Abstract/Summary

Recent advances in urban climate modelling and weather forecasting have allowed for the integration of multiple processes at fine resolutions. Anthropogenic heat flux (QF) is the thermal emission due to human activity and is therefore most relevant in urban areas. It can impact aspects of urban meteorology through the modification of other surface energy balance fluxes. Despite this, QF is often underrepresented in forecasting and urban land surface studies. Whilst current modelling approaches provide reasonable estimates, they do not have the capability for detailed scenario modelling. This thesis presents a novel, agent-based QF modelling approach (Dynamic Anthropogenic activitieS impacting Heat emissions – DASH) with human behaviours governing its fundamental dynamics, integrating simple building energy and transport models. This model can be used to investigate a city’s response to scenarios such as population growth or climate change. To facilitate inclusion with broader urban land surface studies and weather models, DASH is adapted to two more computationally efficient schemes in such a way that spatial, temporal and thermal response behaviours are still represented. DASH is also coupled to an urban land surface model, SUEWS, to allow for feedback with the outdoor environment, e.g. temperature response. DASH is developed for Greater London for October 2014 – September 2015 at a local resolution. It is evaluated against both an existing model and energy statistics for the same area and period. Expected diurnal, weekly and seasonal patterns are observed, along with variations due to building use and demographics. Areally weighted mean annual QF is 6.43 W m-2 in the evaluated instance, and 8.47 W m-2 when coupled to SUEWS (under different forcing meteorology). The two more efficient schemes, with parameters derived from DASH, show means of 6.68 and 7.44 W m-2 , but broader distributions overall.