ADVANCES IN ATMOSPHERIC SCIENCES, VOL. 24, NO. 5, 2007, 907–914 Modeling of Trophospheric Ozone Concentrations Using Genetically Trained Multi-Level Cellular Neural Networks H. Kurtulus OZCAN ∗ 1 , Erdem BILGILI 2 , Ulku SAHIN 1 , O. Nuri UCAN 3 , and Cuma BAYAT 4 1 Istanbul University, Engineering Faculty, Environmental Eng. Dept. 34320, Avcilar, Istanbul, Turkey 2 Tuzla Marine Education Center, Tuzla, Istanbul, Turkey 3 Istanbul University, Engineering Faculty, Electrical-Electronics Eng. Dept. 34320, Avcilar, Istanbul, Turkey 4 Beykent University 34500, Buyukcekmece, Istanbul (Received 12 September 2006 revised 2 February 2007) ABSTRACT Tropospheric ozone concentrations, which are an important air pollutant, are modeled by the use of an artificial intelligence structure. Data obtained from air pollution measurement stations in the city of Istanbul are utilized in constituting the model. A supervised algorithm for the evaluation of ozone concentration using a genetically trained multi-level cellular neural network (ML-CNN) is introduced, developed, and applied to real data. A genetic algorithm is used in the optimization of CNN templates. The model results and the actual measurement results are compared and statistically evaluated. It is observed that seasonal changes in ozone concentrations are reflected effectively by the concentrations estimated by the multilevel-CNN model structure, with a correlation value of 0.57 ascertained between actual and model results. It is shown that the multilevel-CNN modeling technique is as satisfactory as other modeling techniques in associating the data in a complex medium in air pollution applications. Key words: genetic algorithm, cellular neural networks (CNN), ozone, meteorological data DOI: 10.1007/s00376-007-0907-y 1. Introduction Air pollutants exert a wide range of impacts on biological, physical and economic systems. Their ef- fects on human health are of particular concern. The decrease in respiratory efficiency and impaired capabil- ity to transport oxygen through the blood caused by a high concentration of air pollutants may be hazardous to those having pre-existing respiratory and coronary artery disease (Sharma et al., 2003). Ozone (O 3 ) is a reactive gas that forms naturally on a limited scale in the Earth’s atmosphere and is the most important of the oxidizing agents. Ozone re- siding in the stratosphere (a layer 12–48 m above the Earth) acts as a shield to protect the Earth’s surface from the Sun’s harmful ultraviolet radiation. Closer to the Earth, in the troposphere, ozone is not a pollutant thrown from pollutant sources into the atmosphere, but is formed with the help of factors such as sunlight and heat, and with the adverse effects of various pollu- tants such as VOCs and NO x . As ozone is a secondary pollutant, it is directly associated with the other fac- tors affecting air pollution and meteorological agents (Wahab-Abdul and Al-Alawi, 2002). Tropospheric ozone (O 3 ) is the most common pho- tochemical oxidant in the air. While stratospheric ozone (12–48 m above the Earth) is necessary to cur- tain solar ultraviolet radiation, high concentrations of ozone residing closer to the Earth has negative ef- fects on living beings. It causes coughs, dyspnea, tra- chea contractions, headaches, chest contractions and burns, pulmonary disfunction, changes in the cellular structure of erythrocytes, angina, as well as eye, nose and larynx irritations. Furthermore, it penetrates into plant fibers, damaging plant cell metabolism, and gen- erates spots and stains on the leaves (Tecer, 2000). A wide variety of operational warning and forecast- ing systems based on empirical, causal, statistical and ∗ Corresponding author: H. Kurtulus OZCAN, hkozcan@istanbul.edu.tr