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Abstract: By focussing on air pollutant concentration levels only, the variation in population mobility is not taken into account when assessing the exposure. Transportation policies have an impact on both concentration levels and mobility patterns. The impact of a fuel price increase policy on population exposure to elemental carbon (EC) was evaluated and compared to the base scenario (current situation), taking into account time-activity patterns – including time in commute. We assessed the effect on exposure of both the change in concentrations and whereabouts. The decrease in exposure due to the fuel price increase using residential information only was limited to areas near highways and urban centres. Integrating population movement, exposures to EC were higher and the decrease in exposure was no longer limited to areas near traffic hotspots. For inhabitants of urban areas, the exposure integrating time-activity patterns was more similar to the residential exposure, as they spent more time in their own neighbourhood. For people living further away from traffic hotspots, the estimated impact of the policy was higher than expected for residential exposure. These people profited both from the higher decrease in concentrations at their work/shop/leisure destinations in more urban areas and, as they have to travel longer, also had a larger gain from the high decrease in concentrations during transport. Therefore, the impact of changing concentrations is underestimated when using residential exposure only. These results show the importance of taking into activity-travel patterns when planning future actions. [Copyright &y& Elsevier]

Abstract: There is often a large discrepancy between the questions raised by policy makers and the responses offered by scientists. Current modeling approaches do not answer some of the typical questions that decision-makers face, as they do not provide solutions to policy-makers dealing with concrete political negotiation and decisions. In this paper, we try to bridge the gap by creating an integrated model chain that can respond to such concrete policy questions. The paper describes a model chain consisting of an activity-based transport model, a road traffic emission model, a bi-gaussian atmospheric dispersion model and a concentration measurement interpolation model. Subsequently results are compared to observations, in order to test its usability for simulating air quality and assessing dynamic exposure. The model is shown to represent the main cycles governing air quality, such as the intra-daily, the intra-weekly and the intra-annual cycle. Finally, this paper provides an example of the use of such a model chain by assessing the impact of different trip motives on the intra-daily NO2 cycle. [Copyright &y& Elsevier]