Heavy metals (HMs) are pollutants that have both anthropogenic and natural sources. In the last decade, the European Commission (EC) has imposed limit and target values for some of them that are ...toxic both for humans and for the environment. This study aims to assess the HM concentrations over Italy by means of the atmospheric modelling system (AMS) of the MINNI project. The AMS is based on the chemical transport model (CTM) FARM. The sensitivity of model simulations to horizontal grid resolution, lateral boundary conditions and the contribution of emissions from neighbouring countries has been also evaluated. The simulations have been carried out for the year 2005 considering a spatial resolution of 20 km over the Italian domain and 4 km over northern Italy (Po Valley). The CTM has been extended to take into account the HMs considered by EC directives such as arsenic (As), cadmium (Cd), nickel (Ni) and lead (Pb). Both anthropogenic and natural emissions have been considered in this study. Model results have been compared with available observations. Results show realistic concentration of HMs and suggest the importance of using boundary conditions, while foreign emissions have less impact. In addition, the present work highlights the necessity of more observations in space and time for a comprehensive validation of the model. High-resolution simulation gives more realistic pattern with respect to the low-resolution one for the highly polluted areas. However, future improvements require a better knowledge of the space/time distribution of the emissions, currently not available.
The combined use of air quality monitoring data and state-of-the art dispersion models provides a more realistic representation of the spatial distribution of pollutants and allows a reduction in the ...uncertainties involved in the assessment of the exposure in epidemiological studies. Data assimilation is a method which combines such information to produce an optimal representation of the state of the atmosphere. In this work, we tested two approaches to merge these information sets: the successive corrections method (SCM) and the statistical optimal interpolation (OI). These methods have been extended in order to take into account the spatial representativeness of measurements. PM
10
, NO
2
, and O
3
concentration fields produced by an air quality modeling system, run with two nested domains covering much of Central Italy and the Rome urban area, have been used to identify the optimal values for the horizontal and vertical scaling distances that are key parameters for the SCM and OI methods. A statistical analysis of the results obtained from the application of these methods demonstrated that lower RMSE values resulted from the use of the OI method. Further, PM
2.5
modeling results over the Rome urban area and additional measurements collected during experimental campaigns, performed within the population exposure to polycyclic aromatic hydrocarbons (EXPAH) LIFE+ Project, allowed the evaluation of this approach in reconstructing PM
2.5
levels at EXPAH monitoring sites, which were not used in the data assimilation process. The results confirmed the potential of these methods to improve the estimation of modeled concentrations, by taking into account local phenomena not resolved by the model, but clear from the observations, and also in providing more reliable data to be used in exposure studies.
The aim of this study was to identify areas of potential relevant exposure to pollutants within Rome's urban core. To meet this goal, intensive field campaigns were conducted and simulations were ...performed, using the flexible air quality regional model (FARM), to study winter and summer pollution episodes. The simulations were performed using a complete emission inventory that included traffic flow model results of the Roman street network to better describe, with respect to the available diffuse national emission inventory, the hourly variation of traffic emissions in the city. The meteorological reconstruction was performed by means of both prognostic and diagnostic models by using experimental data collected during the field campaigns. To evaluate the capability of the FARM model to capture the main features of the selected episodes, a comparison of modelled results against observed air quality data for different pollutants was performed at urban and rural sites. FARM performed well in predicting ozone (O
3) and nitrogen dioxide (NO
2) concentrations, showing a good reproduction of both daily peaks and their diurnal variations. The model also showed a good capability to reproduce the magnitude of volatile alkane, aromatic and carbonyl compound concentrations. PM
10 model results revealed the tendency to under-predict the observed values. PM composition model results were compared with observed data, evidencing good results for elemental carbon (EC), nitrate (NO
3
−) and ammonium (NH
4
+), underestimation for sulphate (SO
4
2−) and poor performance for organic matter (OM). The soil components of PM were found to be significantly under-predicted by the model, especially during Saharan dust episodes. Overall, the study results show large areas of high O
3 and PM
10 concentrations where levels of pollutants should be carefully monitored and population exposure evaluated.
Two bias adjustment techniques, the hybrid forecast (HF) and the Kalman filter (KF), have been applied to investigate their capability to improve the accuracy of predictions supplied by an air ...quality forecast system (AQFS). The studied AQFS operationally predicts NO2, ozone, particulate matter and other pollutants concentrations for the Lazio Region (Central Italy). A thorough evaluation of the AQFS and the two techniques has been performed through calculation and analysis of statistical parameters and skill scores. The evaluation performed considering all Lazio region monitoring sites evidenced better results for KF than for HF. RMSE scores were reduced by 43.8% (33.5% HF), 25.2% (13.2% HF) and 41.6% (39.7% HF) respectively for hourly averaged NO2, hourly averaged O3 and daily averaged PM10 concentrations. A further analysis performed clustering the monitoring stations per type showed a good performance of the AQFS for ozone for all the groups of stations (r = 0.7), while satisfactory results were obtained for PM10 and NO2 at rural background (r = 0.6) and Rome background stations (r = 0.7). The skill scores confirmed the capability of the adopted techniques to improve the reproduction of exceedance events.
The carbonaceous aerosol accounts for an important part of total aerosol mass, affects human health and climate through its effects on physical and chemical properties of the aerosol, yet the ...understanding of its atmospheric sources and sinks is still incomplete. This study shows the state-of-the-art in modelling carbonaceous aerosol over Europe by comparing simulations performed with seven chemical transport models (CTMs) currently in air quality assessments in Europe: CAMx, CHIMERE, CMAQ, EMEP/MSC-W, LOTOS-EUROS, MINNI and RCGC. The simulations were carried out in the framework of the EURODELTA III modelling exercise and were evaluated against field measurements from intensive campaigns of European Monitoring and Evaluation Programme (EMEP) and the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI). Model simulations were performed over the same domain, using as much as possible the same input data and covering four seasons: summer (1–30 June 2006), winter (8 January – 4 February 2007), autumn (17 September- 15 October 2008) and spring (25 February - 26 March 2009). The analyses of models’ performances in prediction of elemental carbon (EC) for the four seasons and organic aerosol components (OA) for the last two seasons show that all models generally underestimate the measured concentrations. The maximum underestimation of EC is about 60% and up to about 80% for total organic matter (TOM). The underestimation of TOM outside of highly polluted area is a consequence of an underestimation of secondary organic aerosol (SOA), in particular of its main contributor: biogenic secondary aerosol (BSOA). This result is independent on the SOA modelling approach used and season. The concentrations and daily cycles of total primary organic matter (TPOM) are generally better reproduced by the models since they used the same anthropogenic emissions. However, the combination of emissions and model formulation leads to overestimate TPOM concentrations in 2009 for most of the models. All models capture relatively well the SOA daily cycles at rural stations mainly due to the spatial resolution used in the simulations. For the investigated carbonaceous aerosol compounds, the differences between the concentrations simulated by different models are lower than the differences between the concentrations simulated with a model for different seasons.
This work describes the extension of the Flexible Air quality Regional Model (FARM) to polycyclic aromatic hydrocarbons (PAHs). Modules accounting for the partitioning of these species between ...gaseous and particulate phases were inserted in a simplified version of the model and in a more state–of–the–art configuration implementing the SAPRC99 gas–phase chemical mechanism coupled with the aero3 aerosol module. Both versions of FARM were applied over Italy for the year 2005. The analysis of model results was focused on benzoapyrene (BaP), which is considered a marker substance for the carcinogenic risk of PAHs. Simulated BaP concentrations were compared with observed data, collected at background sites mainly located in Po Valley, and with concentrations produced at continental scale by EMEP/MSC–E model. Higher BaP yearly average concentrations were simulated by the national modelling system as a result of different factors: the higher resolution adopted by the national modelling system, the greater Italian emissions estimated by the national inventory and the effects induced by the use of a high resolution topography on meteorological fields and thus on the dispersion of pollutants. The comparison between observed and predicted monthly averaged concentrations evidenced the capability of the two versions of FARM model to capture the seasonal behaviour of BaP, characterised by higher values during the winter season due to the large use of wood for residential heating, enhanced by lower dispersion atmospheric conditions. The statistical analysis evidenced, for both versions of the model, a good performance and better indicators than those associated to EMEP/MSC–E simulations. A source apportionment was then carried out using the simplified version of the model, which proved to perform similarly to the full chemistry version but with the advantage to be computationally less expensive. The analysis revealed a significant influence of national sources on BaP concentrations, with non–industrial combustion employing wood burning devices being the most important sector. The contribution of the industrial sectors is relevant around major industrial facilities, with the largest absolute contribution in Taranto (above 1ng m−3), where steel industries are the largest individual source of PAHs in the country.
Passive air sampling (PAS) consisting of polyurethane foam (PUF) disks were deployed simultaneously over four periods of 2–5 months at four locations in urban and sub–urban sites of Bari and San Vito ...Taranto in Southern Italy. The purpose of the study was to characterize the urban pollution for two groups of semi volatile organic compounds (SVOCs), polychlorinated biphenyls (PCBs) and polycyclic aromatic hydrocarbons (PAHs), by using two different approaches consisting of PAS–PUF and air quality models (Flexible Air quality Regional Model, FARM). The concentrations in the air ranged from 20 to 200pg m−3 for PCBs and from 5 to 48ng m−3 for PAHs with the highest concentrations being detected at Bari center. PCB composition was dominated by the 3–Cl congeners (periods 1 and 2) and by 5–Cl (periods 3 and 4). PCB–28 and –37 were the most abundant congeners during the four periods. The PAHs profile was dominated by the 3–ring (70±6)%, with phenanthrene alone accounting for (49±2)%. On a seasonal basis opposite patterns were observed for PCBs and PAHs showing high PCB concentrations during the warm periods, period 3: summer and 2: spring, while PAHs were found during cool periods, period 4: autumn, and 1: winter. The results obtained from the application of the FARM model, during 2010, and limited to period 4 in this study, showed similar estimated levels for PCBs indicating a good performance for PCB modeled concentrations whilst for benzobfluoranthene (BbF) the results showed a less better agreement. This study represents one of the few efforts at characterizing PCBs and PAHs compositions in ambient air in southern Italy and also represents one of the preliminary attempts at using PAS–PUF to give more insight into a modeling prediction in Italy. These results also provide useful information for the future development of the FARM model.
Population exposure assessment plays a central role in developing efficient policies to control the significant health impacts caused by ambient pollution. Policy development requires comparison of ...alternative control options, which by definition can only be conducted using models. The current work presents results from an integrated model developed for Rome, Italy, to estimate the exposure distributions of children. Spatial distribution of the hourly PM
10
levels in 2005 was modeled by a chemical transport model and the modeled concentrations were adjusted using a procedure based on the observed PM
10
concentrations at urban stations. The PM
10
exposures of children were then estimated accounting for: the time–activity patterns in indoors, outdoors, and in traffic; adjusted ambient levels; and outdoor to indoor infiltration factors. The mean annual exposure level was 22 μg/m
3
, compared to the mean observed ambient concentration at a central station of 48 μg/m
3
, with higher seasonal levels estimated for spring and summer than for autumn and winter. The differences are caused by the longer time spent outdoors and higher residential ventilation rates during spring and summer. The highest integrated exposures took place in the northeasterly districts. Average exposure levels in almost the whole city exceeded 20 μg/m
3
. Short-term exposures were also investigated during a winter PM
10
episode for which exposure levels in excess of 30 μg/m
3
were calculated. Cumulative distribution results for the children indicate that the 24-h limit of 50 μg/m³ set for the protection of human health is not exceeded by the exposures of children during the episode. The results of this study are important for a correct interpretation of the epidemiological studies taking into account the relationship of exposures and ambient air quality and for the development of alternative policy options to reduce children’s exposures by lifestyle modification and interventions focused on the reduction of the infiltration of PM
10
into indoor environments.
Issue Title: Special Issue: Conference on Air Quality --- Science and Application, Istanbul, March 2009/Guest Edited by Otto Hänninen, Sotiris Vardoulakis, Denis A. Sarigiannis and Ranjeet S. Sokhi ...Population exposure assessment plays a central role in developing efficient policies to control the significant health impacts caused by ambient pollution. Policy development requires comparison of alternative control options, which by definition can only be conducted using models. The current work presents results from an integrated model developed for Rome, Italy, to estimate the exposure distributions of children. Spatial distribution of the hourly PM^sub 10^ levels in 2005 was modeled by a chemical transport model and the modeled concentrations were adjusted using a procedure based on the observed PM^sub 10^ concentrations at urban stations. The PM^sub 10^ exposures of children were then estimated accounting for: the time-activity patterns in indoors, outdoors, and in traffic; adjusted ambient levels; and outdoor to indoor infiltration factors. The mean annual exposure level was 22 μg/m^sup 3^, compared to the mean observed ambient concentration at a central station of 48 μg/m^sup 3^, with higher seasonal levels estimated for spring and summer than for autumn and winter. The differences are caused by the longer time spent outdoors and higher residential ventilation rates during spring and summer. The highest integrated exposures took place in the northeasterly districts. Average exposure levels in almost the whole city exceeded 20 μg/m^sup 3^. Short-term exposures were also investigated during a winter PM^sub 10^ episode for which exposure levels in excess of 30 μg/m^sup 3^ were calculated. Cumulative distribution results for the children indicate that the 24-h limit of 50 μg/m³ set for the protection of human health is not exceeded by the exposures of children during the episode. The results of this study are important for a correct interpretation of the epidemiological studies taking into account the relationship of exposures and ambient air quality and for the development of alternative policy options to reduce children's exposures by lifestyle modification and interventions focused on the reduction of the infiltration of PM^sub 10^ into indoor environments.PUBLICATION ABSTRACT
Population exposure assessment plays a central role in developing efficient policies to control the significant health impacts caused by ambient pollution. Policy development requires comparison of ...alternative control options, which by definition can only be conducted using models. The current work presents results from an integrated model developed for Rome, Italy, to estimate the exposure distributions of children. Spatial distribution of the hourly PM sub(10) levels in 2005 was modeled by a chemical transport model and the modeled concentrations were adjusted using a procedure based on the observed PM sub(10) concentrations at urban stations. The PM sub(10) exposures of children were then estimated accounting for: the time-activity patterns in indoors, outdoors, and in traffic; adjusted ambient levels; and outdoor to indoor infiltration factors. The mean annual exposure level was 22 mu g/m super(3), compared to the mean observed ambient concentration at a central station of 48 mu g/m super(3), with higher seasonal levels estimated for spring and summer than for autumn and winter. The differences are caused by the longer time spent outdoors and higher residential ventilation rates during spring and summer. The highest integrated exposures took place in the northeasterly districts. Average exposure levels in almost the whole city exceeded 20 mu g/m super(3). Short-term exposures were also investigated during a winter PM sub(10) episode for which exposure levels in excess of 30 mu g/m super(3) were calculated. Cumulative distribution results for the children indicate that the 24-h limit of 50 mu g/m super(3) set for the protection of human health is not exceeded by the exposures of children during the episode. The results of this study are important for a correct interpretation of the epidemiological studies taking into account the relationship of exposures and ambient air quality and for the development of alternative policy options to reduce children's exposures by lifestyle modification and interventions focused on the reduction of the infiltration of PM sub(10) into indoor environments.
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