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Ling Chen¹, Jiawei Wang¹, Mengyuan Zhu¹

¹State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, NO. 163 Xianlin Avenue, Nanjing 210023, China.

|November 3, 2024

概括

一个新的健康废水质量指数 (HEQi) 模型确定了废水评估的14个关键参数. 该模型突出了中国的区域差异,强调需要减少北方的传统污染物和中东地区的新兴污染物.

科学领域:

环境科学环境科学
水质管理水质管理
分析化学分析化学

背景情况:

传统的水质管理与新出现的污染物和废水处理厂 (WWTP) 排放中的生物毒性风险作斗争.
现有的方法可能无法充分解决现代废水排放带来的复杂风险.

研究的目的:

开发一种新的评估参数系统和健康废水质量指数 (HEQi) 模型来评估WWTP废水.
确定关键的常规,离子,生物毒性和新兴污染物参数,这些参数对于有效的水质管理至关重要.

主要方法:

从176个中国的水污染物中编制了一个包括9个常规参数,22个离子,25个生物毒性参数和54个新兴污染物的综合数据集.
四个聚类和五个分类算法应用于65个模型,通过半监督机器学习选择14个显著参数.
开发的HEQi模型与水质指数 (WQI),模糊合成评估 (FSE) 和以类似于理想解决方案的顺序偏好技术 (TOPSIS) 相比较.

主要成果:

总共有14个参数,包括TN,TP,NH4+-N,NO2--N,Se,SO42-,Caenorhabditis elegans体宽,72hpf斑马鱼胚胎化率,四环素,乙氨基,gemfibrozil,PFBA,PFHxA和HFPO-DA,被选择用于HEQi模型.
该HEQi模型证明了WWTP废水的有效分类.
区域分析表明,中国北部和东北部需要专注于减少常规参数 (特别是NO2-N),而中国中部和东部必须加强消除生物毒性和新出现的污染物.

结论:

与传统方法相比,HEQi模型提供了更准确和更全面的废水废水质量的评估.
该研究揭示了中国在废水处理方面存在着独特的区域挑战,需要定制的管理策略.
这项研究为改善水质评估和确保废水安全排放提供了创新的工具和见解.

关键词:

生物毒性生物毒性机器学习机器学习市政废水的城市废水.进行参数选.水质分类模型的水质分类模型.

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