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Learning Principal Component Analysis by Using Data from Air Quality Networks

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Pérez Arribas, Luis Vicente and León González, María Eugenia and Rosales Conrado, Noelia (2017) Learning Principal Component Analysis by Using Data from Air Quality Networks. Journal of Chemical Education . ISSN 0021-9584

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Official URL: https://doi.org/10.1021/acs.jchemed.6b00550



Abstract

With the final objective of using computational and chemometrics tools in the chemistry studies, this paper shows the methodology and interpretation of the Principal Component Analysis (PCA) using pollution data from different cities. This paper describes how students can obtain data on air quality and process such data for additional information related to the pollution sources, climate effects, and social aspects over pollution levels by using a powerful chemometrics tool such as principal component analysis (PCA). The paper could also be useful for students interested in environmental chemistry and pollution interpretation; this statistical method is a simple way to display visually as much as possible of the total variation of the data in a few dimensions, and it is an excellent tool for looking into the normal pollution patterns.


Item Type:Article
Uncontrolled Keywords:Graduate Education/Research, Upper-Division Undergraduate, Environmental Chemistry, Computer-Based Learning, Chemometrics
Subjects:Sciences > Chemistry > Analytic chemistry
ID Code:41572
Deposited On:01 Mar 2017 11:27
Last Modified:01 Mar 2017 13:12

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