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The characterization of vehicle exhaust emissions of volatile organic compounds (VOCs) is essential to estimate their impact on the formation of secondary organic aerosol (SOA) and, more generally, air quality. This paper revises and updates non-methane volatile organic compounds (NMVOCs) tailpipe emissions of three Euro 5 vehicles during Artemis cold urban (CU) and motorway (MW) cycles. Positive matrix factorization (PMF) analysis is carried out for the first time on proton transfer reaction time-of-flight mass spectrometer (PTR-ToF-MS) datasets of vehicular emission. Statistical analysis helped to associate the emitted VOCs to specific driving conditions, such as the start of the vehicles, the activation of the catalysts, or to specific engine combustion regimes. Merged PTR-ToF-MS and automated thermal desorption gas chromatography mass spectrometer (ATD-GC-MS) datasets provided an exhaustive description of the NMVOC emission factors (EFs) of the vehicles, thus helping to identify and quantify up to 147 individual compounds. In general, emissions during the CU cycle exceed those during the MW cycle. The gasoline direct injection (GDI) vehicle exhibits the highest EF during both CU and MW cycles (252 and 15 mg/km), followed by the port-fuel injection (PFI) vehicle (24 and 0.4 mg/km), and finally the diesel vehicle (15 and 3 mg/km). For all vehicles, emissions are dominated by unburnt fuel and incomplete combustion products. Diesel emissions are mostly represented by oxygenated compounds (65%) and aliphatic hydrocarbons (23%) up to C22, while GDI and PFI exhaust emissions are composed of monoaromatics (68%) and alkanes (15%). Intermediate volatility organic compounds (IVOCs) range from 2.7 to 13% of the emissions, comprising essentially linear alkanes for the diesel vehicle, while naphthalene accounts up to 42% of the IVOC fraction for the gasoline vehicles. This work demonstrates that PMF analysis of PTR-ToF-MS datasets and GC-MS analysis of vehicular emissions provide a revised and deep characterization of vehicular emissions to enrich current emission inventories.

Particles are emitted by different sources and are also formed in the atmosphere. Despite the large impact of atmospheric particles on health and climate, large uncertainties remain concerning their representation in models. To reduce these uncertainties as much as possible, a representation of the main processes involved in aerosol dynamics and chemistry is necessary. For that purpose, SSH-aerosol was developed to represent the evolution of the mass and number concentrations of primary and secondary particles, across different scales, using state-of-the-art modules, taking into account processes that are usually not considered in air-quality or climate modelling. For example, the particle mixing state and the growth of ultra-fine particles are taken into account in the aerosol dynamics, the affinity of semi-volatile organic compounds with water and viscosity are taken into account in the partitioning between the gas and particle phases of organics and the formation of extremely low-volatility organic compounds from biogenic precursors is represented. SSH-aerosol is modular and can be used with different levels of complexity. It may be used as standalone to analyse chamber measurements. It is also designed to be easily coupled to 3D models, adapting the level of complexity to the spatial scale studied.