An Energy Development Facility (EDF) has been evaluated as an odor source to optimize the evaluation of odor persistency. The objectives were to identify the odor characteristics and intensity from the EDF and to determine the relative contribution and variability of the different odors emitted.

   The method includes using the Odor Profile Method to identify each odor character and intensity and using olfactometry as an odor dilution system to determine the persistency of the odor, i.e., the rate of decrease of an odor with dilution. The results showed that air coming from the EDF can pose a rancid and sweet odor nuisance for the community near the EDF and possibly a weak musty odor nuisance for the area further away from the EDF. 

   Competing interests: The author has declared that no competing interests exist.

   Academic editor:  Carloz N. Díaz

   Content quality: This paper has been peer-reviewed by at least two reviewers. See scientific committee here

   Citation: Yuge (Gloria) Bian, Zhihang (Peter) Yin, Bart Kraakman, Scott Cowden and I.H. (Mel) Suffet, 2021. Using olfactometry to evaluate odor persistency from sites emitting odor, 9th IWA Odour & VOC/Air Emission Conference, Bilbao, Spain, www.olores.org.

   Copyright:  2021 Olores.org. Open Content  Creative Commons license. It is allowed to download, reuse, reprint, modify, distribute, and / or copy articles in olores.org website, as long as the original authors and source are cited. No permission is required from the authors or the publishers.

   ISBN: 978-84-09-37032-0

   Keyword: odor measurement, masking effect, persistency curve, odor attribution

Download Presentation

Video

Abstract

   An Energy Development Facility (EDF) has been evaluated as an odor source to optimize the evaluation of odor persistency. The objectives were to identify the odor characteristics and intensity from the EDF and to determine the relative contribution and variability of the different odors emitted. The method includes using the Odor Profile Method to identify each odor character and intensity and using olfactometry as an odor dilution system to determine the persistency of the odor, i.e., the rate of decrease of an odor with dilution.

   The results showed that air coming from the EDF can pose a rancid and sweet odor nuisance for the community near the EDF and possibly a weak musty odor nuisance for the area further away from the EDF. The biofilter at the facility has medium intensity fecal and rotten vegetable odors but they did not contribute to projected odor nuisance in the affected neighbourhood. The main odor problem is from the indoor area of the EDF where the incoming organic waste, digesters and compost tunnels are located. An interesting finding was that the musty odor can be masked by other odors such as fecal, rotten vegetable, and rancid that are of higher odor intensity. The musty odor persists while these odors dissipate with dilution.

1. Introduction

An Energy Development Facility (EDF) is one of the possible facilities that could cause an odor nuisance to a nearby community. The EDF produces clean, green renewable energy while producing a feedstock for composting. It processes “wet” organic waste material that is collected primarily from commercial industries. The waste includes food waste and residential waste (mainly yard trimmings), which would otherwise go to a landfill. The indoor EDF contains an indoor collection floor area with digesters and compost tunnels. The indoor EDF area was open to the outdoor air. Also, a biofilter was operated above the collection floor area.

   An odor persistence study was used to characterize the types of odors and their intensities from the EDF and its potential effect on the nearby community. The objective was to evaluate whether the air emitted from the EDF contributes to the odor nuisance at the impacted community. Air samples were collected upwind of the EDF, from the EDF’s indoor collection floor area that was open to the outdoor air, from a biofilter effluent over the collection floor area and a sample downwind from the facility.

2. Methods

   The Odor Profiling Method (OPM) and Olfactometry were used to produce odor persistence curves from the air samples collected at the site. The Odor Profile Method identifies each odor character and intensity and the olfactometer was used as an odor dilution system to determine the persistency of the odor, i.e., the rate of decrease of an odor with dilution.

2.1. Odor Profiling Method

   The Odor Profile Method (OPM) was based upon the Flavor Profile Analysis (FPA) method for the food and drinking water industries, specifically Method 2170, the “Flavor Profile Analysis” of “Standard Methods of Water and Wastewater” (Rice et al., 2017). The FPA has a 7-level sugar scale to determine the intensity of an odorant. The FPA was developed for the headspace of drinking water. It has been used for over 30 years and is a standard method to evaluate odor problems and for quality control of specific odors in drinking water. The method was developed for air analysis studies by Burlingame, (1999); Burlingame, et al., (2003); Burlingame (2009) and Curren et al., (2014) as the OPM.

   The OPM includes identifying one or more odor notes in the air sampled and determining the odor intensity for each odor note. Panelists are calibrated to the odor intensity scale —threshold (1), slight (2), weak (4), medium (6), medium–strong (8), strong (10) and very strong (12)—using sugar-in-water solutions tasted by mouth that represent weak 4, (5% sugar), medium–strong 8, (10% sugar) and very strong 12, (15% sugar) as described by Rice et al., (2017). Curren et al., (2014) showed that the sugar solution intensity calibration method for the OPM works as well as the butanol standard method, ASTM, Method E544-10 (2004) and in fact was easier to use. The OPM method is based upon the Weber–Fechner Law (Fechner, 1859), where a single odorant’s intensity is proportional to the Log of the odorant’s concentration.

   Whereas the concentrations are units such as ppb or µg/m³, and k is a constant (called the Weber–Fechner coefficient) that is unique to each chemical odorant. Figure 1 shows the relationship between Odor Intensity and the Log (Concentration). The odor level of detection (1) and recognition (4) of the odor character are shown. An action level of 3 below recognition has been suggested to minimize an odor problem. An odor panel of four is the minimum number of panelists needed for an OPM analysis.

Fig 1.: Weber-Fechner Curve

2.2 Olfactometry for Developing the Odor Persistency Curves

The AC’SENT International Olfactometer (St. Croix Sensory, Inc., 2005), a dynamic dilution venturi-nozzle style olfactometer was used to develop persistency curves of individual odor characteristics in an air sample. The olfactometer mixes odorous air samples with odor-free blank air at different levels of dilution for presentation to an OPM odor panel of four. Olfactometry follows the ASTM E679-04 (2011) and the EN 13725 (2003) Standard of Practice of Olfactometry using a total flow rate at 20 liters per minute.

The Direct Presentation Method (St. Croix Sensory, Inc., 2005) was used to generate odor persistency curves of odor intensity vs the log Dilution Ratio. The Direct Presentation Method is a method for presenting an odor sample at a specific concentration to a panelist for a specified amount of time of 3 seconds at each dilution level. The test administrator selects different dilution levels. In the odor persistency analyses, 4 panelists determined by using the OPM, the character and intensity of different odors that were present at each dilution level. The average of the 4 panelists at each dilution was used for each point on a persistency curve. Thus, persistency curves (intensity vs log dilution ratio) were generated.

3. Results and Discussion

3.1 OPM Data for Evaluating the Relationship of Upwind, the Source(s) of Odor Nuisance at the EDF and Downwind from the EDF

   The odor panel evaluated the original samples for its’ odor character and intensity by the OPM. The upwind sample represent the air before reaching the EDF and the downwind sample represent the air sample after leaving the EDF that possibly adds odors and entering the community. The indoor receiving area (open to the environment) and a biofilter effluent to the outside were also evaluated.

   Table 1 indicates that air had a weak musty odor before reaching the EDF. The air sample leaving the EDF includes a medium level of rancid odor and a mild level of sweet odor. The rancid and sweet odor came primarily from the indoor area. The biofilter showed a medium level of rotten vegetable and fecal odors.

Table 1 Odor Profiling Analysis Data at the Energy Development Facility

Note: If less than 1/2 of the panelists name an odor, this is called an other odor note and no intensity is included.

3.2 Persistency Curves - Energy Development Facility

   Figures 2-5 present the persistency curves for the air sample related to the EDF. The upwind persistency curve in Figure 2 shows only a very low musty odor was observed. The downwind persistency curve in Figure 3, shows that at higher dilution, the musty odor started to show up with the decrease of rancid odor, indicating that the musty odor was masked. Figure 4 shows that the sample collected at the indoor area of EDF has a very high level of rancid and sweet odors at an OPM intensity of 10. After dilution of 2.5 log units, the rancid and sweet odors disappeared and the musty odor showed up as it was masked. Figure 5, shows the air sample taken after the biofilter treatment exiting the indoor area at the EDF. The persistency curve shows high of levels of fecal and rotten vegetable odors at an OPM intensity of 5.5 and 4.5, respectively. After a 2 dilution of 2 log units, these odors disappear and the musty odor that was in the upwind samples showed up as it was masked. It should be noted that musty odors from the floor and biofilter samples could also be added to the musty odor upwind but would be masked by the high off-odors of rancid, decaying vegetation and fecal odors.

Fig 2.: Persistency Curve at Energy Development Facility Upwind

Fig 3.: Persistency Curve at Energy Development Facility Downwind

Fig 4.: Persistency Curve at Energy Development Facility Indoor

Fig 5.: Persistency Curve at Energy Development Facility Biofilter NEED DATE AND TIME

4. Conclusion

   This study shows that a series of persistency curve can indicate whether a facility will cause odor nuisance to a community. Upwind air sample have to be monitored to eliminate the possibility that the air reaching the facility has already been contaminated. Air samples from different locations in the facility have to be compared with the upwind and downwind air samples to determine the contribution to the off-site odor nuisance from the facility. Odors such as rancid, rotten vegetable, and fecal of higher intensity can mask odors like musty that is at a lower odor intensity but are more persistent. Air inspectors might detect a high level of a nuisance odor at a certain location within a facility, however, odors that are influencing the surrounding neighborhood might be different after dilution.

   For the Energy Development Facility, the upwind sample had a minimum background musty odor. The biofilter area has a medium level of fecal and rotten vegetable odor which did not contribute to the downwind air to the community. This indicates the indoor area of the EDF was the major source of odor to the community because of a very high level of rancid odor. The rancid odor escaped from the facility should be perceived by neighborhood and should be eliminated at the source. The results also indicate that air coming out from the EDF could possibly add to a weak musty odor nuisance for the area further away from the EDF after the rancid odor dissipates.

5. Reference

   ASTM, 2004-10, Standard Practice for Referencing Suprathreshold Odor Intensity, ASTM, West Conshohocken, PA, USA.

   ASTM, 2011. E679-04, Standard Practice for Determination of Odor and Taste Thresholds by a Forced-choice Ascending Concentration Series Method of Limits pp. 1-7, ASTM, West Conshohocken, PA, USA.

   Burlingame, G.A. Odor Profiling of Environmental Odors. Water. Sci. Tech. 1999, 40, 31–38.

   Burlingame, G.A.; Suffet, I.H.; Khiari, D.; Bruchet, A.L. Development of an Odor Wheel Classification Scheme for Wastewater. Water Sci. Tech. 2003, 49, 201–209.

   Burlingame, G.A. A Practical Framework Using Odor Survey Data to Prioritize Nuisance Odors. Water Sci. Techl. 2009, 59, 595–602.

   Curren, J.; Snyder, C.; Abraham, S.; Suffet, I.H. Comparison of Two Standard Odor Intensity Evaluation Methods for Odor Problems in Air or Water. Water Sci. Tech. 2014, 69, 142–146. 

   European Committee for Standardization, 2003. Air quality – Determination of Odour Concentration by Dynamic Olfactometry, EN 13725. Brussels, Belgium.

   Fechner, G. Elemente de Psychophysik; Thesis, Leipzig University, Leipzig, Germany, 1859.

   Rice, W.; Baird, R.B.; Eaton, A.D. (Eds.) Method 2170, Flavor Profile Analysis (FPA).  In Standard Methods for the Evaluation of Water and Wastewater, 23rd ed.; Publishers— American Public Health Association (APHA), American Water Works Association (AWWA) and Water Environment Federation (WEF): Washington, DC, USA, 2017.

   St. Croix Sensory, Inc. (2005). AC’SCENT® International Olfactometer: User Manual. Lake Elmo, MN