TU Delft has been given a leading role in the DisTUrbE (DISpersion by Turbulence in the URBan Environment) project, which is intended to lead to a better prediction of air pollution in urban areas. The project is supported by STW and includes the appointment of two PhD candidates, a postdoctoral researcher and an investment fund of 200,000 euros. This makes the total project worth more than 900,000 euros. Other partners include ECN, KEMA, TNO, FlowMotion and Rijkswaterstaat.
Dr Gerrit Elsinga, project manager of DisTUrbE says: 'Our target is to trace the turbulent mechanisms that are responsible for the spread of air pollution in the vicinity of the main roads in a city. Here, we are focusing on the scale of buildings and roads (10-1000 m) and on the prediction of peak concentrations of pollution.'
Peak concentration
Air pollution in urban areas is forming an increasingly greater problem. The effectiveness with which the air quality is regulated depends on the reliability with which the concentrations of polluted substances can be predicted. In several simple cases, the average concentration can be predicted with reasonable accuracy. However, it is the peak concentrations in particular that form a danger to public health. And these depend on the details of the turbulent airflow at a given moment. These details are not yet included in current models.
Moreover, model studies mainly relate to average conditions, while air pollution especially forms a direct threat to public health during extreme weather conditions and with so-called 'sudden releases', such as during accidents, natural disasters and acts of terrorism.
Street and neighbourhood level
The most important challenge is to obtain a good description of the air pollution at the intermediate scale (10-1000 m), where the complexity of the airflow is determined by the typical dimensions of streets and neighbourhoods. According to Elsinga: 'The development of adequate models that give accurate and reliable results at the level of individual streets and neighbourhoods in an urban environment makes it possible to make a good prior estimation of the effects of measures for improving the air quality. It is of the greatest importance to obtain a sound, reliable model for densely-populated areas such as the Netherlands, where people are living adjacent to main roads and industrial areas.'
'Pollution predictor'
'Our numerical results will be validated with experimental data obtained from existing field measurements and detailed data from measurements in laboratory set-ups. The results of this research will be used in case studies that will be performed in cooperation with our partners, including consultants (FlowMotion, KEMA, CERC), technological institutes (TNO, ECN), and local and national authorities (City of Rotterdam, Rijkswaterstaat).'
'We expect that this research will lead to reliable models and a significant improvement in the quantitative prediction of air pollution. This will in turn contribute to the improvement of air quality in cities.One can imagine that this will finally get the form of a 'pollution forecast' (similar to a weather forecast), as was done by CERC during the Olympic Games in Beijing in 2008.'
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