Effects of geographical and anthropogenic factors on dissolved heavy metals distribution and tiered ecological risk assessment in the Yangtze River Basin

Abstract

Complex anthropogenic activities and geographic conditions in the Chang Jiang(Yangtze R.) Basin have led to significant spatial variations in dissolved heavy metal contents, posing potential threats to aquatic ecosystems. To investigate the ecological risks and drivers of dissolved heavy metals in the Chang Jiang(Yangtze R.) Basin, physicochemical indicators, heavy metals, and nutrient salts were collected and measured, and the ecological risk was evaluated by using a tiered ecological risk assessment and structural equation model (SEM) for driver analysis. The results revealed that the mean values of As, Pb, Cr, Zn, Ni, Cd, and Cu were lower than those of Class III, among which the coefficients of variation of Cd and Pb were greater than 100%, which were affected by human activities. Tiered ecological risk assessment, ranging from deterministic point estimation methods to probabilistic hazard quotient evaluation approaches, demonstrated that Zn poses a potential ecological risk to aquatic organisms and is the key contaminant driving ecological risk in the study area, whereas As, Pb, Cr, Ni, Cd, and Cu do not constitute adverse ecological risk. The results of the SEM revealed that T, elevation, and land use types were the main drivers of spatial variations in the levels of heavy metals, with standardized path coefficients of –0.82, 0.21, and 0.14, respectively. The results of this study can provide theoretical support for ecological risk assessment and driver analysis of dissolved heavy metal pollution, which is of great practical importance for surface water pollution prevention and water environmental protection.

Graphical abstract

Keywords

Chang Jiang(Yangtze R.) Basin / Heavy metals / Ecological risk / Monte Carlo / Structural equation model (SEM) / Drivers

Highlight

	● Tiered method can be used to evaluate the ecological risks of heavy metals.
	● Zn is the key pollutant driving ecological risks.
	● Structural equation model reveals the driving mechanisms of heavy metal pollution.
	● Temperature, elevation, and land use types highly influence heavy metal distribution.

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