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Cluster Analysis of Wibs Single Particle Bioaerosol Data : Volume 5, Issue 5 (07/09/2012)

By Robinson, N. H.

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Book Id: WPLBN0003977154
Format Type: PDF Article :
File Size: Pages 36
Reproduction Date: 2015

Title: Cluster Analysis of Wibs Single Particle Bioaerosol Data : Volume 5, Issue 5 (07/09/2012)  
Author: Robinson, N. H.
Volume: Vol. 5, Issue 5
Language: English
Subject: Science, Atmospheric, Measurement
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Huffman, J. A., Kaye, P. H., Gallagher, M., Allan, J. D., Robinson, N. H., & Foot, V. E. (2012). Cluster Analysis of Wibs Single Particle Bioaerosol Data : Volume 5, Issue 5 (07/09/2012). Retrieved from

Description: The Centre for Atmospheric Science, School of Earth Atmospheric and Environmental Science, The University of Manchester, UK. Hierarchical agglomerative cluster analysis was performed on single-particle multi-spatial datasets comprising optical diameter, asymmetry and three different fluorescence measurements, gathered using two dual Waveband Integrated Bioaerosol Sensor (WIBS). The technique is demonstrated on measurements of various fluorescent and non-fluorescent polystyrene latex spheres (PSL) before being applied to two separate contemporaneous ambient WIBS datasets recorded in a forest site in Colorado, USA as part of the BEACHON-RoMBAS project. Cluster analysis results between both datasets are consistent. Clusters are tentatively interpreted by comparison of concentration time series and cluster average measurement values to the published literature (of which there is a paucity) to represent: non-fluorescent accumulation mode aerosol; bacterial agglomerates; and fungal spores. To our knowledge, this is the first time cluster analysis has been applied to long term online PBAP measurements. The novel application of this clustering technique provides a means for routinely reducing WIBS data to discrete concentration time series which are more easily interpretable, without the need for any a priori assumptions concerning the expected aerosol types. It can reduce the level of subjectivity compared to the more standard analysis approaches, which are typically performed by simple inspection of various ensemble data products. It also has the advantage of potentially resolving less populous or subtly different particle types. This technique is likely to become more robust in the future as fluorescence-based aerosol instrumentation measurement precision, dynamic range and the number of available metrics is improved.

Cluster analysis of WIBS single particle bioaerosol data

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