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近年来,MF和超滤(UF)[1]在饮用水厂中得到了广泛应用,但其污染仍然是影响其运行的一个主要问题。因此,越来越多的水厂使用臭氧(O3)作为预氧化剂,以减轻膜污染[2],并减少消毒副产物的形成[3]。但是,由于臭氧难以完全矿化水体中的天然有机物(NOM)[4],因此,会形成各种降解中间产物[5]。在臭氧投加量适当时,臭氧预氧化可以降低有机物的分子质量(MW),进而提高后续混凝效果[6],并增加NOM的可生物降解性[7];相反,过量投加臭氧可能会将NOM氧化成难以通过混凝、活性炭吸附、生物降解、膜过滤和消毒[8]去除的极性产物。这不仅降低了预氧化效果,还会增加水厂的投资运营成本。因此,有必要合理控制臭氧投加量,进而在优化有机物氧化、控制膜污染的同时,降低水厂运行成本。
然而,由于缺乏合适的技术,许多水厂在实际生产过程中仅仅根据经验值控制臭氧投加量,这使得实际投加量与最佳臭氧投加量之间存在较大偏差[9]。因此,迫切需要开发一种适用于水厂的简便技术,通过对臭氧处理进出水水质的监测分析,实现对臭氧投加量的优化控制。而该技术的关键是水质的在线分析与数据处理。在各种现有水质监测技术中,紫外可见光谱是一种简单、易于操作且准确度高的技术,可用于NOM的快速分析。天然水体中的NOM含有不同类型的生色团,这些生色团的紫外-可见吸收光谱信号相互叠加,导致NOM通常没有特征吸收峰[10]。在常规水质分析中,UV254可用于评价芳香族有机物和共轭双键有机物的含量[11],而其与总有机碳浓度(DOC)的比值(SUVA254)则反映芳香族有机物占总NOM的比例[12-13]。然而,UV254只在单波长下获得,无法利用其他波长下的光谱信息。
近年来,随着LED灯源和光纤光谱仪技术的发展,基于紫外-可见全光谱的水质在线分析已逐渐成为可能。目前,某些水厂已采用在线浸没式的多光谱紫外可见分光光度计,实时监控溶解性有机碳(DOC)、SUVA254和光谱斜率等水质指标[13-14]。上述发现表明,采用多波长光谱分析可以获得水中不同NOM组分的更多信息。例如,275~295 nm处的光谱斜率(S275~295)与NOM的分子质量成反比[15],因而有研究[16]使用S275~295来解释DOM的高效尺寸排阻色谱数据。还有研究[12]表明,某些波段的光谱斜率与SUVA254和SUVA280具有良好的相关性。这些结果表明,多波长光谱参数与NOM的结构特征之间可能存在相关关系,而这种关系可以用于跟踪饮用水臭氧氧化过程中NOM的结构变化,并进一步用于臭氧投加量的控制。但是,要想使用这些实时光谱数据优化臭氧投加量,实现经济高效的NOM去除和膜污染缓解,还需要全面了解最佳臭氧投加量与特定光谱参数之间的关系。基于此,本研究采用不同浓度腐殖酸(HA)配置的模拟地表水,在接近水厂实际生产的连续流条件下,探究了预臭氧氧化过程中NOM组成变化与其光谱特征之间的关系,旨在确定合适的光谱参数和数据分析方法,为膜法水厂在实际应用中臭氧投加量优化提供参考。
基于微滤技术供水厂的臭氧预氧化前置工艺中臭氧投加量的优化
Optimization of ozone dosage in the pre-oxidation process of water treatment plants with microfiltration technology
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摘要: 通过臭氧预氧化降解水体中溶解性有机物(DOM)对DOM的氧化效果以及微滤(MF)膜污染的缓和效应进行了研究,并分析了臭氧氧化过程中光谱参数变化的规律,进而提出一种通过多目标优化模型确定最佳臭氧投加量的方法。结果表明,臭氧预氧化技术能够将中等分子质量的芳香类DOM转化为低分子质量的有机化合物,对应的UV254去除率最高可达90.34%,从而显著改变了MF进水的光谱特性。此外,臭氧预氧化还显著缓解了DOM造成的膜污染,膜污染指数(FI)最多可降低51.49%。根据上述结果可建立多目标优化模型,并用于确定臭氧预氧化-膜过滤工艺最佳臭氧投加量。根据层次分析法,对SUVA254、FI和臭氧利用率3个客观指标分配不同的权重,以满足不同饮用水厂的需求。此外,模型分析中可用光谱斜率作为SUVA254的替代参数,特别是S275~295 (R2=0.979 7),用UV254作为FI的替代参数(R2=0.879 9),进而简化模型系数的获取。以上研究结果可为水厂在实际应用中优化臭氧投加量、综合提高水处理效果、缓解膜污染并降低运行成本提供参考。Abstract: Through ozone pre-oxidation to degrade dissolved organic matter (DOM) in water, the efficiency of pre-ozonation for dissolved organic matter (DOM) removal and membrane fouling control were studied, and the variations in the UV-vis spectra of the treated water were analyzed. Furthermore, a multi-objective optimization model was proposed for identifying the optimal ozone doses for pre-oxidation. The results showed that pre-ozonation could transform aromatic DOM with medium molecular weight into small organics, the corresponding UV254 removal efficiencies could not exceed 90.34%, which significantly changed the spectral characteristics of the feedwater to the membrane filter. Moreover, pre-ozonation noticeably mitigated membrane fouling by DOM, and the fouling index (FI) decreased by no higher than 51.49%. Accordingly, the simplified multi-objective optimization model was developed to identify suitable ozone dosing for the integrated ozonation pre-oxidation -microfiltration process. Different weights were assigned to three objective factors, i.e., SUVA254, FI, and ozone utilization ratio through the analytic hierarchy process, to account for the diverse needs of drinking water treatment plants (DWTPs). To further simplify instrumental requirements, SUVA254 used in the model may be replaced with the spectral slope parameters, especially S275~295 (R2=0.979 7), and FI may be replaced with UV254 (R2=0.879 9). These findings provided useful guidance for DWTPs to optimize ozone dosage, comprehensively improve DOM removal, mitigate membrane fouling, and reduce operational costs.
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Key words:
- dissolved organic matter /
- membrane fouling /
- ozone dosing /
- pre-oxidation /
- spectral slope
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表 1 臭氧投加量与臭氧流量之间的关系
Table 1. Relationship between ozone dosage and ozone flow rate
臭氧流量/(L·min−1) 臭氧投加量/(mg·L−1) 0.020 0.73 0.040 1.45 0.075 2.72 0.150 5.45 0.300 10.89 0.450 16.34 0.600 21.78 表 2 不同指标的判断矩阵和权重分配
Table 2. Judgement matrix and weight distribution for different objective factors
指标i 指标j A 权重Wi SUVA254 臭氧
利用率FI SUVA254 1 0.5 0.5 0.629 961 0.2 臭氧
利用率2 1 1 1.259 921 0.4 FI 2 1 1 1.259 921 0.4 注:A表示SUVA254、臭氧利用率和FI 3个指标相乘后开3次方的结果。 表 3 不同权重分配和HA浓度下的最佳臭氧投加量
Table 3. Optimal ozone dosage with different weight settings and HA concentrations
序号 权重分配 不同HA浓度下的最佳臭氧投加量/(mg·L−1) SUVA254 FI 臭氧利用率 I II III IV V 1 0.2 0.3 0.5 0.7 1 1.5 2 2.5 2 0.3 0.2 0.5 1.5 1.7 2.1 2.6 2.9 3 0.5 0 0.5 2.5 2.6 3 3.7 4.1 4 0.2 0.4 0.4 2.1 2.5 3.1 3.6 3.9 5 0.3 0.3 0.4 2.8 3 3.6 4.2 4.5 6 0.4 0.2 0.4 3.2 3.4 4 4.7 5.1 7 0.6 0 0.4 3.8 4 4.6 5.8 6.5 8 0.2 0.5 0.3 4.4 4.5 5 5.4 5.5 9 0.3 0.4 0.3 4.6 4.8 5.4 6 6.2 10 0.4 0.3 0.3 4.8 5 5.7 6.5 6.9 11 0.5 0.2 0.3 5 5.2 5.9 7.1 7.7 12 0.7 0 0.3 5.1 5.4 6.3 8 9.2 13 0.6 0.2 0.2 7.1 7.2 8.2 9.9 10.9 14 0.8 0 0.2 6.8 7.2 8.4 10.8 12.4 注:Ⅰ、Ⅱ、Ⅲ、Ⅳ和Ⅴ分别代表HA 浓度为5、10、15、20和25 mg·L−1的模拟配水。 -
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