Collaborative Studies on Soot Particle Formation and Characterization

煤烟颗粒是许多燃烧过程中不必要地排放的碳纳米颗粒。烟尘颗粒被认为是导致气候变化的第二大因素，并对人类健康造成不利影响，因为烟尘是一种致癌、遗传毒性和致畸污染物。该NSERC联盟寻求通过促进对烟尘形成物理的理解和数值模拟来促进减少燃烧产生的烟尘颗粒的排放。尽管烟尘排放的有害后果和减少烟尘排放的迫切需要，但在烟尘形成过程中仍然存在严重阻碍减排的关键知识缺口。为了促进对碳烟形成过程的理解，这个与瑞尔森大学和密歇根大学合作的国际NSERC联盟将整合两个现有的碳烟预测模型-一个专注于碳烟前体的化学增长，另一个专注于产生碳烟的燃烧的颗粒和流体动力学-创建一个新的、强大的预测工具。合成工具的应用将有助于阐明有利于碳烟形成的燃烧条件，为什么会这样，以及如何对其进行修改以最大限度地减少排放。预计这项研究的结果将1)加深对碳烟颗粒产生机理的基本理解，2)产生新的碳烟形成模型，显著提高预测的准确性、适用性和细节，以及3)有助于缓解与碳烟形成相关的环境和健康问题。通过这样做，这项研究将支持加拿大的环境努力，改善空气质量和人民的健康，并帮助加拿大工业实现大胆的减排目标。

Soot particles are carbon nanoparticles that are unnecessarily emitted from many combustion processes. Soot particles are considered the second worst contributor to climate change and adversely affect human health, as soot is a carcinogenic, genotoxic, and teratogenic pollutant. This NSERC Alliance seeks to facilitate the reduction in combustion-generated soot particle emissions by advancing the understanding and numerical modelling of the physics of soot formation. Despite the detrimental consequences of soot emissions and the pressing need for their reduction, there remains key knowledge gaps in the soot formation process that have severely inhibited reduction. To advance the understanding of the processes that lead to soot formation, this proposed international NSERC Alliance with Ryerson University in cooperation with the University of Michigan, will integrate two existing models for soot prediction - one focused on the chemical growth of soot precursors and the other focused on the particle and fluid dynamics of soot-producing combustion - to create a novel, robust predictive tool. The application of the resultant tool will help elucidate the combustion conditions that are conducive to soot formation, why they are so, and how they can be modified to minimize emissions. The outcomes of this research are expected to 1) lead to a stronger fundamental understanding of the mechanisms that produce soot particles, 2) produce new soot formation models with significantly enhanced predictive accuracy, applicability, and detail, and 3) help to mitigate the environmental and health issues associated with soot formation. In doing so, this research will support Canada's environmental efforts, ameliorate the air quality and health of its people, and assist Canadian industries in meeting bold emissions reductions targets.