How differentiating design strategies across building components lead to maximum reduction of adverse environmental impacts
Notice bibliographique
Résumé
Abstract Purpose The building sector is responsible for substantial adverse environmental impact and vast material consumption. Eco-design of buildings is a potential mitigation strategy; however, quantitative evidence of the mitigation potential is lacking. Therefore, the purpose of this study is to quantify the environmental consequences of applying multiple combinations of various eco-design strategies to a building, thereby providing new insights into eco-designing buildings and potential focal points to mitigate the environmental impacts of the building sector. Method A multi-step approach was used to quantify the environmental consequences of conjointly applying various eco-design strategies to a building. In this approach, combinations of the eco-design strategies were applied to eight different components of a case building, such as interior walls and floor separations. Life cycle inventories were compiled for the original building design and for when the combinations of eco-design strategies were applied. The inventories were used as input for a consequential LCA, quantifying the potential environmental impacts across 16 impact categories. The impacts were then summed up to represent the total impact of a building, resulting in almost 3 million different design scenarios, and thereby environmental impact scenarios. The results were interpreted using statistical analysis such as linear regression. Results and discussion Results show that to minimize adverse environmental impacts construction materials should be used in the following prioritized order, biotic materials, inert natural materials, inorganic materials, and finally reclaimed materials. The fact that reclaimed materials are the least favorable for impact reductions goes against the findings of previous studies. However, this is because previous studies apply attributional modeling, while this study appliesy consequential modeling. The results indicate that the impact category climate change, can be a good proxy for the overall impact reduction across categories. However, the results also show that the distribution of the impacts for the design scenarios differs greatly across the assessed impact categories, which would not have been identified if only focusing on climate change. Conclusions Noticeable impact reductions are observed when the same combination of eco-design strategies is applied to all building components; however, the greatest possible reductions are noticed when applying specific combinations to specific building components. We therefore recommended that building designers differentiate the design and material used for different types of building components. Furthermore, LCA practitioners should be included in the design process, to ensure that the proposed solutions contribute to mitigating adverse environment impacts.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».