Surfatm-PM: a model of bi-directional particulate matter exchanges over a grassland

According to the Global Burden of Diseases, PM_2.5 (particles with a diameter under 2.5 µm) is the leading cause of diseases and deaths in 2021 (Brauer et al., 2024). Along with decreased emissions, removal through deposition is used to reduce exposure to particulate matter (PM). With a leaf area index (m² of leaf per m² of land) usually higher than 1, plants allow for a higher deposition surface, hence more particle removal from ambient air. Thus, understanding and estimating PM deposition on vegetation is necessary to assess the impact of vegetation on air quality. In situ measurements above vegetation have shown that PM (vertical) deposition velocity can be positive and negative (Pellerin et al., 2017). No 1-dimensional PM deposition model can predict such values. The objective of this study is to implement a working bi-directional PM exchange scheme in the Surfatm exchange model (Personne et al., 2024), a 1-dimensional SVAT model, using a resistive scheme. The bi-directional fluxes are introduced using a compensation point approach, which can be interpreted as the PM surface concentration. This allows the concentration gradient to change signs depending on the difference of concentration between ambient air and the surface. Two PM exchange datasets above a grassland in Lusignan (France) are used to calibrate and validate the model respectively (Pellerin et al., 2017). The Surfatm-PM model can predict positive and negative deposition velocities, with notable differences attributable to the formation mechanism of the particles, such as the process of coagulation or nucleation or condensation between ambient air and (vegetated) interfaces.