Developing a Predictive Understanding of Soot Formation in Wildfires

野火排放的煤烟颗粒对人类健康、农业、空气和水质以及全球和区域气候都有巨大的有害影响。燃烧过程对烟尘颗粒的组成和反应性、毒性、对农业生产力、作物价值和水质的影响、在大气中的处理、成核云的能力、大气寿命和传输以及光学和辐射特性都有很大的影响。此外，来自烟尘颗粒的大量辐射换热增加了控制和扑灭中到大规模野火的难度。气候变化导致的日益严重的干旱和荒地-城市界面的扩大进一步增加了大型和不可控野火的频率，造成了沉重的大气烟尘负荷及其影响。减少野火损失需要有效的方法来预测和控制火势蔓延。烟尘的辐射是野火传播模型的一个关键组成部分，但目前的模型不能准确地模拟烟尘形成的化学过程，很大程度上是因为严重缺乏对烟尘产生机制的理解。该项目的目标是通过有针对性的实验和建模来解决与野火相关的烟尘形成化学理解的空白，并获得足够的烟尘形成机制知识，以开发一个现实的子模型，用于纳入野火传播模型。对烟灰形成的先进的基本理解也有助于在广泛的条件下预测烟灰的形成，并用于诸如发动机，熔炉，锅炉和爆炸物等应用。该项目还将为下一代科学家和工程师提供培训，这些科学家和工程师将应对气候变化的挑战，以及在荒地-城市交界处日益频繁的大规模火灾。该项目的目标是：(1)确定最可能的煤烟形成的前体，导致颗粒表面生长的物种，以及野火期间颗粒形成和生长的机制；(2)建立生物源有机化合物和生物质热解和燃烧过程中煤烟形成的预测模型。真空紫外光电离气溶胶质谱法将用于探测生物源性有机化合物热解和燃烧过程中产生的前体和颗粒组成。与这些实验相关的颗粒大小分布将使用扫描迁移率粒度仪和颗粒体积分数来测量，光学性质将使用激光诱导白炽灯来测量。这些实验结果与理论研究相结合，将用于建立煤烟起始和生长的化学动力学模型。最重要的预期结果是改进了野火传播和排放预测中的烟尘形成和辐射传热子模型。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Soot particles emitted from wildfires have enormous detrimental effects on human health, agriculture, air and water quality, and global and regional climate. The combustion processes involved in soot-particle production strongly influence their composition and reactivity, toxicity, impact on agricultural productivity, crop value, and water quality, processing in the atmosphere, ability to nucleate clouds, atmospheric lifetime and transport, and optical and radiative properties. In addition, large radiative heat transfer from soot particles increases the difficulty of controlling and extinguishing medium- to large-scale wildfires. Increasing droughts from climate change and expansion of the wildland-urban interface further increase the frequency of large and uncontrollable wildfires responsible for heavy atmospheric-soot loading and their impact. Reducing wildfire damage requires effective methods to predict and control fire spread. Radiation from soot is a critical component of wildfire-propagation models, but current models do not accurately model soot-formation chemistry, largely because of a severe lack of understanding of soot-production mechanisms. The goal of this project is to address gaps in the understanding of soot-formation chemistry relevant to wildfires and gain enough knowledge of soot-formation mechanisms via targeted experiments and modeling to develop a realistic sub-model for incorporation into wildfire-propagation models. An advanced fundamental understanding of soot formation could also benefit predictions of soot formation under a wide range of conditions and for applications such as engines, furnaces, boilers, and explosives. This project will also provide training for the next generation of scientists and engineers who will tackle the challenges of climate change and the increasing frequency of large-scale fires at the wildland-urban interface.The objectives of this project are to (1) identify the most likely precursors to soot inception, species that lead to particle surface growth, and mechanisms for particle inception and growth during wildfires and (2) develop a predictive model for soot inception during pyrolysis and combustion of biogenic organic compounds and biomass. Vacuum-ultraviolet photoionization aerosol mass spectrometry will be used to probe the precursors and composition of particles generated during the pyrolysis and combustion of biogenic organic compounds. Particle-size distributions associated with these experiments will be measured using a scanning mobility particle sizer and particle volume fraction, and optical properties will be measured using laser-induced incandescence. The results of these experiments, coupled with theoretical investigations, will be used to develop a chemical kinetic model for soot inception and growth. The most significant expected outcome is the improvement soot-formation and radiative-heat-transfer sub-models in wildfire propagation and emissions predictions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.