基于水质特征因子和Monte Carlo理论的雨水管网混接诊断方法  

Quantification of Non-Storm Water Flow Entries into Storm Drains Using Monte Carlo Based Marker Species Approach

作　　者：徐祖信[1] 汪玲玲[1] 尹海龙[1] 

机构地区：[1]同济大学污染控制与资源化研究国家重点实验室,上海200092

出　　处：《同济大学学报（自然科学版）》2015年第11期1715-1721,1727,共8页Journal of Tongji University:Natural Science

基　　金：国家水体污染控制与治理科技重大专项(2013ZX07304-002;2014ZX07303-003);上海市研发基地建设项目(13DZ2251700)

摘　　要：基于水质特征因子法,引入蒙特卡罗理论,建立了分流制排水系统雨污混接诊断的定量分析方法.以上海市某混接分流制排水系统为研究对象,采用安赛蜜和总氮、氟化物、硬度分别作为表征生活污水、半导体工业废水和地下水混接的水质特征因子,对雨水管网混接来源进行了解析.与观测值对比验证表明,由于蒙特卡罗方法考虑了混接来源中多个混接点空间质量浓度差异性以及测量误差等不确定性因素,与目前采用的确定性解析方法相比,可以显著提高解析结果的可靠性,在实现解析结果闭合的同时,解析误差能够控制在10%以内.据此,提出了建立水质特征因子数据库的指导原则.This paper proposed a Monte Carlo based method to quantify non-storm water flow entries into storm drains, in conjunction with mass balance of marker profiles between sources and exit. The proposed model was applied to a separate storm and sewer system in Shanghai, China. The sanitary sewage, semiconductor wastewater and groundwater with inappropriate entries into storm drains were quantified using acesulfame and total nitrogen, fluoride, total hardness as marker species respectively. Compared with the traditional deterministic approach, the proposed approach is able to account for the measurement errors and the impact of variability of the source marker profiles resulting from the spatial heterogeneities and therefore presents reliable source flow components that add up to 100%. Good precision was found between simulated and measured data, with a relative error of less than 10% in this case. The guideline to establish data library of marker species was also presented.

关 键 词：水质特征因子 雨污混接 旱流污染 蒙特卡罗分析 化学质量平衡 

分 类 号：X52[环境科学与工程—环境工程]