Collaborative Studies on Soot Particle Formation and Characterization

煤烟颗粒是碳纳米颗粒，在许多燃烧过程中不必要地排放出来。煤烟颗粒被认为是气候变化的第二大罪魁祸首，并对人类健康产生不利影响，因为煤烟是一种致癌、遗传毒性和致畸的污染物。该NSERC联盟旨在通过推进对煤烟形成物理的理解和数值模拟，促进减少燃烧产生的煤烟颗粒排放。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抑制减排的关键知识空白。为了促进对导致烟灰形成过程的理解，这个提议的国际NSERC联盟与瑞尔森大学和密歇根大学合作，将整合两种现有的烟灰预测模型-一种侧重于烟灰前体的化学生长，另一种侧重于烟灰产生燃烧的颗粒和流体动力学-创造一种新颖，强大的预测工具。所得到的工具的应用将有助于阐明有利于烟灰形成的燃烧条件，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。本研究的结果有望：(1)导致对产生烟尘颗粒的机制有更强的基本理解；(2)产生新的烟尘形成模型，显著提高预测精度、适用性和细节；(3)有助于减轻与烟尘形成相关的环境和健康问题。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，并协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.