| Title | A dataset of criteria on the use of thermal insulation solutions in building facades located in Norway, Portugal and Italy |
|---|---|
| ID_Doc | 19692 |
| Authors | Parracha, JL; Bartolucci, B; Boccacci, G; Ogut, O; Bartels, G; Siani, AM; Frasca, F; Bertolin, C; Mendes, MP; Flores-Colen, I |
| Title | A dataset of criteria on the use of thermal insulation solutions in building facades located in Norway, Portugal and Italy |
| Year | 2023 |
| Published | |
| Abstract | The building sector is responsible for a significant percent-age of the energy consumption in Europe. The level of thermal insulation of the building envelope leads to decrease energy consumption, thus contributing towards a sustainable and efficient built environment. As a result, the choice of the most suitable thermal insulation solution to be applied both in new construction and in retrofitting of building facades is fundamental for a satisfactory thermal performance of the building. Nevertheless, the thermal insulation solution should not be chosen considering only the thermal performance, but rather based on a set of performance parameters (i.e., water resistance, fire performance, impact on the environment and human health, among others) and climate-related requirements. This data article includes a dataset on criteria adopted in three European countries (namely Norway, Portugal, and Italy) considering a PESTE analysis (i.e., criteria related to Political, Economic, Social, Technological, and Environmental questions). The main objective was to evaluate the knowledge and perception of people living and/or working in these countries about the use and the performance of thermal insulation solutions in building facades. To this aim a questionnaire was developed within the scope of the EEA Granted EFFICACY research project (November 2022 - February 2023), whose overall objective is to create a database that serves as a reference for the choice of thermal insulation solutions to be applied in building facades for thermal and energy performances optimization. This database contributes to systemize criteria and can be extended by other researchers or professionals in the area, as well as in other countries. (c) 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ ) |
| https://doi.org/10.1016/j.dib.2023.109622 |
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