Assessment of impacts produced by anthropogenic sources in a little city near an important industrial area (Modugno, Southern Italy).

An annual monitoring campaign of VOCs, consisting of twelve sampling periods, was carried out from June 2008 to June 2009 in Modugno, a city located in the Apulia region (Southern Italy), in order to assess the urban air quality, identify the main emission sources, and quantify the cancer and no-cancer risk attributable to inhalation exposures. Monitoring, carried out by using the Radiello diffusive samplers, was conducted in eleven sampling sites throughout the city taking into account the traffic density and the architecture of the city. From the study of the data, it was found that, among all considered VOCs, benzene, toluene, ethylbenzene, and xylenes (BTEX) are the pollutants at higher concentration. The analysis of VOC concentrations, the study of the topography of the city, and the use of different diagnostic ratios between the BTEX species showed that the vehicular traffic emissions were the predominant source of VOCs in the urban area of Modugno. Despite that the annual concentration of benzene is lower than the regulatory limit, the estimation of cancer risk showed that the global lifetime cancer risk attributed to the investigated VOC exposure was not negligible and therefore should be taken into account in future regulatory approaches.

First atmospheric mercury measurements at a coastal site in the Apulia region: seasonal variability and source analysis.

In the framework of the Italian Special Network for Mercury (ISNM) "Reti Speciali", a sampling campaign to monitor atmospheric mercury (Hg) was carried out at Monte Sant'Angelo (MSA). This is a coastal monitoring station in the Apulia region, representative of the Southern Adriatic area, within the Mediterranean basin. This work presents continuous Gaseous Elemental Mercury (GEM) measurements over about three years at MSA, using the Lumex RA-915AM mercury analyzer. The aim was to obtain a dataset suitable for the analysis of Hg concentrations in terms of source and transport variation. Diurnal cycles of GEM were evaluated to observe the influence of local atmospheric temperature and wind speed on potential re-emissions from surrounding sea and soil surfaces. Data were also analyzed in terms of long-range transport, using backward trajectory cluster analysis. The spatial distribution of potential sources, contributing to higher measured GEM values, was obtained employing Potential Source Contribution Function (PSCF) statistics. The influence of major Hg anthropogenic point sources, such as mining activities and coal-fuel power plants, both regionally and continentally, from mainland Europe, was observed. The role of the vegetation GEM uptake in modulating the seasonal GEM variability was also investigated. The potential of wildfire influence over the highest detected GEM levels was further examined using active fire data and the evaluation of the vegetation dryness index during the selected episodes.

Neural network model for the prediction of PM10 daily concentrations in two sites in the Western Mediterranean.

An artificial neural network (ANN) was developed and tested to forecast PM10 daily concentration in two contrasted environments in NE Spain, a regional background site (Montseny), and an urban background site (Barcelona-CSIC), which was highly influenced by vehicular emissions. In order to predict 24-h average PM10 concentrations, the artificial neural network previously developed by Caselli et al. (2009) was improved by using hourly PM concentrations and deterministic factors such as a Saharan dust alert. In particular, the model input data for prediction were the hourly PM10 concentrations 1-day in advance, local meteorological data and information about air masses origin. The forecasted performance indexes for both sites were calculated and they showed better results for the regional background site in Montseny (R(2)=0.86, SI=0.75) than for urban site in Barcelona (R(2)=0.73, SI=0.58), influenced by local and sometimes unexpected sources. Moreover, a sensitivity analysis conducted to understand the importance of the different variables included among the input data, showed that local meteorology and air masses origin are key factors in the model forecasts. This result explains the reason for the improvement of ANN's forecasting performance at the Montseny site with respect to the Barcelona site. Moreover, the artificial neural network developed in this work could prove useful to predict PM10 concentrations, especially, at regional background sites such as those on the Mediterranean Basin which are primarily affected by long-range transports. Hence, the artificial neural network presented here could be a powerful tool for obtaining real time information on air quality status and could aid stakeholders in their development of cost-effective control strategies.

Assessment of the impact of the vehicular traffic on BTEX concentration in ring roads in urban areas of Bari (Italy).

A BTEX monitoring campaign, consisting of two weekly periods, was carried out in Bari, south-eastern Italy, in order to evaluate the impact of the vehicular traffic on the air quality at the main access roads of the city. Twenty-one sampling sites were selected: the pollution produced by the traffic in the vicinity of all exits from the ring road and some access roads to the city, those with higher traffic density, were monitored. Contemporarily the main meteorological parameters (ambient temperature, wind, atmospheric pressure and natural radioactivity) were investigated. It was found that in the same traffic conditions, barriers, buildings and local meteorological conditions can have important effects on the atmospheric dispersion of pollutants. This situation is more critical in downtown where narrow roads and high buildings avoid an efficient dispersion producing higher levels of BTEX. High spatial resolution monitoring allowed both detecting the most critical areas of the city with high precision and obtaining information on the mean level of pollution, meaning air quality standard of the city. The same concentration pattern and the correlation among BTEX levels in all sites confirmed the presence of a single source, the vehicular traffic, having a strong impact on air quality.