Protocols for reliable field olfactometry odor evaluations

Robin C. Brandt, M. Arlene A. Adviento-Borbe, Herschel Adams Elliott, Eileen Fabian

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Specific gasses (odorants) are often poorly correlated with odors, which require human perception. Thus, olfactometry is used to quantify odors, which commonly contain a complex mixture of offensive compounds. Laboratory-based dynamic olfactometry is expensive and time-consuming, and it is accompanied with sample container/ preservation issues. Field olfactometry provides real-time measurements at lower detection levels, but is influenced by environmental factors. This study explores the use of field olfactometry for quantifying dilutions-to-threshold (D/T) of environmental malodors. Nasal Ranger® Field Olfactometer (NRO) instruments were used to collect 3096 individual D/T observations at livestock facilities in central Pennsylvania. Twelve to 16 observations were collected at each sampling station using multiple assessors, capturing four concurrent readings each. The multiple-assessor repeat observation (MARO) technique revealed that the reproducibility of D/T observations (across assessors) was more precise than replicate observations by individual assessors (repeatability). Observations were significantly (P<0.0001) influenced by odor source distance, wind direction, barometric pressure, and wind velocity. Power analysis showed that the 16-sample MARO using NRO method achieved 95% odor panel confidence with a power value of 0.90 at lower-D/T (2,4) and upper-D/T (30, 60) levels. Mid-range D/T settings of 7 and 15 exhibited the greatest odor panelist variability. This study shows that MARO field olfactometry can reliably estimate odor D/T differences, even with weather variations. It is noteworthy, however, that the greatest numbers of observations (n= 85-91) are needed at D/T levels of 7 to 15 (to achieve 95% confidence), precisely the range used to define nuisance odor conditions in some states.

Original languageEnglish (US)
Pages (from-to)457-466
Number of pages10
JournalApplied Engineering in Agriculture
Volume27
Issue number3
StatePublished - Jun 24 2011

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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