Ozone is considered one of the most significant pollutants with respect to the potential impacts to human health and natural ecosystem, both in terms of critical episodes and as long-term exposures.
Consequently, in order to assess the comprehensive effects of photochemical pollution, not only ozone peak concentrations need to be examined, but also ozone exposures on “seasonal” scale need to be quantified.
Modelling systems can represent suitable tools for this purpose (Carmichael et al.,1986). As a matter of fact, the Italian law designates the integrated use of representative stations, for monitoring activities, emission inventories and modelling systems, for simulating air pollutants transport, transformation and diffusion, as the best approach for air quality assessment.
In this study an integrated modelling system has been developed in order to perform a simulation of the photochemical pollution.The main modules of the modelling system are: the emission pre-processor, the prognostic nonhydrostatic meteorological model RAMS (Regional Atmospheric Modelling System, Pielke et al.,1992), the interface module RAMS-CAMx, which is distributed by Environ as free software (http://www.camx.com/down/support.php) and the Eulerian model CAMx (Comprehensive Air Quality Model with extensions, Environ, 2005).
The modelling system has been applied over a domain, in Northwest Italy, covering areas characterized by different emission level: eastern Piedmont valley (low emission level area) and industrial triangle Milan-Turin-Genoa (high emission level area). This region is often affected by severe summer photochemical pollution episodes driven by both anthropogenic emissions and meteorological conditions.
The Po river valley is very industrialised and populated and it is characterised by strong urban, industrial and traffic emissions; moreover, the presence of the Alps often gives rise to weak circulation and stagnant conditions.
In this paper, the results of the six-summer months simulation (from April to September 1999) are compared with ozone and nitrogen dioxide data measured at 8 monitoring stations, grouped in urban, suburban and rural sites.
The model performances, analysed and discussed in term of statistical indices, shows a general satisfactory agreement.