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Aims We aimed at investigating the relationship between particulate matter (PM) and daily admissions for cardiovascular diseases (CVDs) at national level in Italy. Methods and results Daily numbers of cardiovascular hospitalizations were collected for all 8084 municipalities of Italy, in the period 2013–2015. A satellite-based spatiotemporal model was used to estimate daily PM10 (inhalable particles) and PM2.5 (fine particles) concentrations at 1-km2 resolution. Multivariate Poisson regression models were fit to estimate the association between daily PM and cardiovascular admissions. Flexible functions were estimated to explore the shape of the associations at low PM concentrations, also in non-urban areas. We analysed 2 154 810 acute hospitalizations for CVDs (25% stroke, 24% ischaemic heart diseases, 22% heart failure, and 5% atrial fibrillation). Relative increases of total cardiovascular admissions, per 10 µg/m3 variation in PM10 and PM2.5 at lag 0–5 (average of last 6 days since admission), were 0.55% (95% confidence intervals: 0.32%, 0.77%) and 0.97% (0.67%, 1.27%), respectively. The corresponding estimates for heart failure were 1.70% (1.28%, 2.13%) and 2.66% (2.09%, 3.23%). We estimated significant effects of PM10 and PM2.5 also on ischaemic heart diseases, myocardial infarction, atrial fibrillation, and ischaemic stroke. Associations were similar between less and more urbanized areas, and persisted even at low concentrations, e.g. below WHO guidelines. Conclusion PM was robustly associated with peaks in daily cardiovascular admissions, especially for heart failure, both in large cities and in less urbanized areas of Italy. Current WHO Air Quality Guidelines for PM10 and PM2.5 are not sufficient to protect public health.

Daily air pollution has been linked with mortality from urban studies. Associations in rural areas are still unclear and there is growing interest in testing the role that air pollution has on other causes of death. This study aims to evaluate the association between daily air pollution and cause-specific mortality in all 8092 Italian municipalities.Natural, cardiovascular, cardiac, ischemic, cerebrovascular, respiratory, metabolic, diabetes, nervous and psychiatric causes of death occurred in Italy were extracted during 2013-2015. Daily ambient PMWe estimated a positive association between PMShort-term exposure to particulate matter was associated with mortality from nervous diseases. Mortality from metabolic diseases was associated with NO

The number of cities, or parts of cities, where air quality has been computed using the PMSS 3D model now appears to be sufficient to allow assessment and understanding of performance. Two fields of application explain the growing number of sites: the first is the long-term air quality assessment required in urban areas for any building or road project. The geometric complexity found in such areas can justify the use of a 3D approach, as opposed to Gaussian ones. However, these studies have constraining rules that can make the modelling challenging: several scenarios are needed (current, future with project, future without project), the long-term impact implies a long physical time period to be computed, and the spatial extension of the domain can be large in order to cover the traffic impact zone of the project. The second type of application is dedicated to services and, essentially, to forecasting. As for impact assessments, the modelling can be challenging here because of the extension of the domain if the target area is a whole city. Forecast also adds the constraint of time, as results are requested early, and the constraint of robustness. The CPU amount needed to meet all these requirements is important. It is therefore crucial to optimize all possible parts of the modelling chain in order to limit cost and delay. The sites presented in the article have been modelled with PMSS for long periods. This allows feedback to be provided on different topics: (a) daily forecasts offer an opportunity to increase the robustness of the modelling chain, (b) quantitative validation at air quality measurement stations, (c) comparison of annual impact based on a whole year, and based on a sampling list of dates selected thanks to a classification process, (d) large calculation domains with widespread pollutant emissions offer a great opportunity to qualitatively check and improve model results on numerous geometrical configurations, (e) CPU time variations between different sites provide valuable information to select the best parametrizations, to predict the cost of the services, and to design the needed hardware for a new site.

Urban air quality in cities is strongly influenced by road traffic emissions. Micro-scale models have often been used to evaluate the pollutant concentrations at the scale of the order of meters for estimating citizen exposure. Nonetheless, retrieving emissions information with the required spatial and temporal details is still not an easy task. In this work, we use our modelling system PMSS (Parallel Micro Swift Spray) with an emission dataset based on Floating Car Data (FCD), containing hourly data for a large number of road links within a 1 × 1 km2 domain in the city of Rome for the month of May 2013. The procedures to obtain both the emission database and the PMSS simulations are hosted on CRESCO (Computational Centre for Research on Complex Systems)/ENEAGRID HPC facilities managed by ENEA. The possibility of using such detailed emissions, coupled with HPC performance, represents a desirable goal for microscale modeling that can allow such modeling systems to be employed in quasi-real time and nowcasting applications. We compute NOx concentrations obtained by: (i) emissions coming from prescribed hourly modulations of three types of roads, based on vehicle flux data in the FCD dataset, and (ii) emissions from the FCD dataset integrated into our modelling chain. The results of the simulations are then compared to concentrations measured at an urban traffic station.

In a complex environment such as an urban area, accurate prediction of the atmospheric dispersion of airborne harmful materials such as radioactive substances is necessary for establishing response actions and assessing risk or damage. Given the variety of urban atmospheric dispersion models available, evaluation and inter-comparison exercises are vital for assessing quantitatively and qualitatively their capabilities and differences. To that end, the European Commission/Directorate General Joint Research Centre with support from the European Commission/Directorate General-Migration and Home Affairs, and with the contribution of the U.S. Defense Threat Reduction Agency, launched the Urban Dispersion INternational Evaluation Exercise (UDINEE) project. Within UDINEE, nine atmospheric dispersion models are evaluated and intercompared. Sulphur hexafluoride concentrations from puffs released near the ground during the Joint Urban 2003 (JU2003) field experiment are used in UDINEE to evaluate atmospheric dispersion models. The JU2003 experiment is chosen because UDINEE aims at the better understanding of modelling capabilities for radiological dispersal devices in urban areas, and the neutrally-buoyant puff releases performed in the JU2003 experiment are the closest scenario to this purpose. The present study evaluates the capability of models at simulating the presence and concentration levels of the tracer at sampling locations. The fraction of predicted concentrations and time-integrated concentrations within a factor-of-two of observations are less than 0.36 and 0.4 respectively. The analysis reveals an improvement in the performance of models by using time-varying inflow conditions. Since the simulation of the dispersion of puff release is particularly challenging, the results of UDINEE could constitute a benchmark for future model developments.

The capabilities of nine atmospheric dispersion models in predicting near-field dispersion from puff releases in an urban environment are addressed under the Urban Dispersion INternational Evaluation Exercise (UDINEE) project. The model results are evaluated using tracer observations from the Joint Urban 2003 (JU2003) experiment where neutrally-buoyant puffs were released in the downtown area of Oklahoma City, USA. Sulphur hexafluoride concentration time series measured at ten sampling locations during four daytime and four night-time puff releases are used to evaluate how the models simulate the puff passage at the measurement locations. The neutrally-buoyant puff releases in the JU2003 experiment are the closest scenario to radiological dispersal device (RDD) releases in urban areas, and therefore, UDINEE is a first step towards improving the emergency response to an RDD explosion in the urban environment. We investigate for each puff and sampler the model capability of simulating the peak concentration; the peak and puff arrival times; and time duration, defined as the period over which concentrations exceed 10% of the peak concentration. This analysis points out differences on the performance of models: the fraction within a factor-of-two values ranges from 0.10 to 0.6 for peak concentration, from 0 to 1 for the peak and arrival times, and from 0 to 0.8 for the time duration. The results reveal that the characteristics of the release site largely influence the model simulation as it affects initial puff size and the initial downwind spread of the puff.

Background/aim The relationship between air pollution and respiratory morbidity has been widely addressed in urban and metropolitan areas but little is known about the effects in non-urban settings. Our aim was to assess the short-term effects of PM10 and PM2.5 on respiratory admissions in the whole country of Italy during 2006–2015. Methods We estimated daily PM concentrations at the municipality level using satellite data and spatiotemporal predictors. We collected daily counts of respiratory hospital admissions for each Italian municipality. We considered five different outcomes: all respiratory diseases, asthma, chronic obstructive pulmonary disease (COPD), lower and upper respiratory tract infections (LRTI and URTI). Meta-analysis of province-specific estimates obtained by time-series models, adjusting for temperature, humidity and other confounders, was applied to extrapolate national estimates for each outcome. At last, we tested for effect modification by sex, age, period, and urbanization score. Analyses for PM2.5 were restricted to 2013–2015 cause the goodness of fit of exposure estimation. Results A total of 4,154,887 respiratory admission were registered during 2006–2015, of which 29% for LRTI, 12% for COPD, 6% for URTI, and 3% for asthma. Daily mean PM10 and PM2.5 concentrations over the study period were 23.3 and 17 μg/m3, respectively. For each 10 μg/m3 increases in PM10 and PM2.5 at lag 0–5 days, we found excess risks of total respiratory diseases equal to 1.20% (95% confidence intervals, 0.92, 1.49) and 1.22% (0.76, 1.68), respectively. The effects for the specific diseases were similar, with the strongest ones for asthma and COPD. Higher effects were found in the elderly and in less urbanized areas. Conclusions Short-term exposure to PM is harmful for the respiratory system throughout an entire country, especially in elderly patients. Strong effects can be found also in less urbanized areas.

The role of atmospheric dispersion models is becoming increasingly relevant to assess air pollution urban population exposure for epidemiological studies. Estimating urban air quality is challenging, because of the intrinsic characteristics of cities atmospheric structure, such as high density of primary emissions and presence of local dispersion processes, that produce strong concentration gradients. Therefore, very high spatial resolution simulations may often be required to improve the accuracy of estimations. The objective of this study is developing a microscale hybrid modelling system (HMS) to carry out, in a reasonable computational time, long-term simulations providing hourly concentration fields at building-resolving scale in extended urban areas in order to calculate annual indicators to evaluate exposure. The proposed system couples two atmospheric dispersion models suited for different scales: a Eulerian chemical transport model, FARM (Flexible Air quality Regional Model), accounting for dispersion phenomena due to regional and local emission sources, and a Lagrangian particle micro-scale dispersion model, PMSS (Parallel Micro Swift Spray), used to compute concentrations induced by vehicular traffic inside the city. The HMS has been applied on 12 × 12 km2 domain in Rome with a horizontal resolution of 4 m for calculating NO2 and PM10 concentrations for all year 2015. This study has been carried out in the frame of project BEEP (Big data in Environmental and occupational Epidemiology), that is an Italian research project in epidemiological field. Results show that the combined use of the two models reproduces the spatial and temporal variability of the observed atmospheric pollutants with a good agreement. The statistical analysis performed on daily average concentrations proves that the HMS suits the standard acceptance criteria for urban dispersion model evaluation, with a FAC2 of 0.92 and 0.80 and a Fractional Bias of −0.03 and −0.2 for NO2 and PM10 respectively. Furthermore, the implementation of an innovative kernel method to calculate concentrations in PMSS has made possible to reduce the computational time by 80%, leading to an average computational time of 3 h per simulated day on an HPC (High Performance Computing) system with 180 cores.

A 3D dry deposition scheme for particulate matter (PM) is presented as a Free-Libre and Open-Source Software (FOSS) library, DePaSITIA (RSE SpA). This combines some advanced formulations for the deposition mechanisms of sedimentation, inertial impaction, turbulent impaction and interception. The scheme also considers bouncing effects. The input quantities relate to the canopy elements (Leaf Area Density, leaf equivalent diameter, leaf shape, orientation and roughness parameters), the transporting fluid (local mean velocity, friction velocity) and the particulate matter (PM local mean concentration, median diameter and density). The deposition scheme is coupled with a well-known Lagrangian Stochastic model for pollutant dispersion, the Open-Source code SPRAY-WEB (Università del Piemonte Orientale et al.). The coupled numerical solution is validated on a laboratory test case representing the dispersion of particulate matter from two line sources within a canopy atmospheric boundary layer. The deposition interfaces are represented by the trees of a scaled spruce forest. Validation refers to the average vertical profile of the deposited mass (not the mean concentration) normalized by the above-canopy mean concentration. Some inter-comparisons are also reported considering uniform Leaf Area Density, the additional effects of molecular diffusion, the height-dependent relative contribution of each deposition mechanism and an alternative deposition scheme. The results of this test case are available as a FOSS tutorial. Considering the Fractional Bias obtained for the deposited mass (FB = 27%), this numerical solution seems suitable to simulating stationary dispersion phenomena within complex canopy boundary layers, assessing the height-dependent dry deposition fluxes of atmospheric PM. The current numerical solution might be improved and applied to elevated obstacles such as electric insulators. Article Highlights: oDevelopment of a height-dependent dry deposition scheme 37 for particulate matter, coupled with a pollutant dispersion code.oValidation on a vertical profile of deposited pollutant mass.oAssessment of each deposition mechanism; availability of the code and tutorial as Open-Source Software; possible application to any elevated or ground-level 3D obstacle.

Long-term exposure to air pollution has been related to mortality in several epidemiological studies. The investigations have assessed exposure using various methods achieving different accuracy in predicting air pollutants concentrations. The comparison of the health effects estimates are therefore challenging. This paper aims to compare the effect estimates of the long-term effects of air pollutants (particulate matter with aerodynamic diameter less than 10 μm, PM10, and nitrogen dioxide, NO2) on cause-specific mortality in the Rome Longitudinal Study, using exposure estimates obtained with different models and spatial resolutions. Annual averages of NO2 and PM10 were estimated for the year 2015 in a large portion of the Rome urban area (12 × 12 km2) applying three modelling techniques available at increasing spatial resolution: 1) a chemical transport model (CTM) at 1km resolution; 2) a land-use random forest (LURF) approach at 200m resolution; 3) a micro-scale Lagrangian particle dispersion model (PMSS) taking into account the effect of buildings structure at 4 m resolution with results post processed at different buffer sizes (12, 24, 52, 100 and 200 m). All the exposures were assigned at the residential addresses of 482,259 citizens of Rome 30+ years of age who were enrolled on 2001 and followed-up till 2015. The association between annual exposures and natural-cause, cardiovascular (CVD) and respiratory (RESP) mortality were estimated using Cox proportional hazards models adjusted for individual and area-level confounders. We found different distributions of both NO2 and PM10 concentrations, across models and spatial resolutions. Natural cause and CVD mortality outcomes were all positively associated with NO2 and PM10 regardless of the model and spatial resolution when using a relative scale of the exposure such as the interquartile range (IQR): adjusted Hazard Ratios (HR), and 95% confidence intervals (CI), of natural cause mortality, per IQR increments in the two pollutants, ranged between 1.012 (1.004, 1.021) and 1.018 (1.007, 1.028) for the different NO2 estimates, and between 1.010 (1.000, 1.020) and 1.020 (1.008, 1.031) for PM10, with a tendency of larger effect for lower resolution exposures. The latter was even stronger when a fixed value of 10 μg/m3 is used to calculate HRs. Long-term effects of air pollution on mortality in Rome were consistent across different models for exposure assessment, and different spatial resolutions.

Background. Storage tanks in oil and gas processing facilities contain large volumes of flammable compounds. Once the fuel-air mixture is ignited, it may break out into a large fire or explosion. The growing interest in monitoring air quality and assessing health risks makes the evaluation of the consequences of a fire an important issue. Atmospheric dispersion models, which allow for simulation of the spatial distribution of pollutants, represent an increasingly widespread tool for this type of evaluations. Objectives. The present study discusses the set up and results of a modeling study relevant to a hypothesized fire in an oil refinery. Methods. After choosing the most suitable dispersion models, i.e. the Lagrangian model SPRAY and the puff model CALPUFF, estimation of the required input data is discussed, focusing on the source variables, which represent the most uncertain input data. The results of the simulations were compared to regulatory limits to effectively evaluate the environmental consequences. Finally, a sensitivity analysis was employed to identify the most influential variables. Results. The simulation results revealed that ground concentration values were far below the cited long-term limits. However, the most interesting outcome is that depending on the dispersion model and the source type modeled, different results may be obtained. In addition, the sensitivity study indicates that the source area is the most critical variable, since it determines a significantly different behavior depending on the modeled source types, producing, in some cases, variability in the pollutant ground concentrations on selected receptors up to +/− 60%. Conclusions. Depending on the selected model and the algorithms available to describe the physics of emission, the results showed a different sensitivity to the input variables. Although this can be explained from a mathematical point of view, the problem remains of choosing case by case the option that best approximates the real behavior of the incidental source under investigation. Competing Interests. The authors declare no competing financial interests.

In order to support environmental policies, epidemiological studies and urban mobility planning, a multi-scale modelling system was developed to provide hourly NOx (NO + NO2) concentration fields at a building-resolving scale in the urban area of Modena, a city in the middle of the Po Valley (Italy). The modelling system relied on two different models: the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), which is able to compute concentration fields over regional domain by considering specific emission scenarios, and Parallel Micro SWIFT SPRAY (PMSS), a Lagrangian particle model accounting for dispersion phenomena within the urban area. PMSS was used to simulate at building-scale resolution the NOx dispersion produced by urban traffic flows in the city of Modena. Conversely, WRF-Chem was selected to estimate the NOx background concentrations over three nested domains with resolution of 15, 3 and 1 km in order to take into account emissions both at regional and local scale by excluding traffic emissions sources over the city of Modena. The estimation of traffic emissions in the urban area of Modena was based on a bottom-up approach relying on the Emission Factors suggested by the European Monitoring and Evaluation Programme (EMEP/EEA) and traffic fluxes estimated by the PTV VISUM model. By contrast, other anthropogenic emissions were taken from the TNO-MACC III inventory at the scales resolved by the WRF-Chem model. Simulation was performed between 28 October and 8 November 2016, the same period whereby a direct vehicle flow measurement campaign was carried out continuously, with 4 Doppler radar counters in a four-lane road in Modena, to reproduce the hourly modulation rates of the emissions. The performances of the model chain were finally assessed by comparing modelled NOx concentrations with observations at two air quality monitoring stations located inside the urban domain. Simulated and observed NOx hourly concentrations exhibit a large agreement, in particular for urban traffic site where detailed traffic emissions estimation (real traffic modulation combined with a bottom-up approach) proved to be very successful in reproducing the observed NOx pattern. At the urban background station, notwithstanding a general underestimation of the observed concentrations (more pronounced than at the urban traffic site), the analysis of hourly daily modelled concentrations shows that PMSS combined with WRF-Chem provided a daily pattern in line with observations. These features highlight the strength of this modelling chain in representing urban air quality, in particular at traffic sites, whose concentration levels make them the most critical area of the city; characteristics that chemical transport models alone cannot express, due to the coarser resolution to which they operate and to their inability to reproduce street canyons and urban structures.

A multi-scale modelling system was developed to provide hourly NOx concentration fields at a building-resolving scale in the urban area of Modena, a city in the middle of the Po Valley (Italy), one of the most polluted areas in Europe. The WRF-Chem model was applied over three nested domains and employed with the aim of reproducing local background concentrations, taking into account meteorological and chemical transformation at the regional scale with nested resolutions of 15 km, 3 km and 1 km. Conversely, the PMSS modelling system was applied to simulate 3D air pollutant dispersion, due to traffic emissions, with a very high-resolution (4 m) on a 6 km × 6 km domain covering the city of Modena. The methodology employed to account for anthropogenic emissions relies on two different strategies. Traffic emissions were based on a bottom-up approach using emission factors suggested by the European Environmental Agency with traffic fluxes estimated by the PTV VISUM model in the urban area of Modena, combined with direct traffic flow measurements performed between October 28 and November 8, 2016 which was used for the hourly vehicle modulation. Other anthropogenic emissions were taken from the TNO-MACC III inventory at the scales resolved by the WRF-Chem model. Simulations were performed for the same period whereby the traffic measurement campaign was carried out. 2 m temperature and 10 m wind speed were captured quite well by the WRF-Chem model with statistical metrics in line with similar case studies related to the Northern Italy. The NOx concentrations reproduced in the Po Valley area by WRF-Chem were on average simulated reasonably well with a general negative bias in almost all the examined rural background monitoring stations. Additionally, the deployment of an emission inventory at the original resolution (7 km) highlighted that increasing resolution from 3 km to 1 km does not generally improve the model performance. Nevertheless, simulated and observed NOx hourly concentrations in the urban area of Modena exhibit a large agreement in particular for urban traffic site where detailed traffic emission estimations proved to be very successful in reproducing the observed NOx trend. At urban background stations, despite a general underestimation of the observed concentrations, the combination of WRF-Chem with PMSS provided daily pattern in line with observations. The analysis of the modelled NOx daily cycle pointed out also that at both traffic and background urban stations the morning NOx peak concentration was on average underestimated. This could be explained with an overestimation of mixing phenomena between 07:30 a.m. and 10:00 a.m. by WRF-Chem which leads to a greater dispersion of NOx along the vertical and thus a morning underestimation. The statistical analysis showed finally that PMSS combined with WRF-Chem at both the resolutions (3 km and 1 km) and at both traffic and background sites fulfilled standard acceptance criteria for urban dispersion model evaluation, confirming that the proposed multi-modelling system can be employed as a tool to support environmental policies, epidemiological studies and urban mobility planning.

When modelling the dispersion of pollutants in the atmosphere, uncertainty in the simulation results that depend on the available data used as input conditions is a critical issue, particularly in the context of emergency response to the accidental release of harmful substances. In the framework of the UDINEE Project, a Lagrangian particle dispersion model is used to simulate puff emissions in four different test cases, using input wind velocity data from two different datasets, both representative of the flow at the time of the release. The effect of the choice of the input data on the final concentration distribution at ground level is discussed and compared with observations. A statistical analysis is applied to estimate the deviation between the results of the two runs. The bias between the two concentration fields, connected to the variability and the uncertainty in the input flow, is found to be of similar magnitude to the typical bias between model predictions and observations.

Noxious atmospheric releases may originate from both accidents and malicious activities. They are a major concern for public authorities or first responders who may wish to have the most accurate situational awareness. Nonetheless, it is difficult to reliably and accurately model the flow, transport, and dispersion processes in large complex built-up environments in a limited amount of time and resources compatible with operational needs. The parallel version of Micro-SWIFT-SPRAY (PMSS) is an attempt to propose a physically sound and fast response modelling system applicable to complicated industrial or urban sites in case of a hazardous release. This paper presents and justifies the choice of the diagnostic flow and Lagrangian dispersion models in PMSS. Then, it documents in detail the development of the parallel algorithms used to reduce the computational time of the models. Finally, the paper emphasizes the preliminary model validation and parallel performances of PMSS based on data from both wind tunnel (Evaluation of Model Uncertainty) and in-field reduced-scale (Mock Urban Setting Test) and real-scale (Oklahoma City) experimental campaigns.

After the summer 2015 chlorine releases during the Jack Rabbit II field experiment at Dugway Proving Ground, a special sonic anemometer study was carried out in October 2015 and March 2016. The goal was to provide documented wind fields in similar conditions to the actual releases and to study building wakes without risk for the instruments. This study included 30 sonic anemometers that were placed around these "buildings" to best capture the recirculating regions. Building wakes are important for the dispersion of pollutants in cities and around industrial plants and therefore we have selected two time periods during March 2016, in order to present model to model and model to data comparisons. There are four models involved in the comparison ranging from a diagnostic wind model with wake parameterization and Lagrangian particle dispersion and a CFD model with a k-epsilon turbulence closure and solving the Eulerian dispersion equation. Detailed comparisons are carried out for the wind speed and for the turbulence level. Six virtual releases are added in the simulations to investigate how the wake resolving method can affect the dispersion. For the wind speed comparison, the models give fair to good comparison with the sonic measurements. However, for the turbulence comparison the results clearly show a need for improvement, even for the k-epsilon closure, which still provides the best results. For the concentrations, for which there is no corresponding measurements, we find that the simulations are much closer than for the turbulence comparison.

The evaluation of the spatial representativeness of air quality monitoring stations is of fundamental relevance when observed concentration levels are used in air quality assessment. Since no reference method is provided, there is a need to develop tools for its quantitative assessment. In this paper we test a recently developed methodology for spatial representativeness area assessment, based on the analysis of time series of model concentrations by means of a Concentration Similarity Frequency (CSF) function, on the Taranto-via Machiavelli industrial monitoring station, located in a mid-size city in Southern Italy. The complex territorial context, the peculiar anthropogenic emissions features, dominated by the contribution of the largest steelworks in Europe, and the critical situation of human health in the city make this application an interesting case study to assess the portability of the CSF approach, so far applied only to background stations, to industrial sites that experience high concentration variability. A comprehensive characterization of the main anthropogenic emissions of the area was carried out, with detailed treatment of dust emission by wind erosion from industrial mineral piles; a Lagrangian modelling approach was chosen to simulate PM10 dispersion patterns, to achieve a reliable and high resolution description of concentration variability around the site. The resulting representativeness area of the station is 0.067 km2, fulfilling EU prescriptions for industrial stations. The comprehensive evaluation results, through the comparison with the observed data, showed good performances pointing out the reliability of the estimated concentration fields around the site and consequently of the assessment of its representativeness area.

The composition in Volatile Organic Compounds (VOC) of the biogas produced by seven landfills of Giugliano (Naples, Campania, Italy) was determined and VOC emission rates assessed to verify if these compounds represent a potential threat to the population living nearby. VOC composition in the biogas could not be predicted, as heterogeneous waste was dumped from the late 1980s to the early 2000s and then underwent biological degradation. No data are available on the amount and composition of VOC in the biogas before the landfills closure as no operational biogas collection system was present. In this study, VOC composition was determined by gas chromatography–mass spectrometry (GC–MS), after collecting samples from collection pipes and from soil fractures in cover soil or capping. Individual VOC were quantified and data compared with those collected at two landfills in Latium, when they were still in operation. Relevant differences were observed, mainly due to waste aging, but no specific VOC revealing toxic waste dumping was found, although the concurrent presence of certain compounds suggested that dumping of industrial wastes might have occurred. The average VOC emission was assessed and a dispersion model was run to find out if the emitted plume could affect the health of population. The results suggested that fugitive emissions did not represent a serious danger, since the concentrations simulated at the neighboring cities were below the threshold limits for acute and chronic diseases. However, VOC plume could cause annoyance at night when the steady state conditions of the atmosphere enhance pollutants accumulation in the lower layers. In addition, some of the emitted VOC, such as alkylbenzenes and monoterpenes, can contribute to tropospheric ozone formation.

Unexpected releases of hazardous airborne materials may happen in various circumstances, more frequently in accidental situations, less usually due to malicious activities. In all cases, the risk for the population and the rescue team is real and must be evaluated in order to take appropriate protection measures. Numerical models are more and more used in emergency response tools for predicting the atmospheric dispersion of pollutants and estimating impacted areas. Still, flow and dispersion modelling in a built-up environment may be very challenging given the complex geometry and meteorological conditions. Here, we present and evaluate a modelling approach that is a compromise between accuracy and timeliness of the computations. It is based on a 3D Lagrangian Particle Dispersion model driven by 3D flow and turbulence input provided by either a diagnostic mass-consistent model or a model solving the Reynolds-Averaged Navier-Stokes equations. This modelling system has been validated on a panel of experimental test cases from the Cooperation in Science and Technology (COST) Action ES1006 in both idealized and realistic urban mock-ups, wind tunnel and field trials, continuous and puffs releases. The sensitivity of the model to the meteorological input data is assessed. The results are discussed comparing predicted concentrations to measurements. The performances of the modelling system are evaluated through a statistical analysis. They were found to depend on the type of test case, type of release and location of the source in the built-up domain. Results show that the model is compliant with the validation criteria, established in literature for the reference metrics, in the large majority of the test cases. The modelling system proved to be robust enough to be used in the context of emergency response, when fast but still reliable results are needed.

A modelling study, supported by a sensitivity analysis, is proposed for assessing the distinctive features of the dispersion of ship emissions in the Venice Lagoon. The main aspects on which the analysis focuses are the appropriate parameterization of the turbulence variables in the lagoon, the proper treatment of the lagoon-sea surface temperature and the evaluation of different parameterizations for the plume rise to describe the pollutant emissions from moving ships. The results of the study are discussed in the context of the environmental impact assessment of present and future scenarios.

Three different modelling techniques to simulate the pollutant dispersion in the atmosphere at the microscale and in presence of obstacles are evaluated and compared. The Eulerian and Lagrangian approaches are discussed, using RAMS6.0 and MicroSpray models respectively. Both prognostic and diagnostic modelling systems are considered for the meteorology as input to the Lagrangian model, their differences and performances are investigated. An experiment from the Mock Urban Setting Test field campaign observed dataset, measured within an idealized urban roughness, is used as reference for the comparison. A case in neutral conditions was chosen among the available ones. The predicted mean flow, turbulence and concentration fields are analysed on the basis of the observed data. The performances of the different modelling approaches are compared and their specific characteristics are addressed. Given the same flow and turbulence input fields, the quality of the Lagrangian particle model is found to be overall comparable to the full-Eulerian approach. The diagnostic approach for the meteorology shows a worse agreement with observations than the prognostic approach but still providing, in a much shorter simulation time, fields that are suitable and reliable for driving the dispersion model.

Il comprensorio Acerrano si inserisce in una realtà territoriale ed ambientale complessa, per la presenza di fattori di pressione ambientale diversificati e per le problematiche comuni alla cosiddetta 'terra dei fuochi'. Nel dominio oggetto di studio sono presenti: ? l'impianto di incenerimento e valorizzazione di rifiuti solidi urbani; ? sorgenti di inquinanti di tipo industriale e di trattamento dei rifiuti; ? intenso traffico veicolare (autostrade, strade principali e centri urbani); ? sorgenti emissive legate al riscaldamento degli edifici ad uso residenziale/terziario. In questo contesto, l'attività del progetto SAmbA ha realizzato un apparato d'indagine ambientale integrato, basato su misure da piattaforme mobili terrestri ed aeroportate, rilievi di dettaglio dei parametri biofisici ed ambientali e simulazioni modellistiche dell'evoluzione della qualità dell'aria che hanno permesso di quantificare l'apporto delle diverse sorgenti alla qualità dell'aria nel comprensorio acerrano. Sul territorio oggetto di studio sono stati dislocati apparati sperimentali per il monitoraggio della qualità dell'aria e condotte campagne di misura con strumentazione installata su mezzi mobili stradali e su aerei, per approfondire le informazioni sulla qualità ambientale del territorio e far fronte alle carenze informative ed al contempo fornire elementi quantitativi di verifica per le simulazioni modellistiche. Il precedente Studio modellistico di ricaduta delle emissioni del termovalorizzatore di Acerra contestualizzato all'interno della realtà territoriale (©CNR Edizioni, ISBN 978 88 8080 229 7, Aprile 2016), ha fornito dati quantitativi per la determinazione dell'impatto ambientale dell'impianto di termovalorizzazione dei rifiuti, mediante un approccio integrato che ha quantificato l'apporto delle diverse sorgenti inquinanti nel comprensorio di Acerra - attraverso l'uso combinato un modello dispersivo di tipo lagrangiano a particelle e di un modello fotochimico. Il presente volume riporta i risultati di dettaglio delle ampie e diversificate misure e analisi ambientali svolte, che consentono di ricomporre un quadro complesso a partire dall'analisi di numerosi parametri ambientali a diverse scale di indagine.

A main research task of COST Action ES1006 is the evaluation of atmospheric dispersion models by their comparison against test data from qualified field and laboratory experiments and by a model inter-comparison. The model comparison and evaluation carried out for three test cases is presented, addressing the performance of the different modelling approaches, quantifying the scatter of results when different models are applied and assessing the effect of uncertainties.

Lo studio è finalizzato alla determinazione dell'impatto ambientale dell'impianto di termovalorizzazione dei rifiuti di Acerra mediante un approccio integrato che, a partire della verifica delle principali sorgenti emissive, prevede rilievi di qualità dell'aria dei comprensori limitrofi e simulazioni modellistiche. Nell'ambito di questo progetto si è realizzato un apparato d'indagine ambientale integrato, basato su misure da piattaforme mobili terrestri ed aeroportate, rilievi di dettaglio dei parametri biofisici ed ambientali e simulazioni modellistiche dell'evoluzione della qualità dell'aria che hanno permesso di ottenere un "source apportionment" a scala locale in grado di quantificare l'apporto delle diverse sorgenti alla qualità dell'aria nel comprensorio di Acerra.

The location of an unknown source and its pollutant emissions are estimated from concentration observations by means of two approaches, both making use of the adjoint of a Lagrangian particle dispersion model. In the first approach, plausible source locations are estimated by identifying areas with maximum spatial and temporal consistency among backward trajectories from each sensor. In the second approach, a variational method is used to minimise the objective function and to estimate emissions at each grid-box reached by backward trajectories: the resulting map provides information on the source location and on its uncertainty. The two methods are compared using a hierarchy of test cases, starting from a controlled field experiment up to real world operational cases. Both methods give acceptable results with regard to the source location, and the variational method gives a more accurate estimation of the emitted masses. Main sources of uncertainty are discussed.

This paper evaluates the relative impact on air quality of harbour emissions, with respect to other emission sources located in the same area. The impact assessment study was conducted in the city of Taranto, Italy. This area was considered as representative of a typical Mediterranean harbour region, where shipping, industries and urban activities co-exist at a short distance, producing an ideal case to study the interaction among these different sources. Chemical and meteorological field campaigns were carried out to provide data to this study. An emission inventory has been developed taking into account industrial sources, traffic, domestic heating, fugitive and harbour emissions. A 3D Lagrangian particle dispersion model (SPRAY) has then been applied to the study area using reconstructed meteorological fields calculated by the diagnostic meteorological model MINERVE. 3D short term hourly concentrations have been computed for both all and specific sources. Industrial activities are found to be the main contributor to SO2. Industry and traffic emissions are mainly responsible for NOx simulated concentrations. CO concentrations are found to be mainly related to traffic emissions, while primary PM10 simulated concentrations tend to be linked to industrial and fugitive emissions. Contributions of harbour activities to the seasonal average concentrations of SO2 and NOx are predicted to be up to 5 and 30 μg m−3, respectively to be compared to a overall peak values of 60 μg m−3 for SO2 and 70 μg m−3 for NOx. At selected urban monitoring stations, SO2 and NOx average source contributions are predicted to be both of about 9% from harbour activities, while 87% and 41% respectively of total concentrations are predicted to be of industrial origin.

According to EU Directive 96/62/CE, Piedmont Region set up a project to perform air quality assessment by means of an integrated modelling system. To verify the system reliability, simulations of two air pollution episodes have been programmed. Results obtained from the simulation of a winter peak episode are presented here. The model domain covers an area of 80x80km^2 centred on the city of Turin and the simulation period lasts four days (28th-31st January 2000). SPRAY Lagrangian particle model, coupled with the MINERVE diagnostic wind field code, has been used to reconstruct the episode, taking into account CO and NO"x. Computed ground level concentrations have been compared with measured values at different sites (urban, sub-urban and remote). The analysis of results reveals that the system capability in reproducing concentrations behavior is higher in ''urban background'' or suburban stations, and lower in sites heavily affected by nearby traffic; this is attributed to spatial resolution effects, local traffic emissions modulation and urban boundary layer modelling. These aspects are discussed, highlighting possible improvements.

This paper reports the results of an integrated assessment of traffic impact on a tourist-popular high altitude region which includes mountain passes and road tunnels. A modeling system for air quality assessment and management has been established and revised. The system has been used to evaluate the impact of traffic due to the re-opening of the Mont Blanc tunnel: the increase in NO x concentrations ranges from 50% at the bottom of the upper valley to 150% near to tunnel entrance.

The effect of using in dispersion modeling different parameterizations for the wind velocity fluctuations standard deviations is investigated for low-wind conditions.

The new residential district ‘CityLife’ is under construction inside the city of Milan, northern Italy, replacing the old structure of the trade fair. It consists of relatively insulated blocks, surrounded by many gardens and commercial buildings and no car traffic at the surface. The objective of this study is to simulate and compare the pollution level inside this new area with a more common residential district located not so far away. High resolution simulations have been performed inside two domains – having linear dimension of approximately 1 km – using a microscale modeling system, taking directly into account the effects of buildings and street canyons to the atmospheric mean flow and turbulence. Emissions coming from car traffic (around the new district and inside the old one), underground traffic (emerging from ground-level openings in the new district) and heating systems (during winter) have been taken into account. Background values have been estimated from local measurements using a box model and added to the simulated concentration fields in order to produce a complete view of the local pollution levels. Both average levels of pollution at district scale and local behaviours into sub-zones of the two domains where similar activities are supposed to take place are compared showing the potential benefits inside the new district both in absolute terms and in percentage, setting in evidence which portion of the pollution can be reduced by local interventions.

In this work we simulated the Macdona (USA) chlorine railway accident with the Lagrangian dispersion model MicroSpray, twice: firstly by using the standard version and then by using a recently developed new two-phase module. MicroSpray was coupled with the diagnostic MicroSwift model, which provides the 3-D wind field in presence of obstacles and orography, and was used to test the two options. The results obtained in the two simulations, with and without the new module, are presented and the differences are discussed.

The possibilities offered by a mass-consistent model and by a non-hydrostatic meteorological model to reconstruct the wind field features at local scale, for wind energy applications in complex terrain, have been verified. The mass-consistent model has been applied to compute the space distribution of wind speeds and their variation with height to identify the areas suitable to wind turbine siting. The model has been initialized on the basis of a data set similar to the one available from a standard experimental campaign. Even though some subgrid scale characteristics of the flow are missing, the modeled field has been judged to give a rather satisfactory description of the winds over the studied region. The non-hydrostatic flow model has been applied to investigate the possibility to describe the local scale wind field characteristics starting from synoptic meteorological information. Upper air stratification proved to be important in determining the local scale wind speed and distribution even in near-neutral ground level stratification. The model results have been compared with both measurements and mass-consistent model.

The capability of two 3D Lagrangian particle models (ARCO and SPRAY) in simulating the airborne dispersion in highly complex terrain is tested. The simulations are compared to the tracer experiment TRANSALP-I performed on the 19th of October 1989 in the Alpine region (Canton of Ticino, Switzerland). TRANSALP exercises were part of the EUROTRAC-TRACT Subproject. Tracer was released during one hour (11.00–12.00) near the ground at Iragna, a few kilometres upwind from the bifurcation of two valleys (Leventina and Blenio Valleys); about 40 samplers, located in the two valleys in the range of 40 km, measured 1/2 h average mean concentrations near the ground for five hours. The results of the simulations are presented and discussed. A statistical model evaluation aimed at quantifying the performance of the two models was carried out. The simulations reproduced with a reasonable degree of accuracy the general behaviour of the observed phenomena: the split of the plume between the two valleys, the space and time distribution of the concentration, the concentration maxima locations.

Recently, Thomson and Montgomery (1994, Atmospheric Environment 28 , 1981–1987) stated the correct method of treating the reflection of particle velocity at the boundaries in Lagrangian particle diffusion models for non-Gaussian turbulence. Unfortunately, this method does not have an analytical solution. Two different approximated analytical solutions are proposed and compared. It is concluded that both of them satisfy the well-mixed condition and do not appreciably depart from the correct solution. The one consuming less time is proposed.

Pollutant transport and dispersion in complex orography are usually difficult to model accurately, due to the problem of properly reproducing wind and turbulence fields and interactions between pollutants and orography. In these situations the well-known Gaussian approach is limited. For studies of line sources (i.e. highways), models are available which are adequate for flat terrain and steady-state conditions (i.e. US-EPA recommended CALINE-3 and HIWAY-2). In complex terrain, however, no well-tested models are available. A possible approach to the problem is the use of a wind field model with a Lagrangian dispersion model well suited to consider both orography-induced inhomogeneities and line sources. We present the application of SPRAY particle model to reproduce pollutants dispersion from a highway at the bottom of a deep alpine valley, where pollutants are well confined and stagnation may occur. Model results for NOx are compared to those of the EPA recommended model HIWAY-2 and to measured concentrations.

The transfer of a passive tracer in inhomogeneous turbulent flow is investigated. Starting from Lumley's constitutive equation, we derived an expression for the ratio between the effective eddy diffusivity K and eddy diffusivity K as a function of three length scales characterizing the local turbulence structure, flux variations and turbulence inhomogeneities. The theoretical predictions for the one-dimensional case of inhomogeneous symmetric turbulence were validated through a comparison with the numerical results of a Lagrangian particle model simulating a wind tunnel experiment of dispersion in the lee of an idealized two-dimensional hill. A qualitative agreement is reached between the theoretical evaluation of K and the value obtained from the numerical simulation.

Spray, a 3D Lagrangian particle model for the simulation of complex flow dispersion, is presented. Its performance is tested against the Environmental Protection Agency wind tunnel concentration distribution of passive tracer released from elevated point sources, located in the lee region of a two-dimensional schematic hill, in a neutrally stratified boundary layer. Based on the measured values of the first two moments of the turbulent flow velocity, the mean fields are computed over a regular grid using a mass-consistent model, whereas the turbulence structure is simply interpolated. From these fields, trajectories of tracer particles are computed using a linear formulation of the Langevin equation, with a correlated, skewed forcing. The self-consistence test (well-mixed condition), aimed at maintaining an initially well-mixed particle distribution uniform in time, has shown satisfactory results in the region under study. The computed concentration field turns out to be in good agreement with th...

The goal of this work is to investigate, compare and evaluate three different modelling approaches to describe pollutant dispersion at the microscale and in presence of obstacles. The observed data used as reference for the comparison are those of the Mock Urban Setting Test (MUST) field campaign, providing flow and dispersion data measured within an idealized urban roughness. A case in neutral conditions was chosen.