Applying linear and nonlinear models for the estimation of particulate matter variability.

In this study, data collected from an urban air quality monitoring network are being used for the purpose of evaluating various methodologies used for spatial interpolation in the context of proposing an effective yet simple to apply scheme for PM spatial point estimations. The examined methods are the Inverse Distance Weighting, two linear regression models, the Multiple Linear Regression and the Linear Mixed Model, along with a Feed Forward Neural Network (FFNN) model. These schemes utilize daily PM and PM concentrations collected from five and three air quality monitoring sites respectively.

The impact of sea breeze under different synoptic patterns on air pollution within Athens basin.

Air quality in densely populated urban coastal areas is directly related to the coupling of the synoptic and the local scale flows. The dispersion conditions within Athens basin, under the influence of different meteorological forcings, lead to distinct spatio-temporal air pollution patterns. The aim of the current observational research is to identify and examine the effect of sea breeze under different atmospheric circulation patterns on air pollution levels for a one-year study period (2007).

On the limits of the air pollution predictability: the case of the surface ozone at Athens, Greece.

Purpose: The aim of this study is to investigate the potential effects of increased urbanization in the Athens city, Greece on the intrinsic features of the temporal fluctuations of the surface ozone concentration (SOC).

Methods: The detrended fluctuation analysis was applied to the mean monthly values of SOC derived from ground-based observations collected at the centre of Athens basin during 1901-1940 and 1987-2007.

Results: Despite the present-day SOC doubling in respect to SOC historic levels, its fluctuations exhibit long-range power-law persistence, with similar features in both time periods.