Dr Yee Van Fan joins the CircEUlar team at the University of Oxford, bringing experience in sustainability assessments and scenario modelling of material recovery and energy

Dr Yee Van Fan joins the CircEUlar team at the University of Oxford, bringing experience in sustainability assessments and scenario modelling of material recovery and energy

From assessing optimal treatment strategies for waste collection and management systems, and forecasting GHG emissions from waste flows by understanding relationships with demographic and socioeconomic factors, his research includes life cycle analysis of the solid waste management sector from micro to macro scales.

Cooling buildings with waste drilling fluid

Cooling buildings with waste drilling fluid

Drilling fluids contain a mineral that is the main ingredient for the world’s most promising cooling paints: barite. Can we recover this mineral from soon-to-be-obsolete fossil wells to cool our houses in a heated world?

How can machine learning help prioritize building energy retrofits?

How can machine learning help prioritize building energy retrofits?

In a recent study, our partner Technische Universität Berlin (Sustainability Economics of Human Settlements) – TUB looked at 25 million buildings in France, Spain and the Netherlands and tried to estimate the construction year and retrofit need. The overarching goal was to assess if machine learning methods can facilitate the identification of retrofit candidates at scale.

New mobility and the circular economy

New mobility and the circular economy

Recent years have seen the rapid increase of micro e-mobility ownership and the launch of public rental schemes across many European cities. However, its long-term impact is dependent on its ability to complement other sustainable modes, and ultimately to displace car use and ownership.