Abstract
Olfactometry is globally acknowledged as a technique to determine odor concentrations, which are used to characterize odors for regulatory purposes, e.g., to protect the general public against harmful effects of air pollution. Although the determination procedure for odor concentrations is standardized in some countries, continued research is required to understand uncertainties of odor monitoring and prediction. In this respect, the present paper strives to provide answers of paramount importance in olfactometry. To do so, a wealth of measurement data originating from six large-scale olfactometric stack emission proficiency tests conducted from 2015 to 2017 was retrospectively analyzed. The tests were hosted at a unique emission simulation apparatus—a replica of an industry chimney with 23 m in height—so that for the first time, conventional proficiency testing (no sampling) with real measurements (no reference concentrations) was combined. Surprisingly, highly variable recovery rates of the odorants were observed—no matter, which of the very different odorants was analyzed. Extended measurement uncertainties with roughly 30–300% up to 20–520% around a single olfactometric measurement value were calculated, which are way beyond the 95% confidence interval given by the widely used standard EN 13725 (45–220%) for assessment and control of odor emissions. Also, no evidence has been found that mixtures of odorants could be determined more precisely than single-component odorants. This is an important argument in the intensely discussed topic, whether n-butanol as current reference substance in olfactometry should be replaced by multi-component odorants. However, based on our data, resorting to an alternative reference substance will not solve the inherent problem of high uncertainty levels in dynamic olfactometry. Finally, robust statistics allowed to calculate reliable odor thresholds, which are an important prerequisite to convert mass concentrations to odor concentrations and vice versa.
Highlights
The emission of malodors into the environment has numerous adverse effects like annoyance, health effects, or depreciation of property values
The odor threshold c0,k of n-butanol is defined in EN 13725 to be c0 = 123 μg/m3 and the thresholds of all other components were deduced from the results reported by the participants of all proficiency tests run at HLNUG, during which the component was dosed: THT was dosed in all six proficiency tests, ETX and PIG in four tests, and RLI and AAC in two tests
The results presented here rely on the outcomes of six proficiency tests performed in 2015, 2016, and 2017, analyzing six substances and mixtures (NBU, AAC, RLI, THT, PIG, which is a mixture with more than 10 different components, and ETX as a mixture of organic solvents)
Summary
The emission of malodors into the environment has numerous adverse effects like annoyance, health effects, or depreciation of property values. Odor is classified as atmospheric pollutant by many jurisdictions and odor measurement and regulation is Responsible editor: Philippe Garrigues. Department I3 (Air Pollution Control, Emission), Hessian Agency for Nature Conservation, Environment and Geology, Kassel, Germany handled by local jurisdictions, states, provinces, and countries in different manners (Brancher et al 2017). In odor-regulating countries, odor evaluation is usually performed by collecting air samples at the source of emission, measuring odor concentration by means of dynamic olfactometry (olfaction—the sense of smell) or the triangle bag method in Japan, and predicting odor concentrations at nearby receptors employing atmospheric dispersion models. An intrinsic challenge and important origin of uncertainty is that the measured response is a perception commonly registered by human panelists with individual sensitivities towards odors. In an attempt to reduce this effect, panelists are selected based
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