Implementation of the MOSAIC aerosol module (v1.0) in the Canadian air quality model GEM-MACH (v3.1)

Abstract. The Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) aerosol thermodynamics and sectional framework has been implemented into the Canadian operational air quality model GEM-MACH. The original aerosol sub-model in GEM-MACH is based on the Canadian Aerosol Module (CAM), which uses a single-moment (mass) sectional scheme, and inorganic thermodynamics derived from the equilibrium ISORROPIA model without base metal cations. MOSAIC features non-equilibrium inorganic thermodynamics and a double-moment (mass and number) sectional scheme. For evaluation we conduct four 1-year simulations with the same emissions and meteorology over the North America domain. A reference run (REF) with the Zhang et al. (2001) aerosol dry deposition scheme and a sensitivity run (EMR) with updated parameters from Emerson et al. (2020) are conducted for each aerosol model option. The results are compared to station observations and surface monthly-mean model–observation synthesis data. MOSAIC exhibits a shift in the accumulation-mode mass and number distribution compared to CAM that results in more aerosol dry deposition in the REF run and a surface PM2.5 sulfate low bias of about 15 % relative to CAM. This bias is essentially removed in the MOSAIC EMR run, resulting in a better fit to aggregated urban and rural stations compared to CAM over the North America domain. Comparison with the AERONET volume size distribution inversion product shows that MOSAIC gives a much higher level of agreement in terms of location of the accumulation-mode peak diameter and separation of the accumulation and coarse modes. PM2.5 nitrate and ammonium for the MOSAIC EMR run shows overall better agreement with observation station data compared to both REF and EMR CAM runs at rural stations. At urban stations, MOSAIC has a high bias for nitrate relative to CAM and observations during summer, but it is reduced in the EMR run compared to the REF run. The high bias in ammonium seen with CAM for both REF and EMR runs relative to aggregated rural and urban station observations is reduced with MOSAIC by about 25 % between April and November.