Dispersion models have proven to assist the development of regulation strategies for the mitigation of odour impact. Nevertheless, the complexity derived from the definition of the sources and the replication of the subjective perception of chemical mixtures raise the question whether it is enough to perform an assessment based exclusively on the predictions of models. Furthermore, there is still an ongoing debate on the most appropriate methodology to reproduce sub-hourly peak concentrations. With this in mind, the active participation of the affected community could help to identify better the processes that cause odour annoyance and tune the results obtained with the dispersion models. Recently, the AirQ application has been implemented in the Czech Republic to allow citizens to report odour episodes to the entity in charge. Hence, the goal of this work was to integrate the information collected from the complainants with the simulations from the Gaussian model SYMOS, and the Lagrangian models AUSTAL and GRAL. The evaluation was performed in three sites with different emission characteristics and terrain: a pig farm, a pet food producer, and an edible oil industry. The outcome of this approach allowed to evaluate the suitability of each model depending the characteristics of the source, compare the use of a constant peak-to-mean factor of 4 against the Concentration Variance Model, and determine the applicability of certain odour impact criteria (OIC) for establishing separation distances.
Keywords: Citizen science; Lagrangian model; Odour dispersion; Peak-to-mean factor.
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