透水路面渗透物中半挥发性有机化合物的检测。

IF 1.8 Q3 WATER RESOURCES
Thomas P O'Connor
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引用次数: 2

摘要

美国环境保护署的爱迪生环境中心(EEC)有一个研究和示范透水停车场,由三种不同的透水系统组成:透水沥青、透水混凝土和透水互锁混凝土摊铺机。自2010年1月开始进行水质和水量分析。本文描述了半挥发性有机化合物(SVOCs)的分析,以确定碳氢化合物是否存在于通过渗透表面渗透的水中。在2010年2月8日至2013年4月1日的3年时间里,对11个日期采集的样本进行了SVOCs分析。结果大致分为三类:42种化学物质未被检测到;12种化学物质(11种化学试验)的检出率小于或小于10%;22种化学物质的检测频率为10%或更高(范围从10%到66.5%)。对22种观察最多的化学物质进行了基础和探索性统计分析。由于检测频率低,样品稀释度低,影响了检出限,统计分析受到限制。利用基础统计学的Kaplan-Meier估计方法,将三个可渗透表面的渗透数据作为非参数数据进行分析;使用Tarone-Ware比较假设检验时,不同路面类型的中位数浓度存在统计学上的差异。结果表明,根据观察到的多孔沥青渗透浓度是否大于、类似于或小于透水联锁混凝土摊铺机渗透浓度,可以划分出三组。识别出这三个基团,就可以对化学属性进行单向分析;八向水分配(logkow)、苯环数和分子复杂性均显著。利用Spearman秩序非参数法进一步检验了渗透液中22种最常观察到的化学物质的检测频率与化学属性之间的相关性;多孔沥青的检测频率与分子量(MW)、亨利常数(Henry’s constant)、对数K OW和分子复杂度呈显著相关,而两种透水混凝土的检测频率与化学参数无显著相关。通过对渗透中22种最常观测到的SVOC进行统计分析得出的结论表明,多孔沥青是低对数K OW和MW的化学物质的来源,是高对数K OW和MW的化学物质的汇,而两种类型混凝土的SVOC渗透浓度没有明显的规律。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Detection of Semivolatile Organic Compounds in Permeable Pavement Infiltrate.

Detection of Semivolatile Organic Compounds in Permeable Pavement Infiltrate.

Detection of Semivolatile Organic Compounds in Permeable Pavement Infiltrate.

The U.S. Environmental Protection Agency's Edison Environmental Center (EEC) has a research and demonstration permeable parking lot comprised of three different permeable systems: permeable asphalt, pervious concrete, and permeable interlocking concrete pavers. Water quality and quantity analysis has been ongoing since January 2010. This paper describes analysis of semivolatile organic compounds (SVOCs) to determine if hydrocarbons were in water that infiltrated through the permeable surfaces. SVOCs were analyzed in samples collected from 11 dates over a 3-year period, from February 8, 2010 to April 1, 2013. Results are broadly divided into three categories: 42 chemicals were never detected; 12 chemicals (11 chemical test) were detected at a rate of less than 10% or less; and 22 chemicals were detected at a frequency of 10% or greater (ranging from 10 to 66.5% detections). Fundamental and exploratory statistical analyses were performed on the 22 most observed chemicals. The statistical analyses were limited due to low frequency of detections and dilutions of samples, which impacted detection limits. The infiltrate data through three permeable surfaces were analyzed as nonparametric data by the Kaplan-Meier estimation method for fundamental statistics; there were some statistically observable differences in median concentration between pavement types when using Tarone-Ware comparison hypothesis test. A result was that three groups could be identified based on whether observed porous asphalt infiltrate concentration were greater than, similar to, or less than permeable interlocking concrete pavers infiltrate concentration. Identifying these three groups allowed one-way analysis on chemical attributes; the octonal water partitioning (logK OW), number of benzene rings, and molecular complexity were all significant. These 22 most observed chemicals in the infiltrate were further tested by Spearman rank order nonparametric for correlations between frequency of detection and chemical attributes; significant correlations were observed for porous asphalt frequency of detection and molecular weight (MW), Henry's constant, log K OW and molecular complexity, while both permeable concretes did not have any significant correlations between frequency of detection and chemical parameters. Conclusions from the statistical analyses on the 22 most frequently observed SVOCs in the infiltrate indicate that porous asphalt acts as a source for chemicals with low log K OW and MW and a sink for chemicals with high log K OW and MW, while no significant pattern was observed in the SVOC infiltrate concentrations of the two types of concrete.

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CiteScore
3.80
自引率
15.80%
发文量
37
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