Odour impact criteria
To use
dispersion models for odour emission two different approaches are under
discussion. The first is the use of a conventional dispersion model, which
delivers mean values for an integration period of 30 to 60 minutes. Most of these
models are used for regulatory purposes. The disadvantage of such models is the
underestimation of the odour concentration at a receptor point, depending on
the stability of the atmosphere and the travel time (distance) of the emission.
This underestimation has to be compensated by the applied odour impact criteria
which define the proportion of time which can be exceeded by a certain odour
concentration. The second approach is the assessment of the odour concentration
over the duration of one single breath (about 4 to 5 s) by using a so-called
peak-to-mean ratio. Such an assessment of the maximum expected odour
concentration mimics the odour sensation of a human nose in a more realistic
way. In this paper we used the Austrian Odour
Dispersion Model (Schauberger et al., 2000 and 2002a) which is based on the
regulatory Gaussian dispersion model and a module which takes into account
turbulent mixing, to calculate the peak-to-mean ratio. The peak-to-mean ratio
is reduced with increasing distance from the source using the wind velocity and
the stability of the atmosphere. In Germany a constant peak-to-mean ratio of 10 is
used, leading to an overestimation of the momentary odour concentration
especially for larger distances.
The
definitions of the various national odour impact criteria differ to quite an
extent. Miedema and Ham (1988) and Miedema et al. (2000) found a strong
relationship between the 98 percentile of the odour concentration and the
percentage of the highly annoyed neighbours. They used an ambient odour
concentration for an integration time of 1 hour, calculated by a dispersion
model without consideration of the peak-to mean ratio. In Germany, the odour impact criterion is
defined by an exceedance probability of 10% for a threshold of 1 OU/m³. To
apply this odour impact criterion, the calculated odour concentration (one hour
mean value of the regulatory dispersion model) is multiplied by a constant
factor of 10.
This
demonstrates that the representative time scale for the ambient odour
concentration (between 60 minutes and some seconds), calculated by the
dispersion model and the odour impact criteria are not independent. An
underestimation of the perceived odour concentration by neglecting the peak to
mean ratio is compensated by a strong criterion (Miedema et al, 2000), whereas
an overestimation of the perceived odour concentration e. g. by a constant
factor 10 (Germany) is compensated by weaker
criteria. The source type (area or point; height), the distance between source
and receptor, and the stability of the atmosphere are the main variables of the
peak to mean ratio (Schauberger et al., 2000a and 2002), causing its decrease
with distance, static stability, and wind speed. The Environment Agency, UK (2002), however, suggests to just use the
1 hour mean value as in Miedema et al. (2000), without correction by a peak to
mean factor.
Apart
from the exceedance probability, the odour concentration threshold of the
impact criterion is of importance. The odour is measured by the human nose as a
sensor by comparing a diluted odour sample with odour free air. This means that
the detection threshold of 1 OU/m³ can only be perceived in an odour free
environment (laboratory). Therefore the perceived odour concentration in the
field must be higher than 1 OU/m³ to be distinguished against the
background concentration. Field experiments must be designed such that an odour
source can be distinguished against the background odour. Nicell (1994) assumes an odour
concentration of 3 OU/m³ to allow for a discrimination, and one of
5 OU/m3 for unmistakable perception (also defined as a
complaint level).
Further
on, the perception of the odour intensity goes with the logarithm of the odour
concentration according to the Weber-Fechner law (e. g., Misselbrook et al.,
1993). Based upon laboratory-based experiments on perceived intensity, the
Environment Agency, UK (2002), defines: 1 OU/m³
is the point of detection, 5 OU/m³ is a faint odour, and 10 OU/m³ is
a distinct odour. The discrepancy between the definition of 1 OU/m³ in the
laboratory by using odour free air and the situation in the field was solved by
introducing the sniffing unit (van
Langenhove and van Broeck, 2001; Defoer and van Langenhove, 2003).
All
these aspects of the odour impact criteria show the difficulties to compare
various methods used in different countries.
Then
the occurrence of the odour sensation was analysed according to the FIDO
(frequency, intensity, duration and offensiveness) factors which were suggested
by Watts and Sweeten (1995) to assess odour
nuisance. In New
Zealand
(Ministry for the Environment, 2003) and Victoria, Australia (Department of Sustainability and Environment, 2000), a fifth factor, the location, in addition is in use. This
factor describes the nuisance with regard to the sensitivity of the receiving
environment. The location factor can directly be compared with the factor
reasonableness, suggested by Miner (1995). He defines reasonableness of odour
sensation as odour causing fewer objections within a community where odour is traditionally
part of the environment. For example, it is expected that rural smells will
occur as part of the rural environment and industrial smells in industrial
areas. Problems then often arise if incompatible activities are located near
each other. For example, complaints about existing intensive farming operations
often occur when land use in the vicinity is changing. Lohr (1996) found that
personal knowledge of the operator of the livestock unit, long term residency,
economic dependence on farming, familiarity with livestock farming and
awareness of the agricultural-residential context are related to a reduced
incidence of formal complaints. An assessment of this factor is often done by
the land use category where the neighbours are situated. A pure residential
area has a higher protection level than a rural area.
In
many national guide lines, the separation distance between residential houses
and livestock buildings is modified according to the reasonableness and/or
location factor (e.g., Austria (Schauberger et al., 1997; Schauberger and Piringer, 1997a and
1997b), The Netherlands (Ministrie van Landbouw, 1991), Germany (VDI 3471,1986; VDI 3472,
1986), and Switzerland (Richner and Schmidlin,
1995)). For pure residential areas the protection level is higher compared to
rural sites. E.g., the separation distance for rural sites, calculated by the
Austrian guideline, is half of the distance compared to pure residential areas.
In New South Wales, Australia (NSW Environmental Protection Authority,
2001), the odour threshold CT depends on the population density D
(inhabitants/km²) by CT = -(log D - 4.5)/0.6
(eg, 2 OU/m³ for urban areas (D is about 2000 /km²) and 4 OU/m³
for rural sites (D is about 125 /km²)).
In
a similar way this objective is included in the odour impact criteria for the
evaluation of dispersion models. An adaptation of the protection level is
realised by one of the two parameters of the impact criteria. In Germany the exceedance probability is
growing to reduce the protection level, in Australia the adaptation of the impact criteria is
done by the odour threshold. An overview of the odour impact criteria and the
corresponding land use categories used in several countries, can be found in
Schauberger et al. (2001).
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