Sensitivity of pollutant concentrations in urban streets to asphalt and traffic-related emissions.

The higher concentrations of atmospheric particles, such as black carbon (BC) and organic matter (OM), detected in streets compared to the urban background are predominantly attributed to road traffic. The integration of this source of pollutant in air quality models nevertheless entails a high degree of uncertainty and some other sources may be missing. Through sensitivity scenarios, the impacts on pollutant concentrations of sensitivities related to traffic and road-asphalt emissions are evaluated. The 3D Eulerian model Polair3D and the street network model MUNICH are applied to simulate various scenarios and their impacts at the regional and local scales. They are coupled with the modular box model SSH-aerosol to represent formation and aging of primary and secondary gas and particles. Traffic emissions are calculated with the COPERT methodology. Using recent volatile organic compound speciations for light vehicles with more detailed information pertaining to intermediate, semi- and low-volatile organic compounds (I/S/LVOCs) leads to limited reductions of OM concentrations (10% in streets). Changing the method of estimating I/S/LVOC emissions leads to an average reduction of 60% at emission and a decrease of the OM concentrations of 27% at the local scale. An increase in 219% of BC emissions from tire wear, consistent with the uncertainties found in the literature, doubles the BC concentrations at the local scale, which remain underestimated compared to observations. I/S/LVOC emissions are several orders of magnitude higher when considering emissions from road asphalt due to pavement heating and exposure to sunlight. However, simulated concentrations of PM at the local scale remain within acceptable ranges compared to observations. These results suggest that more information is needed on I/S/LVOCs and non-exhaust sources (tire, brake and road abrasion) that impact the particle concentration. Furthermore, currently unconsidered emission sources such as road asphalt may have non-negligible impacts on pollutant concentrations in streets.

Detailed Speciation of Non-Methane Volatile Organic Compounds in Exhaust Emissions from Diesel and Gasoline Euro 5 Vehicles Using Online and Offline Measurements.

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.