The present study is aimed to detect and evaluate metal accumulation in the sediments of Meriç-Ergene Basin, which is an industry-intensive area in Turkey. Ten metals and Total Organic Carbon (TOC) concentrations were determined in sediment samples collected from forty-one different sampling points selected considering the pollutant source types and the flow direction from the upstream towards the downstream in July and December 2020 representing the dry and wet periods. Concentrations measured were evaluated in terms of pollution levels, relationship with each other and source distribution using risk indexes and various statistical techniques. According to the findings, TOC and metal concentrations in sediments taken from regions where industrial activities are concentrated were significantly higher. The values measured in these areas especially for chromium, copper and zinc were 8–11 times more of the reference regions. The index calculations showed that the pollution level at industry-intensive areas were enriched by cadmium, chromium, copper, lead, zinc and these particular regions had higher ecological risk than the agricultural areas and the reference site. Hierarchical Cluster Analysis (HCA) was performed to statistically categorize the sampling points and three common spatial distributions were obtained. Principal Component Analysis (PCA) was used to identify common sources of metals, and correspondingly, two common source groups were identified. Accordingly, there appeared a similar pattern and dense pollution in the sediments of the industrialized areas, and more than half of the metal load was found to be due to industrial activities and to the still active unsanitary landfills.

本研究旨在检测和评估土耳其工业密集区 Meriç-Ergene 盆地沉积物中的金属积累。在 2020 年 7 月和 2020 年 7 月和 12 月代表干湿期的污染物源类型和从上游向下游的流动方向选择的 41 个不同采样点收集的沉积物样品中，确定了 10 种金属和总有机碳 (TOC) 浓度. 使用风险指数和各种统计技术，根据污染水平、相互关系和源分布对测量的浓度进行评估。根据调查结果，取自工业活动集中地区的沉积物中的 TOC 和金属浓度明显较高。在这些区域测量的值，尤其是铬、铜和锌的值是参考区域的 8-11 倍。指数计算表明，工业密集区的污染水平富含镉、铬、铜、铅、锌，这些特定区域的生态风险高于农业区和参考地点。执行层次聚类分析 (HCA) 以对采样点进行统计分类，并获得三种常见的空间分布。使用主成分分析 (PCA) 来识别金属的常见来源，并相应地识别出两个常见的来源组。相应地，工业区沉积物出现了类似的格局和密集的污染，