Estimation of debris waste generation
Notice bibliographique
Résumé
As of the beginning of 2022, Ukraine had approximately 8 million residential buildings with a total residential area of 892.1 million square meters. The number of apartments in residential buildings and non-residential structures in Ukraine totaled 15.5 million units. Due to hostilities and regular shelling, the number of damaged and destroyed residential buildings is increasing daily. As of January 2024, over 250,000 buildings have been damaged or destroyed, including 222,000 private homes, over 27,000 multi-apartment buildings, and 526 dormitories. The direct damage from the destruction of these objects is estimated at 58.9 billion USD. The regions with the most destroyed residential buildings include Donetsk, Kyiv, Luhansk, Kharkiv, Chernihiv, and Kherson. The generation of a large amount of debris waste requires planning for the demolition of destroyed buildings, dismantling of rubble, transportation to temporary waste storage sites, and the planning and selection of equipment for processing debris waste. Currently, Ukraine lacks an official methodology for estimating the volume of debris waste. To provide scientifically grounded methodological recommendations for estimating the amount of debris waste, the experience of various countries that have experienced technological disasters or natural disasters was studied, including Japan, Canada, and countries in the Middle East. The experience of managing debris waste in the communities of Chernihiv, Kyiv, and Mykolaiv regions was also examined. As a result of reviewing international experience, it was determined that the most appropriate approach is to use specific waste generation indicators per unit area – the waste generation rate. It is accepted that the area used to determine the volume of debris waste should be within the boundaries of the destruction or demolition (section, floor, or part of the building). A calculation of the waste generation rate was conducted based on the consumption of primary materials for typical series of multi-apartment residential buildings, monolithic-frame multi-apartment residential buildings, and residential buildings in cottage developments, including buildings of preschool and general secondary education institutions and hospitals.The resulting waste generation rates can be used to estimate the calculated amount of waste generated due to the damage or destruction of residential buildings, buildings of general secondary and preschool education institutions, and healthcare facilities as a result of hostilities, terrorist acts, sabotage, or work to eliminate their consequences. The waste generation rates do not apply to engineering structures, transportation infrastructure, or non-residential buildings.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».