Knowing the air we breathe

Intelair is able to map air quality over the area it has been set up in. It takes into account vehicle emissions levels, weather patterns and geographical features amongst other factors so as to give an accurate real time air quality “forecast.” It’s been designed to be set up over urban areas, where initial readings are taken by probes and the system is trained and calibrated. Once the system has been set up it can be maintained by non-specialists and is perfectly suited for local municipalities to provide for their residents.

Intelair is developed by EMISIA and the Laboratory of Heat Transfer and Environmental Engineering at the Aristotle University of Thessaloniki.

Environmental and emissions policies under the microscope will allow for the development of more clean air solutions

Intelair is able to map air quality over the area it has been set up in, as in this part of downtown Athens. When policy makers see for themselves where and when “red zones” and reasonable health limits are approached, the environmental and emissions policies that have allowed these limits will come under scrutiny.

The flip side for policy makers though, is that the eff¬ects of any regulations they implement can now be tangibly measured and evaluated, and, before they have even been implemented. Intelair also paves the way for innovative new emissions solutions because each one can easily be evaluated.

A look under the lid of intelair, a self-improving innovative algorithm

Normally, in order to deal with air pollution problems and abatement strategies you would need complicated computer models that take a lot of time and processing power to simulate the combined pollutants and their motion through the air because there is a vast amount of data to process. This would be so costly in time and money that using current modelling methods would be unfeasible.

While Intelair applies a traditional model, it only needs to do it once, after which the model is simplified, using an innovative algorithm. This algorithm trains and calibrates the model using more sophisticated approaches.

Additional concentration measurements can be used to check and align the model and, therefore, improve the algorithms in a repeatable self-improving feedback process. In this way, the amount of data that needs to be processed
is significantly reduced, while maintaining accurate forecasts.

An Intelair case study

Intelair can provide rapid assessment of local intervention and policy scenarios, including -but not limited to- traffic restrictions, fleet composition change and fuel substitution. Comparative assessment of various proposed interventions can be easily obtained for specific locations in a city or at the level of average urban background, as illustrated in the image below: the effect of three different mitigation measures is quantified in terms of the reduction in NO2 and PM10 annual average concentrations.

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