arXiv:1111.2008v1 [physics.data-an] 8 Nov 2011 Optimal variables for describing the evolution of NO2 concentration F. Raischel a , A. Russo b , M. Haase c , D. Kleinhans d,e , P.G. Lind a, f a Center for Theoretical and Computational Physics, University of Lisbon, Av. Prof. Gama Pinto 2, 1649-003 Lisbon, Portugal b Center for Natural Resources and the Environment, Instituto Superior T´ ecnico, Av. Rovisco Pais, 1049-001 Lisboa, Portugal c Institute for High Performance Computing, University of Stuttgart, Nobelstr. 19, D-70569 Stuttgart, Germany d Institute for Marine Ecology, University of Gothenburg, Box 461, SE-405 30 G¨ oteborg, Sweden e Institute of Theoretical Physics, University of M¨ unster, D-48149 M¨ unster, Germany f Departamento de F´ ısica, Faculdade de Ciˆ encias da Universidade de Lisboa, 1649-003 Lisboa, Portugal Abstract By implementing a recent technique for determination of stochastic eigendirections of two coupled stochastic variables, we inves- tigate the evolution of fluctuations of NO 2 concentrations at two monitoring stations in the city of Lisbon, Portugal. We analyze the stochastic part of the measurements recorded at the monitoring stations by means of a method where the two concentrations are considered as stochastic variables evolving according to a system of coupled stochastic differential equations. Analysis of their structure allows for transforming the set of measured variables to a set of derived variables, one of them with reduced stochasticity. For the specific case of NO 2 concentration measures, the set of derived variables are related to the total amount of NO 2 concentra- tion observed in the two stations and the relative concentration between them. Having one variable with reduced stochasticity, we briefly discuss how to increase the predictive power of the measurement series. Keywords: Stochastic Systems, Environmental Research, Pollutants, Langevin Equation, Predictability PACS: [2010] 02.50.Ga, 02.50.Ey, 92.60.Sz, \rcsInfo $Id: no2_rrhkl.tex,v 1.35 2011/11/08 18:17:31 stud Exp $ Preprint submitted to arxiv November 9, 2011