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Ambient air pollutants, such as NO2, are strongly traffic-related and show considerable spatiotemporal variations at street levels. However, most large-scale epidemiological studies of chronic diseases, risk assessment, and the quantification of global, national, and local burden of diseases assess long-term health effects using annual or multi-year averaged ambient NO2 concentrations at a person’s front-door home location.
Studies have shown that NO2 exposure assessmentsusing only the concentration values at the front-door addresses as a proxy for exposure can differ considerably from personal exposure assessments that account for human space-time activities.
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Meng Lu, Oliver Schmitz, Ilonca Vaartjes, Derek Karssenberg,
Activity-based air pollution exposure assessment: Differences between homemakers and cycling commuters,
Health & Place,Volume 60,2019,102233,
https://doi.org/10.1016/j.healthplace.2019.102233.
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We develop agent-based modelling approach to model human space-time behaviour for exposure assessment. Features include for example:
- 1. Allowing flexible inclusion of irregular (e.g. holiday) activity schedules for long-term exposure modeling.
- 2. Estimating or empirically specifying probability distributions for each activity. This includes for example, departure time, travel means andpossible destinations.
- 3. Repeated Sampling from the specified or estimated distributions repeatedly for uncertainty quantification and more accurate estimation of exposures through ensembling.
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