Description and validation of Vehicular Emissions from Road Traffic (VERT) 1.0, an R-based framework for estimating road transport emissions from traffic flows

VERT (Vehicular Emissions from Road Traffic) is an R package developed to estimate traffic emissions of a wide range of pollutants and greenhouse gases based on traffic estimates and vehicle fleet composition data, following the EMEP/EEA methodology. Compared to other tools available in the literature, VERT is characterised by its ease of use and rapid configuration, while it maintains great flexibility in user input. It is capable of estimating exhaust, non-exhaust, resuspension, and evaporative emissions and is designed to accommodate future updates of available emission factors. In this paper, case studies conducted at both urban and regional scales demonstrate VERT's ability to accurately assess transport emissions. In an urban setting, VERT is integrated with the Lagrangian dispersion model GRAMM–GRAL and provides NOx concentrations in line with observed trends at monitoring stations, especially near traffic hotspots. On a regional scale, VERT simulations provide emission estimates that are highly consistent with the reference inventories for the Emilia-Romagna region (Italy). These findings make VERT a valuable tool for air quality management and traffic emission scenario assessment

Measurement report: Source attribution and estimation of black carbon levels in an urban hotspot of the central Po Valley – an integrated approach combining high-resolution dispersion modelling and micro-aethalometers

Understanding black carbon (BC) levels and its sources in urban environments is of paramount importance due to the far-reaching health, climate, and air quality implications. While several recent studies have assessed BC concentrations at specific fixed urban locations, there is a notable lack of knowledge in the existing literature on spatially resolved data alongside source estimation methods. This study aims to fill this gap by conducting a comprehensive investigation of BC levels and sources in Modena (Po Valley, Italy), which serves as a representative example of a medium-sized urban area in Europe. Using a combination of multi-wavelength micro-aethalometer measurements and a hybrid Eulerian-Lagrangian modelling system, we studied two consecutive winter seasons (February-March 2020 and December 2020-January 2021). Leveraging the multi-wavelength absorption analyser (MWAA) model, we differentiate sources (fossil fuel combustion, FF, and biomass burning, BB) and components (BC vs. brown carbon, BrC) from micro-aethalometer measurements. The analysis reveals consistent, minimal diurnal variability in BrC absorption, in contrast to FF-related sources that exhibit distinctive diurnal peaks during rush hours, while BB sources show less diurnal variation. The city itself contributes significantly to BC concentrations (52 +/- 16 %), with BB and FF playing a prominent role (35 +/- 15 % and 9 +/- 4 %, respectively). Long-distance transport also influences BC concentrations, especially in the case of BB and FF emissions, with 28 +/- 1 % and 15 +/- 2 %, respectively. When analysing the traffic-related concentrations, Euro 4 diesel passenger cars considerably contribute to the exhaust emissions. These results provide valuable insights for policy makers and urban planners to manage BC levels in medium-sized urban areas, taking into account local and long-distance sources

Measurement report: Source attribution and estimation of black carbon levels in an urban hotspot of the central Po Valley: An integrated approach combining high-resolution dispersion modelling and micro-aethalometers

Understanding black carbon (BC) levels and their sources in urban environments is of paramount importance due to their far-reaching health, climate and air quality implications. While several recent studies have assessed BC concentrations at specific fixed urban locations, there is a notable lack of knowledge in the existing literature on spatially resolved data alongside source estimation methods. This study aims to fill this gap by conducting a comprehensive investigation of BC levels and sources in Modena (Po Valley, Italy), which serves as a representative example of a medium-sized urban area in Europe. Using a combination of multi-wavelength micro-aethalometer measurements and a hybrid Eulerian-Lagrangian modelling system, we studied two consecutive winter seasons (February–March 2020 and December 2020–January 2021). Leveraging the multi-wavelength absorption analyser (MWAA) model, we differentiate sources (fossil fuel combustion, FF, and biomass burning, BB) and components (BC vs. brown carbon, BrC) from micro-aethalometer measurements. The analysis reveals consistent, minimal diurnal variability in BrC absorption, in contrast to FF-related sources, which exhibit distinctive diurnal peaks during rush hours, while BB sources show less diurnal variation. The city itself contributes significantly to BC concentrations (52 % ± 10 %), with BB and FF playing a prominent role (35 % ± 15 % and 9 % ± 4 %, respectively). Long-distance transport also influences BC concentrations, especially in the case of BB and FF emissions, with 28 % ± 1 % and 15 % ± 2 %, respectively. When analysing the traffic related concentrations, Euro 4 diesel passenger cars considerably contribute to the exhaust emissions. These results provide valuable insights for policy makers and urban planners to manage BC levels in medium-sized urban areas, taking into account local and long-distance sources

IMPATTO DELLA DIFFUSIONE DI VEICOLI ELETTRICI E A IDROGENO SULLE CONCENTRAZIONI DI PM10 IN EMILIA-ROMAGNA

PM10 is a critical pollutant for the air quality in Emilia Romagna, a Northern Italy region that includes a large part of the Po Valley. The atmospheric levels of PM10 are strongly affected by vehicular traffic emissions, due to fuel exhaust and also to tires, brake and road surface wear, and to road dust resuspension (non-exhaust emissions). This study presents atmospheric PM10 scenarios deriving from vehicular traffic emissions in Emilia Romagna as resulting in 2030 from the growth of the Fuel Cell Electric Vehicle (FCEV) and battery electric vehicles (BEV) fleet in the region. Both exhaust and non-exhaust vehicular emissions are considered, evaluated according to the most up-to-date regional bottom-up emission inventory, which attributes about 60% of total primary PM10 traffic emissions to wear processes. PM10 concentration maps for actual (2019) and 2030 scenarios are obtained by a Lagrangian dispersion model (PMSS). Preliminary results highlight the future impact on atmospheric PM10 from tires, brake and road surface wear produced by battery electric vehicles, due to their larger mass compared to FCEVs, which have smaller batteries and mass. These emissions will partially offset the lack of PM10 exhaust emissions for electric vehicles. Finally, the daily primary PM10 levels by traffic emissions simulated by PMSS and CHIMERE models were compared at specific sites relevant for the studied domain, i.e. the regulatory air quality monitoring stations, only for actual (2019) scenario

µ-MO assessing the contribution of NOXtraffic emission to atmospheric pollution in modena by microscale dispersion modelling

Based on the air pollutant emission inventory data (INEMAR – Arpa Emilia-Romagna 2010) road traffic in Modena, a city in the central Po valley (Northern Italy), contributes up to the 60% of the total emission in terms of NOx, followed by Domestic Heating (15%) and Industrial Combustion (14%). Goal of the -MO project is to assess the road traffic impact on air quality in the urban area of Modena by a combined experimental and modelling approach. Dispersion of vehicular NOxwas simulated by Parallel Micro Swift Spray (PMSS, Arianet srl, Italy and Aria Technologies, France) over a domain of 6 km x 6 km, including most of the urban areas of Modena, with a horizontal resolution of 4 m. The atmospheric emission sources were estimated by merging local fleet composition data, traffic flux at rush hours simulated by PTV VISUM mobility software and direct measurements collected by radar traffic counters, provided by the Municipality of Modena. The modelling system, implemented on a 16 cores cluster (64 GB of total memory), includes PSWIFT, a parallelized mass-consistent diagnostic wind field model, and PSPRAY, a three-dimensional parallel lagrangian particle dispersion model, both able to take into account obstacles (buildings). A run of the system on an entire day has been performed and is presented. In the next step of the work, NOxatmospheric concentration measurements will be provided by the two urban air quality monitoring sites and by a set of 10 monitoring boxes distributed over the domain and featured by small sensors for NO, NO2and particulates. Among the final goals of the -MO project there is the tentative source-apportionment of urban atmospheric NOxbetween traffic emissions, domestic heating and regional background, to support epidemiological studies and finally future urban development strategies