A comprehensive risk assessment of metals in riverine surface sediments across the rural-urban interface of a rapidly developing watershed

Abstract

Metal contamination in aquatic environments is a severe global concern to human health and aquatic ecosystems. This study used several risk assessment indices, to evaluate metal (Cu, Zn, Pb, Cd and Cr) environmental risk of riverine surface sediments across the rural-urban interface of the rapidly developing Wen-Rui Tang River watershed in eastern China. Risk assessments were determined for 38 sites based on the potential ecological risk index (RI), consensus-based sediment quality guidelines (SQGs) and risk assessment code (RAC). Land-use cluster analysis showed that sediments were severely contaminated, especially for Cd, whose concentrations were~100 times higher than background levels and had a high proportion in the bioaccessible fraction. According to RI, E Cd r was identified with extremely high risk potential, resulting in the highest ecological risk of Cluster 4 (industrial). Similarly, risk within Cluster 4 (industrial) was also ranked highest by SQGs assessment due to the high proportion of industrial land use. Zinc was determined with high risk due to its high concentration compared to its effect range medium (ERM) value. Discrepancies in predicting environmental risks from metals among the three indices were mainly attributed to the contrasting definitions of these metrics. Environmental risk uncertainty derived from spatial variation was further estimated by Monte Carlo simulation and ranked as: Zn > Cd > Cr > Pb > Cu. This comprehensive environmental risk assessment provides important information to guide remediation strategies for management of metal contamination at the watershed scale.

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

“…For example, Ji et al (2019) detected a high ecological risk due to an elevated exchangeable metal fraction in Baiyangdian Lake (China) and Nemati et al (2011) identified medium and high risk for Zn and Cd in Sungai Buloh sediments by RAC index derived form a modified BCR sequential extraction procedure. Based on the perceived of the various metal fractions, several indices have been developed to provide comprehensive and reliable results for assessing potential metal toxicity risks from contaminated in sediments (Wang et al, 2019a). As an example, Siddiqui and Pandey applied a modified a modified contamination index to evaluate ecological risk associated with sediment metals at the basin-scale (Siddiqui and Pandey, 2019).…”

“…However, little information is available to quantify contributions derived from various pollution sources or to evaluate the spatial distribution of source apportionment. Our previous studies focused on the spatial distribution and qualitative contribution of pollution sources for metals based on land-use, population, industry (Wang et al, 2019a;Xia et al, 2018;Luo et al, 2019). This study builds on our previous studies with the primary objectives of (i) conducting risk assessments based on metal chemical fractions; (ii) analyzing the correlations among metals to qualitatively identify potential pollution source by PCA and co-occurrence network; (iii) exploring source types and quantifying the proportion of various sources for each metal and (iv) characterizing the spatial influence of source intensity at the watershed scale.…”

Mineralogy and heavy metal assessment of the Pietra del Pertusillo reservoir sediments (Southern Italy)

“…The study of heavy metal contamination in an aquatic environment has attracted increasing attention because of its abundance, persistence, and environmental toxicity (Sun et al 2016;Patel et al 2018;Wang et al 2019;Varol et al 2020). It has been observed that to define more accurately the quality of sediments potentially affected by heavy metals and pollutants, a correct option could be an intensive comparison of applied sediment quality guidelines (SQGs) (Burton 2018;Birch 2018;Liu et al 2019;Jones et al 2019).…”

Evaluation of nitrate pollution sources in surface water across the typical rural-urban interface: a case study of Wen-Rui Tang River, China

“…Different land-use categories may contribute different pollution sources to riverine nitrate. Original landuse categories were aggregated by merging similar land-use types into seven broader categories: vegetated land (forest, grassland and urban green belts), agriculture, commercial (cultural entertainment, commercial, administrative, municipal utility lands), industrial and mining, transportation, residential, and water (Wang et al, 2019). To better assess the sources in the selected watershed, hierarchical cluster method was used to group the sampling sites into different classes according to land-use proportions for sampling sites.…”