Due to the complex and subjective nature of odour perception, estimating the impact of pollutant sources on the community requires the use of multiple tools. Currently, the European standard EN 16841:2016 - Part 1 describes a technique to evaluate odour in ambient air through sniff testing called the grid method, useful to build datasets comparable with dispersion modelling results. Another methodology to assess the exposure to offensive odours is based on the active participation of the affected community. In the Czech Republic, the AirQ system is being used to collect the complaints of voluntary subjects residing nearby problematic sources. Nevertheless, for this application to give meaningful information, the data has to be cross-checked against wind direction and validated using near-real time output of a dispersion model.
The presented study aimed to evaluate the performance of Lagrangian models AUSTAL and GRAL, and Czech Gaussian model SYMOS by using the field inspection dataset gathered in a pig-fattening farm located in Styria (Austria), and the output of the AirQ system in the vicinity of a feed production industry in the city of Prague. Results show the importance of an appropriate selection of the peak-to-mean factor and provide relevant knowledge for the future consideration of the most suitable dispersion model for odour assessment in the Czech Republic.