Contrasting effects of urban trees on air quality: From the aerodynamic effects in streets to impacts of biogenic emissions in cities.

Urban trees are often not considered in air-quality models although they can significantly impact the concentrations of pollutants. Gas and particles can deposit on leaf surfaces, lowering their concentrations, but the tree crown aerodynamic effect is antagonist, limiting the dispersion of pollutants in streets. Furthermore, trees emit Biogenic Volatile Organic Compounds (BVOCs) that react with other compounds to form ozone and secondary organic aerosols. This study aims to quantify the impacts of these three tree effects (dry deposition, aerodynamic effect and BVOC emissions) on air quality from the regional to the street scale over Paris city. Each tree effect is added in the model chain CHIMERE/MUNICH/SSH-aerosol. The tree location and characteristics are determined using the Paris tree inventory, combined with allometric equations. The air-quality simulations are performed over June and July 2022. The results show that the aerodynamic tree effect increases the concentrations of gas and particles emitted in streets, such as NOx (+4.6 % on average in streets with trees and up to +37 % for NO2). This effect increases with the tree Leaf Area Index and it is more important in streets with high traffic, suggesting to limit the planting of trees with large crowns on high-traffic streets. The effect of dry deposition of gas and particles on leaves is very limited, reducing the concentrations of O3 concentrations by -0.6 % on average and at most -2.5 %. Tree biogenic emissions largely increase the isoprene and monoterpene concentrations, bringing the simulated concentrations closer to observations. Over the two-week sensitivity analysis, biogenic emissions induce an increase of O3, organic particles and PM2.5 street concentrations by respectively +1.1, +2.4 and + 0.5 % on average over all streets. This concentration increase may reach locally +3.5, +12.3 and + 2.9 % respectively for O3, organic particles and PM2.5, suggesting to prefer the plantation of low-emitting VOC species in cities.

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.

Sensitivity study to select the wet deposition scheme in an operational atmospheric transport model.

The ability of operational atmospheric transport models to simulate the soil contamination caused by deposition processes is important in the response to a nuclear crisis. The Fukushima accident was characterized by wet deposition of Cs-137, which is difficult to simulate accurately based on observations. A sensitivity study investigated seven wet deposition schemes integrated into operational atmospheric transport models. Deposition maps produced from the multiple simulations are compared with each other and with the observed deposition. Similarities and discrepancies in average behavior are presented for a number of modeling cases on the basis of criteria representing soil contamination crisis management needs. This study confirms the importance of the wet deposition scheme in a crisis management context. None of the schemes used in the study are the best option to satisfy all the comparison criteria. This study suggests that crisis managers must not exclusively trust a single model for selecting responses. At the current time, it is preferable to use several wet deposition schemes in the modelling tools for emergency responses.

Identification of sensitive parameters in the modeling of SVOC reemission processes from soil to atmosphere.

Semi-volatile organic compounds (SVOCs) are subject to Long-Range Atmospheric Transport because of transport-deposition-reemission successive processes. Several experimental data available in the literature suggest that soil is a non-negligible contributor of SVOCs to atmosphere. Then coupling soil and atmosphere in integrated coupled models and simulating reemission processes can be essential for estimating atmospheric concentration of several pollutants. However, the sources of uncertainty and variability are multiple (soil properties, meteorological conditions, chemical-specific parameters) and can significantly influence the determination of reemissions. In order to identify the key parameters in reemission modeling and their effect on global modeling uncertainty, we conducted a sensitivity analysis targeted on the 'reemission' output variable. Different parameters were tested, including soil properties, partition coefficients and meteorological conditions. We performed EFAST sensitivity analysis for four chemicals (benzo-a-pyrene, hexachlorobenzene, PCB-28 and lindane) and different spatial scenari (regional and continental scales). Partition coefficients between air, solid and water phases are influent, depending on the precision of data and global behavior of the chemical. Reemissions showed a lower variability to soil parameters (soil organic matter and water contents at field capacity and wilting point). A mapping of these parameters at a regional scale is sufficient to correctly estimate reemissions when compared to other sources of uncertainty.