IGLC.net EXPORT DATE: 19 June 2026 @CONFERENCE{Marxen2026, author={Marxen, Martin Veis and Hansen, Andreas Hougaard and Pedersen, Kristian Birch and Wandahl, SΓΈren }, editor={Hamzeh, Farook and Poshdar, Mani and Garcia-Lopez,, Nelly P. }, title={Validating location-based carbon emissions forecasting}, journal={Proceedings of the 34th Annual Conference of the International Group for Lean Construction (IGLC 34)}, booktitle={Proceedings of the 34th Annual Conference of the International Group for Lean Construction (IGLC 34)}, year={2026}, pages={558-568}, url={http://www.iglc.net/papers/details/2564}, doi={10.24928/2026/0277}, affiliation={M.Sc. (CivEng), Senior Client Advisor, Exigo A/S, Denmark, mv@exigo.dk ; B.Sc. (BacEng), Specialist, Demark, ahh@exigo.dk ; M.Sc. (CivEng), Master of IT, PhD, Part-time Lecturer, Department of the Built Environment, Aalborg University, CEO and founder of Exigo A/S, Denmark, kbp@exigo.dk, https://orcid.org/0000-0002-4400-2046 ; Professor, Department of Civil & Architectural Engineering, Aarhus University, Denmark, swa@cae.au.dk, https://orcid.org/0000-0001-8708-6035 }, abstract={Following previous papers regarding quantifying and planning greenhouse gas (GHG) emissions using Location-Based Scheduling (LBS), this research seeks to validate the previously defined methodology. By implementing the defined methodology on a real-world construction project (an actual dataset), this paper assesses its accuracy and discusses the key factors in forecasting carbon emissions using LBS. This research identifies the need for accurate usage factors [ π‘ˆ π‘’π‘ π‘Žπ‘”π‘’ ] of the machinery (i.e. percentage of time machines are actively used) on site. In the literature (For Construction Pros, 2009), such usage factors were previously defined as ranging from 40% to 80%. However, that range has proven to be an oversimplification, and the usage factors depend heavily on the type of machinery and the nature of the related schedule activity. Using accurate on-site machinery usage factors, the LBS method for forecasting GHG emissions deviates by 9% from the actual emissions measured in the case project. This accuracy is significantly better than other methods, e.g., those using generic data such as BUILD data (BUILD, 2024), which deviate by 32% from the actual emissions measured for the project. In accordance with previous papers in the series on quantifying and planning GHG emissions using LBS, this paper focuses on the A5 phase of the LCA and excludes emissions from waste and transportation. }, author_keywords={Location-based Management System (LBMS), Location-based Scheduling (LBS),Takt Planning (TP), environment, Greenhouse Gas (GHG) emissions, forecasting. }, address={Singapore, Singapore }, issn={2789-0015 }, publisher={ }, language={English}, document_type={Conference Paper}, source={IGLC}, }