The air quality element of the project will be a fully computational model that couples external and internal airflows in naturally ventilated buildings at building, block and borough scales. The model will calculate the potential for the city air flow system to act as a natural HVAC system, examining pollutant and temperature distributions in complex city geometries, fully coupling with naturally ventilated buildings and green and blue spaces. Validation of the model will be provided through laboratory, wind tunnel and in field measurements.
The cost-benefit model will assess the economic, social and environmental viability of decision choices, linking the scientific and engineering models with implementation advice. The cost-benefit model will include modules for the built environment, public spaces and transportation, providing estimates of the life-cycle costs and benefits of scenarios at the building, block and borough scales. Although not in the current proposal, it is envisaged that the model will extend to include social and health effects.
The ultimate aim of this project is to find a cost-beneficial method in which to change the way our cities are developing. The Victorians improved health by covering sewage systems- let's see if we can do the same by improving air quality.
This project encompases a transdisciplinary research group from the Universities of Cambridge, Surrey and ICL, but we know that innovations take place beyond our reach, therefore we want to work with other academics and industry partners to further our work.
We want to inform decision makers to ensure the results of this project can benefit cities across the globe, therefore we are excited to share all elements of our research to ensure the sustainable development of cities for the future.
By combining the computational model and laboratory process studies, it will be possible to develop reduced order models that allow for real time analysis and emergency response. The models will mainly consist of ordinary differential equations, solved in Matlab, and will be capable of producing gross features such as mean pollutant concentrations and temperatures in regions of a city. Reduced Order Models will be used to provide scoping studies.