ArticleToxics2025
Risk Assessment of Heavy Metals in Road-Deposited Sediments and Correlation Distribution of DOM and Heavy Metals in Beijing, China.
Article in Toxics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Machine learning-driven geochemical fingerprinting and risk characterization of mineral dust across different operational settings in El-Gedida Iron Mine, Egypt.Environmental geochemistry and health · 2025Article
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Authors and funding
8 authors.
Funding
Abstract
Road-deposited sediments (RDS) from 28 sites in Beijing were studied and analyzed for eight heavy metals. In RDS, the levels of Cr, Ni, Cu, Zn, As, Cd, Pb and V were 2.76, 1.11, 2.40, 1.65, 1.09, 6.52, 4.13 and 0.06 times the background values, respectively. The levels were rated in accordance with the geoaccumulation index (Igeo) as follows: Cd>Pb>Zn>Cu>Cr>Ni>As>V. In the four functional zones, the potential ecological risk index method showed that most of the heavy metals have environmental risk index values (Eri) of less than 40, but the multifactor environmental risk value (RI) for Pb in the transportation area exceeded 150. Four functional areas had Cd values greater than 160, exhibiting the highest risk. The human health risk assessment revealed that exposure pathways followed this decreasing order: ingestion > dermal > inhalation. Three DOM fractions were resolved in the sediments of the four functional zones, including terrestrial fulvic-acid-like fractions (C1), humic-acid-like fractions (C2), and tryptophan-like fractions (C3), and the DOM fractions were affected by both exogenous and endogenous sources. A positive correlation existed between DOM and Ni and Cu in the transportation zone, and the correlation between DOM and heavy metals in other zones was not apparent. In conclusion, heavy metals in different functional zones affected the concentration and characteristics of DOM, and there was a strong correlation between heavy metals and DOM concentration and features.
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