It should be noted that the “factor of two” proposed above has been selected somewhat
arbitrarily based on the authors’ experience, and that it is the philosophy of the approach,
rather than the actual definition of the “grey area” range. Some case studies have been
examined using this approach and the factor of two appears to be appropriate. However, as
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this methodology is implemented, the factor of two may be modified to fit with further case
study information as it becomes available.
Acceptable Grey
When interpreting dispersion model results as described above, the sensitivity of the model
results to changes in the input data assumptions, and the amount of conservatism in that
input data should be considered. Aspects include: (i) odour emission rate data used – source
of data, use of variable or worst-case emissions, offensiveness of odour type; (ii) land use
and occupation where adverse effects are predicted to occur – population density, sensitivity
of receiving environment, time of day when adverse effects occur; (iii) model algorithm
assumptions – dispersion coefficients, use of surface roughness factors, other model settings;
and (iv) meteorological file used – use of appropriate site-specific files, influence of calm
conditions. By considering these factors, a judgment of whether the model results indicate
any adverse effects can then be made. Any significant uncertainty in the input factors will be
reflected as uncertainties in the modelling outputs. This should be considered in determining
if a modelling approach is appropriate to any particular application.