Suffet, I. H. (Mel)

Dr. Mel SUFFET, Distinguished Professor, Dept. of Env.l Health Sci., UCLA, School of Public Health Institute of the Env. Sustainability, College of Letters and Science, LA, CA Air Pollution Odor Nuisance Research Areas: 1) Analysis, fate treatment of odorous chemical in the air 2) Odor nuisance evaluation in urban areas and industrial sites, e.g., compost, landfills, wastewater plants 3) Developing analytical methods - GC/MS and GC/Sensory Analysis to determine the chemicals causing odors 4) Treatment of odor nuisance problems at the source by unique bio-treatment systems

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Description: An Evaluation of Masked Nuisance Odors from a Source by Chemical and Sensory...

An Evaluation of Masked Nuisance Odors from a Source by Chemical and Sensory Analyses

Abstract

Nuisance odors are caused by chemical odorants. Recent studies at the Orange County Sanitation District (OCSD) at two wastewater treatment plants showed that, besides hydrogen sulfide [H2S], eight other odorants in four different family of compounds were consistently present (1). These were rotten vegetable and garlic odorants (methyl mercaptan [MM], dimethyl sulfide [DMS] and dimethyl disulfide [DMDS]), ammonia, earthy/musty/moldy odorants (2-methylisoborneol [MIB] and 2-isopropyl-3-methoxypyrazine [IPMP]) and fecal odorants (indole and skatole). The odor profile method (OPM) with a trained odor panel was used to assess these odors during dilution of the samples. The OPM uses a 7-point odor intensity scale that is based upon the drinking water flavor profile analysis (FPA), a standard method of water analysis (2). The odorous air was diluted by an olfactometer in stages from Teflon bag samples and followed by an OPM analysis to show the decrease of odor upon dilution and the appearance of masked odors. The wastewater odor wheel was used to standardize odor descriptors during the analysis, Figure 1 (3). The objective of this study was to describe a new methodology to: 1) determine the concentration at which each odorant most probably becomes a public nuisance and 2) demonstrate how olfactometry and the OPM can be used together to show masking of odorants in real life foul air samples when the samples are diluted from a source. Experimental The Odor Threshold Concentrations (OTCs) were determined by a triangular forced choice sample presentation for each odorant (4). Each panelist was forced to choose between two blanks and an odorous sample. The panelists were asked to provide an odor intensity rating during dilution of the sample by an olfactometer, using the FPA scale. The odor intensity scale is based upon the Weber-Fechner Law (4) where a single odorant's intensity is proportional to the Log of the odorant's concentration. Odor Intensity (I) = k Log (Concentration) + b Figure 2 shows the relationship between odorant intensity and the corresponding log value of odorant concentration. The red line is the odor concentration-intensity curve, which is asymptotic on both ends towards no odor and unbearable odor, respectively. The blue line is the section of the red line that obeys the Weber-Fechner Law. The odor threshold concentration (OTC) corresponds to odor intensity one (I=1) and the odor recognition concentration (ORC) corresponds to odor intensity four (I=4) for each odor when 50% of an odor panel can define the corresponding odor intensity. An action level or odor nuisance concentration (ONC) was suggested to be set at the intensity of three (I=3) to ensure action is taken before 50% of the general population recognizes the odor. Results: Odor Persistency Curves for Odorants Observed at the Wastewater Treatment Plants Figure 3 shows the OTC and the ORC of the nine persistent odorants at two wastewater treatment facilities determined by Weber-Fechner curves for each odorant using dynamic olfactometry combined with the OPM. The OTCs were within range of those determined in the literature. The ONCs have never been referenced in the literature. The odor nuisance concentration results presented here are important to odor control because they provide information defining the nuisance odorant's isopleths in modeling and avoid a public nuisance. Observing the Odor Masking Effect Observed at the Wastewater Treatment Plants Dynamic olfactometry combined with the OPM were also used with actual foul air samples from different sources. When analyzing the dilution of the initial source concentration, it was observed that the initially prominent fecal and sulfur odors gradually decreased with increased dilution (Figure 4). However, a musty odor began to gradually appear while the fecal and sulfur odors became undetectable. We named this observation the 'peeling of an onion effect'. It is apparent that this occurs because the musty odors in the foul air sample are masked by the fecal and the sulfur odors. An example of the 'peeling of an onion effect' is shown in Figure 4, which are the results of dynamic olfactometry analysis combined with the OPM. It illustrates the gradual change in odors perceived with progressing dilutions of a foul air sample of Activated Sludge Reactor at OCSD. The fecal (I=5.6) and sulfur (I=4.2) odors were initially prominent (with no musty odors reported) in the foul air. During dilution, the intensities of both the fecal and the sulfur odors decreased. At greater dilution ratios, musty odors emerged, and the other odors became undetectable, producing the 'peeling of an onion effect'. The results indicate that while fecal and sulfur odors may dominate at or near the sources, musty odors may be the primary nuisance at or beyond the fence line after some downwind distance where the public may be affected. The 'peeling of an onion effect' occurs due to the low OTCs of musty odorants; MIB (0.02 ppb) and IPMP (0.004 ppb) compared to those of fecal odorants; indole (0.5 ppb) and skatole (0.018 ppb) and sulfur odorants; DMS (3.0 ppb), H2S (0.51 ppb), DMDS (0.2 ppb), and MM (0.08 ppb). In the presence of fecal and sulfur odorants at high concentration levels, the musty odor is less perceivable unless the fecal and/or sulfur odors are 'peeled away'. Figure 4 shows that the slope of the regression line for IPMP is the most gradual, indicating that musty odors are more persistent in air because its odor intensity decreases slower with downwind dilution than the other odorants. In comparison, the fecal and sulfur odorants lines are clearly steeper, indicating a faster decrease in odor intensities with downwind distances. Thus, musty odors may cause problems at or beyond fence-line even if they are initially masked by sulfur or fecal odors at odor sources. This estimation must be verified by onsite OPM analyses at downwind distances from odor sources as atmospheric and topographical conditions will affect this behavior.

This paper was presented at the WEF Odors and Air Pollutants Conference, May 16-19, 2023.

SpeakerSuffet, I. H. (Mel)

Presentation time

15:45:00

16:15:00

Session time

13:30:00

16:45:00

SessionYou Can't Manage What You Can't Measure

Session number3

Session locationCharlotte Convention Center, Charlotte, North Carolina, USA

TopicOdor Measurement, Monitoring, and Performance