Measurement of Ambient Odors Using Dynamic Forced-Choice Triangle Olfactometer

Certain odor control regulations specify use of the Scentometer for ambient odor measurement. This evaluation is usually performed by a single individual who is surrounded by the odorous environment to be measured. A method is desired where an ambient odor sample can be evaluated by an adequate size panel in an odor-free atmosphere. A dynamic forced-choice triangle olfactometer was designed and constructed to measure ambient odors. Teflon bags of 18 liter capacity collect a sample within 2-3 minutes which includes pre-flushing the bag. The sample is evaluated by a dynamic olfactometer equipped with 5 dilution levels (81×, 27×, 9×, 3× and undiluted sample). Three sniffing ports are provided at each dilution level to present dynamically one diluted odor stimulus and two odor-free air blanks. Each panelist is required to indicate which port contains the odor. Evaluation of one sample is routinely completed by a panel of 9 within less than 15 minutes. The odor threshold value (ED₅₀) for the panel is calculated by use of a simple table derived statistically. No significant loss of odor was observed in sampling and in storage of rendering odors up to 48 hours. Bags were reusable after flushing with odor-free air. Reproducibility of log ED₅₀ values by the same panel was within a σ = 0.10 log₁₀. Agreement in evaluating duplicate field samples by two different panels was within the same limits. Under controlled laboratory conditions, a Scentometer reading of D/T = 2 was equivalent to an ED₅₀ = 4.8; and D/T = 7 was equal to ED₅₀ = 9.5.     

1-Butanol removal from a contaminated airstream under continuous and diurnal loading conditions

A polysulfone microporous membrane module was investigated for control of 1-butanol-contaminated gas streams. A diurnal loading condition, using two different butanol concentrations, was used to simulate start-up and stop conditions associated with shift work. The membrane module was also used to remove 1-butanol from air under continuous loading conditions in a bioreactor. The reactors were seeded with a mixed bacterial consortium capable of butanol biodegradation. Biokinetic parameters for butanol utilization were determined for the culture to be a maximum specific utilization rate (k) equal to 4.3 d(-1) and a half saturation constant (Ks) equal to 8.9 mg L(-1). A biofilter running only with diurnal loading conditions giving a "40-hr work-week" had an average 1-butanol removal rate of 29% (111 ppm, 74 gm(-3) hr(-1)) from a 350-ppm influent at the end of an 8-hr operational day. End-of-day removal varied between 4 and 67% during the operational period. With continuous steady-state operation followed by placement on a diurnal loading schedule and influent butanol concentrations increased to 700 ppm, butanol removal averaged 38% (269 ppm, 145 gm-3 hr(-1)). Under continuous loading, steady-state conditions, 1-butanol removal from the airstream was greater than 99% (200 ppm, 73 gm-3 hr(-1)). These results suggest that the bioreactor can be operated on a diurnal schedule or 40-hr week operational schedule without any decline in performance.     

1-Butanol Removal from a Contaminated Airstream under Continuous and Diurnal Loading Conditions

Abstract

A polysulfone microporous membrane module was investigated for control of 1-butanol-contaminated gas streams. A diurnal loading condition, using two different butanol concentrations, was used to simulate startup and stop conditions associated with shift work. The membrane module was also used to remove 1-butanol from air under continuous loading conditions in a bioreactor. The reactors were seeded with a mixed bacterial consortium capable of butanol biodegradation. Biokinetic parameters for butanol utilization were determined for the culture to be a maximum specific utilization rate (k) equal to 4.3 d^?1 and a half saturation constant (K_s) equal to 8.9 mg L^?1. A biofilter running only with diurnal loading conditions giving a “40-hr workweek” had an average 1-butanol removal rate of 29% (111 ppm, 74 gm^?3 hr^?1) from a 350-ppm influent at the end of an 8-hr operational day. End-of-day removal varied between 4 and 67% during the operational period. With continuous steady-state operation followed by placement on a diurnal loading schedule and influent butanol concentrations increased to 700 ppm, butanol removal averaged 38% (269 ppm, 145 gm^?3 hr^?1). Under continuous loading, steady-state conditions, 1-butanol removal from the airstream was greater than 99% (200 ppm, 73 gm^?3 hr^?1). These results suggest that the bioreactor can be operated on a diurnal schedule or 40-hr week operational schedule without any decline in performance.     

Improvement of odor intensity measurement using dynamic olfactometry

Odor intensity reveals a dose-effect relationship between inhaled odor and perceived odor sensation by the receptors, while odor concentration reflects the odor strength at the emission sources. The study reports significant improvements in experimental procedures in establishing the odor concentration-intensity (OCI) relationships using a newly developed digital olfactometer. The improvements in experimental procedures have been made to meet the requirements of both the VDI guideline 3882.1 and the European standard (EN13725). Several areas which could affect the reliability of the results have been identified in some similar studies. The latest digital olfactometer was calibrated automatically to ensure accurate and repeatable dilution ratios. Cross contamination has been eliminated through the instrument design and extensive cleaning procedures, making random presentation possible. Stringent panelist screening and continuous performance monitoring ensures consistent sensitivity of the panel. The extension of odor intensity category to temperature sensation gives a reference to assist judgments of perceived odor sensation. The DynaScent calculation method has simplified odor intensity calculation and can be applied to many odor samples. A total of 38 odor samples from three alumina refinery sites and two sewage treatment plants were collected for analysis. The results have confirmed the efficiency of the olfactometer. Distinct Odor Concentrations (DOCs) were calculated for each sample using both VDI and DynaScent methods. A student t test on two major odor types confirmed that there are no significant differences between two methods. The study has shown the DOCs for refinery odor and wastewater odor are in the range of 3.8-15.4 and 4.2-15.6 odor unit (OU)/m3 respectively. The study demonstrated that the improvements are critical in achieving reliable odor intensity measurement. This can lead to the setup of quantitative odor impact criteria for different industries and sites.     

Improvement of Odor Intensity Measurement Using Dynamic Olfactometry

Abstract

Odor intensity reveals a dose-effect relationship between inhaled odor and perceived odor sensation by the receptors, while odor concentration reflects the odor strength at the emission sources. The study reports significant improvements in experimental procedures in establishing the odor concentration-intensity (OCI) relationships using a newly developed digital olfactometer. The improvements in experimental procedures have been made to meet the requirements of both the VDI guideline 3882.1 and the European standard (EN13725). Several areas which could affect the reliability of the results have been identified in some similar studies. The latest digital olfactometer was calibrated automatically to ensure accurate and repeatable dilution ratios. Cross contamination has been eliminated through the instrument design and extensive cleaning procedures, making random presentation possible. Stringent panelist screening and continuous performance monitoring ensures consistent sensitivity of the panel. The extension of odor intensity category to temperature sensation gives a reference to assist judgments of perceived odor sensation. The Dyna-Scent calculation method has simplified odor intensity calculation and can be applied to many odor samples. A total of 38 odor samples from three alumina refinery sites and two sewage treatment plants were collected for analysis. The results have confirmed the efficiency of the olfactometer. Distinct Odor Concentrations (DOCs) were calculated for each sample using both VDI and DynaScent methods. A student t test on two major odor types confirmed that there are no significant differences between two methods. The study has shown the DOCs for refinery odor and wastewater odor are in the range of 3.8-15.4 and 4.2-15.6 odor unit (OU)/m³ respectively. The study demonstrated that the improvements are critical in achieving reliable odor intensity measurement. This can lead to the setup of quantitative odor impact criteria for different industries and sites.     

Sensory Measurement of Ambient Traffic Odors

Laboratory determinations of ambient traffic odors were conducted in the streets of Stockholm. The measurements were made with a sensory method based on signal detection theory. The occurrence of odors was expressed by an index of detectability (d′) which was compared to the ambient carbon monoxide concentration and the rhythm of the traffic. The results showed that the detection technique employed could well be adjusted to field conditions by use of a mobile odor laboratory. Also, the odor index (d′) was correlated with other parameters in the trafficked environment in the expected way. The odorous emissions are likely to be diluted quickly as distance from the street increases. However, the relevance of the index of detectability as a measure of dose and response needs to be studied further.     

Comparison of models used for the determination of odor thresholds

Several methods of data analysis used for the evaluation of odor detection thresholds have been examined through application to two samples of n-butanol. Panels of seven-ten people, working with a six level, IITRI, ternary forced choice olfactometer, were presented with initial concentrations of 99.5 and 52.1 ppm n-butanol during three trials. The ranking-plotting and ASTM E-679 methods were applied to the evaluation of discrimination-recognition thresholds of the odorous samples. It was found that single evaluations of detection or discrimination-recognition thresholds by either method were always ± 50%of the mean of six trials.The effects of successful guessing on the magnitudes of detection thresholds were examined in terms of a model based on the principle of maximum likelihood estimation of one, two and three trials of panel response. The magnitude of the discrimination threshold obtained by this method always fell between the detection and discrimination-recognition thresholds evaluated by the currently used models. The mean discrimination threshold of n-butanol for six trials was found to be 0.65 ± 0.25 ppm. It appears that the magnitude obtained from one trial with seven panel members would be sufficiently reliable for regulatory purposes when only one field sample is available, since any subsequent trials did not produce threshold values better than ± 40 % of the mean of six tests involving seven and ten panel members exposed to two different initial concentrations.     

Using olfactometry to measure intensity and threshold dilution ratio for evaluating swine odor.

Intensity and threshold dilution ratio are two important indices for odor control of swine buildings. Although odor threshold dilution ratio is a widely used index to describe an odor, it should be related to intensity to be more useful. A method was proposed to measure both indices simultaneously by using a dynamic forced-choice olfactometer. Four air samples were taken from each of four swine rooms including farrowing, finisher, gestation, and nursery. A panel of eight people was used to evaluate odor intensity. Odor threshold dilution ratios were calculated according to the American Society for Testing and Materials (ASTM) Standard Practice E679-91 to be 333, 424, 25, and 221 for samples collected from farrowing, finisher, gestation, and nursery rooms, respectively. After the samples were diluted 14.7 times, the odor intensities were evaluated to be 3.79, 3.46, 0.48, and 4.0 for the above-mentioned rooms, respectively. The data collected were used to develop a mathematical model.     

Filters and Filter Media for the Cement Industry

To correlate the odor strength of natural gas with its sulfur analysis, the recognition odor thresholds of 18 sulfur compounds were determined using an untrained panel of 35 peopie. For each test a series of odor concentrations graduated in increments of 10^0.2 was presented to the panel in random order over a range of concentrations above and below the olfactory thresholds of all panelists. Each odor was tested on at least three different days. Desired odor concentrations were produced by dynamic blending of gaseous mixtures of the odorous compounds with air. All testing was done out-of-doors during clement weather when no ambient odors were apparent. The range of olfactory response was found to be much greater for certain compounds than for others. Branching of the hydro-carbon chain increased odor strength. Certain compounds appeared to evoke anomalous responses.     

Development of the Relationship between Odor Intensity and Threshold Dilution Ratio for Swine Units

ABSTRACT

The following models of odor intensity for swine units were evaluated: the Weber-Fechner law model, the power law model, the Stevens model, and the Beidler model. Data were collected from four swine rooms (farrowing, finisher, gestation, and nursery) and odor threshold dilution ratios were measured by a panel using a dynamic forced-choice olfactometer. Odor intensity scales were determined by eight panelists using a six-point category scale method. A nonlinear parameter estimation method was used to estimate the parameters in each of the models. The widely used Weber-Fechner law did not adequately fit the data of odor intensity and threshold. Both the power law and the Beidler models described the data effectively, but the Beidler model showed the best fit of the data and was used as the model to represent the relationship between odor intensity and threshold dilution ratio for swine buildings.     

Correlating emissions with time and temperature to predict worst-case emissions from open liquid area sources

The two primary factors influencing ambient air pollutant concentrations are emission rate and dispersion rate. Gaussian dispersion modeling studies for odors, and often other air pollutants, vary dispersion rates using hourly meteorological data. However, emission rates are typically held constant, based on one measured value. Using constant emission rates can be especially inaccurate for open liquid area sources, like wastewater treatment plant units, which have greater emissions during warmer weather, when volatilization and biological activity increase. If emission rates for a wastewater odor study are measured on a cooler day and input directly into a dispersion model as constant values, odor impact will likely be underestimated. Unfortunately, because of project schedules, not all emissions sampling from open liquid area sources can be conducted under worst-case summertime conditions. To address this problem, this paper presents a method of varying emission rates based on temperature and time of the day to predict worst-case emissions. Emissions are varied as a linear function of temperature, according to Henry's law, and a tenth order polynomial function of time. Equation coefficients are developed for a specific area source using concentration and temperature measurements, captured over a multiday period using a data-logging monitor. As a test case, time/temperature concentration correlation coefficients were estimated from field measurements of hydrogen sulfide (H2S) at the Rowlett Creek Wastewater Treatment Plant in Garland, TX. The correlations were then used to scale a flux chamber emission rate measurement according to hourly readings of time and temperature, to create an hourly emission rate file for input to the dispersion model ISCST3. ISCST3 was then used to predict hourly atmospheric concentrations of H2S. With emission rates varying hourly, ISCST3 predicted 384 acres of odor impact, compared with 103 acres for constant emissions. Because field sampling had been conducted on relatively cool days (85-90 degrees F), the constant emission rate underestimated odor impact significantly (by 73%).     

Soil Bed System for Control of Rendering Plant Odors

Biofilter technology has been applied recently to treating rendering odors. Soil beds are one class of biofilter but as yet have not been used for this application. Although wet scrubbers have been a traditional method of odor control, their capital and operating costs are impacting more severely. Soil bed systems are less expensive to install and operate.

A soil bed system was installed at a rendering plant in Arizona and has been in operation since September 1983. The soil bed treats 1100 m³/h (650 cfm) of cooker noncondensables with a surface area of 420 m²(4500 ft²). The pressure drop across the soil bed is 5 cm (2 in.) of water. Odor sensory testing with the MTRI forced-choice triangle dynamic olfactometer indicates an odor removal efficiency of 99.9 percent is obtained with the soil bed. Soil bed odor removal efficiency is equivalent to or superior than that for incineration or scrubbing of high intensity odors from the rendering process. Recent experience during this past winter indicates a soil bed is a viable method for operation in a northern climate with severe winter weather conditions. Also, monitoring of the leachate from a soil bed indicated no contamination.     

Odor concentration decay and stability in gas sampling bags

This paper presents results of an experimental study into factors contributing to decay of odor samples during storage, between 4 and 40 hr after sample collection. The odor studied was sampled from a tobacco processing plant as part of collaborative research with a view to establishing a manual outlining methods for odor annoyance management, specifically for the tobacco industry. In August and September 1997, an experimental program was carried out in which two types of tobacco odor were sampled: Burley Toaster and Mix. The dependent variable was odor concentration in the bag, measured by dynamic olfactometry in accordance with the draft Comité Européen de Normalisation (CEN) standard EN13725 "Air Quality-Determination of Odor Concentration by Dynamic Olfactometry." The independent variables were sampling bag material, degree of dilution during sampling, dilution gas used, particle removal during sampling, and age of sample in hours. In the first phase, 94 odor analyses were carried out. In a second test, 32 samples were analyzed for odor concentration. In addition, 16 samples were analyzed using gas chromatography-mass spectrometry (GC-MS). Analysis of the results (analysis of variance) led to the unexpected conclusion that Nalophan film bags performed significantly better than metalized Cali-Bond layered film as a bag material. The odor concentration of samples in Nalophan bags remained relatively stable between 4 and 12 hr after sampling. After 30 hr, decay to about half the initial concentration, as measured at 4 hr, was observed. Particle removal during sampling caused the odor concentration in the bags to be reduced by approximately 20%. For practical reasons, particle removal remains useful, to avoid contamination of equipment. Using air or nitrogen as the neutral gas for pre-dilution during sampling or the dilution factor used (between factor 2 and 6) did not appear to have an effect on the decay characteristic of odor samples. The following recommendations are suggested for the practice of collecting odor samples and apply specifically to tobacco processing emissions: Analyze samples as soon as possible, preferably within 12 hr; When samples age for more than 12 hr, decay is likely to cause a reduction in odor concentration to half the original concentration at age 30 hr; Use sampling bags made of Nalophan NA or benchmark performance of other materials against Nalophan NA before using alternative materials; Use pre-dilution when sampling only for the purpose of avoiding condensation during sample storage. Use an appropriate minimum dilution factor to avoid condensation; Both nitrogen and high-purity (synthetic) air are suitable to use as neutral gas for pre-dilution; and When sampling tobacco odors, use an odorless filter to remove particles. This practice removes a source of variation and avoids contamination of equipment. The effect on results, despite being consistently lower in odor concentration, is not meaningful in terms of perceived intensity or annoyance potential.     

Correlating Emissions with Time and Temperature to Predict Worst-Case Emissions from Open Liquid Area Sources

Abstract

The two primary factors influencing ambient air pollutant concentrations are emission rate and dispersion rate. Gaussian dispersion modeling studies for odors, and often other air pollutants, vary dispersion rates using hourly meteorological data. However, emission rates are typically held constant, based on one measured value. Using constant emission rates can be especially inaccurate for open liquid area sources, like wastewater treatment plant units, which have greater emissions during warmer weather, when volatilization and biological activity increase. If emission rates for a wastewater odor study are measured on a cooler day and input directly into a dispersion model as constant values, odor impact will likely be underestimated. Unfortunately, because of project schedules, not all emissions sampling from open liquid area sources can be conducted under worst-case summertime conditions. To address this problem, this paper presents a method of varying emission rates based on temperature and time of the day to predict worst-case emissions. Emissions are varied as a linear function of temperature, according to Henry’s law, and a tenth order polynomial function of time. Equation coefficients are developed for a specific area source using concentration and temperature measurements, captured over a multiday period using a data-logging monitor. As a test case, time/temperature concentration correlation coefficients were estimated from field measurements of hydrogen sulfide (H₂S) at the Rowlett Creek Wastewater Treatment Plant in Garland, TX. The correlations were then used to scale a flux chamber emission rate measurement according to hourly readings of time and temperature, to create an hourly emission rate file for input to the dispersion model ISCST3. ISCST3 was then used to predict hourly atmospheric concentrations of H₂S. With emission rates varying hourly, ISCST3 predicted 384 acres of odor impact, compared with 103 acres for constant emissions. Because field sampling had been conducted on relatively cool days (85–90 °F), the constant emission rate underestimated odor impact significantly (by 73%).     

Consultant Guide/1986

ABSTRACT

To obtain annual odor emission profiles from intensive swine operations, odor concentrations and emission rates were measured monthly from swine nursery, farrowing, and gestation rooms for a year. Large annual variations in odor concentrations and emissions were found in all the rooms and the impact of the seasonal factor (month) was significant (P < 0.05). Odor concentration was low in summer when ventilation rate was high but high in winter when ventilation rate was low, ranging from 362 (farrowing room in July) to 8934 (nursery room in December) olfactory unit (OU) m^?3. This indicates that the air quality regarding odor was significantly better in summer than that in winter. Odor emission rate did not show obvious seasonal pattern as odor concentration did, ranging from 2 (gestation room in November) to 90 (nursery room in April) OU m^?2 sec^?1; this explains why the odor complaints for swine barns have occurred all year round. The annual geometric mean odor concentration and emission rate of the nursery room was significantly higher than the other rooms (P < 0.05). In order to obtain the representative annual emission rate, measurements have to be taken at least monthly, and then the geometric mean of the monthly values will represent the annual emission rate. Incorporating odor control technologies in the nursery area will be the most efficient in reducing odor emission from the farm considering its emission rate was 2 to 3 times of the other areas. The swine grower-finisher area was the major odor source contributing 53% of odor emission of the farm and should also be targeted for odor control. Relatively positive correlations between odor concentration and both H₂S and CO₂ concentrations (R ² = 0.58) means that high level of these two gases might likely indicate high odor concentration in swine barns.

IMPLICATIONS The emissions of air pollutants including odors, greenhouse gases, and toxic gases have become a major environmental issue facing animal farms in the U.S.A. and Canada. To ensure the air quality in the vicinity of intensive livestock farms, air dispersion models have been used to determine setback distances between livestock facilities and neighboring residences based on certain air quality requirement on odor and gases. Due to the limited odor emission data available, none of the existing models can take account of seasonal variations of odor emissions, which may result in great uncertainties in setback distance calculations. Therefore, the obtained seasonal odor and gas emission rates by this study can be used by the government regulatory organizations and researchers in air dispersion modeling to get improved calculation of setback distances.     

Sensory and chemical characterization of VOC emissions from building products: impact of concentration and air velocity

The emissions from five commonly used building products were studied in small-scale test chambers over a period of 50 days. The odor intensity was assessed by a sensory panel and the concentrations of selected volatile organic compounds (VOCs) of concern for the indoor air quality were measured. The building products were three floor coverings: PVC, floor varnish on beechwood parquet and nylon carpet on a latex foam backing; an acrylic sealant, and a waterborne wall paint on gypsum board. The impacts of the VOC concentration in the air and the air velocity over the building products on the odor intensity and on the emission rate of VOCs were studied. The emission from each building product was studied under two or three different area-specific ventilation rates, i.e. different ratios of ventilation rate of the test chamber and building product area in the test chamber. The air velocity over the building product samples was adjusted to different levels between 0.1 and 0.3 m s^-1. The origin of the emitted VOCs was assessed in order to distinguish between primary and secondary emissions. The results show that it is reasonable after an initial period of up to 14 days to consider the emission rate of VOCs of primary origin from most building products as being independent of the concentration and of the air velocity. However, if the building product surface is sensitive to oxidative degradation, increased air velocity may result in increased secondary emissions. The odor intensity of the emissions from the building products only decayed modestly over time. Consequently, it is recommended to use building products which have a low impact on the perceived air quality from the moment they are applied. The odor indices (i.e. concentration divided by odor threshold) of primary VOCs decayed markedly faster than the corresponding odor intensities. This indicates that the secondary emissions rather than the primary emissions, are likely to affect the perceived air quality in the long run. Some of the building products continued to affect the perceived air quality despite the concentrations of the selected VOCs resulted in odor indices less than 0.1. Therefore, odor indices less than 0.1 as an accept criterion cannot guarantee that a building product has no impact on the perceived air quality.     

Comments

Regarding the TT-4 Odor Committee paper on Odor Regulation, we believe that the basic goal of a regulation should be to prevent ambient odors that are a nuisance to the community and that control methods to reach these goals should not be specified by regulatory bodies. In enforcing odor regulations, the cost effectiveness of alternate solutions should be considered. For example, we consider a limit on the total odor emission to be a penalty on large installations which is not cost effective.     

Development of a livestock odor dispersion model: part I. Model theory and development

A livestock odor dispersion model (LODM) was developed to predict mean odor concentration, odor frequency, instantaneous odor concentration, and peak odor concentration from livestock operations. This model is based on the Gaussian fluctuating plume model and has the ability to consider the instantaneous concentration fluctuations and the differences between odor and traditional air pollutants. It can predict odor frequency from the routine hourly meteorological data input and deal with different types of sources and multiple sources. Also, the relationship between odor intensity and odor concentration was incorporated into the model.     

Prospects for Exhaust Control by Engine Modification

In order to assist in assessing potential odor problems arising from chemical manufacturing operations, the odor thresholds of 53 commercially important odorant chemicals have been determined using a standardized and defined procedure. The odor threshold data previously available have shown wide variation reflecting the diversity of procedures and techniques used. Factors that may affect the odor threshold measurement include the mode of presentation of the stimulus to the observer, the influence of extraneous odorants in the presentation system, the type of observer used, the definition of the odor response, the treatment of the data obtained, and the chemical purity of the odorant. The experimental approach used has minimized these variations. The odorants were presented to a trained odor panel in a static air system utilizing a low odor background air as the dilution medium. The odor threshold is defined as the first concentration at which all panel members can recognize the odor. The effect of chemical purity has been determined by measuring the odor threshold of materials representing different modes of manufacture or after purification by gas chromatographic procedures. The threshold concentrations range over six orders of magnitude. Trimethylamine exhibited the lowest threshold (0.00021 ppm volume); methylene chloride was not recognizable below 214 ppm. Of the 53 chemicals, sulfur bearing compounds exhibit low threshold values on the order of parts per billion. Aside from the sulfides, it is not possible to anticipate the odor threshold of a material based on its chemical structure or functionality.