Characterizing the anthropogenic-induced trace elements in an urban aquatic environment: A source apportionment and risk assessment with uncertainty consideration
Publikation: Beitrag in Fachzeitschrift › Forschungsartikel › Beigetragen › Begutachtung
Beitragende
Abstract
The spatial distribution of water quality status, especially in water bodies near intensively urbanized areas, is tightly associated with patterns of human activities. For establishing a robust assessment of the sediment quality in an urban aquatic environment, the source apportionment and risk assessment of Cr, Mn, Ni, Cu, Zn, As, Cd, Hg, and Pb in sediments from an anthropogenic-influenced lake were carried out with considering uncertainties from the analysis methods, random errors in the sample population and the spatial sediment heterogeneity. The distribution analysis of the trace metals with inverse distance weighting-determined method showed that the pollutants were concentrated in the middle and southern areas of the lake. According to the self-organizing map and constrained positive matrix factorization receptor model, agricultural sources (24.8%), industrial and vehicular sources (42.5%), and geogenic natural sources (32.7%) were the primary contributors to the given metals. The geogenic natural had the largest random errors, but the overall result was reliable according to the uncertainty analysis. Furthermore, the stochastic contamination and ecological risk models identified a moderate/considerable contamination level and a moderate ecological risk to the urban aquatic ecosystem. With consideration of uncertainties from the spatial heterogeneity, the contamination level of Hg, and the ecological risk of Cd in had a 20–30% probability of the increase.
Details
Originalsprache | Englisch |
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Aufsatznummer | 111288 |
Fachzeitschrift | Journal of environmental management |
Jahrgang | 275 |
Publikationsstatus | Veröffentlicht - 1 Dez. 2020 |
Peer-Review-Status | Ja |
Externe IDs
PubMed | 32866925 |
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Schlagworte
ASJC Scopus Sachgebiete
Schlagwörter
- Positive matrix factorization, Self-organizing map, Stochastic risk assessment, Trace elements, Uncertainty analysis