Evaluation of human mobility models, for exposure to air pollutants

The subject of the present study is to find the best way of making a simulation model for the exposure assessment of mobile individuals. For that purpose we consider and apply several very different approaches to model movement patterns in a more or less random way and compare them in terms of the exposure resulting for the individuals. The models combine random movement with agenda-driven movement. We do not aim to involve all details of real conditions into the models, but explain and review the general concepts and provide an inter-comparison of these concepts. Stationary and ergodic behaviour are explained and applied as well as performance criteria for a comparative evaluation of the investigated algorithms. In particular, the present study investigates the exposure to air contaminants of persons moving in heterogeneously polluted urban areas by help of movement simulations. For that purpose we applied four different movement algorithms: Lévy-modulated correlated random walk (LMCRW), Potential field controlled walk (PTW), Reference point mobility model (RPM), and RPM with a pre-defined daily agenda of targets (RPMA). We find that none of the studied algorithm results in purely random trajectories. PTW and RPMA prove to be suitable for human mobility modelling, because they provide conditions for very individual-specific trajectories and exposure. Suggesting these models we demonstrate the plausibility of their results for exposure to air-borne benzene and the combined exposure to benzene and nonane. It appears however that inter-individual variation in the individual-specific short-term exposure diminishes with runtime and when long-term exposure is considered.