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首页> 外文学位 >Development of a Novel Methodology for the Identification of VOC Emission Sources in Indoor Environments based on the Material Emission Signatures and Air Samples measured by PTR-MS.
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Development of a Novel Methodology for the Identification of VOC Emission Sources in Indoor Environments based on the Material Emission Signatures and Air Samples measured by PTR-MS.

机译：根据PTR-MS测量的材料排放特征和空气样品，开发一种用于识别室内环境中VOC排放源的新方法。

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摘要

One of the recent important challenges in the research field of indoor air quality is the identification of indoor Volatile Organic Compound (VOC) emission sources to clearly pinpoint the sources of concern in a field condition. This study represents the first attempt in developing a new technique to find the sources that may be invisible or hidden based on the inspection even of experts when a building with problems of indoor air quality is suspected. The objectives of this study were 1) to determine VOC emission signatures specific to nine typical building materials by using an on-line analytical monitoring device, Proton Transfer Reaction - Mass Spectrometry (PTR-MS), 2) to explore the correlation between the PTR-MS measurements and the measurements of acceptability by human subjects, 3) to develop and evaluate a methodology to identify individual sources of VOC emissions based on the measurements of mixed air samples and the PTR-MS material emission signatures, 4) to determine the long-term variation of VOC emission signatures over time, and 5) to develop a method to account for the long-term variation of emission signatures in the application of the emission source identification method. Samples of nine building materials were tested individually and in combination, including carpet, ceiling material, gypsum board, linoleum, two paints, polyolefine, PVC and wood. VOC emissions from each material were measured in a 50-liter small-scale chamber. Chamber air was sampled by PTR-MS to establish a database of emission signatures unique to each individual material. Sorbent tube sampling and TD-GC/MS analysis were also performed to identify the major VOCs emitted and to compare the resulting data with the PTR-MS emission signatures. The data on the acceptability of air quality assessed by human subjects were obtained from a previous experimental study in which the emissions from the same batch of materials were determined under the same area-specific ventilation rates as in the case of the current measurements with PTR-MS. The same task was performed to measure combined emissions from material mixtures for the application and validation of a signal separation methodology and its source identification enhancement by the consideration of long-term emissions. The methodology was developed based on signal processing principles by employing the method of multiple regression least squares (MRLS) and a normalization technique. Source models were employed to track the change of individual material emission signatures by PTR-MS over a long period of time. It is concluded that: 1) PTR-MS can be an effective tool for establishing VOC emission signatures of material types, and there were sufficient correlations (i.e. Correlation coefficient r -0.92 ) between the PTR-MS measurements and the acceptability of air quality for the nine materials tested when the sum of selected major individual VOC odor indices was used to represent the emission level measured by PTR-MS; 2) the proposed method for source identification could identify the individual sources at high success rates under laboratory conditions with two, three, five and seven materials present; and 3) the long-term (over nine months) variation of emission factors of the tested materials could be well represented by an empirical power-law model or a mechanistic diffusion based model, and the model coefficients could be estimated based on relatively a short-term set of emission measurements (i.e. within 28 days). The source models could also be used to predict the variation of material emission signatures, which could in turn be used for source identification. Further experiments and investigation are needed to apply the presented source identification method under real field conditions.
机译：室内空气质量研究领域中最近的重要挑战之一是识别室内挥发性有机化合物（VOC）排放源，以明确指出现场条件下的关注源。这项研究代表了一种新技术的首次尝试，即在怀疑室内空气质量存在问题的建筑物的基础上，甚至通过专家的检查，找到一种可能看不见或隐藏的污染源。这项研究的目的是1）通过使用在线分析监测设备质子转移反应-质谱（PTR-MS）确定9种典型建筑材料特有的VOC排放特征，2）探索PTR之间的相关性-MS测量和人类受试者的可接受性测量，3）根据混合空气样品的测量结果和PTR-MS材料的排放特征，开发和评估一种方法来识别VOC排放的个体来源，4）确定长时间VOC排放特征随时间的长期变化，以及5）开发一种在排放源识别方法的应用中解决排放特征的长期变化的方法。分别对9种建筑材料的样品进行了组合测试，包括地毯，天花板材料，石膏板，油毡，两种涂料，聚烯烃，PVC和木材。每种材料的VOC排放均在50升的小型室内进行测量。通过PTR-MS对室内空气进行采样，以建立每种材料唯一的排放特征数据库。还进行了吸附剂管采样和TD-GC / MS分析，以识别排放的主要VOC，并将所得数据与PTR-MS排放特征进行比较。人类受试者评估的空气质量可接受性数据来自先前的一项实验研究，在该实验中，与当前使用PTR-A测量的情况相同，在相同的区域特定通风率下确定了同一批材料的排放。多发性硬化症。进行了相同的任务，以测量材料混合物的总排放量，以考虑和应用信号分离方法，并考虑到长期排放，从而增强了信号源的识别能力。该方法是根据信号处理原理通过采用多元回归最小二乘（MRLS）和归一化技术开发的。使用源模型通过PTR-MS跟踪了长时间内单个物质排放特征的变化。结论：1）PTR-MS可以作为建立材料类型VOC排放特征的有效工具，并且PTR-MS的测量值与空气质量的可接受性之间具有足够的相关性（即相关系数r <-0.92）。对于使用所选主要主要VOC气味指数的总和表示通过PTR-MS测量的排放水平的9种材料； 2）提出的来源识别方法可以在实验室条件下以两种，三种，五种和七种材料在高成功率下识别出各个来源； 3）可以通过经验幂律模型或基于机械扩散的模型很好地表示被测材料的排放因子的长期（超过9个月）变化，并且可以基于相对较短的模型估算模型系数排放量测量的长期设置（即28天内）。源模型还可以用于预测物质排放特征的变化，进而可以用于源识别。需要进行进一步的实验和研究，以在实际条件下应用提出的源识别方法。

著录项

  • 作者

    Han, Kwanghoon.;

  • 作者单位

    Syracuse University.;

  • 授予单位 Syracuse University.;
  • 学科 Environmental Health.;Engineering Environmental.;Engineering Mechanical.
  • 学位 Ph.D.
  • 年度 2011
  • 页码 251 p.
  • 总页数 251
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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