Small-Particle Pollution Modeling Using Fuzzy Approaches
Air pollution caused by small particles is a major public health problem in many cities of the world. One of the most contaminated cities is Mexico City. The fact that it is located in a volcanic crater surrounded by mountains helps thermal inversion and imply a huge pollution problem by trapping a thick layer of smog that float over the city. Modeling air pollution is a political and administrative important issue due to the fact that the prediction of critical events should guide decision making. The need for countermeasures against such episodes requires predicting with accuracy and in advance relevant indicators of air pollution, such are particles smaller than 2.5 microns (PM2.5). In this work two different fuzzy approaches for modeling PM2.5 concentrations in Mexico City metropolitan area are compared with respect the simple persistence method.
KeywordsAir Pollution Modeling PM2.5 Pollution Fuzzy Inductive Reasoning ANFIS Persistence Time Series Analysis
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- 1.WHO World healt oranization. Air quality guidelines: the global update 2005 (2006) Google Scholar
- 3.NWM: National Weather Service of Mexico (2012), http://smn.cna.gob.mx/
- 11.Klir, G., Elias, D.: Architecture of Systems Problem Solving, 2nd edn. Plenum Press, New York (2002)Google Scholar
- 15.Nauck, D., Klawonn, F., Kruse, R.: Neuro-Fuzzy Systems. John Wiley & Sons (1997)Google Scholar
- 16.SIMAT (2012), http://www.sma.df.gob.mx/simat/
- 17.Muñoz, R., Carmona, M.R., Pedroza, J.L., Granados, M.G.: Data analysis of PM2.5 registered with TEOM equipment in Azcapotzalco (AZC) and St. Ursula (SUR) stations of the automatic air quality monitoring network (RAMA). In: National Congress of Medicine Engineering and Ambient Sciences, pp. 21–24 (2000) (in Spanish)Google Scholar
- 20.Salini, G., Perez-Jara, P.: Time series analysis of atmosphere pollution data using artificial neural networks technique. Revista Chilena de Ingeniería 14(3), 284–290 (2006)Google Scholar