A modelling approach for estimating background pollutant concentrations in urban areas

Air pollution control strategies have helped to improve the air quality over Europe over the last twenty years. Despite this success, the improvements have been insufficient to protect health of those who spend most of their time within urban areas and particularly near major roads. Given the inherent complexity of urban environments and the incomplete understanding of the physical and chemical processes involved in pollutant dispersion, it is a challenging task to estimate urban air quality. In order to address this issue, a new regression model for estimating the urban increment for all cities of a region up to Europe as a whole is developed. The model is able to capture the higher pollutant concentrations commonly found within urban areas for assessing the localized effects associated to urban emissions. This approach is used for estimating annual concentrations of PM10 and NO2 for all urban areas with more than 50 000 inhabitants in Germany for the reference year 2005. The results showed that there are differences on air quality levels across urban areas in Germany. This information is relevant when evaluating the impact of emission reduction policies on air quality, which should take into account the cost–benefit of each measure. Furthermore, as the modelling approach allows for flexibility changing initial conditions and building scenarios, the added values of this approach are the large spatial domain covered, the high spatial resolution, and its inherent flexibility to address other environmental issues, such as analysis of emission reduction scenarios, the human exposure to certain pollutants and their associated human health impacts.