Supplementary files for: ”Risk of Mould Growth in Future Climate in Different European Locations for Two Bio-based Insulation Systems for Interior Retrofitting”

Supplementary data for: Nickolaj Feldt Jensen, Eva B. Møller, Kurt Kielsgaard Hansen and Carsten Rode, 2022. Risk of Mould Growth in Future Climate in Different European Locations for Two Bio-based Insulation Systems for Interior Retrofitting. The article is submitted for review for the 5th Central...

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Main Authors: Jensen, Nickolaj Feldt, Møller, Eva B., Hansen, Kurt Kielsgaard, Rode, Carsten
Format: Dataset
Language:unknown
Published: Technical University of Denmark 2022
Subjects:
Online Access:https://dx.doi.org/10.11583/dtu.19300001
https://data.dtu.dk/articles/dataset/Supplementary_files_for_Risk_of_Mould_Growth_in_Future_Climate_in_Different_European_Locations_for_Two_Bio-based_Insulation_Systems_for_Interior_Retrofitting_/19300001
id ftdatacite:10.11583/dtu.19300001
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spelling ftdatacite:10.11583/dtu.19300001 2023-05-15T17:04:15+02:00 Supplementary files for: ”Risk of Mould Growth in Future Climate in Different European Locations for Two Bio-based Insulation Systems for Interior Retrofitting” Jensen, Nickolaj Feldt Møller, Eva B. Hansen, Kurt Kielsgaard Rode, Carsten 2022 https://dx.doi.org/10.11583/dtu.19300001 https://data.dtu.dk/articles/dataset/Supplementary_files_for_Risk_of_Mould_Growth_in_Future_Climate_in_Different_European_Locations_for_Two_Bio-based_Insulation_Systems_for_Interior_Retrofitting_/19300001 unknown Technical University of Denmark Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 CC-BY Building science, technologies and systems Dataset dataset 2022 ftdatacite https://doi.org/10.11583/dtu.19300001 2022-04-01T10:40:03Z Supplementary data for: Nickolaj Feldt Jensen, Eva B. Møller, Kurt Kielsgaard Hansen and Carsten Rode, 2022. Risk of Mould Growth in Future Climate in Different European Locations for Two Bio-based Insulation Systems for Interior Retrofitting. The article is submitted for review for the 5th Central European Symposium on Building Physics 2022. The authors are awaiting link/DOI for the article. Abstract: This research project investigated the hygrothermal performance of two bio-based insulation systems for interior retrofitting solid masonry walls; loose-fill cellulose insulation and hemp fibre insulation mats. The study was carried out through HAM simulations calibrated with 1 year and 2 months of measurements and material data from a field experiment in Denmark’s Nordic, maritime climate. The experimental setup comprised a 40-foot (12.2 m) insulated reefer container with controlled indoor climate, reconfigured with several holes (1x2 m each) accommodating the solid masonry walls. Some of the masonry walls had exterior hydrophobisation. The calibrated simulation models were used to investigate the long-term robustness of the bio-based insulation systems to the future climate conditions caused by different emission scenarios between year 2020 and 2050, for several locations around Europe. The focus of the study was on the conditions in the interface between the masonry and the internal insulation, and the mould risk was evaluated using the VTT mould growth model. The findings showed high relative humidity levels in the masonry/insulation interface with a high risk of mould growth, already exposed to the current climate data. The results indicate that the future climate conditions would exacerbate the hygrothermal conditions in the insulated masonry walls. Exterior hydrophobisation positively affected the hygrothermal balance in the insulated masonry walls, lowering the risk of mould growth under future climate conditions. However, the results indicate that in some cases, the insulation systems would still experience critical relative humidity levels despite the combination with hydrophobisation. The dataset comprises several Excel file containing:- Typical meteorological year (TMY) weather data for Bologna, Bratislava, Copenhagen, Dublin, Kiruna, Moscow, and Munich. - Future climate data based on SRES A1B and RCP4.5 emission scenarios, for Bologna, Bratislava, Copenhagen, Dublin, Kiruna, Moscow, and Munich. - Model calibration results (comparisons between measurements from experimental set-up and simulation results)- Simulation results using TMY data (Relative humidity and temperature)- Simulation results using SRES A1B and RCP4.5 data (Relative humidity and temperature)- Mould growth predictions calculated using the VTT model by Hukka and Viitanen, based on simulation results using TMY data- Mould growth predictions calculated using the VTT model by Hukka and Viitanen, based on simulation results using SRES A1B and RCP4.5 data Dataset Kiruna DataCite Metadata Store (German National Library of Science and Technology) Kiruna
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic Building science, technologies and systems
spellingShingle Building science, technologies and systems
Jensen, Nickolaj Feldt
Møller, Eva B.
Hansen, Kurt Kielsgaard
Rode, Carsten
Supplementary files for: ”Risk of Mould Growth in Future Climate in Different European Locations for Two Bio-based Insulation Systems for Interior Retrofitting”
topic_facet Building science, technologies and systems
description Supplementary data for: Nickolaj Feldt Jensen, Eva B. Møller, Kurt Kielsgaard Hansen and Carsten Rode, 2022. Risk of Mould Growth in Future Climate in Different European Locations for Two Bio-based Insulation Systems for Interior Retrofitting. The article is submitted for review for the 5th Central European Symposium on Building Physics 2022. The authors are awaiting link/DOI for the article. Abstract: This research project investigated the hygrothermal performance of two bio-based insulation systems for interior retrofitting solid masonry walls; loose-fill cellulose insulation and hemp fibre insulation mats. The study was carried out through HAM simulations calibrated with 1 year and 2 months of measurements and material data from a field experiment in Denmark’s Nordic, maritime climate. The experimental setup comprised a 40-foot (12.2 m) insulated reefer container with controlled indoor climate, reconfigured with several holes (1x2 m each) accommodating the solid masonry walls. Some of the masonry walls had exterior hydrophobisation. The calibrated simulation models were used to investigate the long-term robustness of the bio-based insulation systems to the future climate conditions caused by different emission scenarios between year 2020 and 2050, for several locations around Europe. The focus of the study was on the conditions in the interface between the masonry and the internal insulation, and the mould risk was evaluated using the VTT mould growth model. The findings showed high relative humidity levels in the masonry/insulation interface with a high risk of mould growth, already exposed to the current climate data. The results indicate that the future climate conditions would exacerbate the hygrothermal conditions in the insulated masonry walls. Exterior hydrophobisation positively affected the hygrothermal balance in the insulated masonry walls, lowering the risk of mould growth under future climate conditions. However, the results indicate that in some cases, the insulation systems would still experience critical relative humidity levels despite the combination with hydrophobisation. The dataset comprises several Excel file containing:- Typical meteorological year (TMY) weather data for Bologna, Bratislava, Copenhagen, Dublin, Kiruna, Moscow, and Munich. - Future climate data based on SRES A1B and RCP4.5 emission scenarios, for Bologna, Bratislava, Copenhagen, Dublin, Kiruna, Moscow, and Munich. - Model calibration results (comparisons between measurements from experimental set-up and simulation results)- Simulation results using TMY data (Relative humidity and temperature)- Simulation results using SRES A1B and RCP4.5 data (Relative humidity and temperature)- Mould growth predictions calculated using the VTT model by Hukka and Viitanen, based on simulation results using TMY data- Mould growth predictions calculated using the VTT model by Hukka and Viitanen, based on simulation results using SRES A1B and RCP4.5 data
format Dataset
author Jensen, Nickolaj Feldt
Møller, Eva B.
Hansen, Kurt Kielsgaard
Rode, Carsten
author_facet Jensen, Nickolaj Feldt
Møller, Eva B.
Hansen, Kurt Kielsgaard
Rode, Carsten
author_sort Jensen, Nickolaj Feldt
title Supplementary files for: ”Risk of Mould Growth in Future Climate in Different European Locations for Two Bio-based Insulation Systems for Interior Retrofitting”
title_short Supplementary files for: ”Risk of Mould Growth in Future Climate in Different European Locations for Two Bio-based Insulation Systems for Interior Retrofitting”
title_full Supplementary files for: ”Risk of Mould Growth in Future Climate in Different European Locations for Two Bio-based Insulation Systems for Interior Retrofitting”
title_fullStr Supplementary files for: ”Risk of Mould Growth in Future Climate in Different European Locations for Two Bio-based Insulation Systems for Interior Retrofitting”
title_full_unstemmed Supplementary files for: ”Risk of Mould Growth in Future Climate in Different European Locations for Two Bio-based Insulation Systems for Interior Retrofitting”
title_sort supplementary files for: ”risk of mould growth in future climate in different european locations for two bio-based insulation systems for interior retrofitting”
publisher Technical University of Denmark
publishDate 2022
url https://dx.doi.org/10.11583/dtu.19300001
https://data.dtu.dk/articles/dataset/Supplementary_files_for_Risk_of_Mould_Growth_in_Future_Climate_in_Different_European_Locations_for_Two_Bio-based_Insulation_Systems_for_Interior_Retrofitting_/19300001
geographic Kiruna
geographic_facet Kiruna
genre Kiruna
genre_facet Kiruna
op_rights Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
cc-by-4.0
op_rightsnorm CC-BY
op_doi https://doi.org/10.11583/dtu.19300001
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