Probabilistic assessment of heavy metal risks in sewage sludge using BCR speciation and Bayesian networks.

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Bibliographic Details
Title: Probabilistic assessment of heavy metal risks in sewage sludge using BCR speciation and Bayesian networks.
Authors: Janaszek-Kowalik A; Kielce University of Technology, Faculty of Environmental Engineering, Geodesy and Renewable Energy, Tysiaclecia P.P. 7, 25-314, Kielce, Poland., Kowalik R; Kielce University of Technology, Faculty of Environmental Engineering, Geodesy and Renewable Energy, Tysiaclecia P.P. 7, 25-314, Kielce, Poland. Electronic address: rkowalik@tu.kielce.pl., da Silva AF; Department of Chemistry, Federal University of Technology-Paraná, Brazil (UTFPR), Avenida João Miguel Caram 3131, Jardim Morumbi, Londrina, 86036-370, PR, Brazil., Nešović A; University of Kragujevac, Institute for Information Technologies, Jovana Cvijića bb, 34000, Kragujevac, Serbia., Kozłowski T; Kielce University of Technology, Faculty of Environmental Engineering, Geodesy and Renewable Energy, Tysiaclecia P.P. 7, 25-314, Kielce, Poland., Kanuchova M; Faculty of Mining, Ecology, Process Control and Geotechnologies, Technical University of Kosice, Letna 9, 042 00, Kosice, Slovakia.
Source: The Science of the total environment [Sci Total Environ] 2026 Jul 25; Vol. 1041, pp. 181913. Date of Electronic Publication: 2026 May 29.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 0330500 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-1026 (Electronic) Linking ISSN: 00489697 NLM ISO Abbreviation: Sci Total Environ Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1879-1026
DOI:10.1016/j.scitotenv.2026.181913