Development of Predictive Frameworks for Indoor Air Quality
University of Bath: Manuel Herrera, Jonathan Norman
University of Bristol: Bryan Bzdek (PI), Dan Schien
Cardiff University: Martin Weinel, Yi Jin
University of Exeter: Kelly Thornber
Project details
This project unites efforts in aerosol science, computer science and architecture across GW4 to develop a predictive framework for indoor air quality using parameters that are easily measured, including energy usage, human activity and outdoor conditions. In collaboration with the EPSRC-funded SPHERE programme (which develops homes into experimental facilities), this project will take some primary experimental steps to establish what kinds of domestic activities are likely to create aerosol particles, including cooking, vacuuming, opening/closing windows and mopping). The team will then use existing SPHERE infrastructure to develop data-driven models of human activity which can then be scaled up to all existing SPHERE homes. The project will also involve a one-day workshop which will aim to identify substantial research questions that can be addressed in a full proposal to a funding body, as well as outline a preliminary publication. The group aim to establish a long-term collaborative project in this research area.
Project Update
On 18 January 2019 a GW4-sponsored workshop on Indoor Air Quality was held at the University of Bristol. Attendees hailed from all four GW4 institutions and represented areas including chemistry, computer science, architecture, civil engineering, and psychology. In addition, there were representatives from government agencies and private industry. The workshop identified several potentially significant areas for investigation. For example, the push towards more energy efficient buildings may have negative impacts on indoor air quality. Moreover, the potential impacts of consumer products on indoor air quality are often poorly known. This workshop has resulted in the development of collaborative relationships aimed at investigating areas like these in the future.