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Portable analytical system employing tunable separation and microsensor array detection for indoor air quality monitoring.

机译:便携式分析系统采用可调分离和微传感器阵列检测功能,可进行室内空气质量监测。

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摘要

Exposure to air contaminants in non-industrial indoor workplaces has become a general public health concern. Among the contaminants found in such environments, volatile and semi-volatile organic compounds ((S)VOCs) have attracted the most attention because of their ubiquity and possible etiologic roles in sick building syndrome. Currently, determining the presence and concentrations of (S)VOCs rely on labor- and capital-intensive sample collection and laboratory analytical methods, which limit the quality and quantity of data collected. The primary goal of this research is to develop a portable indoor-air quality (IAQ analyzer for the determination of complex (S)VOC mixtures at low part-per-billion (ppb) concentrations.; The key features of the instrument are a multi-adsorbent preconcentrator/focuser, a dual-column, high-speed separation module with tunable retention capabilities, and a detector comprising a microfabricated sensor array whose output provides a characteristic ‘fingerprint’ of each analyte.; An emphasis is placed on the development of the preconcentrator/focuser. Results demonstrate that with proper design the tradeoffs between maintaining adequate capacity as well as efficient thermal desorption efficiency can be achieved. Variables affecting the performance of the preconcentrator/focuser are investigated and modeled, and it is shown that a 3-adsorbent bed containing only 12 mg of adsorbent material can quantitatively capture and thermally desorb more than 40 compounds at 100 ppb each in a 1 L sample volume.; The detector utilizes an array of three polymer-coated surface acoustic wave (SAW) sensors in addition to characterizing detector performance, an investigation is made of the fundamental mechanisms governing responses in such sensors, which arise from changes in the polymer mass and modulus upon vapor sorption. A previously established model is revised based on the new finding of a partition coefficient bias and the consequent recognition of the importance of free volume effects on sensor responses.; Through laboratory testing and modifications in the design of the prototype instrument, conditions are established for optimizing the separation, recognition, and quantification of the components of a mixture of 30 (S)VOCs at low-ppb concentrations. Chamber testing assesses performance as a function of environmental variables and concentration fluctuations and demonstrates that results are comparable to those obtained from standard methods.
机译:在非工业室内工作场所中接触空气污染物已成为普遍的公共卫生问题。在此类环境中发现的污染物中,挥发性和半挥发性有机化合物((S)VOC)由于其普遍存在和在病态建筑综合症中的可能病因作用而引起了人们的最大关注。当前,确定(S)VOC的存在和浓度取决于劳动和资本密集的样本收集和实验室分析方法,这限制了所收集数据的质量和数量。这项研究的主要目的是开发一种便携式室内空气质量(IAQ分析仪,用于测定低十亿分之一(ppb)浓度的复杂(S)VOC混合物。 -吸附剂预浓缩器/聚焦器,具有可调保留功能的双柱高速分离模块和检测器,该检测器包含微型传感器阵列,其输出可提供每种分析物的特征性“指纹”。结果表明,通过适当的设计,可以在维持足够的容量和高效的热脱附效率之间进行权衡,对影响预浓缩器/聚焦器性能的变量进行了研究和建模,结果表明,3-仅含12 mg吸附剂材料的吸附剂床可以定量捕获和热解吸1 L样品中40多种100 ppb的化合物v olume。该检测器除了表征检测器性能外,还利用三个由聚合物涂覆的表面声波(SAW)传感器组成的阵列,研究了控制此类传感器响应的基本机理,这些机理是由聚合物质量和蒸气模量的变化引起的吸附。基于分配系数偏差的新发现并因此认识到自由体积效应对传感器响应的重要性,对先前建立的模型进行了修改。通过实验室测试和对原型仪器设计的修改,为优化分离,识别和定量低ppb浓度的30种(S)VOC混合物的成分建立了条件。箱式测试根据环境变量和浓度波动评估性能,并证明结果与标准方法可比。

著录项

  • 作者

    Lu, Chia-Jung.;

  • 作者单位

    University of Michigan.;

  • 授予单位 University of Michigan.;
  • 学科 Health Sciences Occupational Health and Safety.; Engineering Environmental.
  • 学位 Ph.D.
  • 年度 2002
  • 页码 246 p.
  • 总页数 246
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 职业性疾病预防;环境污染及其防治;
  • 关键词

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