Flat roofs can employ a range of technologies to improve sustainability, such as photovoltaic (PV) panels, green roofs, cool roofs, or a combination of these options. Yet, weighing the benefits, costs, and performance of different roofing technologies is complex, especially when different stakeholders are involved. Decision analysis techniques, such as multi-criteria decision analysis (MCDA), can be used to systematically evaluate a diverse range of rooftop options to assess trade-offs in a quantitative way and avoid decision biases. This study offers a holistic comparison of different roof types, considering stakeholder preferences and uncertainty using MCDA. Ten flat roof options are compared, including black, gravel, cool, extensive green and semi-intensive green roofs, each with or without a rooftop PV installation, for nine objectives and three hypothetical stakeholder profiles. Performance is evaluated using building energy simulation, hydrologic modeling, and literature research. Uncertainty analyses are used to evaluate the effects of model assumptions on the MCDA results. For assumed preferences of an urban planner and environmentalist, semi-intensive green roofs with integrated PV installation are the best performing option; however, for a hypothetical building owner more concerned with costs, a gravel roof with PV ranks best. Uncertainty plays a role in the results, in particular, the uncertainty of the predicted outcome of options for the building owner, which can change the top-ranking options considerably. The uncertainty analyses are useful to identify consensus options over all three stakeholder types. Despite considerable uncertainty, extensive and semi-intensive green roofs with PV are recommended as relatively robust best-performing options.
L o a d i n g
Organization
Swiss Federal Institute of Aquatic Science and Technology (Eawag) - view all
Update frequencyunknown
Last updated3 weeks ago
OverviewEPA SWMMEnergyPlusGreen roofsMulticriteria decision analysisPythonReflective roofsSolar panelsUncertainty analysisValueDecisionsmulti-attribute value theory
Additional Information
KeyValue
Harvest Object Id7667963b-92a9-49d1-98eb-00548c88c790
Harvest Source Idd0230d8d-fb2c-4caf-94e8-8ad52bd38ad9
Harvest Source TitleThe Eawag Research Data Institutional Repository
