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使用同位素标记物和基于CEC的诊断指标,分离城市废水源

Ioannis Matiatos¹, George Amaxidis¹, Sergios Lagogiannis¹

¹Institute of Marine Biological Resources and Inland Waters, Hellenic Centre for Marine Research, 19013 Anavissos Attikis, Greece.

Environmental research

|February 26, 2026

概括

这项研究结合了酸盐同位素和令人关注的污染物 (CECs),以确定城市河流中的废水来源. 综合方法准确地归因人类的废水贡献,优于传统方法.

科学领域:

环境化学环境化学
水质监测水质监测
废水处理废水处理

背景情况:

城市河流面临来自多个废水源的复杂污染.
区分人类和动物的废水输入对于有效管理至关重要.
现有的诊断工具经常与重叠的污染信号作斗争.

研究的目的:

开发和验证城市河流废水源归因的新方法.
为了提高准确性,将同位素标记物与新出现的污染物 (CECs) 整合在一起.
评估检测到的污染物所带来的生态风险.

主要方法:

在两年内从五个城市河流站收集了每月的水样.
分析了酸盐同位素 (δ¹⁵N-NO_{3^-),常规水化学,以及一套CEC.}
使用贝叶斯混合模型与CEC衍生索引 (HWI,HI) 和源签名.

主要成果:

酸盐度和δ¹⁵N-NO_{3^-值表明下游废水的影响越来越大.}
仅凭同位素数据就无法区分人类和动物的废水来源.
综合方法揭示了所有地点的人类废水贡献>60%;高HI确定了医院废水.

结论:

将酸盐同位素与基于CEC的诊断指标相结合,在复杂的城市系统中显著提高了废水源归因.
CECs为同位素提供了补充信息,揭示了医院废水等来源.
这种方法对城市水质监测和管理有直接影响,突出了高的生态风险.

关键词:

贝叶斯混合模型是贝叶斯混合模型.新出现的污染物引起了人们的关注.诊断指标诊断指标酸盐的同位素是酸盐的同位素.城市河流城市河流废水来源归因废水来源归因

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