Developing a Predictive Understanding of Soot Formation in Wildfires

对野火中烟灰形成的预测性了解

• 批准号: 2328647
• 负责人: Hope Michelsen
• 金额: $ 38.37万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2328647&HistoricalAwards=false
• 关键词: Developing; Predictive; Understanding; Soot; Formation

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.

从野火发出的烟灰颗粒对人类健康，农业，空气和水质以及全球和地区气候的巨大有害影响。涉及烟灰生产的燃烧过程强烈影响其组成和反应性，毒性，对农业生产力，作物价值和水质的影响，大气中的加工，对云的构成能力，大气生命周期和运输以及光学和辐射特性。另外，大量的辐射热转移来自烟灰颗粒会增加控制和扑灭大规模野火的难度。由于气候变化和野生世界界面的扩张而增加干旱，进一步增加了负责大气较重的大气堆积及其影响的大型和不可控制的野火的频率。减少野火损害需要有效的方法来预测和控制火灾传播。来自烟灰的辐射是野火突出模型的关键组成部分，但是当前模型并不能准确地对烟灰化学进行建模，这主要是因为严重缺乏对烟灰生产机制的了解。该项目的目的是解决与野火相关的烟灰形成化学方面的差距，并通过有针对性的实验和建模来获得足够的了解烟灰形成机制，以开发现实的子模型，以纳入野火刺激模型。对烟灰形成的先进基本理解也可以使在广泛的条件下和应用等应用（例如发动机，炉子，锅炉和爆炸物）的应用下对烟灰形成的预测有益。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，以及在野生城市界面处大规模火灾的频率的增加。该项目的目标是（1）确定烟灰的前体，确定在颗粒表面的增长和在野性期间的粒子增长和（2）在野外的粒子增长和（2）在野外的机制（2））的（2），以实现野性和2）。生物有机化合物和生物量的燃烧。真空 - 耗分型光电定化气溶胶质谱法将用于探测在热解和生物有机化合物的热解和燃烧过程中产生的颗粒的前体和组成。与这些实验相关的粒度分布将使用扫描迁移率粒度和粒子体积分数来测量，并使用激光诱导的白炽灯测量光学性能。这些实验的结果以及理论研究将用于开发一种化学动力学模型，以实现烟灰的成立和生长。最重要的预期结果是在野火传播和排放预测中的改进烟灰形成和辐射加热转移子模型。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛影响的审查标准通过评估来通过评估来支持的。