Platikanov Stefan, Puig Xavier, Martín Jordi, Tauler Romà
Department of Environmental Chemistry, IIQAB-CSIC, Jordi Girona, 18-26, Barcelona 08026, Spain.
Water Res. 2007 Aug;41(15):3394-406. doi: 10.1016/j.watres.2007.04.015. Epub 2007 May 18.
Formation and occurrence of trihalomethanes (CHCl3, CHBr3, CHCl2Br, and CHBr2Cl) are investigated in water chlorination disinfection processes in the Barcelona's water works plant (WWP). Twenty-three WWP variables were measured and investigated for correlation with trihalomethane formation. Multivariate statistical methods including principal component analysis (PCA), multilinear regression (MLR), stepwise MLR (SWR), principal component regression (PCR) and partial least squares regression (PLSR) have been used and compared to model and predict the complex behavior observed for the measured trihalomethane concentrations. The results, obtained by PCA as well as the evaluation of the statistical significance of the coefficients in the linear regression vectors, revealed that the most important WWP variables for trihalomethane formation were: water temperature, total organic carbon, added chlorine concentrations, UV absorbance and turbidity at different sites of the WWP, as well as other variables like wells supply flow levels and carbon filters age. Overall, MLR and PLSR methods performed the best and gave similar good predictive properties. Best results were obtained for the total sum of trihalomethane concentrations, TTHM, with average modeling and prediction relative errors of 12% and 16%, respectively. Among the individual trihalomethanes, the concentrations of CHBr3 were the worst predicted ones with average modeling and prediction relative errors between 21-25% and 29-31%, respectively, followed by CHCl2Br with 23-26% and 25-27%. Better predictions were obtained for the concentrations of CHBr2Cl with relative modeling and prediction errors varying between 14-17% and 21%, and for the concentrations of CHCl3 with 21-24% and 23-25% errors, respectively.
在巴塞罗那自来水厂的水氯化消毒过程中，对三卤甲烷（CHCl3、CHBr3、CHCl2Br和CHBr2Cl）的形成与产生情况进行了研究。测量并研究了23个自来水厂变量与三卤甲烷形成之间的相关性。使用并比较了包括主成分分析（PCA）、多元线性回归（MLR）、逐步多元线性回归（SWR）、主成分回归（PCR）和偏最小二乘回归（PLSR）在内的多元统计方法，以对测得的三卤甲烷浓度所观察到的复杂行为进行建模和预测。通过主成分分析以及对线性回归向量中系数的统计显著性评估所获得的结果表明，自来水厂中三卤甲烷形成的最重要变量为：水温、总有机碳、加氯浓度、紫外线吸光度以及自来水厂不同位置的浊度，还有诸如井水供应流量水平和活性炭过滤器使用年限等其他变量。总体而言，多元线性回归和偏最小二乘回归方法表现最佳，具有相似的良好预测性能。对于三卤甲烷浓度总和（TTHM）获得了最佳结果，平均建模和预测相对误差分别为12%和16%。在各个三卤甲烷中，CHBr3的浓度预测效果最差，平均建模和预测相对误差分别在21 - 25%和29 - 31%之间，其次是CHCl2Br，分别为23 - 26%和25 - 27%。对于CHBr2Cl浓度的预测效果较好，相对建模和预测误差在14 - 17%和21%之间变化，对于CHCl3浓度的预测误差分别为21 - 24%和23 - 25%。
