Volume & Issue no: Volume 6, Issue 4, July - August 2017
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Title: |
Modelling Long-Term Pattern Pollutants Using Recurrence Quantification Tools. Case-study: PM10 at Mexico City |
Author Name: |
Marco A. Aceves-Fernandez, Santiago Miguel Fernandez-Fraga |
Abstract: |
Abstract
Various techniques have been used to model the long-term
trends for particulate matter (PM) in the environment.
However, the non-linear behavior of airborne pollution (PM10,
in this case) and the variety of compounds present in the
environment make long-term pattern modelling a challenging
task.
In this contribution, Recurrence plots and its extension RQA
(Recurrence Quantification Analysis) explore the long-term
trends on PM10 in Mexico City. To determine the feasibility of
this technique over a long period of time, data was obtained for
various monitoring stations from different stations over 12
years. The trends resulted were then compared with statistical
analyses from other authors. The results confirm that this
technique could be used to model long-term patterns of
particulate matter given that the right RQA tools are used.
Furthermore, the importance of this work relies on the fact that
this type of analysis with such an amount of data using RPs has
not been carried out before, which makes this tool to find PM10
trends buried in large databases, useful for this case analysis.
Also, different approaches have been performed and
preliminary conclusions are drawn from these experiments.
Keywords: Recurrence Plots; Recurrence Quantification
Analysis; PM10; Particulate Matter |
Cite this article: |
Marco A. Aceves-Fernandez, Santiago Miguel Fernandez-Fraga , "
Modelling Long-Term Pattern Pollutants Using Recurrence Quantification Tools. Case-study: PM10 at Mexico City" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) ,
Volume 6, Issue 4, July - August 2017 , pp.
021-027 , ISSN 2278-6856.
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