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The main purpose of this work is to estimate the air pollution effects of 2003 forest fires through the application of two air quality modelling systems (CHIMERE and LOTOS-EUROS) over Portugal and its intercomparison. Forest fire emissions were estimated based on specific southern European emissions factors, on type of vegetation and area burned, and incorporated in the emission input data of both modelling systems. Results showed a significant performance improvement when forest fires are taken into account. PM10 and O3 values can reach differences in the order of 30%, showing the importance and the influence of this type of emissions from local to regional air quality. The different results of the two models may give an indication of the uncertainty associated by using different models to investigate the impact of forest fires. Historical datasets of area burned, number of fires and air quality data were evaluated from 1995 to 2005 aiming to investigate a potential relationship between forest fire activity and air pollutants concentrations. The obtained results point to statistically significant correlations between fire activity in Portugal and PM10 and O3 levels in the atmosphere. [ABSTRACT FROM AUTHOR]

Air pollution is a major environmental health problem causing approximately 3 million deaths per year in the world, as a result of exposure to particulate matter (PM). Portugal, as a European Union Member, should follow the main objectives for management and quality of ambient air, namely those related to particulate matter. An increase of scientific studies during the last years have confirmed that long-term exposure to particulate matter pollution leads to adverse health effects. These studies generally use air pollution measurements from stationary air monitoring sites to determine population exposure levels. However, because of the large local variations in pollution concentrations, the estimates are often associated with high uncertainties. Besides that, aerosols are comprised not only of primary particles emitted directly to the atmosphere, but also of products from gas-to-particle conversion (sulphur oxides, nitrogen oxides, volatile organic compounds and semi-volatile organic compounds) in clear air and clouds. Thus, considerable research is needed to better understand the complex processes of aerosols formation, transport and deposition. For an improvement on these processes knowledge and more accurate exposure estimation, air quality models can be used as important tools with the ability to provide detailed information on pollutants concentration fields. The main purpose of this study is to perform a first long-term air quality assessment for Portugal, regarding aerosols and particulate matter pollution. The CHIMERE chemistry-transport model, forced by the MM5 meteorological fields, was applied over the Continental region of Portugal for the 2001 year period, with 10 km horizontal resolution, using an emission inventory obtained from a spatial topdown disaggregation of the 2001 EMEP national database. In order to verify the ability of the model system to simulate particulate matter, an evaluation model exercise is performed based on statistical comparison between PM10 and PM2.5 concentration data observed at 20 air monitoring ground stations and the correspondent simulated values. Besides that, PM components (nitrate, sulphate, ammonium, etc.) are evaluated at two specific sampling (experimental) sites near two urban waste incinerators. There is a model trend to overestimate particulate pollution episodes (peaks) at urban sites, especially in winter season. This could be due to an underprediction of the winter model vertical mixing or an incorrect spatial and temporal disaggregation and consequent overestimation of local PM emissions. Time series spectral decomposition was also used to evaluate the model performance (accuracy) at different time scales. Nevertheless, as a first approach, and despite the complex topography and coastal location of Portugal affected by sea salt natural aerosols emissions, the results obtained show a modelling system able to reproduce the particulate matter levels temporal evolution and spatial patterns. The concentration maps reveal specific areas with critical particulate matter values that are not yet covered by the air quality monitoring network. In this way, this longterm simulation study could be used as a useful tool for air quality management, as well as for protecting human health. [ABSTRACT FROM AUTHOR]