【作者】 蒋伟；

【导师】 王紫雯； 柳景青；

【作者基本信息】 浙江大学 ， 市政工程， 2014， 博士

【摘要】 氧化还原电位(ORP)是水处理中常用的水质综合指标,可用来反映溶液体系的宏观氧化还原特性,具有便于研制价格低廉,操作方法简单,检测结果迅速准确等优点。本文的主要目的是完善给水管网铁释放机理,建立铁释放预测模型。本文利用室内小试针对氧化还原电位(ORP)与铁释放的相关性展开研究；分析并提出了铁释放ORP作用机理,并且基于此机理提出建立了铁释放预测模型；最终利用室内、室外管网中试平台对该预测模型进行验证。现有铁释放机理研究认为铁释放可分为好氧阶段与缺氧阶段。但由于缺乏定量研究,该机理尚未建立相应的数学模型,无法用于铁释放预测。本文利用由2条管龄不同的腐蚀管道制成的小试装置研究了不同影响因素及水平下(溶解氧、余氯、一氯胺、pH、温度、氯离子、硫酸根)铁释放与ORP的相关性。利用实验结果建立了铁释放的ORP预测模型。同时研究了铁细菌对铁释放的影响效果与ORP的关系。室内小试的实验结果表明：1.ORP与铁释放具有一定的相关性,ORP会因为铁释放量上升而下降,并且它也可以分辨出铁释放的好氧阶段与缺氧阶段。2.ORP与铁释放的相关性并不会因管材、水质条件变化的改变。3.因此ORP可以对复杂水质条件下的铁释放风险进行评价。ORP≤100mV,铁释放量超标；ORP>300mV,铁释放量达标。4.对于铁释放问题,ORP与铁细菌存在协同作用,ORP>100mV时,铁细菌对铁释放基本不存在影响；而ORP<100mV后,铁细菌对铁释放有明显的促进作用。基于上述实验结果与前人研究成果,本文提出了铁释放的ORP机理。本机理认为：1.ORP决定了二价铁的氧化速率,提高ORP会加快二价铁的氧化速率,减少铁释放量。2.当ORP低于临界值后,二价铁将无法被氧化,铁释放进入缺氧阶段。3.铁浓度上升会导致ORP下降。基于此机理,本文提出了铁释放的ORP预测模型,该模型认为水中的铁释放量与ORP符合指数模型。并可以根据ORP值对铁释放风险进行评价。利用室内、室外管网中试对该模型的准确性进行验证。实验结果表明该模型的准确性在不同季节、不同管材、不同管网位置、不同运行工况的情况下均得到了很好验证。更多还原

【Abstract】 As a common measurement in water treatment, oxidation reduction potential (ORP) is used to characterize the oxidation capacity of solution. It has many advantages such as easy to develop, low cost, simple operation method, and rapid and accurate test results.The object of this paper is to complete the theory systems of iron release from corroded iron pipes in drinking water distribution systems, and set up a forecast model about iron release. Relationships between ORP and iron release was investigated. Then a new ORP mechanism of iron release was analyzed and presented, and a new iron release prediction model based on the mechanism was established. Eventually the prediction model was validated in pilot-scale drinking water distribution systems.At present iron release can be divided into oxic and anoxic conditions. However, by lack of quantitative research, it doesn’t establish the corresponding mathematical model and it isn’t used to predict iron release. This paper examined correlations between iron release and ORP under different factors and levels (such as dissolved oxygen, free chlorine, monochloramine, pH, temperature, chloride, sulfate) using bench-scale pipe reactor made of two different service age corroded pipes. And according to results, iron release prediction model based on ORP was established. Meanwhile, relationship between influence of iron bacteria on iron release and ORP was investigated.Results indicate that:1. ORP correlates with iron release, ORP would decease by the amount of released iron increasing; it also can identify oxic and anoxic conditions of iron release.2. This correlation isn’t affected by changes of pipe scales and water quality.3. Consequently, ORP can assess risks of iron release under complex conditions. When ORP is below100mV, iron release seriously; However when ORP is greater than300mV, iron release is governed well.4. The effect of iron bacteria on iron release is influenced by ORP. When ORP is greater than100mV, the influence of iron bacteria on iron release is negligible. However, for ORP values lower100mV, iron bacteria would increase iron release. Based on these results and previous work, this paper puts forward the ORP mechanism of iron release. The ORP mechanism indicates that:1. The rate of reaction rate of ferrous to ferric is decided directly by ORP; Increasing ORP can enhance the reaction rate and reduce amount of iron release.2. If ORP is lower than the critical value, ferrous will not be oxide, iron release will be in anoxic conditions.3. Iron concentrations increasing would reduce ORP values. According the ORP mechanism the ORP prediction model of iron release was set up. The model that iron release and ORP accords with exponential model. And the risk of iron release could be evaluated by ORP values.The model was verified in pilot-scale drinking water systems. The results indicate that the accuracy of model is well validated in different factors such as seasons, pipes, locations and flow conditions.更多还原