给水管网中污染物的存在形式、溯源特性及解决方案研究现状

Research Progress on Pollutant Occurrence Forms, Source Tracing Characteristics and Countermeasures in Water Distribution Systems

摘要: 给水管网作为连接水厂与用户终端的关键基础设施，其内部污染物来源复杂、形态多样，迁移与转化过程相互耦合，长期以来制约着饮用水的安全供给。本文围绕管网中污染物的赋存形态展开综述，涵盖悬浮态颗粒物、溶解态金属离子、管壁腐蚀产物、消毒副产物(DBPs)、生物膜及病原微生物等主要类型；在此基础上，分别沿水力模型驱动、机器学习数据驱动以及化学–生物指纹示踪三条技术路径，对现有污染溯源方法的原理与适用条件进行了评述；此外，从管材更新、水力调度优化、消毒工艺协同以及在线监测预警等方面探讨了管网污染控制的可行策略。本文认为，管网污染防控的重心应当从被动应急逐步转向主动预防，而实现这一转变的关键在于打通从水源到用户终端各环节之间的信息壁垒，推动监测手段、仿真模型与数据分析方法的协同融合。

Abstract: Water distribution networks (WDNs), serving as critical infrastructure connecting treatment plants to end users, are subject to complex contamination processes characterized by diverse pollutant sources, multiple occurrence forms, and coupled migration-transformation mechanisms, which have long posed challenges to the safe delivery of drinking water. This paper presents a comprehensive review of pollutant occurrence forms within distribution systems, encompassing suspended particulate matter, dissolved metal ions, pipe corrosion products, disinfection by-products (DBPs), biofilms, and pathogenic microorganisms. Building upon this foundation, the current state of contamination source identification methodologies is critically evaluated along three technical pathways: hydraulic model-driven simulation-optimization approaches, machine learning-based data-driven methods, and chemical-biological fingerprint tracing techniques, with particular attention to their underlying principles and applicable conditions. Furthermore, feasible strategies for pollution control in distribution networks are discussed from the perspectives of pipe material renewal, hydraulic scheduling optimization, synergistic disinfection process control, and online monitoring with early warning systems. This review argues that the focus of WDN contamination management should progressively shift from reactive emergency response toward proactive prevention, and that the key to achieving this transition lies in bridging the information gaps across all stages from source water to end-user taps, and in promoting the deep integration of monitoring technologies, simulation models, and data-driven analytical methods.