Chemical Characterization of Volatile Organic Emissions from Complex Environmental Mixtures

摘要 复杂的环境物质对人类、动物和环境福利构成风险， 天灾人祸。没有两种灾难是相同的：污染物的成分和来源各不相同， 灾害地点在位置、蔓延速度、风化、气候和生态系统方面各不相同。这些因素有助于 环境污染物的复杂性，产生不可预测成分的复杂混合物。减轻 因此，这些复杂混合物造成的危害至关重要，因为受影响的人的健康 社区和第一响应者依赖于环境危害的表征， 分析技术。最近的广泛研究确定多环芳香族化合物（PAC）是 典型的环境污染物。PAC可用作复杂混合物的替代物，因为它们 是无处不在的持久性，可以通过传统的分析仪器来表征， 类似的化合物。分析指纹技术（GC-MS变体、GC-FID、FT-ICR MS等）和 计算实践大大提高了我们对环境污染物的理解，包括 然而，这些化合物的相当大一部分和成分的详细分子鉴定仍然存在 很难破译因此，这个整体项目的重点是开发分析到体外的 在灾害情景下收集的环境样品中，全面描述PAC的方法。 实现这一目标的目标有三个方面：首先，我们将对数百个 使用快速、非靶向离子迁移谱-质谱（IMS-MS），聚焦 以PAC组分为基础，全面鉴定单个分子成分。二、效果 随着时间的推移，环境风化对复杂混合物的化学成分和生物活性的影响将是 通过模拟环境中复杂化学品泄漏的案例研究进行评估。最后，我们将测试 各种按比例缩小的被动给药方法的相关性和可靠性， 复杂的物质和生物活性部分的完整表征。为了补充这项研究，我们 我建议在洛斯阿拉莫斯国家实验室（LANL）实习，以探索更多的分析特性 空气中的PAC部分在复杂的混合物。长波红外（LWIR）成像技术， 在LANL率先推出，使集中源的气体排放可视化，包括城市， 广泛的排放，现场羽流，最相关的这项研究，挥发性，空气中的化学物质，可能是 在灾难发生时释放。通过这种分析方法，单个挥发性有机化合物（VOC） 迄今为止鉴定的化合物已被收集到约700种成分的光谱库中。由协作 利用LANL，我们的目标是利用长波红外成像技术，通过靶向 PAC。我们假设，化学表征代表性复杂混合物的VOC部分将 最终改进风险评估，为灾害情景的减灾战略提供信息。

ABSTRACT Complex environmental substances pose risks to human, animal, and environmental welfare in the event of natural or manmade disasters. No two disasters are alike: contaminants vary in composition and source, and disaster sites vary in location, rate of spreading, weathering, climate, and ecosystem. Such factors contribute to the complexity of environmental pollutants, yielding intricate mixtures of unpredictable composition. Mitigation of hazards posed by these complex mixtures is therefore of the utmost importance, as the health of afflicted communities and first responders is dependent upon characterization of environmental hazards through analytical techniques. Extensive recent research identified polycyclic aromatic compounds (PAC) to be representative environmental contaminants. PAC can be used as a proxy for complex mixtures because they are ubiquitously persistent, can be characterized by traditional analytical instrumentation, and are structurally similar compounds. Analytical fingerprinting techniques (GC-MS variants, GC-FID, FT-ICR MS, etc.) and computational practices have considerably advanced our understanding of environmental pollutants, including PAC; still, a substantial fraction of these compounds and detailed molecular identification of constituents remain challenging to decipher. Therefore, this overall project is focused on the development of an analytical-to-in vitro approach to comprehensively characterize PAC in environmental samples collected from disaster scenarios. The aims to accomplish this are three-fold: first, we will conduct untargeted chemical analysis of several hundred environmental samples using rapid, untargeted ion mobility spectrometry-mass spectrometry (IMS-MS), focusing on the PAC fraction as a basis to comprehensively identify individual molecular constituents. Second, the effect of environmental weathering on the chemical composition and bioactivity of complex mixtures over time will be evaluated by a case study modeling a complex chemical spill in the environment. Finally, we will test the relevance and reliability of various scaled-down passive dosing methods to enable both in vitro toxicity testing of complex substances and complete characterization of the bioactive fraction. To supplement this research, we propose an externship at Los Alamos National Laboratory (LANL) to explore additional analytical characterization of the airborne fraction of PAC in complex mixtures. Longwave-infrared (LWIR) imaging, a technique that has been pioneered at LANL, enables visualization of gaseous emissions from concentrated sources, including city- wide emissions, field plumes, and most relevant to this research, volatile, airborne chemicals that may be released during disaster events. With this analytical approach, individual volatile organic compounds (VOCs) identified thus far have been collected into a spectral library of approximately 700 constituents. By collaboration with LANL, we aim to characterize the VOC fraction of environmental mixtures using LWIR imaging by targeting PAC. We hypothesize that chemically characterizing the VOC fraction of representative complex mixtures will ultimately improve exposure assessment to inform hazard mitigation strategies for disaster scenarios.