One of the sustainable mobility policies aimed to reduce road traffic emissions in urban areas is the implementation of zero-emission zones (ZEZ) which are areas where only electric vehicles, pedestrians, and cyclists are allowed. The assessment of possible benefit of ZEZ on emissions, air quality and human health can be performed with a dedicated modelling chain. The goal of this work is to simulate a 2030 ZEZ mobility scenario in Milan city centre (Italy), introducing changes to the vehicle fleet composition within the ZEZ, as suggested by the Air Quality and Climate Plan of the municipality. Then we evaluated the benefits in terms of both air quality and citizens' health. The assessment of the environmental and health effects is done thanks to a modelling suite composed of a road traffic, an emission, a hybrid air quality models, plus a fourth module for human health impacts. In this specific case study, the modelling chain is applied to the metropolitan city of Milan for the reference year 2017 first, and then for two hypothetical mobility scenarios referred to 2030: the temporal evolution of baseline simulation as planned by the NEC (National Emission reduction Commitments) directive and by local emission containment measures (BAS30) and the BAS30 scenario with the implementation of the mobility policy (ZEZ30). The impact of the policy can be inferred by comparing the two scenarios. Road traffic emission in 2030 are expected to strongly decrease from the 2017 levels (-84% for NOx and-28% for PM2.5). The road traffic emission reduction introduced by the ZEZ30 scenario compared to the BAS30 scenario is high in the model cells contained within the ZEZ area (complete removal of NOx emissions and up to-45% PM2.5), but given the limited area of the ZEZ the citywide reduction of emissions is 2.24% for NOx and 0.91% for PM2.5. NO2 concentrations are expected to decrease of circa 54% inside the city of Milan under the BAS30 scenario compared with 2017 (35% for PM2.5). Again, the reduction introduced by the ZEZ are low and are mostly included within the ZEZ area (maximum 2% and 0.6 % for NO2 and PM2.5 respectively). Considering the ZEZ30 scenario, morbidity and mortality indicators are expected to decrease of 50% circa compared with 2017. In conclusion, the introduction of the ZEZ in 2030 is expected to have a marginal effect compared to the BAS30 scenario due to the limited spatial extent of the simulated ZEZ, the limited effect of electric vehicles on non-exhaust emissions, and the already strong emission reductions achieved using the projected 2030 vehicle fleet.

A 4-module modelling chain for assessing urban traffic emissions' impacts on air quality and human health is presented. The first module simulates the traffic flows for the urban road network, separately considering private and public transport; the second performs a bottom-up assessment of road traffic emissions, including non-exhaust components and dust resuspension; the third uses a Eulerian Chemistry and Transport Model for regional and urban scale air quality simulation, combining traffic emissions with all the other anthropogenic and natural emissions. Lastly, the fourth module assesses the effects of air quality on human health based on the latest WHO-recommended Concentration Response Functions for mortality. As test case, the modelling chain was applied to the city of Milan (Italy). The added value of the modelling chain is evaluated by comparing the simulation results for NO2 and particulate matter ambient concentrations with those obtained with the classic top-down approach and with observed data. Simulation results show improvements in the accuracy of model predictions over the urban area and highlight the importance of properly accounting for dust resuspension in traffic policy evaluations because of its increasing contribution to PM10 traffic emissions in the future.

Road dust suspension is an increasing concern in terms of being a source of atmospheric particulate matter (PM) in cities, due to its toxicity and the lack of knowledge on emission estimates, impact and mostly with respect to measures to control or mitigate it. Both technological and policy measures have been proposed, but their application is limited by the gap of knowledge on their effectiveness in the real world. This study analyses the real-world emission factors of road dust at ten sites in the city of Milan (Italy), with an emphasis on the impact of different fleet speeds at one particular road. PM10 emission factors were estimated by means of both the EPA method (based on silt loadings) and the vertical profile of dust deposition. Road dust silt loadings varied within 0.006–0.066 g m−2, with the highest loadings found at sites affected by construction works. Typical urban roads were found to have fleet-averaged emission factors within 13–32 mg vehicle−1 km−1, which is in the central range of the literature values in Europe. The emission factors estimated by means of the vertical profile approach were within 19–26 mg VKT−1, which agree quite well with the EPA method if corrected for speed. In fact, a power-law relation was found between fleet speed and emission factor estimates, with an exponent close to 1.5 for speeds within 36–57 km h−1. These results suggest that the limitation of the maximum traffic speed can be effective for mitigating road dust emissions in cities.

Recent observation and modeling-based studies have shown how air quality has been positively affected by the containment measures enforced due to the COVID-19 outbreak. This work aims to analyze Lombardy’s NO2 atmospheric concentration during the spring lockdown. The region of Lombardy is known for having the largest number of residents in Italy and high levels of pollution. It is also the region where the first European confinement measures were imposed by the Italian government. The modeling suite composed of CAMx (Comprehensive Air Quality Model with Extensions) and WRF (Weather Research and Forecasting model) provides the setting to compare the atmospheric NO2 concentration from mid-February to the end of March with a business as usual situation. The main interest in this work is to investigate the response of NO2 atmospheric concentration to increasingly reduced road traffic. We can simulate, for the first time, a real circumstance of progressively reduced mobility, as well as validating it with measured air quality data. Focusing on the city of Milan, we found that the decrease in NO2 concentration reflects progressively reduced traffic contraction. In the case of a large traffic abatement (71%), the concentration level is reduced by one third. We also find that industrial activities have a relevant impact on NO2 atmospheric concentration, especially in the provinces of Brescia and Bergamo. This study provides an overview of how incisive policies must be implemented to achieve the set environmental targets and protect human health.

A hybrid modelling system (HMS) was developed to provide hourly concentrations at the urban local scale. The system is based on the combination of a meteorological model (WRF), a chemical and transport eulerian model (CAMx), which computes concentration levels over the regional domains, and a lagrangian dispersion model (AUSTAL2000), accounting for dispersion phenomena within the urban area due to local emission sources; a source apportionment algorithm is also included in the HMS in order to avoid the double counting of local emissions.The HMS was applied over a set of nested domains, the innermost covering a 1.6 x 1.6 km(2) area in Milan city center with, 20 m grid resolution, for NOx simulation in 2010. For this paper the innermost domain was defined as "local", excluding usual definition of urban areas. WRF model captured the overall evolution of the main meteorological features, except for some very stagnant situations, thus influencing the subsequent performance of regional scale model CAMx. Indeed, CAMx was able to reproduce the spatial and temporal evolution of NOx concentration over the regional domain, except a few episodes, when observed concentrations were higher than 100 ppb. The local scale model AUSTAL2000 provided high-resolution concentration fields that sensibly mirrored the road and traffic pattern in the urban domain. Therefore, the first important outcome of the work is that the application of the hybrid modelling system allowed a thorough and consistent description of urban air quality. This result represents a relevant starting point for future evaluation of pollution exposure within an urban context.However, the overall performance of the HMS did not provide remarkable improvements with respect to stand-alone CAMx at the two only monitoring sites in Milan city center. HMS results were characterized by a smaller average bias, that improved about 6-8 ppb corresponding to 12-13% of the observed concentration, but by a lower correlation, that worsened around 1-3% (e.g. from 0.84 to 0.81 at Senato site), due to the concentration peaks produced by AUSTAL2000 during nighttime stable conditions. Additionally, the HMS results showed that it was unable to correctly take into account some local scale features (e.g. urban canyon effects), pointing out that the emission spatialization and time modulation criteria, especially those from road traffic, need further improvement.Nevertheless, a second important outcome of the work is that some of the most relevant discrepancies between modelled and observed concentrations were not related to the horizontal resolution of the dispersion models but to larger scale meteorological features not captured by the meteorological model, especially during winter period. Finally, the estimated contribution of the local emission sources accounted on the annual average for about 25-30% of the computed concentration levels in the innermost urban domain. This confirmed that the whole Milan urban area as well as the outside background areas, accounting all sources outside the innermost domain, play a key role on air quality. The result suggests that strictly local emission policies could have a limited and indecisive effect on urban air quality, although this finding could be partially biased by model underestimation of the observed concentration. (C) 2016 Elsevier Ltd. All rights reserved.

Background. As part of the Strategic Environmental Assessment (SEA) procedure of the General Urban Traffic Plan, the Municipality of Milan introduced Elemental Carbon - basing on the experience with the air quality measurement of Black Carbon within the city - among quantitative indicators. Aims. To obtain a particulate toxicity indicator, easy-to-use within the normal planning activities of a local Public Authority, estimating environmental and health potential effects of different policy scenarios. Methods. Being the carbonaceous nanoparticles such as Black Carbon (BC), a sensitive indicator of the spatial variation of road traffic emissions ('traffic proximity' indicator), the emissions of Elemental Carbon (EC), pollutant closely related to BC, have been adopted as tracers of the population exposure. According to the literature, a critical distance from the vehicular traffic source has been identified to which refer evaluations of some health effects that have 'sufficient evidence' (in. asthma). People living at a distance <75 m from major roads have an increased probability by about 30% of receiving a diagnosis of asthma and by about 40%-50% to be on medication for asthma or have had recent acute episodes in children (McConnell et al, 2006; Perez, 2012; Brugge et al, 2007). Thus an exposure indicator has been defined as the daily mean vehicular EC emissions released at a distance less than 75 meters from places of residence. This indicator has been estimated for several mobility planning scenarios. Results. This approach has proven to allow easy scenario comparison analysis. In the city of Milan, road pricing scenario at 2015 leads to an increase of total population exposed to lower emission levels (<10 grams/day) and to a decrease of total population exposed to highest emission levels (>50 grams/day). Conclusions. BC/EC, excellent tracer of 'traffic proximity' exposure, offers the possibility to verify the effectiveness of different policies in mobility planning.

In order to improve air quality in the Controlled Traffic Zone “Area C” of Milan, in addition to the rules already in force, two topics now under consideration by the municipality are the increase of car-sharing and measures to stimulate the use of electric vehicles, including their adoption for the last-mile delivery of goods. The paper presents the evaluation of the potential benefits of electric vehicles, in particular for the case of goods delivery. Comparisons to present i.c.e. based vehicles are presented in terms of economical aspects (from the point of view of the end user and of the Country), energy consumption and pollution impact (both local and global). Also the contribution to costs and pollution of two-wheels motor vehicles is taken into consideration in order to give a more complete overview of the different traffic segments.

The CAMx chemical and transport Eulerian model has been applied over a domain focused on the Milan area (Northern Italy) for the whole 2004, on the basis of CityDelta III project input data set. Model results have been analysed by mean of the Source Apportionment technique at the Milan receptor. A quantitative analysis of the main processes governing the Secondary Inorganic Aerosols (SIAs) production showed that the overall efficiency of the transformation processes is influenced by several factors, which prevents defining simple relationships between emissions and secondary aerosol compounds.

On the basis of CityDelta III project input dataset, the CAMx chemical and transport Eulerian model has been applied over a 300x300 km 2 domain focused on the Milan area (Northern part of Italy) for the whole 2004. Model results have been analysed by mean of the Source Apportionment technique at the Milan receptor, in order to discriminate the contribution of several key emission sectors, also distinguishing the most emitting area of Milan from the surroundings. Obtained results highlight that road transport is the most relevant sector, followed by agriculture and domestic heating. The source apportionment analysis also revealed that more than 70% of the PM10 is due to emissions outside of Milan.

This work describes the results of the CAMx modelling system application aimed at reconstructing the particulate matter concentration over the Northern Italy basin and analysing the role played by the main emission sources on the pollution levels. Simulations have been performed on yearly basis in the frame of two different modelling exercises. The present analysis has been performed taking into account an overlapping period, covering February 2004. As a first step, CAMx results have been compared to a considerable data set of observed concentrations of NO2 and PM10. Model has been able to correctly reproduce the daily evolution and spatial variability of NO2, while some underestimations of PM10 concentrations have been highlighted. Then the Particulate Source Apportionment tool (PSAT) has been applied, in order to discriminate the contribution of several key emission sectors such as transport, domestic heating and power plants, in relation to three emission areas. Road transport appear's to be the most responsible sector of PM10 concentration, especially in the area between Milan and Turin. The urban area of Milan is characterised by high PM10 concentration with an important contribution by road transport and domestic heating. The analysis has also pointed out the increasing relevance of the emissions coming from areas outside the city during critical pollution episodes, when severe stagnant conditions emphasise the role of secondary particulate matter. Finally, the comparison between the two PSAT applications has put in evidence, as a whole, quite coherent distributions of the relative contribution to PM10 concentration, thus proving the robustness of the source apportionment results. The main differences concerned domestic heating contribution, clearly related to the discrepancies in the emission inventories.

Within the framework of CityDelta open model inter-comparison exercise, two different atmospheric chemical transport models, comprehensive air quality model with extension and transport chemical aerosol model, have been applied over a domain centred on Milan (North of Italy) as a result of a cooperation of five Italian groups. The two models have shared the same input fields for yearly PM10 simulations. The paper illustrates the analysis of the particulate matter-simulated concentrations and the comparison with the available experimental data.

The modelling reconstruction of the processes determining the transport and mixing of ozone and its precursors in complex terrain areas is a challenging task, particularly when local-scale circulations, such as sea breeze, take place. Within this frame, the ESCOMPTE European campaign took place in the vicinity of Marseille (south-east of France) in summer 2001. The main objectives of the field campaign were to document several photochemical episodes, as well as to constitute a detailed database for chemistry transport models intercomparison.CAMx model has been applied on the largest intense observation periods (IOP) (June 21-26, 2001) in order to evaluate the impacts of two state-of-the-art meteorological models, RAMS and MM5, on chemical model outputs. The meteorological models have been used as best as possible in analysis mode, thus allowing to identify the spread arising in pollutant concentrations as an indication of the intrinsic uncertainty associated to the meteorological input.Simulations have been deeply investigated and compared with a considerable subset of observations both at ground level and along vertical profiles. The analysis has shown that both models were able to reproduce the main circulation features of the IOP. The strongest discrepancies are confined to the Planetary Boundary Layer, consisting of a clear tendency to underestimate or overestimate wind speed over the whole domain.The photochemical simulations showed that variability in circulation intensity was crucial mainly for the representation of the ozone peaks and of the shape of ozone plumes at the ground that have been affected in the same way over the whole domain and all along the simulated period. As a consequence, such differences can be thought of as a possible indicator for the uncertainty related to the definition of meteorological fields in a complex terrain area. (C) 2007 Elsevier Ltd. All rights reserved.

This paper gives an overview of the set up, methodology and the obtained results of the CityDelta (phase 1 and 2) project. In the context of the Clean Air For Europe programme of the European Commission, the CityDelta project was designed to evaluate the impact of emission-reduction strategies on air quality at the European continental scale and in European cities. Ozone and particulate matter (PM) are the main components that have been studied. To achieve this goal, a model intercomparison study was organized with the participation of more than 20 modelling groups with a large number of modelling configurations. Two following main topics can be identified in the project. First, in order to evaluate their strengths and weaknesses, the participating models were evaluated against observations in a control year (1999). An accompanying paper will discuss in detail this evaluation aspect for four European cities. The second topic is the actual evaluation of the impact of emission reductions on levels of ozone and PM, with particular attention to the differences between large-scale and fine-scale models. An accompanying paper will discuss this point in detail. In this overview paper the main input to the intercomparison is described as well as the use of the ensemble approach. Finally, attention is given to the policy relevant issue on how to implement the urban air quality signal into large-scale air quality models through the use of functional relationships.

INTRODUCTION Air quality assessment and policies analysis show an increasing interest in long term simulations with Chemical Transport Models (CTMs). In this frame the CityDelta open model inter-comparison exercise (http://rea.ei.jrc.it/netshare/thunis/citydelta/) has been organized by the Joint Research Centre (JRC-IES) of Ispra, in collaboration with EMEP, IIASA and EUROTRAC, as a contribution to the modelling activities in the CAFE (Clean Air For Europe) Project (6 Framework Programme). The aim of CityDelta exercise was to compare the results of different photochemical dispersion models in order to estimate air quality response to local and global emissions variations. The exercise was carried out by twenty scientific groups working on eight European domains. Starting in 2002, the second phase of CityDelta (2003-2004) was focused on estimations of PM10 and PM2.5 concentrations fields, with a special attention devoted to the partitioning of their main inorganic components (nitrates, sulphates and ammonium) and to the response to emission reduction scenarios.

This work is dedicated to the evaluation of the influence of input data on the ability of chemical transport models to reconstruct a given pollution episode. Such a question remains critical in the frame of air pollution forecasting and management. The study relies on the large European ESCOMPTE campaign that took place in the Marseilles area (South-East of France) in summer 2001, and that was dedicated to the constitution of a detailed 3D chemical and meteorological database for a CTM intercomparison exercise. The huge amount of measurement data indeed allowed us to investigate the behaviour of CTMs in a complex environment. In fact, the domain is characterised by the presence of large urban and industrial poles along the coastline served by a dense road network. Submitted to land-sea breeze phenomena, it shows an increasing orographic altimetry which constrains the transport of polluted plumes inland. Simulations, carried out with CAMx and CHIMERE, were focused on two intense ozone episodes: 21-23 June 2001 (moderate synoptic wind) and 24-26 June 2001 (local sea-land breeze circulation).The specificity of this work is to compare the models outputs both in their original configurations and gradually changing the input configuration (meteorological data, boundary conditions) in order to quantify the related effect on the results. The model results were compared with the very rich set of dynamical parameters and chemical data of the campaign, obtained from ground stations, Lidar, aircrafts, boats, balloons, radiosoundings. Statistical indices and performance indicators were also set up and showed that the models could correctly reproduce photochemical smog phenomena over the Marseille area.

Italy often suffers for high concentrations of secondary pollutants: ozone during summer and particulate matter in winter. Modelling reconstruction is a really challenging task, due to the presence of complex orographic systems and the interaction with the Mediterranean Sea. As case study, the year 1999 was simulated and evaluated by measuring data.