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New professor in the EcoSense project

Allan Gross, Professor at AU Herning

What is your research background?
I have a Ph.D. in Geophysics, Master in Theoretical Chemistry and Bachelors in Mathematics and Chemistry from the University of Copenhagen. I have worked as Scientist and Senior Scientist at the Danish Meteorological Institute, Senior Scientist at NERI (AU) and ENVS (AU). From November 2012 I started as Professor at AU Herning. I have been visiting scientist at Fraunhofer-Institute Für Atmosphärische Umwelt forshung, (Germany), Desert Research Institute (USA) and State University of Nevada (USA).

My research expertise are developing, programming and modelling of physical and chemical systems. These activities cover the areas of micro-chemistry and micro-physics, chemical mechanisms development, aerosol physics and their applications to atmospheric modelling.

What are your main research interests?
My research interests are combining mathematics, physics and chemistry to investigate physical and chemical problems on microscopic and macroscopic levels, atmospheric modelling, and graph theory and complex networks.

What will be the main focus of your research at the EcoSense project?
My main contribution to EcoSence will be applying the data collected from smartphones etc. to atmospheric modeling and traffic flow modelling. The focus area will be Aarhus and Copenhagen.

Within air quality modelling the idea is to study which impact different initiatives on reducing the air pollution in these cities will have on the air quality: introducing e.g. 10% of electric cars, changing from fossil fuels to biofuels in the transport sector, etc.

Within traffic flow modelling regions with high traffic density in the two cities will be selected and a traffic gird model will be developed. The model will use near-real-time traffic flow data from EcoSence to model the near-real-time traffic flow. As a service to the public the outcome from the model can be used to inform which route between two places in the city have the lowest air pollution, are the fastest, or have the lowest fuel consumption.