Recent air quality studies have highlighted that important differences in pollutant concentrations can occur over the day and between different locations. Traditional exposure analyses, however, assume that people are only exposed to pollution at their place of residence. Activity-based models, which recently have emerged from the field of transportation research, offer a technique to micro-simulate activity patterns of a population with a high resolution in space and time. Due to their characteristics, this model can be applied to establish a dynamic exposure assessment to air pollution. This paper presents a new exposure methodology, using a micro-simulator of activity–travel behaviour, to develop a dynamic exposure assessment. The methodology is applied to a Dutch urban area to demonstrate the advantages of the approach for exposure analysis. The results for the exposure to PM10 and PM2.5, air pollutants considered as hazardous for human health, reveal large differences between the static and the dynamic approach, mainly due to an underestimation of the number of hours spent in the urban region by the static method. We can conclude that this dynamic population modelling approach is an important improvement over traditional methods and offers a new and more sensitive way for estimating population exposure to air pollution. In the light of the new European directive, aimed at reducing the exposure of the population to PM2.5, this new approach contributes to a much more accurate exposure assessment that helps evaluate policies to reduce public exposure to air pollution.