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.

Response of biogenic secondary organic aerosol formation to anthropogenic NOx emission mitigation.

This study investigates the effects of anthropogenic nitrogen oxide (NOx) mitigation reduction on secondary organic aerosol (SOA) formation from monoterpene and sesquiterpene precursors across Europe, using the three-dimensional (3-D) Chemical Transport Model (CTM) CHIMERE. Two SOA mechanisms of varying complexity are employed: the GENOA-generated Biogenic Mechanism (GBM) and the Hydrophobic/Hydrophilic Organic mechanism (H2O). GBM is a condensed SOA mechanism generated by automatic reduction from near-explicit chemical mechanisms (i.e., the Master Chemical Mechanism - MCM and the peroxy radical autoxidation mechanism - PRAM) using the GENerator of Reduced Organic Aerosol Mechanisms version 2.0 (GENOA v2.0). Conversely, the H2O mechanism is developed primarily based on experimental data, with simplified chemical pathways and SOA formation yields reflecting those from chamber experiments. In the 3-D simulations conducted for the summer of 2018 over Europe, the implementation of GBM significantly improved the model's performance in comparison to simulations using the H2O mechanism, yielding results more consistent with measured aerosol concentrations extracted from the EBAS database. In response to NOx emission mitigation, simulated SOA concentrations increase with GBM but decrease when using the H2O mechanism, unless a highly oxygenated molecules (HOMs) formation scheme is incorporated. The SOA composition becomes more oxidized and concentrations elevate after NOx reduction, particularly in simulations using GBM. These higher concentrations are likely due to enhanced reaction rates of organic peroxy radicals (RO2) with HO2, resulting in more oxidized products from monoterpene degradation that favors HOM formation. The results suggest that detailed SOA mechanisms including autoxidation are necessary for accurate predictions of SOA concentrations in 3-D modeling.

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.

Impact of trees on gas concentrations and condensables in a 2-D street canyon using CFD coupled to chemistry modeling.

Trees grown in streets impact air quality by influencing ventilation (aerodynamic effects), pollutant deposition (dry deposition on vegetation surfaces), and atmospheric chemistry (emissions of biogenic volatile organic compounds, BVOCs). To qualitatively evaluate the impact of trees on pollutant concentrations and assist decision-making for the greening of cities, 2-D simulations on a street in greater Paris were performed using a computational fluid dynamics tool coupled to a gaseous chemistry module. Globally, the presence of trees has a negative effect on the traffic-emitted pollutant concentrations, such as NO2 and organic condensables, particularly on the leeward side of a street. When not under low wind conditions, the impact of BVOC emissions on the formation of most condensables within the street was low owing to the short characteristic time of dispersion compared with the atmospheric chemistry. However, autoxidation of BVOC quickly forms some extremely-low volatile organic compounds, potentially leading to the formation of ultra-fine particles. Planting trees in streets with traffic is only effective in mitigating the concentration of some oxidants such as ozone (O3), which has low levels in cities regardless of this, and hydroxyl radical (OH), which may slightly lower the rate of oxidation reactions and the formation of secondary species in the street.

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.

Simulation of primary and secondary particles in the streets of Paris using MUNICH.

High particle concentrations are observed in the streets. Regional-scale chemistry-transport models are not able to reproduce these high concentrations, because their spatial resolution is not fine enough. Local-scale models are usually employed to simulate the high concentrations in street networks, but they often adopt substantial simplifications to determine background concentrations and use simplified chemistry. This study presents the new version of the local-scale Model of Urban Network of Intersecting Canyons and Highways (MUNICH) that integrates background concentrations simulated by the regional-scale chemistry-transport model Polair3D, and uses the same complex chemistry module as Polair3D, SSH-aerosol, to represent secondary aerosol formation. Gas and aerosol concentrations in Paris streets are simulated with MUNICH, considering a street-network with more than 3800 street segments, between 3 May and 30 June. Comparisons with PM10 and PM2.5 measurements at several locations of Paris show that the high PM10 and PM2.5 concentrations are well represented. Furthermore, the simulated chemical composition of fine particles corresponds well to a yearly measured composition. To understand the influence of the secondary pollutant formation, several sensitivity simulations are conducted. Simulations with and without gas-phase chemistry show that the influence of gas-phase chemistry on the formation of NO2 is large (37% on average over May and across all modelled streets), but the influence on condensables is lower (less than 2% to 3% on average at noon for inorganics and organics), but may reach more than 20% depending on the street. The assumption used to compute gas/particle mass transfer by condensation/evaporation is important for inorganic and organic compounds of particles, as using the thermodynamic equilibrium assumption leads to an overestimation of the organic concentrations by 4.7% on average (up to 31% at noon depending on the streets). Ammonia emissions from traffic lead to an increase in inorganic concentrations by 3% on average, reaching 26% depending on the street segments. Not taking into account gas-phase chemistry and aerosol dynamics in the modelling leads to an underestimation of organic concentrations by about 11% on average over the streets and time, but this underestimation may reach 51% depending on the streets and the time of the day.

Simulation of particle diversity and mixing state over Greater Paris: a model-measurement inter-comparison.

Air quality models are used to simulate and forecast pollutant concentrations, from continental scales to regional and urban scales. These models usually assume that particles are internally mixed, i.e. particles of the same size have the same chemical composition, which may vary in space and time. Although this assumption may be realistic for continental-scale simulations, where particles originating from different sources have undergone sufficient mixing to achieve a common chemical composition for a given model grid cell and time, it may not be valid for urban-scale simulations, where particles from different sources interact on shorter time scales. To investigate the role of the mixing state assumption on the formation of particles, a size-composition resolved aerosol model (SCRAM) was developed and coupled to the Polyphemus air quality platform. Two simulations, one with the internal mixing hypothesis and another with the external mixing hypothesis, have been carried out for the period 15 January to 11 February 2010, when the MEGAPOLI winter field measurement campaign took place in Paris. The simulated bulk concentrations of chemical species and the concentrations of individual particle classes are compared with the observations of Healy et al. (Atmos. Chem. Phys., 2013, 13, 9479-9496) for the same period. The single particle diversity and the mixing-state index are computed based on the approach developed by Riemer et al. (Atmos. Chem. Phys., 2013, 13, 11423-11439), and they are compared to the measurement-based analyses of Healy et al. (Atmos. Chem. Phys., 2014, 14, 6289-6299). The average value of the single particle diversity, which represents the average number of species within each particle, is consistent between simulation and measurement (2.91 and 2.79 respectively). Furthermore, the average value of the mixing-state index is also well represented in the simulation (69% against 59% from the measurements). The spatial distribution of the mixing-state index shows that the particles are not mixed in urban areas, while they are well mixed in rural areas. This indicates that the assumption of internal mixing traditionally used in transport chemistry models is well suited to rural areas, but this assumption is less realistic for urban areas close to emission sources.

Investigating the impact of aqueous-phase chemistry and wet deposition on organic aerosol formation using a molecular surrogate modeling approach.

A molecular surrogate representation of secondary organic aerosol (SOA) formation is used to investigate the effect of aqueous-phase (in clouds and particles) chemical processing and wet deposition on SOA atmospheric concentrations. To that end, the hydrophilic/hydrophobic organic (H(2)O) model was augmented to account for several gas/aqueous-phase equilibria and aqueous-phase processes, including the formation of oxalic, glyoxilic and pyruvic acids, the oxidation of methyl vinyl ketone (MVK) and methacrolein (MACR), the formation of tetrols and organosulfates from epoxydiols (IEPOX), and further oxidation of water-soluble SOA (aging). Among those processes, SOA chemical aging and IEPOX reactions led to the most significant increases (up to 1 µg m(-3) in some areas) in SOA concentrations in a one-month summer simulation over Europe. However, large uncertainties remain in the gas/aqueous-phase partitioning of oxalic acid, MVK, and MACR. Below-cloud scavenging of SOA precursor gases and of gas-phase SVOC was found to affect SOA concentrations by up to 20%, which suggests that it should be taken into account in air quality models.

Comparison of different gas-phase mechanisms and aerosol modules for simulating particulate matter formation.

The effects of two gas-phase chemical kinetic mechanisms, Regional Atmospheric Chemistry Mechanism version 2 (RACM2) and Carbon-Bond 05 (CB05), and two secondary organic aerosol (SOA) modules, the Secondary Organic Aerosoi Model (SORGAM) and AER/EPRI/Caltech model (AEC), on fine (aerodynamic diameter < or =2.5 microm) particulate matter (PM2.5) formation is studied. The major sources of uncertainty in the chemistry of SOA formation are investigated. The use of all major SOA precursors and the treatment of SOA oligomerization are found to be the most important factors for SOA formation, leading to 66% and 60% more SOA, respectively. The explicit representation of high-NO, and low-NOx gas-phase chemical regimes is also important with increases in SOA of 30-120% depending on the approach used to implement the distinct SOA yields within the gas-phase chemical kinetic mechanism; further work is needed to develop gas-phase mechanisms that are fully compatible with SOA formation algorithms. The treatment of isoprene SOA as hydrophobic or hydrophilic leads to a significant difference, with more SOA being formed in the latter case. The activity coefficients may also be a major source of uncertainty, as they may differ significantly between atmospheric particles, which contain a myriad of SOA, primary organic aerosol (POA), and inorganic aerosol species, and particles formed in a smog chamber from a single precursor under dry conditions. Significant interactions exist between the uncertainties of the gas-phase chemistry and those of the SOA module.