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利用信息收集规则数据库开发消毒副产物生成模型并进行解释。

Development and interpretation of disinfection byproduct formation models using the Information Collection Rule database.

作者信息

Obolensky Alexa, Singer Philip C

机构信息

Philadelphia Water Department Bureau of Laboratory Services, 1500 East Hunting Park Ave., Philadelphia, Pennsylvania 19124, USA.

出版信息

Environ Sci Technol. 2008 Aug 1;42(15):5654-60. doi: 10.1021/es702974f.

DOI:10.1021/es702974f
PMID:18754489
Abstract

Multiple linear regression models were used to examine relationships between water quality, treatment, and disinfection byproduct (DBP) formation in Information Collection Rule field data. Finished water models were specified using a cross-validation approach based on data for 225 free chlorine treatment plants. Turbidity, bromide, temperature, alkalinity, total organic carbon, ultraviolet absorbance at 254 nm, pH, chlorine residual, chlorine consumed, and chlorine contact time were employed as independent variables. Important trends within the trihalomethane, dihaloacetic acid, and trihaloacetic acid classes were observed. Bromide was a significant predictor for all DBP species and its influence changed in sign and magnitude with the extent of bromine substitution. A similar pattern followed by alkalinity suggested it plays an important role as an indicator of natural organic matter hydrophobicity and reactivity. Chlorine consumed and organic precursor variables were significant predictors in almost all DBP species models, exhibiting trends opposite to those for alkalinity and bromide. Temperature was the most significant variable in chloroform and chloral hydrate models and its significance declined with increasing bromine substitution within the trihalomethane class. pH had a strong positive influence on chloroform formation, a negative influence on trihaloacetic acid formation, and no influence on dihaloacetic acid formation.

摘要

使用多元线性回归模型来研究信息收集规则实地数据中水质、处理过程和消毒副产物(DBP)形成之间的关系。基于225个游离氯处理厂的数据,采用交叉验证方法指定了成品水模型。将浊度、溴化物、温度、碱度、总有机碳、254nm处的紫外线吸光度、pH值、余氯、耗氯量和氯接触时间作为自变量。观察到三卤甲烷、二卤乙酸和三卤乙酸类别中的重要趋势。溴化物是所有DBP种类的重要预测指标,其影响随着溴取代程度的变化而在符号和大小上发生改变。碱度呈现出类似模式,表明它作为天然有机物疏水性和反应性的指标发挥着重要作用。在几乎所有DBP种类模型中,耗氯量和有机前体变量都是重要的预测指标,呈现出与碱度和溴化物相反的趋势。温度是氯仿和水合氯醛模型中最显著的变量,并且随着三卤甲烷类别中溴取代程度的增加,其显著性下降。pH值对氯仿形成有强烈的正向影响,对三卤乙酸形成有负向影响,对二卤乙酸形成没有影响。

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