Guo Xiao-yong, Fang Li, Zhao Wen-wu, Gu Xue-jun, Zheng Hai-yang, Zhang Wei-jun
Lab of Environmental Spectroscopy, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2008 Aug;28(8):1713-7.
On-line measurement of size and composition of single particle using an aerosol time-of-flight Laser mass spectrometry (ATOFLMS) had been designed in our lab. Each particle's aerodynamic diameter is determined by measuring the delay time between two continuous-wave lasers, A Nd : YAG laser desorbs and ionizes molecules from the particle, and the time-of-flight mass spectrometer collects a mass spectrum of the generated ions. Then the composition of single particle is obtained. ATOFLMS generates large amount of data during the process period. How to process these data and extract valuable information is one of the key problems for the ATOFLMS. In this paper, the fuzzy clustering used to classify large numbers of mass spectral of air indoor by an ATOFLMS. Each revised spectrum is converted to a normalized 300-point vector, each point representing one mass unit. Then the positive ion mass spectra of a single particle are described as 300-dimensional data vectors using the ion masses as dimensions and the ion signal peak areas as values. The data vectors of all particles measured are written into a classification matrix. Each spectrum's data was stored as one row in this matrix. The Fuzzy c-means algorithm is an iterative method starting the calculation with random class centers to find a substructure in the data. The procedure works in such a way that finally similar objects (particle spectra) have a minimum distance between their corresponding data vectors, on the one hand, and to the center of a cluster, on the other hand. So the aim of the iteration is to find local minima in the N-dimensional space where N is the number of evaluated peak masses. The particle data used in this study were collected over a period one day in Hefei. During the campaign, inorganic salts, mineral particles, and carbonaceous particles, with varying degrees of secondary components, were identified. The detection results of particle size exhibit that aerosol is predominanantly in the form of fine particles, and the particles whose diameter larger than 1 microm are scare. The particles whose diameter less than 1 microm are make up of 95% of the total particles, and these particles are major distributed in 0.4-0.8 microm.
我们实验室设计了一种利用气溶胶飞行时间激光质谱仪（ATOFLMS）对单颗粒尺寸和成分进行在线测量的方法。通过测量两个连续波激光之间的延迟时间来确定每个颗粒的空气动力学直径，一台钕钇铝石榴石（Nd:YAG）激光从颗粒中解吸并使分子电离，飞行时间质谱仪收集所产生离子的质谱图，进而获得单颗粒的成分。在这个过程中，ATOFLMS会产生大量数据。如何处理这些数据并提取有价值的信息是ATOFLMS的关键问题之一。本文中，模糊聚类用于对ATOFLMS测量得到的大量室内空气质谱图进行分类。每个修正后的光谱被转换为一个归一化的300点向量，每个点代表一个质量单位。然后，将单颗粒的正离子质谱图用离子质量作为维度、离子信号峰面积作为值描述为300维数据向量。所有测量颗粒的数据向量被写入一个分类矩阵。每个光谱的数据作为一行存储在该矩阵中。模糊c均值算法是一种迭代方法，从随机的类中心开始计算以在数据中找到子结构。该过程的工作方式是，最终相似的对象（颗粒光谱）一方面在其相应数据向量之间具有最小距离，另一方面与一个聚类的中心具有最小距离。所以迭代的目标是在N维空间中找到局部最小值，其中N是评估的峰质量数。本研究中使用的颗粒数据是在合肥一天的时间内收集的。在采样期间，识别出了含有不同程度二次成分的无机盐、矿物颗粒和碳质颗粒。颗粒尺寸的检测结果表明，气溶胶主要以细颗粒形式存在，直径大于1微米的颗粒很少。直径小于1微米的颗粒占总颗粒的95%，这些颗粒主要分布在0.4 - 0.8微米之间。
