登录 EN

添加临时用户

基于水质指纹溯源的工业园区水污染精准监管模式及实践

Precision Regulatory Model and Practice for Industrial Park Water Pollution Based on Water Quality Fingerprinting Source Tracking Technology

作者:柴一荻
  • 学号
    2019******
  • 学位
    硕士
  • 电子邮箱
    tru******com
  • 答辩日期
    2024.05.21
  • 导师
    吴静
  • 学科名
    工程管理
  • 页码
    102
  • 保密级别
    公开
  • 培养单位
    005 环境学院
  • 中文关键词
    工业园区;水质荧光指纹;水污染溯源;精细监管;联动执法
  • 英文关键词
    Industrial parks; Water quality fluorescence fingerprint; Pollution source tracing; Refined monitoring; Joint enforcement

摘要

工业园区是国家经济与产业高质量发展的重要支柱,但也带来了严重的水污染与环境风险。水质监测与污染溯源是防范工业园区水污染的关键,但存在预警周期长、溯源技术落后、监管模式粗放等突出问题。本研究针对工业园区监管需求,开发基于水质荧光指纹溯源技术的工业园区水污染全链条精细监管模式。以T市3个不同的典型监管场景下的工业园区为研究对象,建立污染源水质荧光指纹数据库与在线监管平台,进行水质实时预警和溯源。通过与工业园区监管部门、第三方溯源服务团队及园区企业联动,打造典型场景下水污染事件溯源案例,探索工业园区水污染监管新模式。主要研究内容及结论如下:(1)以水质荧光指纹技术为核心,按照“全面感知-精准溯源-联动执法”的原则,构建涵盖感知层、数据分析层、决策层、执行层四个关键环节的监管模式框架,整合水质监测与污染溯源数据,形成由水质荧光指纹预警及溯源数据驱动的多级联动监管模式。构建覆盖“污染源-排污通道-入河/入海排口-受纳水体”全链条的水污染监管体系,开发信息化平台,实现对园区水污染的全面预警和精准溯源,有效提升工业园区环境监管的实时响应能力和整体执行效率。(2)在T市A工业园区构建面向受纳水体的污染精细监管系统,对河水进行水质指纹在线监测和实时溯源。2021年6月至2023年3月期间,监测断面水质主要介于Ⅳ类至劣Ⅴ类之间,其中总磷污染最突出。水质荧光指纹受工业污染源影显著响。2022年上半年水质指纹预警次数较高,与常规水质指标吻合,表明该时期河水受到严重工业污染。2022年4月,系统及时预警总磷污染并精准识别了污染来源,形成了典型预警溯源案例。预警次数与总磷月均浓度相关性系数为0.654,溯源准确率为78%。(3)针对T市D、E工业园区监管分别构建面向污水管网和雨水管网的污染精细监管系统。D园区监管系统在2022年监测到两次明显的水纹强度和重金属浓度同步上升,该系统预警次数与重金属月均浓度相关性为0.42,溯源准确率达到87%。成功发现2次违规排污行为。E园区监管系统在2022年4月监测到较高的水纹强度,通过向上游管网进行排查溯源,确认某化工企业污水管网破裂导致水污染事件发生,为执法部门处理提供了重要依据,该溯源准确率也可达到87%。(4)该精细化监管模应用后,T市地表水水质改善,工业废水异常次数降低,监管系统对污染源形成了震慑效果,助力工业园区水环境持续向好。

Industrial parks are crucial pillars for the high-quality development of national economies and industries, yet they also pose serious water pollution and environmental risks. Water quality monitoring and pollution source tracing are key to preventing water pollution in industrial parks, but challenges such as lengthy warning periods, outdated tracing technologies, and crude regulatory models remain prominent. This study develops a refined, full-chain pollution control model for industrial parks based on water quality fluorescence fingerprint tracing technology, constructing an information platform that overcomes the limitations of traditional methods in integrating water quality monitoring and pollution tracing data. Focusing on industrial parks in three typical regulatory scenarios in City T, the study established a pollution source water quality fluorescence fingerprint database and an online monitoring platform, enabling real-time water quality alerts and pollution source tracing. By coordinating with industrial park regulatory agencies, third-party tracing service teams, and park enterprises, the study explored new models of water pollution control under typical scenarios, creating cases of pollution event source tracing. The main research contents and conclusions are as follows:(1) Centering on water quality fluorescence fingerprint technology and following the principle of "comprehensive perception-precise tracing-joint enforcement", a regulatory framework encompassing the sensing layer, data analysis layer, decision-making layer, and execution layer is constructed. This integrates water quality monitoring and pollution source tracing data, forming a multi-level joint enforcement model driven by water quality fluorescence fingerprint alerts and tracing data. An integrated pollution control system covering "pollution source - discharge channel - river/sea outlet - recipient water body" is developed, along with an information platform, to achieve comprehensive alerts and precise tracing of water pollution in parks, significantly enhancing the real-time response and overall efficiency of environmental regulation in industrial parks.(2) In Industrial Park A in City T, a refined pollution control system targeting recipient water bodies was established, conducting online water quality fingerprint monitoring and real-time source tracing. During the study period, the monitored water quality mostly ranged between Grade IV and below the lowest level of Grade V, with total phosphorus pollution being the most prominent. Industrial pollution sources significantly influenced water quality fluorescence fingerprints. In the first half of 2022, the high frequency of water quality fingerprint alerts correlated with conventional water quality indicators, indicating severe industrial pollution during this period. In April 2022, the system promptly alerted to total phosphorus pollution and accurately identified the pollution source, forming a typical alert and tracing case. The correlation coefficient between alert frequency and monthly average concentration of total phosphorus was 0.654, with a tracing accuracy rate of 78%.(3) For Industrial Parks D and E in City T, refined pollution control systems targeting the sewage network and stormwater network are respectively established. In 2022, Park D's monitoring system detected two significant incidents of simultaneous increases in water pattern intensity and heavy metal concentration. The correlation between the system's alerts and the monthly average concentrations of heavy metals was 0.42, with a traceability accuracy of 87%. Two instances of illegal discharge were successfully identified. In April 2022, the monitoring system in Park E observed a higher water pattern intensity, and by tracing upstream in the network, it confirmed that a rupture in a chemical company’s sewage network caused a water pollution incident. This evidence was crucial for the enforcement agencies, achieving a traceability accuracy of 87%.(4) Following the implementation of this refined monitoring system, he quality of surface water in City T improved, the number of industrial wastewater anomalies decreased, and the monitoring system created a deterrent effect on pollution sources, contributing to the continuous improvement of the water environment in industrial parks.