Dispersion modelling of environmental odours using hourly-resolved emission scenarios: Implications for impact assessments

Abstract Regarding air quality, odours have been repeatedly ranked as the number one reason for public complaints to authorities. The most widely used method for assessing odour impacts is dispersion modelling. However, the entire impact assessment chain is permeated with uncertainty, and the role of different sources of uncertainty is not well understood. A critical component of this chain is the emission, the focus of this work. Here we develop modelling analyses for examining the influence of variable emissions against constant emissions on the outcomes of impact assessments. The analyses are built upon six hourly-resolved emission scenarios and one time-invariant scenario applied for the fattening phase of pig production systems. All seven scenarios are configured to treat total emissions due to a mechanically ventilated shed as coming from an elevated point source with an unobstructed vertical release. A total of 378 impact maps from three sites in two countries (Austria and the U.S.) over relatively flat terrain are scrutinised. The influence and relevance of accounting for variability in odour emissions over time depend strongly on the nature of the emissions (e.g., temporal pattern, presence of stochastic and deterministic components) as well as other factors such as building downwash, odour impact criterion and stack height. Altogether, the results suggest that using hourly odour emission rates can improve the confidence in impact assessments compared with the simulations driven by constant emissions. For odour impact criteria based on high-end percentiles, the assumption of constant emissions can be more easily compromised. In contrast, lower percentiles are found to be more robust in offsetting the source emission variability. Results also indicate that the variability in odour emissions might become less of an issue for releases under the influence of downwash than those without obstacle effects. This systematic work is the largest investigation to date on the consequences of incorporating variable emissions when modelling odour impacts. Our findings demonstrate that the emission scenario used as input to dispersion models can play a central role in dictating the conclusions of odour impact assessments.