化石燃料燃烧排放的soot是大气PM2.5形成的重要因素之一。在火焰中，多环芳烃（PAHs）是soot的前体物，其生成特性对soot的形成有重要影响。当前基于HACA机理的PAHs化学动力学模型（ABF模型）还不完善，导致应用该模型计算和预测soot生成不够准确。本项目采用量子化学从头算法、过渡态理论、单分子反应理论对碳氢燃料的PAHs生成、长大、氧化过程进行系统研究，并采用PLIF技术对预混火焰中PAHs进行在线测量，通过理论和实验研究发展更完善PAHs化学动力学模型，为准确预测发动机燃烧soot生成提供理论基础。

Soot formed in incomplete combustion of hydrocarbons is an important inducement in the formation of PM2.5. Polycyclic aromatic hydrocarbons (PAHs) are generally accepted as the precursors to soot particles in flame, and the character of PAHs has great impact on the formation of soot. ABF model developed on the basis of hydrogen-abstraction-carbon-addition (HACA) mechanism is still popular in use for premixed flames. But the predicted concentration of soot is not accurate enough. The object of this program is to provide an improved chemical mechanism of PAH growth and oxidation using accurate ab initio density functional theory calculations, as well as TST (transition state theory ) theory and RRKM (Rice-Ramsperger-Kassel-Marcus) theory. At the same time, the concentration of various PAHs will be experimentally measured via PLIF technology. Both theoretical an experimental researches contribute to developing an improved and accurate PAHs chemical kinetics model. The improved model can provide theoretical basis for the accurate prediction of soot formation.