MICROANALYTICAL SYSTEM FOR INDOOR VOC MONITORING

描述：开发一款高性能的手持设备 一种可现场鉴定和定量的微量分析系统 低/亚ppb浓度的挥发性有机化合物 遇到的人为和微生物来源(VOCs和MVOCs) 提出了非工业室内工作环境。高级战略 对于样品采集，成分分离和检测将 集成到笔记本大小的可现场使用的仪器中 电脑。它将采用热调制双人床迷你 预浓缩器，用于蒸汽收集，可调，高速分离 模块，以及微机械弯曲板波(FPW)集成阵列 用于蒸汽识别和量化的传感器。预浓缩器将 将捕获的蒸汽分配到两个独立的多孔性聚合物吸附床上 系列，根据蒸汽压和吸附剂的亲和力，然后 以尖锐、离散的脉冲顺序地对它们进行热解吸。一系列 两个短的、高分辨率的微毛细管柱，每个柱上涂有 不同的固定相，将被用来分离混合组分。 柱温将针对每个预浓缩进行快速调整 分数。位于两柱交界处的调压阀 将允许对保留和分离进行预先编程的“调优”， 在&lt；60秒内完成多组分混合物的分离 预浓缩分数。六个部分选定的集成阵列 涂覆聚合物的FPW传感器将提供多通道检测 能力。人工神经网络将被用来识别和 根据反应模式和保留时间区分蒸气。 最多30种挥发性有机化合物混合物的浓度-时间分析曲线将 可在短至7-10分钟的测量间隔内获得并存储在 用于后续数据提取和归档的嵌入式计算机。 预浓缩、分离和分离的物理化学和统计模型 传感器响应将用于优化系统运行参数和 预测任何潜在暴露情景的表现。实验室检测 将展示连续测量复杂蒸气的能力 混合物。这一系统所体现的分析能力和通用性 代表着相对于当前最先进的 蒸汽监测仪器。大大降低了 将实现对室内VOCs和MVOCs的分析，消除对 常规吸附树脂管/气相色谱-质谱仪的采样与分析 监控。这反过来又将促进对暴露的评估。 合理分配和实施合理的干预策略 解决室内环境质量问题。

DESCRIPTION: The development of a high-performance, hand-held microanalytical system capable of on-site identification and quantification of low-/sub-ppb concentrations of volatile organic compounds of anthropogenic and microbial origin (VOCs and MVOCs) encountered in nonindustrial indoor working environments is proposed. Advanced strategies for sample collection, component separation, and detection will be incorporated into a fieldable instrument about the size of a notebook computer. It will employ a thermally modulated dual-bed mini preconcentrator for vapor collection, a tunable, high-speed separation module, and an integrated array of micromachined flexural-plate-wave (FPW) sensors for vapor recognition and quantification. The preconcentrator will partition captured vapors onto two separate porous-polymer adsorbent beds in series, according to vapor pressure and affinity for the adsorbent, and then thermally desorb them sequentially in sharp, discrete pulses. A series of two short, high-resolution micro capillary columns, each coated with a different stationary phase, will be used for separating mixture components. The column temperature will be rapidly adjusted for each preconcentrated fraction. A pressure modulation valve at the juncture of the two columns will permit preprogramed "tuning" of retention and separation, with a complete multi-component mixture separation performed in <60 sec for each preconcentrated fraction. An integrated array of six partially selected polymer-coated FPW sensors will provide multi-channel detection capabilities. Artificial neural networks will be used to identify and discriminate among vapors from their response patterns and retention times. Concentration-time analytical profiles for mixtures of up to 30 VOCs will be obtainable at measurement intervals as short as 7-10 min and stored in an embedded computer for subsequent data extraction and archiving. Physicochemical and statistical models of preconcentration, separation, and sensor responses will be used to optimize system operating parameters and to predict performance for any potential exposure scenario. Laboratory testing will demonstrate the capability for continuous measurement of complex vapor mixtures. The analytical power and versatility embodied in this system represent a significant advancement over the current state-of-the-art in vapor monitoring instruments. Dramatic reductions in the time cost of analyses of indoor VOCs and MVOCs will be realized, obviating the need for conventional sorbent-tube/GC-MS sampling and analysis for routine monitoring. This, in turn, will facilitate the assessment of exposure distributions and the implementation of rational intervention strategies to address indoor environmental quality problems.