Classification and predictive leaching risk assessment of construction and demolition waste using multivariate statistical and machine learning analyses.

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Tác giả: Gianluca Bianchini, Andrea Bisciotti, Valentina Brombin, Giuseppe Cruciani, Yu Song

Ngôn ngữ: eng

Ký hiệu phân loại: 271.6 *Passionists and Redemptorists

Thông tin xuất bản: United States : Waste management (New York, N.Y.) , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 220649

Managing construction and demolition waste (CDW) poses serious concerns regarding landfilling and recycling because of the potential release of hazardous elements after leaching. Ceramic materials such as bricks, tiles, and porcelain account for more than 70% of CDW. Fourteen samples of different CDW products from Ferrara (Northeast Italy) were subjected to geochemical analyses, including leaching tests, in accordance with UNI EN 12457-2. The interaction between ceramics and concrete was examined, highlighting the influence of mixed environments on the leaching behavior. Results were compared with an extensive database of more than 150 samples collected from the literature on different CDW types worldwide. Multivariate statistical analysis and machine learning were used to classify the CDW compositions based on the bulk chemical data. Various metrics-contaminant factors (C
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