Developing a Predictive Understanding of Soot Formation in Wildfires

野火排放的烟尘颗粒对人类健康、农业、空气和水质量以及全球和区域气候都有巨大的有害影响。烟尘颗粒生产中涉及的燃烧过程对其组成和反应性、毒性、对农业生产力、作物价值和水质的影响、大气中的处理、云成核能力、大气寿命和传输以及光学和辐射特性都有很大影响。此外，烟尘颗粒的大辐射换热增加了控制和扑灭中到大规模野火的难度。气候变化引起的日益严重的干旱和荒地-城市交界处的扩大进一步增加了导致大气中大量烟尘负荷及其影响的大火和无法控制的野火的频率。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关键组成部分，但目前的模型不能准确地模拟烟尘形成化学，这主要是因为严重缺乏对烟尘产生机制的了解。该项目的目标是解决与野火相关的烟尘形成化学理解方面的空白，并通过有针对性的实验和建模获得关于烟尘形成机制的足够知识，以开发一个现实的子模型，用于纳入野火传播模型。对烟尘形成有深入的基本了解也有助于预测在各种条件下以及在发动机、熔炉、锅炉和炸药等应用中的烟尘形成。该项目还将为下一代科学家和工程师提供培训，他们将应对气候变化和荒地-城市交界面上日益频繁的大规模火灾的挑战。该项目的目标是(1)确定最有可能产生碳烟的前体、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，以及(2)开发生物有机化合物和生物质热解和燃烧过程中碳烟形成的预测模型。真空-紫外光电离气溶胶质谱仪将用于探测生物有机化合物在热解和燃烧过程中产生的颗粒物的前体和组成。与这些实验相关的颗粒尺寸分布将使用扫描迁移率颗粒测量仪和颗粒体积分数来测量，光学特性将使用激光诱导白炽灯来测量。这些实验的结果，加上理论研究，将被用来开发烟尘起始和生长的化学动力学模型。最重要的预期成果是改进野火传播和排放预测中的烟尘形成和辐射热传输子模型。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.