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Cluster analysis of single particle mass spectra measured at Flushing,NY

机译:在纽约法拉盛测量的单颗粒质谱的聚类分析

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摘要

ART-2a and a density based cluster method,density based spatial clustering of application with noise (DBSCAN),have been used for classification of the single particle mass spectra measured at New York City.Using too large of a vigilance factor in ART-2a leads to many similar clusters with overlap,and thus a low vigilance factor was used in this study.The DBSCAN method can identify clusters with complex shapes and various sizes,and representative spectra are chosen to identify different particle types within each cluster.The cluster structure of the single particle mass spectra were examined by DBSCAN.Both methods found that the major clusters were sea salt and anthropogenic combustion emissions.The continua in sulfate,potassium and OC particles were found by DBSCAN and a large cluster was formed,while ART-2a broke it into several small clusters without finding this continuum.A detailed discussion of the cluster analysis results including representative mass spectra,size distributions and temporal behavior will be provided.
机译:ART-2a和基于密度的聚类方法,基于密度的应用与噪声的空间聚类(DBSCAN)已用于对在纽约市测量的单个粒子质谱进行分类。ART-2a中使用了过高的警戒因子导致许多相似的团簇重叠,因此本研究使用了较低的警戒因子。DBSCAN方法可以识别形状复杂且大小各异的团簇,并选择代表性的光谱来识别每个团簇内的不同粒子类型。两种方法均发现了主要的簇是海盐和人为燃烧排放物。DBSCAN发现了硫酸盐,钾和OC颗粒的连续体,并形成了一个大簇,而ART-2a在没有找到该连续体的情况下将其分解为几个小簇。对簇分析结果的详细讨论,包括代表性质谱,尺寸分布将提供时间行为。

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