Discovering patterns of time association among air pollution and meteorological variables
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Date
2021
Journal Title
Journal ISSN
Volume Title
Publisher
Springer
Abstract
Lately, there is a concern about to air pollution, which leads to environmental specialists discovering relevant causes of this phenomenon. Several factors determine the level of pollution, but it is necessary to find behavior patterns between air pollution and meteorological variables. The relations between these variables in distinct hours a day could give clues to discover essential patterns in their relationships. This study revealed relations among five air pollution variables and nine meteorological variables collected for one month in the city Cuenca-Ecuador. The method used considerer an evaluation of the essential time associations using time rolling windows and correlations. The results were revelated using visualization frames for dimensions such as time, correlation rate, and component relation, highlighting 57 strong correlations from 91 pairs of variables, the best positive correlation is between Ozone and Radiation UVA. The best negative correlation is Ozone and Dew Point, both throughout the day.
Resumen
Keywords
Air pollutant, Knowledge, Data mining, Correlation, Big data, Rolling correlations