Resource Efficiency as an environmental performance metric for industry: Exergetic analysis of a clinker manufacturing plant
A Spatiotemporal Environmental Sustainability Assessment Model for Deep and Large-scale Open-pit Copper Mines
Value addition for who? Challenges to local participation in downstream critical mineral ventures in Zambia
Introducing Mat-dp model tools
Machine learning for gap-filling in greenhouse gas emissions databases
Stanford has recently listed Professor Jonathan Cullen in the top 2% of scientists for 2024. The database uses Scopus data provided by Elsevier, and features citation scores and rankings for researchers...
This August, I had the chance to head out to Beijing for the Industrial Ecology Socio-Economic Metabolism (ISIE-SEM) conference with fellow Refficiency members Jonathan Cullen and Fanran Meng....
New paper from Karla Cervantes Barrón and Jonathan Cullen: Using open-source tools to project bulk and critical material demand and assess implications for low-carbon energy and transport systems:...
New paper evaluates the potential of machine learning methods to automate the completion of GHG datasets.
From 24th August – 4th September, Refficiency group leader Professor Jonathan Cullen went to China on a research trip. Firstly, Jonathan attended the Joint ISIE Socio-Economic Metabolism (SEM)...
