Recent advances in pollution source identification technologies in municipal drainage pipe networks
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摘要:
城市市政排水管网污染源种类繁多且难以辨析，在未明确污染源前提下进行污染控制通常会因缺乏针对性而导致效果不佳，目前尚缺乏对已有管网污染物溯源技术的系统梳理，难以快速准确根据污染场景确定相应的溯源技术。系统综述了现有城市市政排水管网污染物溯源技术，包括物理排查法、特征因子法和水纹识别法等，阐明了各种典型技术方法的原理及在管网污染物溯源研究中的应用现状，比较了各溯源技术的优劣性及其应用场景，最后对管网溯源技术的未来研究方向进行了展望。针对排水管网内污染源错位问题，可在对管网物理排查的基础上，耦合使用数值模拟法、水纹识别法及特征因子法，确定目标溯源管段、可能排放行业以及具体排水户等，再结合稳定同位素法，厘清污染物的产生、输送及排放特性。本研究旨在为高效识别污染源位置、源强及排放过程提供基础支撑。
Abstract:The pollution sources in municipal drainage pipe networks are usually diversified. It is of great difficulty to distinguish the various pollution sources. Generally, if the pollution sources are not well identified, the pertinence of pollution control might be impaired. Therefore, it is likely that the mitigation effects will not be satisfactory. Up to now, there still lacks a systematical overview with a focus on the present pollution source identification technologies in municipal drainage pipe networks, which might make it difficult to determine the corresponding traceability technologies according to the pollution scenes quickly and accurately. The existing pollution source identification technologies in municipal drainage pipe networks were systematically reviewed, including the physical investigation, marker species, and water fingerprinting methods, etc. The principles and application status of each typical pollution traceability technology for pipe networks are well illustrated. In addition, the pros and cons of each technology and its application scenarios were compared. At last, the future research orientation of pollution identification technologies in pipe networks was prospected. Aiming at the dislocation of pollution sources in the drainage pipe networks, it was required to apply physical investigation primarily, and then to couple the numerical simulation, water fingerprinting, and marker species methods. Therefore, the target pipe sections, possible discharge industries, and specific drainage entities could be determined. The production, transportation, and discharge characteristics of pollutants could be further clarified using the stable isotope method. This study could provide fundamental support for the efficient identification of the location, intensity, and discharge process of the pollution sources.
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表 1 物理排查法技术特点
Table 1. Characteristics of different physical investigation methods
技术 方法 最适条件 限制条件 物理
检查流量监测 相对独立的排水片区；市政排水管网资料缺乏 流量监测空缺期难以避免，逐段流量观测成本高 烟雾测试 雨水管与生活污水排水管混接；识别由雨水管
破损带来的地下水污染易引起公众恐慌，难以检测所有非法连接及违规排放 染料测试 准确识别污水接入雨水管情况；排水面积小
（小于10家排水户为最佳）；由个体排水户排放
污水、商业或工业用地需收集详细排水管网资料并获取进入管网节点处
施工权限，部分排水户难以进入光纤分布式温度传感 准确识别生活污水接入雨水管情况；无需进入排水户 无法判断工业废水等其他污水错混接入雨水管情况 视频识别 持续排水；排水仅排入单管管段；社区内已有用于其他调查工作的设备 设备相对昂贵；难以捕捉无流水的排水，难以捕捉
其他汇入雨水管的排水管网
探查潜水检测 管径不小于1 200 mm，流速不大于0.5 m/s 工作人员安全风险较大，准确度难以保证 目视检测 管道结构性或功能性缺陷明显 效率低，准确度难以保证 简易工具检测 根据检查目的和管道运行状况选择合适工具 效率低，准确度难以保证 管道内窥摄像检查技术（CCTV）机器人检测 适用管道管径为100~2 000 mm；
直观获取图像信息无法检测深层缺陷 管道潜望镜（QV）检测 辅助CCTV检测 无法检测水面下结构，单次探测距离较短 管道声呐检测 适用于水面以下管道状况检测 无法检测水面上结构 
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表 2 城市市政排水管网不同污染源的特征因子参考浓度
Table 2. Reference concentrations for different pollution source marker species of urban municipal drainage pipe networks
特征因子 生活
污水1)黑水 灰水 地下
水工业废水 地表
径流管渠
污泥数据
来源半导体
企业水产品
加工植物油加工 焙烤
食品
制造
（膨化）焙烤
食品
制造
（糕点）豆制品
加工乳制品
制造方便食
品制造总大肠菌群
数/（个/L）2.0×108 5.8×109 8.9×104 184 217 文献
[24,27-29]粪大肠菌群
数/（个/L）>106 1.7×107~
8.5×1094.9×104 55 123 大肠埃希氏菌
数/（个/L）6.4×107 2.1×109 2.0×104 <100 46 钾浓度/（mg/L） 37.7±7.5 23.6±6.6 135±4 397±23 505±17 18±2 525±135 386±22 52±20 文献
[30-31]钠浓度/（mg/L） 43.8±10.7 38.7±11.6 350±70 56±15 476±32 162±29 376±71 46±5 164±84 氯化物浓度/（mg/L） 189.0±21.8 68.2±7.5 1 012±90 140±10 582±107 77±7 573±38 46±4 257±70 心得安
（对映体分数）0.50±0.02 文献[32] LAS与NH3-N浓度比值（LAS/NH3-N）2） 0.06 1.6 0 文献[33] NH3-N与钾浓度比值
（NH3-N/K）1.8 0.18 0.06 镁与钾浓度比值（Mg/K） 0.4 1.1 2.2 TN浓度/（mg/L） 53.4±8.5 5.0±2.3 19.5±2.8 文献[21] 乙磺胺浓度/（μg/L） 15.1±8.8 0.020± 0.002 1.560±0.032 氟化物浓度/（mg/L） 0.36±0.09 0.37±0.16 10.6±1.41 硬度/（mg/L） 162±24 416±50 92.8±10.8 锌与磷浓度比值（Zn/P） 0.08 0.92 0.44 文献[34] NH3-N与锌浓度比值
（NH3-N/Zn）91.51 3.35 12.82 磷与钾浓度比值（P/K） 0.26 0.15 0.34 1)生活污水根据来源分为黑水和灰水2类。黑水指卫生间粪污及冲厕混合废水，灰水指厨房、浴室、洗手池及洗衣房等排放的废水[35]。2）LAS为阴离子表面活性剂。
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表 3 城市市政排水管网污染物溯源技术优劣及应用场景
Table 3. Advantages and disadvantages of pollutant traceability technologies in urban municipal drainage network and their application scenarios
方法 优越性 局限性 应用场景 物理
排查法可直接探清市政管网主要结构问题，包括错/混接、漏损等；仅需监测水质、水量常规指标；可精准追溯产生污染的具体排水户 管网水体水质与污染排放源之间为非简单线性关系；管网内窥检测技术成本较高；难以鉴定非直接排放源 污水处理厂进水浓度偏低；合流制排水系统雨季溢流污染严重；初期雨水污染负荷重 特征
因子法准确定性、定量分析雨/污管网错/混接类型；监测工作量较小，可仅监测污染源相关特征因子 难以准确厘清复杂污染源；水化学参数稳定性相对较差，仅可在特定场合使用；仅能判断贡献大的污染源，无法得到污染源对水体的质量贡献 污染源存在特征因子；污染源之间特征因子值差异显著 水纹
识别法可兼容在常规监测系统中；可迅速定位
可能导致管网水质异常的工业企业难以对不具有水纹特性的水样发生响应 工业废水污染物溯源；水污染事件预警
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