Odor field inspection: validation of dispersion models

When conducting odor impact investigations in production facilities, there are several technical aspects to take into consideration and regulations to comply with.For example, to ensure maximum reliability of the investigations, it is most important to use dispersion models, i.e., mathematical simulations, which allow describing the dispersion of odor and pollutants in the surrounding area of a production facility. 

These models must be validated and tested, to determine their impact on the actual olfactometric analyses results. 

As regardsthe topic of model validations in the field of olfactory impacts - inthe time-periodbetween December 2021 and January 2022 - LOD srl cooperated with the University of Udine to carryout a study that was the subject of Marco Pontello's thesis for the master'sdegree course on"Environmental Analysis and Management."

The work had two targets:

• to identify and determine how dispersion modeling simulation choices impact on end results;

• to validate dispersion models by applying them to a real case and comparing the simulation results with what it is possible to detect using the odour field inspection methodology.

Odor dispersion modeling is based on:

• olfactometric data;
• meteorological data;
• orography of the area.  

Two Lagrangian dispersion models have been used in this case:

• CALPUFF puff (produced by Sigma Research corporation);
• particles SPRAY (produced by ARIANET).

As these models have a fully deterministic approach, an investigation leading to their validation rarely takes place.

Instead, in this case, several configurations of the CALMET Meteorological Pre-processor (a diagnostic-type pre-processor that starts from observed data and reconstructs the fields of wind, temperature and the most common indicators of turbulence), CALPUFF and SPRAY dispersion models were initially tested.

It was possible to observe significant differences through multiple comparisons, which allowed selecting three configurations out of the seven previously employed

Then, we moved on to the second part of the work, which involved using the previously tested configurations to simulate the context being studied and thus obtain data to be overlaid on those collected on site through field inspection.

Odor field inspection is an analysis and monitoring methodology for direct odor determination on site, described and standardized by UNI EN 16841: 2017. It splits into several methodologies, but generally includes the selection and use of an examiners panel physically moving all over the territory to determine the presence of odor.

Examiners were then selected (based on the requirements of the UNI EN 13725:2022 standard on dynamic olfactometry) to verify that perceptual-olfactive capacities complied with the requirements. 

Windbehavior relative to the survey areawas then analyzed to determine the main direction it originated from. Inaddition, several reconnaissance surveys took place in the surroundings of the plant to assess walkability in the area and outline aninitial hypothetical measurement route.

The dynamic plume method requires the panel of examiners to move all over the area, along a predetermined route on which points are deployed: for each one of them they report the presence/absence of odor. This makes it possible to determine the extent of the fallout area for the emissive plume by estimating transition points between presence and absence of odor.   

Points and measurement route were then digitized on a GIS layer that could be imported into a smartphone, so that examiners could follow the route and record information during each measurement session.

The measurement sessions, which took place between December 2021 and January 2022, started with the convening of the panel at a predetermined point near the facility, from which the sessions would start. During each session, a panel leader was always present to oversee the proper application of the procedure. 

The data collected during the survey were then validated using information from a meteorological station located near the plant: in fact, the standard requires that surveys are considered valid only if carried out within a given range of atmospheric conditions. In order to do so, it was useful to use predictive tools before going to the site in order to limit unnecessary travel and contain the costs of the survey.

After the collected data were validated, estimated impact maps were drawn, representing the area affected by the plume fallout with a snapshot.

To compare this information with the output of the models, it was necessary to collect new meteorological data for the time-period when the surveys took place, and simulate the days in order to obtain overlapping results.

This comparison showed that the model succeeds in faithfully representing the odor dispersion phenomenon. In fact, for most of the survey sessions, the model was able to represent concentrations and dispersion direction detected through field inspection in a correct way.

In two measurements, the model failed to simulate dispersion direction correctly: this is due to the time scan of the weather data, which was 15 minutes because of the exploratory nature of this study. It is very likely that it would be possible to get even better results with smaller scan data, also because of the rapidity with which changes in wind and perceptual-olfactory phenomena take place.

Therefore, this study has produced interesting results that will be further investigated, particularly with regard to the validation part of simulations, which LOD also intends to develop in future projects.

More information and technical details on dispersion models may be found here.