A comprehensive analysis and source apportionment of metals in riverine sediments of a rural-urban watershed

Abstract

Quantitative assessment of metal sources in sediments is essential for implementation of source control and remediation strategies. This study investigated metal contamination in sediments to assess potential ecological risks and quantify pollutant sources of metals (Cu, Zn, Pb, Cd, Cr, Co and Ni) in the Wen-Rui Tang River watershed. Total and fraction analysis indicated high pollution levels of metals. Zinc and Cd posed high ecological risk based on the risk assessment code, with the highest ecological risk found in the southwestern of the watershed. The positive matrix factorization (PMF) model was highly effective in predicting total metal concentrations and identified three contributing metal sources. An agricultural source (factor 1) contributed highly to Cu (74.1%) and Zn (42.5%), and was most prominent in the west and south-central portions of the watershed. Cd (93.5%) showed a high weighting with industrial sources (factor 2) with a hot spot in the southwest. Factor 3 was identified as a mixed natural and vehicle traffic source that showed large contribution to Cr (65.2%), Ni (63.9%) and Pb (50.7%). Spatial analysis indicated a consistent pattern between PMF-identified factors and suspected metal sources at the watershed scale demonstrating the efficacy of the PMF modeling approach for watershed analysis.

Quantifying Source Apportionment, Co‐occurrence, and Ecotoxicological Risk of Metals from Upstream, Lower Midstream, and Downstream River Segments, Bangladesh

“…Likewise, the spatial Moran's I index is also sensitive to outliers, although the I index is strongly suggestive of polluted sources. Xia et al (2020) and Dash et al (2020) found that disproportional events commonly influence the outlier values in sediment source studies, such as when an urban area is enclosed by commercial and residential sites. Thus, the PMF is highly sensitive to outlier values (Supplemental Data, Figure S5).…”

“…Appraisal of metal contamination status, co‐occurrence networks, source apportionment, and ecotoxicological risk evaluation (which are important environmental determinants) is essential for constructing efficient water security regulation and management strategies on a national basin scale. Several studies have appraised the pollution status and ecotoxicological risks of metals in riverine sediments in different parts of the world, for instance, Ustaoğlua and Islam (2020) in Giresun, Northeast Turkey, and Ji et al (2019) in Baiyangdian Lake, China (also see Bhuiyan et al 2017; Xu et al 2019; Khan et al 2020; Xia et al 2020). To determine different metal concentrations, numerous indices have been constructed, such as the geo‐accumulation index (Igeo), enrichment factor, risk index, and toxicity unit in riverine sediments (Siddiqui and Pandey 2019; Niu et al 2020).…”

“…Bhuiyan et al (2015) applied PMF and correlation matrix analysis to identify tannery, municipal, sewage, textile, and agricultural sources of metal in water and sediments in the Buriganga River (Bangladesh). Apart from the potential source types and percentage contribution of pollutants, a few studies have recently focused on the spatial distribution of intensity of possible sources (Xia et al 2020). Spatial characterization of metals through the PMF model can provide a comprehensive understanding of metals (Men et al 2019).…”

Characteristics and Assessment of Toxic Metal Contamination in Surface Water and Sediments Near a Uranium Mining Area

“…Results showed that Cr was significantly positively correlated with Pb (r = 0.951, p < 0.01) and Th (r = 0.803, p < 0.05). It suggests that the three metals (Cr, Pb, and Th) may have the same sources or sedimentary characteristics [39]. Concentrations of U are highly correlated with Th, which indicates that both of these metals might have originated from the uranium mining activities.…”

Quantification of Metal Contaminants and Risk Assessment in Some Urban Watersheds

“…Studies have shown that atmospheric deposition, vehicular transportation-related activities and metallic building envelopes resulting from agricultural, domestic and industrial activities are among the major pollution sources of urban watersheds [7] [8]. The partitioning of sources is further complicated by source interactions [9].…”