基于模糊聚类算法的苯系物二次有机气溶胶质谱数据分析

OH自由基启动苯系物光氧化形成的二次有机气溶胶能够影响气候变化，降低大气能见度，危害人类健康。我们实验室自行研制的气溶胶飞行时间质谱仪能够用于二次有机气溶胶的实时检测研究。该仪器在检测过程中产生大量的实验数据，对这些数据快速、自动处理并提取有价值的信息是整机系统的关键之一。本文介绍模糊聚类算法在苯系物二次有机气溶胶单粒子聚类分析中的成功运用。利用该算法对OH自由基启动1,3,5-三甲苯光氧化形成的二次有机气溶胶单粒子质谱数据进行了聚类分析，在得到的五个聚类中包含了芳香醛、酚类化合物、硝基酚和羧酸等重要的光氧化产物，为研究苯系物光氧化机理提供了新的信息。

Data Analysis of Mass Spectrum of Aromatic Secondary Organic Aerosol Particles using Fuzzy Clustering Algorithms

Secondary organic aerosol (SOA) formed from OH-initiated photooxidation of aromatic hydrocarbons may impact on the radiative balance associated with climate change, visibility degradation, and heath effects. An aerosol time-of-flight mass spectrometry (ATOFMS) designed and manufactured by our laboratory can be used to analyze SOA in real-time and generate thousands of mass spectra from typical measurement campaigns. How to process these data and extract valuable information is one of the key problems for the ATOFMS. In this paper, the Fuzzy C-Means (FCM) algorithm is used to classify large numbers of mass spectrum of SOA particles formed from photooxidation of 1,3,5-trimethylbenzene analyzed by ATOFMS. Experimental results showed that aerosol created by 1,3,5-trimethylbenzene photooxidation can be classify with five distinct chemical particle classes, the predominant components of these five particles are aromatic aldehyde, phenol, nitrophenol and carboxylic acid compounds. These also provide additional insight into the photooxidation mechanism for aromatic hydrocarbons.