Impact of climate change on degradation risks in solid masonry walls: Uncertainty assessment using a multi-model ensemble

被引:1
|
作者
Vandemeulebroucke, Isabeau [1 ]
Kotova, Lola [2 ]
Caluwaerts, Steven [3 ,4 ]
Van Den Bossche, Nathan [1 ]
机构
[1] Univ Ghent, Fac Engn & Architecture, Bldg Phys Grp, UGent Campus UFO,Technicum T4,Sint Pietersnieuwstr, B-9000 Ghent, Belgium
[2] Helmholtz Zentrum Hereon, Climate Serv Ctr Germany GER, Chilehaus Eingang B,Fischertwiete 1, D-20095 Hamburg, Germany
[3] Univ Ghent, Fac Sci, Atmospher Phys Grp, UGent Campus Sterre-S 9,Krijgslaan 281, B-9000 Ghent, Belgium
[4] Royal Meteorol Inst Belgium, Dept Meteorol & Climatol Res, 3 Ave Circulaire, B-1180 Brussels, Belgium
基金
比利时弗兰德研究基金会;
关键词
Built environment; Hygrothermal simulations; Deterioration; Cultural heritage; Historic buildings; Energy retrofit; URBAN HEAT-ISLAND; WIND-DRIVEN RAIN; INTERIOR INSULATION; BUILT HERITAGE; BUILDINGS; STONE; PERFORMANCE; SIMULATION; GHENT; CMIP5;
D O I
10.1016/j.buildenv.2024.111910
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
In climate science, the impact of climate change is assessed through multiple climate models. Usually, hygrothermal analyses use one climate model, making the results only valid for this-highly uncertain-climate evolution, which cannot be generalised. The robustness of the climate change impact on building envelopes is unknown. Therefore, we implemented a multi-model ensemble in hygrothermal simulations for the first time. This paper presents 2160 hygrothermal simulation results to assess the change in degradation risks in solid masonry walls in Hamburg for 10 global-regional climate model chains. Firstly, the results are analysed in 8 ways, each featuring different information on the climate change impact, ensemble spread, and robustness. In Hamburg, the ensemble spread is assessed for the percentage of cases (i.e. building and exposure parameter combinations) with an in(de)creasing risk. For freeze-thaw damage, the spread is 52 % (69 %), indicating a high uncertainty. For wood decay in embedded beam heads, the spread is 28 % (18 %). The smallest spread, and most robust impact, is found for mould growth: 19% (10 %). Secondly, a methodological framework to determine the ensemble size as a trade-off between accuracy and computational demand is presented. The superior level, i.e. most detailed at high computational cost, requires minimum 10 ensemble members. The minimum level applies one climate projection. The advanced level requires 3 ensemble members, providing limited information on the robustness of the climate change impact. To conclude, climate models introduce uncertainty in the climate change impact on building envelopes. Multi-model ensembles should become state-of-the-art in hygrothermal modelling.
引用
收藏
页数:17
相关论文
共 50 条
  • [1] Climate change impact assessment on hydropower generation using multi-model climate ensemble
    Chilkoti, Vinod
    Bolisetti, Tirupati
    Balachandar, Ram
    RENEWABLE ENERGY, 2017, 109 : 510 - 517
  • [2] A multi-model ensemble approach for assessment of climate change impact on surface winds in France
    Najac, Julien
    Boe, Julien
    Terray, Laurent
    CLIMATE DYNAMICS, 2009, 32 (05) : 615 - 634
  • [3] A multi-model ensemble approach for assessment of climate change impact on surface winds in France
    Julien Najac
    Julien Boé
    Laurent Terray
    Climate Dynamics, 2009, 32 : 615 - 634
  • [4] Uncertainty Analysis of Climate Change Impact on River Flow Extremes Based on a Large Multi-Model Ensemble
    De Niel, Jan
    Van Uytven, E.
    Willems, P.
    WATER RESOURCES MANAGEMENT, 2019, 33 (12) : 4319 - 4333
  • [5] Uncertainty Analysis of Climate Change Impact on River Flow Extremes Based on a Large Multi-Model Ensemble
    Jan De Niel
    E. Van Uytven
    P. Willems
    Water Resources Management, 2019, 33 : 4319 - 4333
  • [6] CLIMATE CHANGE PROJECTIONS FOR THE PORTUGUESE VITICULTURE USING A MULTI-MODEL ENSEMBLE
    Fraga, Helder
    Santos, Joao A.
    Malheiro, Aureliano C.
    Moutinho-Pereira, Jose
    CIENCIA E TECNICA VITIVINICOLA, 2012, 27 (01): : 39 - 48
  • [7] Multi-model ensemble analysis of runoff extremes for climate change impact assessments
    Najafi, Mohammad Reza
    Moradkhani, Hamid
    JOURNAL OF HYDROLOGY, 2015, 525 : 352 - 361
  • [8] On the use of observations in assessment of multi-model climate ensemble
    Xu, Donghui
    Ivanov, Valeriy Y.
    Kim, Jongho
    Fatichi, Simone
    STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2019, 33 (11-12) : 1923 - 1937
  • [9] Development of multi-model ensemble approach for enhanced assessment of impacts of climate change on climate extremes
    Tegegne, Getachew
    Melesse, Assefa M.
    Worqlul, Abeyou W.
    SCIENCE OF THE TOTAL ENVIRONMENT, 2020, 704
  • [10] An assessment of a multi-model ensemble of decadal climate predictions
    Bellucci, A.
    Haarsma, R.
    Gualdi, S.
    Athanasiadis, P. J.
    Caian, M.
    Cassou, C.
    Fernandez, E.
    Germe, A.
    Jungclaus, J.
    Kroeger, J.
    Matei, D.
    Mueller, W.
    Pohlmann, H.
    Salas y Melia, D.
    Sanchez, E.
    Smith, D.
    Terray, L.
    Wyser, K.
    Yang, S.
    CLIMATE DYNAMICS, 2015, 44 (9-10) : 2787 - 2806