Variation of surface ozone in Campo Grande, Brazil: meteorological effect analysis and prediction

• Published in: Environmental science and pollution research international 2014-09, Vol.21 (17), p.10550-10559
• Main Authors: Pires, J. C. M, Souza, A, Pavão, H. G, Martins, F. G
• Format: Article
• Language: English
• Subjects: air; Air Pollutants - analysis; Air pollution; algorithms; Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Brazil; Chemical reactions; Earth and Environmental Science; Ecotoxicology; Environment; Environmental Chemistry; Environmental Health; Environmental Monitoring - methods; Environmental Monitoring - statistics & numerical data; Environmental science; Forecasting; Forecasting techniques; Genetic algorithms; Genetic analysis; Genetic diversity; human health; Humidity; issues and policy; Meteorology - methods; Neural networks; Neural Networks (Computer); Neurons; Outdoor air quality; Ozone; Ozone - analysis; Pollutants; prediction; Radiation; rain; Relative humidity; Research Article; Solar radiation; Studies; temporal variation; Temporal variations; Time Factors; Variables; Waste Water Technology; Water Management; Water Pollution Control; Wind; Wind speed
• ISSN: 0944-1344; 1614-7499
• DOI: 10.1007/s11356-014-2977-6

The effect of meteorological variables on surface ozone (O₃) concentrations was analysed based on temporal variation of linear correlation and artificial neural network (ANN) models defined by genetic algorithms (GAs). ANN models were also used to predict the daily average concentration of this air pollutant in Campo Grande, Brazil. Three methodologies were applied using GAs, two of them considering threshold models. In these models, the variables selected to define different regimes were daily average O₃ concentration, relative humidity and solar radiation. The threshold model that considers two O₃ regimes was the one that correctly describes the effect of important meteorological variables in O₃ behaviour, presenting also a good predictive performance. Solar radiation, relative humidity and rainfall were considered significant for both O₃ regimes; however, wind speed (dispersion effect) was only significant for high concentrations. According to this model, high O₃ concentrations corresponded to high solar radiation, low relative humidity and wind speed. This model showed to be a powerful tool to interpret the O₃ behaviour, being useful to define policy strategies for human health protection regarding air pollution.