基于不同水厂水质调查的消毒副产物生成趋势及模型预测

以南方某市具有代表性的7个自来水厂为研究对象，对不同季节和不同处理工艺下的原水、出厂水和管网水的9个常规水质参数和2类含碳消毒副产物进行了检测，考察了水质指标随季节的变化规律和处理工艺对不同水质指标的影响，分析了常规水质参数与消毒副产物生成量之间的关系。结果表明：7个自来水厂出厂水均检出三卤甲烷(trihalomethanes，THMs)和卤乙酸(haloacetic acids，HAAs)；THMs平均质量浓度为8.70~29.35 μg·L⁻¹，HAAs平均质量浓度为13.22~39.06 μg·L⁻¹；管网水中2类消毒副产物浓度水平较出厂水略有增加；THMs的季节变化规律为冬季>春季≈秋季>夏季，HAAs的季节变化性不强。利用IBM SPSS Statistics 20进行了Spearman秩相关系数分析，并分别以原水和出厂水水质参数来建立出厂水THMs或HAAs生成量的回归方程。结果表明：THMs质量浓度预测效果良好，可用于自来水厂水质的化学安全性预警；但对于HAAs质量浓度预测，无论采用原水还是出厂水水质参数所建立的预测方程，预测结果均不理想。

Disinfection by-products formation and model prediction based on water quality surveys of different drinking water treatment plants

In this study, 9 conventional water quality parameters and 2 types of carbon containing disinfection by-products of raw water, factory water and pipe water in different seasons and treatment processes were detected in 7 representative drinking water treatment plants (DWTPs). The variations of water quality with seasons and the removal effect of water treatment processes on water qualities were studied. The relationship between conventional water quality parameters and the amount of disinfection by-products was also analyzed. The results showed that trihalomethanes (THMs) and haloacetic acids (HAAs) were detected in factory water of 7 DWTPs. The average concentrations of THMs and HAAs were 8.70~29.35 μg·L−1 and 13.22~39.06 μg·L−1, respectively. There was a slight increase in the concentration levels of the two types of disinfection by-products in the pipe network water compared with the factory water. The seasonal variation of THMs was as follows: Winter > spring ≈ autumn > summer, and slight seasonal variation of HAAs occurred. Spearman rank correlation coefficient was performed using IBM SPSS Statistics 20, and the production water THMs or HAAs prediction equations were established based on the raw water and factory water quality parameters, respectively. The results found that the prediction effect of THMs concentration was good, which can be used to guide the chemical safety early warning of water quality in waterworks. But for HAAs concentration prediction, regardless of whether the prediction equations established by raw water or factory water quality parameters is used, the prediction results were not ideal and the correlation was poor.