Nielsen, O.K., Plejdrup, M.S., Bruun, H.G., Gyldenkærne, S. and Christensen, J.H., 2019. MapEIre-National mapping of GHG and non-GHG emissions sources project. https://projects.au.dk/mapeire/project-description/.
Residential energy modelling
Ahern, C. and Norton, B., 2020. A generalisable bottom-up methodology for deriving a residential stock model from large empirical databases. Energy and Buildings, 215, p.109886 https://doi.org/10.1016/j.enbuild.2020.109886
Ali, U., Shamsi, M.H., Bohacek, M., Purcell, K., Hoare, C., Mangina, E. and O’Donnell, J., 2020. A data-driven approach for multi-scale GIS-based building energy modeling for analysis, planning and support decision making. Applied Energy, 279, p.115834 https://doi.org/10.1016/j.apenergy.2020.115834
Ali, U., Shamsi, M.H., Bohacek, M., Hoare, C., Purcell, K., Mangina, E. and O’Donnell, J., 2020. A data-driven approach to optimize urban scale energy retrofit decisions for residential buildings. Applied Energy, 267, p.114861 https://doi.org/10.1016/j.apenergy.2020.114861
Ahern, C., 2019. Introducing the Default Effect: Reducing the Gap Between Theoretical Prediction and Actual Energy Consumed by Dwellings Through Characterising Data More Representative of National Dwellings Stocks.
Ali, U., Shamsi, M.H., Hoare, C., Mangina, E. and O’Donnell, J., 2019. A data-driven approach for multi-scale building archetypes development. Energy and Buildings, 202, p.109364 https://doi.org/10.1016/j.enbuild.2019.109364