He Liwei, Chen Guangye, Wang Xinze, Shen Jian, Zhang Hongjiao, Lin Yuanyuan, Shen Yang, Lang Feiyan, Gong Chenglei
Yunnan Dali Research Institute of Shanghai Jiao Tong University, Dali 671000, China.
School of Chemistry and Chemical Engineering, Kunming University, Kunming 650214, China.
Toxics. 2024 Apr 29;12(5):322. doi: 10.3390/toxics12050322.
To explore the contamination status and identify the source of the heavy metals in the sediments in the major inflow rivers of Dianchi Lake in China, sediment samples were collected and analyzed. Specifically, the distribution, source, water quality, and health risk assessment of the heavy metals were analyzed using correlation analysis (CA), principal component analysis (PCA), the heavy metal contamination factor (), the pollution load index (), and the potential ecological risk index (). Additionally, the chemical fractions were analyzed for mobility characteristics. The results indicate that the average concentration of the heavy metals in the sediment ranked in the descending order of Zn > Cr > Cu > Pb > As > Ni > Cd > Hg, and most of the elements existed in less-mobile forms. The was in the order of Hg > Zn > Cd > As > Pb > Cr > Ni; the accumulation of Hg, Zn, Cd, and As was obvious. Although the spatial variability of the heavy metal contents was pronounced, the synthetical evaluation index of the and both reached a high pollution level. The PCA and CA results indicate that industrial, transportation, and agricultural emissions were the dominant factors causing heavy metal pollution. These results provide important data for improving water resource management efficiency and heavy metal pollution prevention in Dianchi Lake.
为探究中国滇池主要入湖河流沉积物中重金属的污染状况并确定其来源,采集并分析了沉积物样本。具体而言,利用相关性分析(CA)、主成分分析(PCA)、重金属污染因子()、污染负荷指数()和潜在生态风险指数()对重金属的分布、来源、水质及健康风险评估进行了分析。此外,还对化学形态进行了迁移特性分析。结果表明,沉积物中重金属的平均浓度排序为Zn > Cr > Cu > Pb > As > Ni > Cd > Hg,且大多数元素以迁移性较小的形态存在。 顺序为Hg > Zn > Cd > As > Pb > Cr > Ni;Hg、Zn、Cd和As的积累较为明显。尽管重金属含量的空间变异性显著,但 和 的综合评价指数均达到了高污染水平。PCA和CA结果表明,工业、交通和农业排放是造成重金属污染的主要因素。这些结果为提高滇池水资源管理效率和预防重金属污染提供了重要数据。