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Are Empirical Equations an Appropriate Tool to Assess Separation Distances to Avoid Odour Annoyance?

1
WG Environmental Health, Department of Biomedical Sciences, University of Veterinary Medicine Vienna, Veterinärplatz 1, A-1210 Vienna, Austria
2
Department of Environmental Meteorology, Central Institute for Meteorology and Geodynamics, Hohe Warte 38, A-1190 Vienna, Austria
3
School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China
4
Environmental and Conservational Sciences, Murdoch University, 90 South Street, Murdoch, Western Australia 6150, Australia
*
Author to whom correspondence should be addressed.
Atmosphere 2020, 11(7), 678; https://doi.org/10.3390/atmos11070678
Received: 29 April 2020 / Revised: 22 June 2020 / Accepted: 24 June 2020 / Published: 27 June 2020
(This article belongs to the Special Issue Environmental Odour)
Annoyance due to environmental odour exposure is in many jurisdictions evaluated by a yes/no decision. Such a binary decision has been typically achieved via odour impact criteria (OIC) and, when applicable, the resultant separation distances between emission sources and residential areas. If the receptors lie inside the required separation distance, odour exposure is characterised with the potential of causing excessive annoyance. The state-of-the-art methodology to determine separation distances is based on two general steps: (i) calculation of the odour exposure (time series of ambient odour concentrations) using dispersion models and (ii) determination of separation distances through the evaluation of this odour exposure by OIC. Regarding meteorological input data, dispersion models need standard meteorological observations and/or atmospheric stability typically on an hourly basis, which requires expertise in this field. In the planning phase, and as a screening tool, an educated guess of the necessary separation distances to avoid annoyance is in some cases sufficient. Therefore, empirical equations (EQs) are in use to substitute the more time-consuming and costly application of dispersion models. Because the separation distance shape often resembles the wind distribution of a site, wind data should be included in such approaches. Otherwise, the resultant separation distance shape is simply given by a circle around the emission source. Here, an outline of selected empirical equations is given, and it is shown that only a few of them properly reflect the meteorological situation of a site. Furthermore, for three case studies, separation distances as calculated from empirical equations were compared against those from Gaussian plume and Lagrangian particle dispersion models. Overall, our results suggest that some empirical equations reach their limitation in the sense that they are not successful in capturing the inherent complexity of dispersion models. However, empirical equations, developed for Germany and Austria, have the potential to deliver reasonable results, especially if used within the conditions for which they were designed. The main advantage of empirical equations lies in the simplification of the meteorological input data and their use in a fast and straightforward approach. View Full-Text
Keywords: environmental odour; emission; annoyance; separation distance; dispersion models; empirical equations environmental odour; emission; annoyance; separation distance; dispersion models; empirical equations
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Brancher, M.; Piringer, M.; Knauder, W.; Wu, C.; Griffiths, K.D.; Schauberger, G. Are Empirical Equations an Appropriate Tool to Assess Separation Distances to Avoid Odour Annoyance? Atmosphere 2020, 11, 678.

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