Odor and Odorous Chemical Emissions from Animal Buildings: Part 2. Odor Emissions

This study was an add-on project to the National Air Emissions Monitoring Study (NAEMS) and focused on comprehensive measurement of odor emissions considering variations in seasons, animal types, and olfactometry laboratories. Odor emissions from four of 14 NAEMS sites with nine barns/rooms (two dairy barns at the WI5B and IN5B sites, two pig finishing rooms at IN3B, and two sow gestation barns and a farrowing room at the IA4B site) were measured during four 13-week cycles. Odor emissions were reported per barn area (OU h-1 m-2), head (OU h-1 head-1), and animal unit (OU h-1 AU-1). The highest overall odor emission rates were measured in summer (1.2 × 105 OU h-1 m-2, 3.5 × 105 OU h-1 head-1, and 6.2 × 105 OU h-1 AU-1), and the lowest rates were measured in winter (2.5 × 104 OU h-1 m-2, 9.1 × 104 OU h-1 head-1, and 1.5 × 105 OU h-1 AU-1). The highest ambient odor concentrations and barn odor emissions were measured from the sow gestation barns of the IA4B site, which had unusually high H2S concentrations. The most intense odor and the least pleasant odor were also measured at this site. The overall odor emission rates of the pig finishing rooms at IN3B were lower than the emission rates of the IA4B sow gestation barns. The lowest overall barn odor emission rates were measured at the IN5B dairy barns. However, the lowest ambient odor concentrations were measured at the ventilation inlets of the WI5B dairy barns

Odor and Odorous Chemical Emissions from Animal Buildings: Part 5—Correlations between Odor Intensities and Chemical Concentrations (gc-ms/o)

Simultaneous chemical and sensory analysis based on gas chromatography-mass spectrometry-olfactometry (GC-MS-O) of air samples from livestock operations is a very useful approach for quantification of target odorous gases and also for ranking of odorous compounds. This information can help link specific gases to odor, that can assist in solving farm odor problems and in evaluating of odor mitigation technologies. In this study, we applied the fundamental Weber-Fechner law to correlate the odor intensity and odorous chemical concentration for 15 individual target compounds (from GC-MS-O) for the gas samples collected from four livestock facilities (dairy barns in Wisconsin and Indiana and swine barns in Iowa and Indiana) over a one year period. The results showed that most of the correlations between odor intensities and chemical concentrations for the 15 odorous VOCs sampled fit well with the Weber-Fechner law and had correlation coefficient (R2) greater than 0.65, with R2s of 0.84, 0.83, and 0.82 for 4-methylphenol, 3-methylbutanoic acid, and 3-methylindole, respectively. The odorous compounds with higher mean odor activity value (OAV) values fit better with the Weber-Fechner law whereas the odorous compounds with lower mean OAV values resulted in relatively poor R2 values to the relatively large variations for odor intensities obtained from GC-MS/O for these compounds with low concentrations. The correlations for odorous compounds between odor intensities and chemical concentrations for swine sites were much better than that for dairy sites. R2s for eight out of fifteen compounds for the two swine sites were greater than 0.60 whereas only one R2 (butyric acid) was greater than 0.60 for two dairy sites

Odor and Odorous Chemical Emissions from Animal Buildings: Part 5. Simultaneous Chemical and Sensory Analysis with Gas Chromatography-Mass Spectrometry-Olfactometry

Simultaneous chemical and sensory analyses using gas chromatography-mass spectrometry-olfactometry (GC-MS-O) for air samples collected at barn exhaust fans were used for quantification and ranking of the odor impacts of target odorous gases. Fifteen target odorous VOCs (odorants) were selected. Air samples were collected at dairy barns in Wisconsin and Indiana and at swine barns in Iowa and Indiana over a one-year period. The livestock facilities with these barns participated in the National Air Emissions Monitoring Study (NAEMS). Gas concentrations, odor character and intensity, hedonic tone, and odor peak area of the target odorants in air samples were measured simultaneously with GC-MS-O. The four individual odorants emitted from both dairy and swine sites with the largest odor impacts (measured as odor activity value, OAV) were 4-methyl phenol, butanoic acid, 3-methyl butanoic acid, and indole. The total odor (limited to target VOCs and referred to as the measured concentrations, odor intensities, and OAVs) emitted from the swine sites was generally greater than that from the dairy sites. The Weber-Fechner law was used to correlate measured odor intensities with chemical concentrations. Odorants with higher mean OAV followed the Weber-Fechner law much better than odorants with lower mean OAV. The correlations between odor intensities and chemical concentrations were much better for the swine sites (typically p \u3c 0.05 and R2 = 0.16 to 0.51) than for the dairy sites (typically p \u3e 0.05 and R2 \u3c 0.15). Linking specific gases to odor could assist in the development and evaluation of odor mitigation technologies for solving livestock odor nuisance problems

Odor and Odorous Chemical Emissions from Animal Buildings: Part 1. Project Overview, Collection Methods, and Quality Control

Livestock facilities have historically generated public concerns due to their emissions of odorous air and various chemical pollutants. Odor emission factors and identification of principal odorous chemicals are needed to better understand the problem. Applications of odor emission factors include inputs to odor setback models, while chemical emission factors may be compared with regulation thresholds as a means of demonstrating potential health impacts. A companion study of the National Air Emissions Monitoring Study (NAEMS) included measurements necessary for establishing odor and chemical emission factors for confined animal feeding operations. This additional investigation was conducted by the University of Minnesota, Iowa State University, West Texas A&M Agri-Life Center, and Purdue University. The objectives were to (1) determine odor emission rates across swine and dairy facilities and seasons using common protocols and standardized olfactometry methods, (2) develop a chemical library of the most significant odorants, and (3) correlate the chemical library with the olfactometry results. This document describes the sampling and quality assurance methods used in the measurement and evaluation of odor and chemical samples collected at two freestall dairy farms, one sow (gestation/farrowing) facility, and one finishing pig site. Odor samples were collected in Tedlar bags and chemical samples were collected in sorbent tubes at barn inlet and exhaust locations using the NAEMS multiple-location gas sampling systems. Quality assurance protocols included interlaboratory comparison tests, which were evaluated to identify variations between olfactometry labs. While differences were observed, the variations among the labs and samples appeared random and the collected odor data were considered reliable at a 0.5% level of statistical significance. Overall, the study took advantage of groundbreaking opportunities to collect and associate simultaneous odor and chemical information from swine and dairy buildings while maintaining accordance with standard methods and comparability across laboratories

Characterization and Quantification of Livestock Odorants using Sorbent Tube Sampling and Thermal Desorption coupled with Multidimensional Gas Chromatography–Mass Spectrometry–Olfactometry (TD-MDGC-MS-O)

Characterization and quantification of livestock odorants is one of the most challenging analytical tasks because odor-causing gases are very reactive, polar and often present at very low concentrations in a complex matrix of less important or irrelevant gases. The objectives of this research is to develop a novel analytical method for characterization of the livestock odorants including their odor character, odor intensity, and hedonic tone and further quantitative analysis of the key odorants responsible for livestock odor emissions. Sorbent tubes packed with Tenax TA were employed for sampling. The automated one-step thermal desorption coupled with multidimensional gas chromatography-mass spectrometry-olfactometry system was developed for simultaneous chemical and odor analysis. Fifteen odorants identified from different livestock species operations are quantified. In addition, odor character, odor intensity and hedonic tone associated with each of the target compounds are also analyzed. The method developed in this research is being used on a multistate, multispecies project focused on quantifying odor and chemical analysis of odor

Air Quality Modeling in Support of the Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS)

A major challenge in traffic-related air pollution exposure studies is the lack of information regarding pollutant exposure characterization. Air quality modeling can provide spatially and temporally varying exposure estimates for examining relationships between traffic-related air pollutants and adverse health outcomes. A hybrid air quality modeling approach was used to estimate exposure to traffic-related air pollutants in support of the Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS) conducted in Detroit (Michigan, USA). Model-based exposure metrics, associated with local variations of emissions and meteorology, were estimated using a combination of the American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) and Research LINE-source dispersion model for near-surface releases (RLINE) dispersion models, local emission source information from the National Emissions Inventory, detailed road network locations and traffic activity, and meteorological data from the Detroit City Airport. The regional background contribution was estimated using a combination of the Community Multi-scale Air Quality (CMAQ) and the Space-Time Ordinary Kriging (STOK) models. To capture the near-road pollutant gradients, refined “mini-grids” of model receptors were placed around participant homes. Exposure metrics for CO, NOx, PM2.5 and its components (elemental and organic carbon) were predicted at each home location for multiple time periods including daily and rush hours. The exposure metrics were evaluated for their ability to characterize the spatial and temporal variations of multiple ambient air pollutants compared to measurements across the study area

Development of a multiple-source odor setback model for livestock production systems

Odors emitted from livestock production systems have been the source of many nuisance complaints and lawsuits towards the agricultural community. These circumstances have resulted in a number of local guidelines for the siting of livestock facilities amongst neighboring residences and community centers, also known as setback guidelines. There exist no country-wide standards for these setback distances, and in some cases local economic growth is hindered due to larger-than-necessary setbacks being enforced. Hence, a significant need for scientific models to determine setback distances that are fair to both livestock producers and neighbors is presented. The purpose of this project is to expand upon the Generation-1 Purdue Odor Setback Model (Lim, et al., 2000) and recommend parametric factor improvement. Odor samples were collected and analyzed via the internationally-standardized forced choice olfactometry method to determine the odor emission rates for dairy lactation barns. Reconstruction of the Purdue Model to an Excel platform allowed for parameterization of up to 10 individual odor sources within a farmstead, each with their own odor emission and abatement characteristics. The resulting individual-source and overall-site setback distances are generated considering the position of each source within the farmstead. Additional odor concentration data were taken downwind of an Indiana-representative dairy and swine facility to test the Model\u27s setback recommendations. It was determined that while the Model predicts favorably compared to raw data, further updates are needed for the factors representing directional wind frequency, effects of topography, and effects of the odor sensitivity of different receptor groups (aka exposures). A new method for determining the applied factor for the directional wind frequency is presented, along with recommendations for topography and exposure factor improvement. Finally, an investigation was made into future odor application of the Gaussian dispersion theory commonly applied to atmospheric pollutants. While the Gaussian method has been historically disregarded for odor-uses, it is presented here that new plume-spread coefficients can be derived from downwind odor concentration data, the Gaussian method can be applied, and adequate estimation of odor setback distances is possible

Odor and Odorous Chemical Emissions from Animal Buildings: Part 4. Correlations Between Sensory and Chemical Measurements

This study supplemented the National Air Emissions Monitoring Study (NAEMS) with one year of comprehensive measurements of odor emission at five swine and four dairy buildings. The measurements included both standard human sensory measurements using dynamic forced-choice olfactometry and chemical analysis of the odorous compounds using gas chromatography-mass spectrometry. In this article, multilinear regressions between odor and gas concentrations (a total of 20 compounds including H2S, NH3, and VOCs) were investigated. Regressions between odor and gas emission rates were also tested. It was found that gas concentrations, rather than emission rates, should be used to develop multilinear regression models. For the dairy sites, H2S, NH3, acetic acid, propanoic acid, 2-methyl propanoic, and pentanoic acids were observed to be the compounds with the most significant effect on sensory odor. For the swine sites, in addition to these gases, higher molecular weight compounds such as phenol, 4-methyl phenol, 4-ethyl phenol, and 1H-indole were also observed to be significant predictors of sensory odor. When all VOCs were excluded from the model, significant correlations between odor and H2S and NH3 concentrations were still observed. Although these coefficients of determination were lower when only H2S and NH3 were used, they can be used to predict odor variability by up to 83% when VOC data are unavailable.This article is from Transactions of the ASABE 55, no. 6 (2012): 2347–2356.</p

Odor and Odorous Chemical Emissions from Animal Buildings: Part 2. Odor Emissions

This study was an add-on project to the National Air Emissions Monitoring Study (NAEMS) and focused on comprehensive measurement of odor emissions considering variations in seasons, animal types, and olfactometry laboratories. Odor emissions from four of 14 NAEMS sites with nine barns/rooms (two dairy barns at the WI5B and IN5B sites, two pig finishing rooms at IN3B, and two sow gestation barns and a farrowing room at the IA4B site) were measured during four 13-week cycles. Odor emissions were reported per barn area (OU h-1 m-2), head (OU h-1 head-1), and animal unit (OU h-1 AU-1). The highest overall odor emission rates were measured in summer (1.2 × 105 OU h-1 m-2, 3.5 × 105 OU h-1 head-1, and 6.2 × 105 OU h-1 AU-1), and the lowest rates were measured in winter (2.5 × 104 OU h-1 m-2, 9.1 × 104 OU h-1 head-1, and 1.5 × 105 OU h-1 AU-1). The highest ambient odor concentrations and barn odor emissions were measured from the sow gestation barns of the IA4B site, which had unusually high H2S concentrations. The most intense odor and the least pleasant odor were also measured at this site. The overall odor emission rates of the pig finishing rooms at IN3B were lower than the emission rates of the IA4B sow gestation barns. The lowest overall barn odor emission rates were measured at the IN5B dairy barns. However, the lowest ambient odor concentrations were measured at the ventilation inlets of the WI5B dairy barns.This article is from Transactions of the ASABE 55, no. 6 (2012): 2335–2345.</p

Odor and Odorous Chemical Emissions from Animal Buildings: Part 5—Correlations between Odor Intensities and Chemical Concentrations (gc-ms/o)

Simultaneous chemical and sensory analysis based on gas chromatography-mass spectrometry-olfactometry (GC-MS-O) of air samples from livestock operations is a very useful approach for quantification of target odorous gases and also for ranking of odorous compounds. This information can help link specific gases to odor, that can assist in solving farm odor problems and in evaluating of odor mitigation technologies. In this study, we applied the fundamental Weber-Fechner law to correlate the odor intensity and odorous chemical concentration for 15 individual target compounds (from GC-MS-O) for the gas samples collected from four livestock facilities (dairy barns in Wisconsin and Indiana and swine barns in Iowa and Indiana) over a one year period. The results showed that most of the correlations between odor intensities and chemical concentrations for the 15 odorous VOCs sampled fit well with the Weber-Fechner law and had correlation coefficient (R2) greater than 0.65, with R2s of 0.84, 0.83, and 0.82 for 4-methylphenol, 3-methylbutanoic acid, and 3-methylindole, respectively. The odorous compounds with higher mean odor activity value (OAV) values fit better with the Weber-Fechner law whereas the odorous compounds with lower mean OAV values resulted in relatively poor R2 values to the relatively large variations for odor intensities obtained from GC-MS/O for these compounds with low concentrations. The correlations for odorous compounds between odor intensities and chemical concentrations for swine sites were much better than that for dairy sites. R2s for eight out of fifteen compounds for the two swine sites were greater than 0.60 whereas only one R2 (butyric acid) was greater than 0.60 for two dairy sites.This proceeding is from International Symposium on Air Quality & Manure Management for Agriculture CD-Rom Proceedings (13–16 September 2010, Double Tree Hotel, Dallas Texas) St. Joseph, Michigan: ASABE, 13 September 2010. ASAE Pub #711P0510cd.</p