[Distribution and Sources of Heavy Metals in the Sediments of Tributaries of the Yangtze River in the Nanjing Section].

Abstract

The heavy metal pollution in the sediments of tributaries directly affects the water quality of the Yangtze River. To investigate the distribution characteristics and pollution sources of heavy metals in the sediments of the incoming rivers in typical cities of the lower Yangtze River, the Nanjing section of the Yangtze River was selected as the study area. Sediment samples were collected from 16 monitoring points, and the monitoring data for As, Hg, Cr, Pb, Cd, Cu, and Zn were statistically analyzed. The potential ecological risk index method and the geo-accumulation index method were used to comprehensively evaluate the heavy metals in the sediments of the incoming rivers. Pearson correlation analysis and positive matrix factorization （PMF） were employed to analyze the sources of heavy metals in the sediments. The results indicated that the average values of seven heavy metals in the sediments of the incoming rivers were generally higher than those in the Yangtze River sediments, with all heavy metal coefficients of variation in the incoming river sediments exceeding 40%, indicating strong spatial heterogeneity. The primary heavy metal in the incoming river sediments in the Nanjing section of the Yangtze River was Cd, and the accumulation level and potential ecological risk of heavy metals in the Shitou River sediments were significantly higher than those in other incoming rivers. From upstream to downstream in the Nanjing section of the Yangtze River, the potential ecological risk index gradually increased, showing a spatial distribution characteristic of "lower upstream, higher downstream." When P < 0.01, Pearson correlation analysis indicated significant positive correlations among multiple heavy metals, suggesting that they may share common pollution sources. The results of the positive matrix factorization method （PMF） indicated that the main pollution sources of the incoming rivers included industrial pollution （26%）, agricultural pollution （29.7%）, and transportation （29.5%）, with the remaining 14.8% attributed to natural sources.