ARIANET

Milano, Italy
Milano, Italy

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Kulkarni S.,University of Iowa | Kulkarni S.,California Air Resources Board | Sobhani N.,University of Iowa | Miller-Schulze J.P.,Wisconsin State Laboratory of Hygiene | And 27 more authors.
Atmospheric Chemistry and Physics | Year: 2015

Particulate matter (PM) mass concentrations, seasonal cycles, source sector, and source region contributions in Central Asia (CA) are analyzed for the period April 2008-July 2009 using the Sulfur Transport and dEposition Model (STEM) chemical transport model and modeled meteorology from the Weather Research and Forecasting (WRF) model. Predicted aerosol optical depth (AOD) values (annual mean value ~0.2) in CA vary seasonally, with lowest values in the winter. Surface PM2.5 concentrations (annual mean value ~10 μg m&3) also exhibit a seasonal cycle, with peak values and largest variability in the spring/summer, and lowest values and variability in the winter (hourly values from 2 to 90 μg m&3). Surface concentrations of black carbon (BC) (mean value ~0.1 μg m&3) show peak values in the winter. The simulated values are compared to surface measurements of AOD as well as PM2.5, PM10, BC, and organic carbon (OC) mass concentrations at two regional sites in Kyrgyzstan (Lidar Station Teplokluchenka (LST) and Bishkek). The predicted values of AOD and PM mass concentrations and their seasonal cycles are fairly well captured. The carbonaceous aerosols are underpredicted in winter, and analysis suggests that the winter heating emissions are underestimated in the current inventory. Dust, from sources within and outside CA, is a significant component of the PM mass and drives the seasonal cycles of PM and AOD. On an annual basis, the power and industrial sectors are found to be the most important contributors to the anthropogenic portion of PM2.5. Residential combustion and transportation are shown to be the most important sectors for BC. Biomass burning within and outside the region also contributes to elevated PM and BC concentrations. The analysis of the transport pathways and the variations in particulate matter mass and composition in CA demonstrates that this region is strategically located to characterize regional and intercontinental transport of pollutants. Aerosols at these sites are shown to reflect dust, biomass burning, and anthropogenic sources from Europe; South, East, and Central Asia; and Russia depending on the time period. Simulations for a reference 2030 emission scenario based on pollution abatement measures already committed to in current legislation show that PM2.5 and BC concentrations in the region increase, with BC growing more than PM2.5 on a relative basis. This suggests that both the health impacts and the climate warming associated with these particles may increase over the next decades unless additional control measures are taken. The importance of observations in CA to help characterize the changes that are rapidly taking place in the region are discussed. © 2015 Atmos. Chem. Phys.


Olry C.,ARIA Technologies | Moussafir J.,ARIA Technologies | Castanier P.,ARIA Technologies | Tinarelli G.,ARIANET | And 2 more authors.
HARMO 2010 - Proceedings of the 13th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes | Year: 2010

The MSS (Micro-SWIFT-SPRAY) model was originally developed for emergency response purposes, in order to provide a fast dispersion solution taking into account buildings in an Urban Environment, or else in an Industrial area with buildings. The model uses a simplified CFD solution (Micro-SWIFT) to represent the flow fields with metric resolution, and a Lagrangian Particle solution (Micro- SPRAY) to compute the 3D dispersion patterns among the obstacles. Photo-catalytic coating techniques (paint, cements) use the properties of TiO2 to produce a significant abatement of NOx in the vicinity of the surface where the coating is applied. An extended set of simulations was performed in cooperation between ARIA Technologies and ITALCEMENTI to examine the abatement performance in various urban situations, such as narrow streets or tunnels, when coating is applied on the ground or on facades or roofs, when traffic is moderate or strong. These simulations have been validated both with field experiments and real world situations (Roma, Berlin). The ensemble of the simulation results have been cast into a library of results which users at ITALCEMENTI can use through a Web interface. This software tool, called EXP'AIR, is presented.


D'Allura A.,ARIANET | Kulkarni S.,University of Iowa | Carmichael G.R.,University of Iowa | Finardi S.,ARIANET | And 8 more authors.
Atmospheric Environment | Year: 2011

In this study, the University of Iowa's Chemical Weather Forecasting System comprising meteorological predictions using the WRF model, and off-line chemical weather predictions using tracer and full chemistry versions of the STEM model, designed to support the flight planning during the ARCTAS 2008 mission is described and evaluated. The system includes tracers representing biomass burning and anthropogenic emissions from different geographical emissions source regions, as well as air mass age indicators. We demonstrate how this forecasting system was used in flight planning and in the interpretation of the experimental data obtained through the case study of the summer mission ARCTAS DC-8 flight executed on July 9 2008 that sampled near the North Pole. The comparison of predicted meteorological variables including temperature, pressure, wind speed and wind direction against the flight observations shows that the WRF model is able to correctly describe the synoptic circulation and cloud coverage in the Arctic region The absolute values of predicted CO match the measured CO closely suggesting that the STEM model is able to capture the variability in observations within the Arctic region. The time-altitude cross sections of source region tagged CO tracers along the flight track helped in identifying biomass burning (from North Asia) and anthropogenic (largely China) as major sources contributing to the observed CO along this flight. The difference between forecast and post analysis biomass burning emissions can lead to significant changes (~10-50%) in primary CO predictions reflecting the large uncertainty associated with biomass burning estimates and the need to reduce this uncertainty for effective flight planning. © 2011 Elsevier ltd.


Anfossi D.,CNR Institute of atmospheric Sciences and Climate | Tinarelli G.,ARIANET | Castelli S.T.,CNR Institute of atmospheric Sciences and Climate | Ferrero E.,University of Piemonte Orientale | And 3 more authors.
International Journal of Environment and Pollution | Year: 2010

Dispersion in low wind speed conditions is governed by meandering that disperses plumes over wide angular sectors, thus g.l.c. are lower than predicted by Gaussian models. It was proposed to model these dispersion situations in homogeneous conditions with two coupled Langevin equations, based on low wind speed turbulence analysis. Their parameters were derived from the autocorrelation functions of horizontal wind that exhibit an oscillations and large negative lobes. We propose a new equation system for: general case of inhomogeneous turbulence; total velocity; for the windy situations (based on the "Thomson simplest solution") and verify that these new solutions satisfy the "well-mixed condition". Copyright © 2010 Inderscience Enterprises Ltd.


Finardi S.,ARIANET | D'Allura A.,ARIANET | Silibello C.,ARIANET | Radice P.,ARIANET | And 4 more authors.
HARMO 2010 - Proceedings of the 13th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes | Year: 2010

This study describes and evaluates two modelling systems developed to provide air quality forecasts and nowcasts over Rome metropolitan area and its surrounding. The systems have been implemented by the regional environmental protection agency (ARPA Lazio) to satisfy the air quality Directive 2008/50/CE requirements. The meteorological model RAMS has been used to reconstruct 3D meteorological fields that drive the Eulerian chemical transport model FARM. Industrial and domestic emission fluxes are based on a local high resolution emission inventory while emissions from road traffic have been estimated by means of traffic modelling. The forecasting system is part of Chemical Weather Forecast Network, promoted by COST ES0602 Action, and provides 72 hours predictions published on ARPA Lazio web site, allowing to identify possible exceedancees of EU air quality standards. The nowcasting system includes a data assimilation module based on the Successive Correction Method (SCM) that considers O3, NO2, Benzene, CO and SO2 measurements. 34 monitoring stations (industrial, urban, suburban and rural) from the regional monitoring network have been used. Air quality analyses are available every 3 hours. A statistical analysis has been applied to evaluate the performance of the two systems and verify their ability to predict/reconstruct air pollution episodes. The evaluation has been based on standard air quality model evaluation indexes and graphics. Both systems show a good agreement with observed levels for the Rome metropolitan areas. The Near Real Time (NRT) system, that uses data-assimilation techniques, show a better performance when compared with experimental data suggesting indications on the more convenient way to get air quality assessment on the fly over Rome metropolitan area. Main weaknesses emerged for the rural area surrounding Rome conurbation claiming for an improvement of the emission inventory.


Morabito A.,U.S. Environmental Protection Agency | Giua R.,U.S. Environmental Protection Agency | Tanzarella A.,U.S. Environmental Protection Agency | Spagnolo S.,U.S. Environmental Protection Agency | And 8 more authors.
Proceedings of the 15th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes, HARMO 2013 | Year: 2013

Dispersion models based on emission inventories and meteorological fields are the primary tool of control agencies to support air quality assessment and source apportionment in complex industrial areas. In this work, a modelling system has been applied to estimate the annual contribution to the total concentrations of different pollutant sources in Taranto, one of the most industrialized areas in Italy, where typical urban emissions are superimposed on industrial ones located in proximity of the city boundary. Main industrial activities consist of an integrated steel plant (one of the largest in Europe) and an oil refinery, together with other smaller industrial facilities which use the Taranto harbour to unload primar y goods and to deliver final products. Modelling system includes the meteorological models SWIFT-SURFPRO and the Lagrangian particle dispersion model SPRAY. The air emissions inventory is partially established using local activity indicators and emission factors. The resolution level of the data is the municipality. In particular, in this study industrial sources (point sources and fugitive), traffic, domestic heating and harbour emissions have been taken into account. The meteorology in the studied area was reconstructed by the SWIFT model from the tridimensional meteorological products supplied, for the year 2007, by the national MINNI project. The annual simulation led to the identification of the main emitting sources and to the source-apportionment of primary pollutants at selected receptor sites, belonging to the air quality monitoring network. Industrial activities were found to be the principal contributor to SO2 emissions. Industry and traffic emissions were, for the most part, responsible for NOx simulated concentrations, while primary PM10 and PM2.5 simulated concentrations appeared to be linked to industrial emissions. Finally, in order to demonstrate the level of representativeness of the system used in this study, the model predictions were compared with measured air quality data.


Finardi S.,ARIANET | Silibello C.,ARIANET | D'Allura A.,ARIANET | Radice P.,ARIANET
Urban Climate | Year: 2014

The Po Valley is a major populated area including different conurbations, with a population density among the highest in Europe. The region is an air pollution hot spot, where the European air quality standards are exceeded for PM10, NO2 and O3. The pollutants exported from the Po Valley to the surrounding areas have been investigated through the application of a chemical transport model. Emission sensitivity simulations have been performed to identify the Po Valley footprint and to quantify its influence on the atmospheric composition. Simulation results suggest that the Po Valley emissions impact extends up to 500km, affecting Italy, the northern Mediterranean sea and the western Balkan peninsula. The outflow directions are determined by meteorological and topographic forcing. The surface area affected is larger during the winter, while the mass injected in the free troposphere is larger during the summer for pollutants with longer lifetime. Secondary PM components show an impact area wider than the other pollutants. NO2 footprint and its contribution to local concentration are relevant especially during wintertime. The Po Valley emissions contribute to the production of ozone at regional scale during the summer, although this contribution remains limited to few percentage points of local concentration levels. © 2014 Elsevier B.V.


Nanni A.,ARIANET | Velay-Lasry F.,ARIA Technologies | Eriksson E.,ARIA Technologies | Soudani A.,ANPE | Abid S.,I2E
HARMO 2010 - Proceedings of the 13th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes | Year: 2010

The calculation of road traffic emissions to air has been performed in Tunisia as part of the national emission inventory and for air pollution dispersion modeling purposes. The emissions have been estimated on the basis of a traffic assignment model, including daily traffic volumes and average speeds on the road network and the origin/destination (O/D) values at the sources and sinks of traffic. The road network studied includes virtually all the motorways and main rural roads in Tunisia as well as the major urban roads of Tunis and other main cities. The traffic model simulation has been based on traffic counts taken at a large number of road sections. The availability of such rich experimental data is a guarantee for the accuracy of the traffic model simulation in order to assure coherence among the different measurements, to attribute values to links without traffic counts, and to estimate the O/D matrix (i.e. The boundary conditions capable to extrapolate at best the measured traffic flows over the entire network). An emission model, based on COPERT methodology, has further been used to estimate atmospheric emissions from "line sources" (the links corresponding to the main roads of the network) and "area sources" (zones of aggregation of O/D nodes giving the contribution of diffuse traffic on the secondary roads). Emissions from area sources, have been estimated from the average trip length inside the area and the extension of the secondary road network. Since the COPERT methodology includes fuel consumption factors, the modeling results have been compared to real data. The methodology shows a good correspondence with the national Tunisian statistics on fuel consumption declared for road traffic, with modeling results only 14% higher than the national fuel consumptions declared for the year 2006. The small differences could be explained by the uncertainties in the distribution of traffic densities and vehicle fleet as well as on the hypothesis made on the vehicle speeds.


Bassan R.,ARPA Veneto | Bellio C.,ARPA Veneto | Piol R.,ARPA Veneto | D'Allura A.,ARIANET | And 2 more authors.
HARMO 2010 - Proceedings of the 13th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes | Year: 2010

An air quality forecasting system named SKYNET was designed for the Belluno Valley, a mountainous area located in the Dolomites mountain range. ARPAV Belluno Department performed a local emission inventory based on a bottom-up approach with particular detail on the estimation of domestic heating contribution, which was investigated through the use of more than 5000 questionnaires submitted to the population. The model has been tested in a winter period of 4 months by comparing the PM10 and NO2 forecasts for following 48 hours with the experimental data derived from two air quality stations located in Belluno and Feltre urban areas. The SKYNET performances have been evaluated with statistical indexes, and the results are overall good for both the stations. There is a particular agreement in the Belluno area, while the model reveals the tendency to under-predict the PM10 values in Feltre. The information generated by the model and a precise knowledge of the emission sources derived from the bottom-up inventory allowed to create an experimental air quality forecasting bulletin tested on a two month period, which gave reliable predictions both in Belluno (80%) and Feltre (71%).


Moussafir J.,ARIA Technologies | Olry C.,ARIA Technologies | Castanier P.,ARIA Technologies | Tinarelli G.,ARIANET | Perdriel S.,CAIRN Developpement
HARMO 2010 - Proceedings of the 13th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes | Year: 2010

The MSS (Micro-SWIFT-SPRAY) model was originally developed for emergency response purposes, in order to provide a fast dispersion solution taking into account buildings in an Urban Environment, or else in an Industrial area with buildings. The model uses a simplified CFD solution (Micro-SWIFT) to represent the flow fields with metric resolution, and a Lagrangian Particle solution (Micro-SPRAY) to compute the 3D dispersion patterns among the obstacles. The present paper introduces first the current status of development of MSS. Then the results of the long-term applications of this modelling system to several real world cases are presented, where the model is applied sequentially, on an hourly basis, on a sequence of one to three years of meteorological data. This is exactly how a standard Long Term Gaussian or Puff model would be used. A parallel version of this system (PMSS) has been jointly developed by ARIA Technologies and CEA and is now under test for this type of applications. We present the advantages and disadvantages of this solution, which is being packaged as "ARIA Impact 3D". We show how it can make use of fully 3D time-dependent meteorological model solutions, and how it compares with Gaussian and Puff modeling systems. The CPU cost, the use of parallel versions, and the realistic dispersion patterns obtained by the Lagrangian Particle approach are discussed.

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