Thermal performance assessment of extensive green roofs investigating realistic vegetation-substrate configurations

  • Stefano CasconeEmail author
  • Antonio Gagliano
  • Tiziana Poli
  • Gaetano Sciuto
Research Article


Green roofing is a sustainable solution for building energy saving, urban heat island mitigation, rainwater management and pollutant absorption. The effectiveness and performance of green roofs depend on layer composition and properties. The uncertainties surrounding green roof performance modeling are mainly related to the vegetation and substrate layer, which are subjected to surrounding climatic conditions. Energy simulation software typically does not use validated models encompassing all possible combinations of vegetation layers and substrates. Therefore, the objective of this research is to investigate different extensive green roof solutions for assessing thermal performance and to provide information on vegetation and substrate layer design. Different simulations executed in EnergyPlus were carried out based on realistic literature data drawn from previous experimental tests conducted on plants and substrates. Several combinations (30 plant-substrate configurations, six vegetative species and five types of substrates) were defined and evaluated. Furthermore, indexes based on the surface temperatures of green roofs were used. Finally, a comprehensive ranking was created based on the scores to identify which extensive green roof combinations offered the highest performance. Greater plant heights, LAI values and leaf reflectivity values improve green roof energy performance in the summer more significantly than substrate modification. During the winter, thermal performance is more heavily dependent on the substrate if succulent vegetation is present, regardless of the substrate used. These results could provide designers with useful data at a preliminary stage for appropriate extensive green roof selection.


extensive green roof vegetation thermal performance surface temperature building energy simulation EnergyPlus 


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This research was funded by “the Notice 5/2016 for financing the Ph.D. regional grant in Sicily” as part of the Operational Program of European Social Funding 2014–2020 (PO FSE 2014–2020).


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Copyright information

© Tsinghua University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Stefano Cascone
    • 1
    Email author
  • Antonio Gagliano
    • 2
  • Tiziana Poli
    • 3
  • Gaetano Sciuto
    • 1
  1. 1.Department of Civil Engineering and ArchitectureUniversity of Catania95123Italy
  2. 2.Department of Electrical, Electronics and Computer EngineeringUniversity of Catania95125Italy
  3. 3.Politecnico di Milano, Department of ArchitectureBuilt environment and Construction engineering20133Italy

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