and were instructed that the stimulus had an intensity value of 100 (arbitrary) odor intensity units. Panelists were then instructed to sample an air stream from a second chamber (experimental sample) and to score the intensity of the odor relative to the reference stimulus. For example, if the subject perceived that the intensity of an experimental sample was half that of the reference stimulus, then a value of 50 was reported for the experimental sample. If the subject perceived that the odor was 75% more intense than the reference stimulus then a value of 175 was reported for the experimental sample. Odor intensity scores were reported between a range of 0 and 200 relative odor intensity units.
Magnitude estimation studies have shown that the perceived magnitude of a stimulus is a power function of the intensity of the stimulus (Stevens, 1957, 1961, 1962). The mathematical relationship between perceived magnitude and physical intensity of the stimulus (Steven's Law) is:
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The magnitude estimation technique was used with a human panel of 14 subjects. The panel ranged in age from 18 to 40 yr and was composed of an equal number of male and female subjects to minimize gender bias. In the first stage of the study, subjects were presented with synthetic swine odor solution Z2 and five dilutions of the solution (100, 83, 67, 50, 33, 17, and 1%) as described in the Composition of Odorant Solutions section. The solutions were placed in emission chambers with encrypted labels and then were fixed in the experimental stimulus position for evaluation. Individuals on the panel were instructed to score the physical intensity of each experimental stimulus relative to the reference stimulus. In subsequent stages of the study, the panel was presented with nine different experimental stimuli, differing only in the concentration of a single odorant. The concentration of a single odorant in the solution was doubled from the original concentration value, while other odorants (the remaining 18) present in the solution were unchanged. Solutions were again diluted over a concentration range from 100 to 1%, and then placed in emission chambers for presentation to the panel. The following nine VOCs were evaluated for potential synergisticantagonistic activity: acetic acid, isobutyric acid, butyric acid, valeric acid, heptanoic acid, phenol, 4-methyl phenol, 4-ethyl phenol, and 3-methyl indole. These nine VOCs were selected based on their universal presence in air samples from swine production facilities and/or due to their low olfactory detection thresholds.
The order in which the first 12 subjects sampled the odorants was balanced using a Latin Square to reduce sampling bias. Panelists evaluated each experimental stimulus twice during individual sessions. Each subject would compare the experimental stimulus with the reference stimulus in one serial order, and then would be presented the same samples for a second trial in a different serial order. Thus, the effects of the presentation order could be randomized in order to reduce sampling bias. Panelists were allowed to evaluate odor stimuli as many times as they wished before reporting the stimulus score to the panel operator. Individual sampling sessions for the duplicate analysis of six experimental stimuli were completed in 15 min for individual panel members and were performed on two separate days during the same week.
| RESULTS AND DISCUSSION |
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In addition to the 19 compounds in synthetic swine odor Z2, a number of other odiferous compounds, such as amine and sulfide-containing compounds, have been correlated with swine manure odor based on solution-phase measurements (Yasuhara et al., 1984). However, with the exception of hydrogen sulfide, organic sulfide and organic amine-containing compounds were not routinely detected in emission plumes from swine production facilities (Zahn et al., 1997, 2001). It has been well established that sulfides and amines are inherently unstable in oxidized atmospheres due to their high chemical reactivity. Sulfides are weak monoprotic and polyprotic (H2S) acids that are highly reactive under aerobic conditions and neutral pH. Ammonia and amines, on the other hand, are weak bases that play a major role in neutralization of sulfur dioxide and nitrogen oxides in the atmosphere (Harper and Sharpe, 1997). Acidbase neutralization of air pollutants has been shown to produce salts that contribute to chemically generated particulate matter in the atmosphere. While there is currently little direct evidence to explain the absence of these compounds in emission plumes, the presence of high concentrations of disulfides such as dimethyl disulfide (the oxidation product of methyl mercaptan) and dimethyl trisulfide (the oxidation product of hydrogen sulfide and methyl mercaptan) provides indirect evidence that free sulfides are readily oxidized in the atmosphere or during sample collection and analysis procedures. In contrast to the labile nature of sulfide and amine-containing compounds, VOCs in synthetic swine odor Z2 exhibit a higher level of chemical stability. Additionally, these compounds were observed to exhibit high atmospheric transport coefficients that permitted long-range atmospheric transport under unstable atmospheric conditions (Zahn et al., 1997). These findings indicate that the compounds present in the synthetic swine odor Z2 represent ideal odorants for use in swine odor research.
Operational Parameters of the Dynamic Emission Chamber
The ability to maintain a constant emission rate of VOCs at the olfactory sampling port during the course of the olfactory evaluation period was considered a critical element in the success of the study. Therefore, preliminary investigations were conducted on synthetic swine odor solutions that were placed in the dynamic emission chamber to determine: (i) if the emission rate of VOCs release from the dynamic emission chamber was constant over a typical olfactory sampling period and (ii) if emission rate of VOCs was proportional to the concentration of VOCs present in the liquid phase of the emission source. The emission rate of 19 VOCs present in synthetic swine odor Z2 was measured by trapping the airborne analytes on adsorption tubes over time intervals and by determining the change in concentration of VOCs present in the liquid over the same time period. Adsorption samples were collected over a 3-h period in 0.5-h intervals from air emitted from the dynamic emission chamber. The cumulative emission rates of acetic acid, 4-methyl phenol, and 4-ethyl phenol over the 3-h sampling period are shown in Fig. 3
. The linear shape of the fitted line (r2 > 0.97) shows that the emission rate for each VOC remained nearly constant during the sampling period. Analysis of the concentration of the other 16 compounds in air samples showed that the emission rate of these compounds also remained nearly constant over the 3-h collection period. The concentration of VOCs present in liquid phase of synthetic swine odor solution Z2 was reduced between 0.05 to 4.0% over the 3-h collection period. Compounds such as dimethyl disulfide that had a relatively low source concentration and a high Henry's law constant showed the greatest change in solution concentration over the sampling period (4.0%), while compounds with lower volatility (benzyl alcohol, 0.1%) or high source concentration (acetic acid, 0.05%), exhibited less change in solution concentration over the sampling period. Comparison of the total amount of VOCs recovered by adsorption tubes with the losses of analytes measured in the solution phase showed that between 94 and 99% of the VOCs emitted from the solution could be recovered and quantified by the thermal desorptiongas chromatography method. The mean emission rate values for four independent emission rate experiments conducted using the 19 odorant compounds are shown in Table 3.
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Also of interest were the extremely high values of r2 that were obtained for analysis of variance. Analysis of variance showed that Stevens' Law could explain, on average, 97% of the variation in the subjects' estimates of odor intensity. This result provides evidence that the VOC delivery system produces highly reproducible olfactory stimuli. A Within Subjects Factorial Analysis of Variance (ANOVA) was used to determine the effects of odorant concentration on the mean perceived odor intensity scores. Two factors were included in the ANOVA: (i) the effect of odorant concentration on olfactory responses over seven odorant concentrations (100, 83, 67, 50, 33, 17, and 1%), and (ii) the effect of synergistic or antagonistic interactions between nine odorants present in synthetic swine odor Z2. This analysis yielded a reliable main effect due to concentration of odorants
, a reliable main effect due to synergisticantagonistic interactions between odorants
, and a reliable interaction between concentration and synergisticantagonistic interactions between odorants
. Subsequent analysis of the main effects showed that several of the chemical mixtures produced reliably greater mean odor intensity ratings than others. The mean rating for each of the solutions and standard error are shown in Table 5.
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The concentrations of odorant solutions evaluated in this study were found to elicit a strong effect on mean perceived odor intensity scores. The value of Fisher's LSD statistic for concentration data was 9.59 odor intensity units (Table 6). As such, the 1% concentration produced statistically lower mean perceived odor intensity scores than the other five concentrations evaluated. The 17% concentration produced odor intensity scores that were statistically lower than the 34, 67, 83, and 100% concentrations. This pattern of statistical significance was observed for all subsequent odorant concentrations. Thus, the human panel was clearly sensitive to changes in concentration across all odorant concentrations used in the study.
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observed between predicted and authentic values for mean perceived odor intensity scores. The quality of the model for odorant concentration data sets was further corroborated by the high level of statistical significance for the analysis
. Table 7 shows the regression coefficients for each of the nine major swine effluent odorants included in the model. Analysis of this table shows that there is a high level of significance for three odorants (p < 0.05) and a lower level of significance for all other terms in the model. The three odorants achieving a high level of significance were acetic acid (p < 0.001), 4-ethyl phenol (p = 0.02), and 3-methyl indole (p = 0.04). This result indicated that the olfactory scaling model could be further simplified by systematically omitting less significant terms from the model. However, cross validation (tests of the model on independent data sets) of simplified versions of the model, created through omission of less significant terms, resulted in models with lower regression coefficients. These results indicated that all of the terms presented in Table 7 contributed to the overall accuracy of the model. The following mathematical representation of parameter estimates from the model includes factors from VOC concentration measurements of odorant solutions evaluated by panelists. These conversion factors are required to convert model input values from units of percent stimulus to µg VOC m-3 of air. A human olfactory response can be predicted for air samples through the concentration of the nine VOCs. The model for swine odor intensity is:
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, and a high level of statistical significance was achieved for this validation
. Future model improvement and validation efforts will focus on expanding the number of target analytes used in the model and on further validation of the model by performing additional VOC and odor intensity measurements at swine production sites.
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A field study by Zahn et al. (2001) reported that odorant concentration of 19 VOCs that were present in odor plumes from swine production facilities could be used to predict odor intensity associated with swine production. Qualitative analyses of VOCs present in air samples from four types of swine manure management systems showed that high odor intensity was associated with relatively intense gas chromatographic profiles; however, these profiles were chemically simplistic in nature when compared with the chromatographic profiles from low-odor lagoon systems that had lower concentration and higher chemical diversity. From these results, it was concluded that chemical concentration, rather than chemical diversity, was the most important factor for predicting odor intensity magnitudes associated with swine production. The results of this study provide additional support for the importance of odorant concentration as a factor in olfactory models. This study has further simplified the list of target VOC odorants from 19 in the earlier study (Zahn et al., 2001) to nine VOC odorants and has shown that synergisms and antagonisms between major odorant compounds do not appear to play a major role in measured odor intensity. This observation is important since the ability to define odorant synergisms and antagonisms has been suggested to be the most significant obstacle in applying chemical methods in odor measurement (Mackie et al., 1998). Data presented in this study provide evidence that the concentration of "specific" nonmethane VOCs that are present in air samples from swine production facilities can be applied to predict the odor intensity associated with swine production systems.
| CONCLUSIONS |
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| ACKNOWLEDGMENTS |
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| NOTES |
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| REFERENCES |
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