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 encompasses 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.
In order to break this vicious cycle, a completely different engineering solution is necessary- this system needs to couple with natural systems, so as not to depend solely on mechanical systems.
This project will develop a facility consisting of an integrated suite of models and associated management and decision support tools that allow the city design to become its own HVAC system. The facility will be comprised of three components:
(i)A fully resolved air quality model
(ii)Reduced order modelling
The city will use natural ventilation in buildings to reduce demand for energy and ensure air pollutants are diluted below levels that cause adverse health. This will also be coupled with increased albedo to reduce heat island effects, plus green (parks) and blue (water) spaces to provide cooling and filtration of pollutants.
* J. Lelieveld et al. (2015) Nature, 525, 367-371
OECD (2012) ISBN 978-92-64-122161
Xiao, D., Fang, F., Pain,C.C., Navon, I.M. (2017) A parameterized non-intrusive reduced order model and error analysis for general time-dependent nonlinear partial differential equations and its applications, Computer Methods in Applied Mechanics and Engineering, 317, 868-889.
Fang, F., Pain, C.C., Navon, I.M., Xiao, D. (2017) An efficient goal based reduced order model approach for targeted adaptive observations, International Journal for Numerical Methods in Fluids, 83(3), 263-275.
Xiao, D., Pan, Y., Fang, F., Xiang J., Pain C.C., Navon, I.M., Chen, M., (2017) A non-intrusive reduced-order model for compressible fluid and fractured solid coupling and its application to blasting, Journal of Computational Physics, 330, 221-244.
Wang, Z., Xiao, D., Fang, F., Govindan, R., Pain, C.c>, Guo, Y., (2017) Model identification of reduced order fluid dynamics systems using deep learning. International Journal for Numerical Methods in Fluids. DOI: 10.1002/fld.4416
It is estimated that by 2050, around four-million deaths per year will be attributable to outdoor air pollution (twice the current mortality rate)*. Currently, approximately half of the energy use, carbon dioxide emissions and exposure to air pollution in cities is due to either buildings or transportation- and this level is increasing. Now, more than ever, there is a pressing need for a roadmap to ensure that decisions can be taken to allow the sustainable development of cities.
Traditional approaches to urban environmental control rely on energy-consuming and carbon/toxin producing heating, ventilation and cooling (HVAC) systems, which produce an unsustainable cycle of increasing energy use.