Application of an activity-based model to evaluate the dynamic population exposure to air pollution

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, these model can be applied to establish a dynamic exposure assessment to air pollution. This paper presents a new exposure methodology, applying an activity-based model, 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, reveal large differences between the traditional static exposure approach and the new dynamic approach, mainly due to an underestimation of the number of hours spent in the urban region by the static method. The authors can conclude that this dynamic population modeling approach is an important improvement over traditional methods and offers a new and more sensitive way for estimating population exposure to air pollution.