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.

In the urban environment, gas and particles impose adverse impacts on the health of pedestrians. The conventional computational fluid dynamics (CFD) methods that regard pollutants as passive scalars cannot reproduce the formation of secondary pollutants and lead to uncertain prediction. In this study, SSH-aerosol, a modular box model that simulates the evolution of gas, primary and secondary aerosols, is coupled with the CFD software, OpenFOAM and Code_Saturne. The transient dispersion of pollutants emitted from traffic in a street canyon is simulated using the unsteady Reynolds-averaged Navier–Stokes equations (RANS) model. The simulated concentrations of NO₂, PM₁₀, and black carbon (BC) are compared with field measurements on a street of Greater Paris. The simulated NO₂ and PM₁₀ concentrations based on the coupled model achieved better agreement with measurement data than the conventional CFD simulation. Meanwhile, the black carbon concentration is underestimated, probably partly because of the underestimation of non-exhaust emissions (tire and road wear). Aerosol dynamics lead to a large increase of ammonium nitrate and anthropogenic organic compounds from precursor gas emitted in the street canyon.

This paper describes the GENerator of reduced Organic Aerosol mechanism (GENOA) that produces semi-explicit mechanisms for simulating the formation and evolution of secondary organic aerosol (SOA) in air quality models. Using a series of predefined reduction strategies and evaluation criteria, GENOA trains and reduces SOA mechanisms from near-explicit chemical mechanisms (e.g., the Master Chemical Mechanism – MCM) under representative atmospheric conditions. As a consequence, these trained SOA mechanisms can preserve the accuracy of detailed gas-phase chemical mechanisms on SOA formation (e.g., molecular structures of crucial organic compounds, the effect of “non-ideality”, and the hydrophilic/hydrophobic partitioning of aerosols), with a size (in terms of reaction and species numbers) that is manageable for three-dimensional (3-D) aerosol modeling (e.g., regional chemical transport models). Applied to the degradation of sesquiterpenes (as β-caryophyllene) from MCM, GENOA builds a concise SOA mechanism (2 % of the MCM size) that consists of 23 reactions and 15 species, with 6 of them being condensable. The generated SOA mechanism has been evaluated regarding its ability to reproduce SOA concentrations under the varying atmospheric conditions encountered over Europe, with an average error lower than 3 %.

Near-explicit chemical mechanisms representing toluene SOA formation are reduced using the GENOA algorithm and used in 3D simulations of air quality over Greater Paris and in the streets of a district near Paris.

SSH-aerosol is developed to represent the evolution of primary and secondary pollutants in the atmosphere by processes linked to gas-phase chemistry, aerosol dynamics (coagulation, condensation/evaporation and nucleation) and intra-particle reactions. The representation of process complexity can be adjusted based on the user's choices. The model uses a sectional size distribution, and offers the capability to discretize chemical composition to account for the mixing state of particles. The algorithms are designed to represent the evolution of ultrafine particles: conservation of mass and number during numerical resolution, taking into account the Kelvin effect, the condensation dynamics of nonvolatile compounds, and nucleation. Different parameterizations are provided for nucleation: binary, ternary, heteromolecular and organic nucleation depending on the compounds involved. For gas-phase chemistry, schemes of different complexities can be handled: from simple schemes to model ozone, oxidants and inorganic chemistry (e.g. CB05, RACM2, Melchior2), to more complex schemes, e.g. from the Master Chemical Mechanism (MCM). The complexity of the schemes used for secondary organic aerosol (SOA) formation may also be adjusted: from schemes built from chamber data to near-explicit schemes from MCM. SOA schemes reduced using the GENOA algorithm are also provided for several precursors (toluene, a sesquiterpene and three monoterpenes), together with their evaluation against chamber or flow-tube experiments. A wall-loss module has also been added for easier comparisons to chamber experiments. Specific developments were made in version 2.0 to automatically link the chosen gas-phase mechanism to SOA formation by using the SMILES structure of organic compounds, allowing for the determination of their hydrophilic and hydrophobic properties and for the partitioning in both organic and aqueous phases. The gas/particle partitioning may also be represented with different complexities. For the organic phase, viscosity may be modelled, adapting the aerosol viscosity to its composition, and coupling organic and inorganic thermodynamics. The dynamic evolution of the partitioning may be computed explicitly or thermodynamic equilibrium may be assumed. Different options are also provided to simulate the chemistry of organic compounds inside the particles with different types of reactions: irreversible 1st order reactions, bulk oligomerization, hydratation of aldehydes and reactions of organic compounds with inorganic ions. The SSH-aerosol model may be installed with a docker for standalone use. It has also been coupled to several 3D models to represent gas and aerosol concentrations: from the local scale with computational fluid dynamic and street network models to the regional scale with chemistry-transport models.