Abstract:

Core sediment samples collected from three distinct areas of Taojia Lake in Songzi County, Hubei Province, were tested for heavy metals including copper (Cu), zinc (Zn), chromium (Cr), nickel (Ni), lead (Pb), and arsenic (As), as well as grain size. The contamination status was assessed using the potential ecological risk index (RI), enrichment factor (EF), and geo-accumulation index (Igeo). Sources of these contaminants were traced through correlation analysis and positive matrix factorization (PMF) modeling. Results indicated that 1) Heavy metal contamination was most severe in the central area of the lake, followed by those in lakeshore and riparian zone in descending order. As depth increased, the contamination at lakeshore alleviated, but aggravated in the central area and the riparian zone. 2) Among the tested heavy metals, arsenic (As) and chromium (Cr) showed the most severe contamination, with As of light contamination and Cr mild-to-moderate contamination. Copper (Cu), zinc (Zn), nickel (Ni), and lead (Pb) exhibited less pollution. 3) Correlation analysis and PMF modeling revealed that heavy metals in the sediments primarily originated from mining activities (18.8%), natural sources (52.4%), and agricultural and industrial activities (28.8%). Specifically, Cu was mainly derived from mining activities, Pb from natural sources, and As from agricultural and industrial activities. Zinc (Zn), nickel (Ni), and Cr were influenced by all three sources. 4) Hydrodynamic conditions and human activities have led to spatial variations in heavy metal distribution in Taojia Lake. The strong hydrodynamics in the riparian zone have diluted heavy metal concentrations, resulting in lower heavy metal levels compared to the lakeshore and the central area. Changes in hydrodynamic conditions affected the vertical distribution of Pb and Ni. Variations in the distribution of Cu and Zn are primarily attributed to mining industrial activities, while annual increases in As levels were linked to agricultural activities.

Key words: sediment, heavy metals, pollution assessment, ecological risk, source analysis