Projectlist

Part II/ACS projects (2024)

• 3D wind velocity field and CO2 sensing: Flux towers are used to measure the exchange of carbon dioxide between the atmosphere and the biosphere. These are typically very expensive. At their heart, they have a CO2 sensor and a 3D wind velocity field sensor. These days, both can be built using off-the-shelf components, such as this CO2 sensor and this airspeed sensor, with three airspeed sensors place on orthogonal axes. This means we can put together a quick-and-dirty flux tower for well under £200 (as opposed to the £80K they charge now). We can also get access to a flux tower near Ely to compare the measurements from a top-of-the-line system to something less expensive. The goal of this project would be to build, deploy, and calibrate this sensing platform.

• Climate change will result in more, more intense, and longer lasting heatwaves. To quantify the impact of heatwaves on building occupants, we have created a new metric called Activity Hours and the Heatalyzer tool also on GitHub. I'm keen to supervise projects that build on this work. Examples include:
  • Integrating more archetypes and geographies into Heatalyzer.
  • What conditions lead to reaching livability and survivability limits?
  • Creating an interactive map to show how the effects of a heatwave will be felt in each area of a city.
  • Developing an interactive website/app to showcase results and aid engagement.
  • Use socioeconomic data (available in the US on a congressional district scale) to map areas that will be affected by heatwaves in terms of their socioeconomic status.
  • Analysing the sensitivity of results to building orientation and ventilation (which need to be modelled in Energy+)
  • Modeling mitigation strategies in Energy+ and adding to the dashboard tool so that citizens can evaluate the impact of each strategy. Mark out strategies that do and do not depend on power grid availablity.
  • Exploiting local storage and energy use flexiblity to mitigate impact on power grid using local energy
  • Determining and representing uncertainity in results due to lack of knowledge of building construction, weather, occpuant health status, acclimitization effects and behaviour changes.
  • Personalization of our results to actual building data, matching the building data to the closest archetype and using all sources of information about the building, such as databases of building stock (e.g. US has 500K building database of representative buildings from NREL).