Modelling dynamic urban structures and air pollution exposure

Despite vast technological improvements and various political control strategies, air pollution is a major concern in urban areas worldwide. Hereby, traffic is acknowledged to be the major source.
Several studies provide evidence for the influence of travel behaviour and other characteristics on air pollution (e.g. Briggs et al., 2008) and research is increasingly expanding this link by investigating which role urban form plays in the discussion about sustainable cities (Jabareen, 2006). In order to meet sustainable growth, many argue that a compact city is the desirable urban form due to shorter travelling distances and reduced conversion of land, just in contrast to the trend towards urban sprawl (e.g. Stone et al., 2007). However, if energy consumption (Newman & Kenworthy, 2000) and total emissions (Cervero, 2000) can be shown to be reduced with more compact urban forms via reduced car use at regional scale, compactness is still debated (Gordon & Richardson, 1997). Residents often respond to externalities such as pollution primarily through spatial behaviour (location and relocation choices) which may have important impacts on the emerging form of cities. As these forms may not be socially optimal and are currently widely debated, there is a need for further research on welfare-enhancing policies.
The question I ask is: if preferences such as exposure to car-related air pollution and the valuation of green space are considered by residents in their choice of residential location, which role do they play in shaping our cities and in overcoming the environmental and social challenge?
In order to investigate this, I compare two approaches: first, a simulation approach by developing a system comprising five spatio-dynamic models; second, a micro-economic urban growth modelling approach considering residential preferences. Opposing the simulation to a further simplified model emanating from micro-economic principles provokes the discussion on complexity versus simplicity in urban modelling.
The simulation method allows to a) model the growth of an urban area (Caruso et al. (2010), b) model the traffic flow which would be generated by residents commuting on the resulting road network, c) estimate the emissions generated, d) model how these emissions are dispersed by wind and finally e) estimate the average exposure residents are faced with at each residential location.
In contrast, the micro-economic approach models residential location in a peri-urban area in mono-centric one-dimensional space. Inspired by works from e.g. Fujita (1989), Arnott et al. (2008), Gubins & Verhoef (2012) and Franceschetti et al. (2013) I aim at complementing existing urban equilibrium models by linking air pollution exposure and traffic congestion externalities with spatiality and residential valuations.
Through contrasting the two approaches I take on the discussion of complexity in urban environmental modelling and investigate how policy interactions impact on intra-urban forms and the well-being of residents.