A New Framework for Modelling Wildfire Smoke Aerosol Concentration
DAN BARTHAUX, Andreas Zuend,
McGill University Abstract Number: 61
Working Group: Combustion
AbstractWildfire smoke is a primary source of particulate matter (PM) pollution. Due to the sheer number of species emitted from a biomass-burning event, it is usually impractical to include much more than the emissions of primary organic aerosols within partitioning schemes for PM forecasts in large-scale air quality models. However, understanding the interplay of secondary organic aerosol formation and air parcel dilution at a more detailed level is of interest for improved representation of wildfire events. In this work we introduce a new framework linking multiple models to simulate the gas-phase chemistry and PM concentration within a smoke plume over time. An emission ratios dataset of detected species (ppb/ppm CO) is compiled from previous studies and used to initialize the F0AM chemical box model applied to a Lagrangian plume parcel with dilution. The HYSPLIT model is used to attain wildfire-associated parcel trajectories and associated hourly variables for the box model. The saturation vapor pressures for the several thousand generated species are then calculated from molecular structure information. The species are further represented on a 2D volatility–polarity grid and lumped into a manageable number of surrogate components. These surrogate components are then used as inputs in a thermodynamic multiphase equilibrium model based on the Aerosol Inorganic–Organic Mixtures Functional groups Activity Coefficients (AIOMFAC) model. This model enables predictions of the gas–particle partitioning from the mixture of surrogate components while accounting for changes in temperature and relative humidity along the trajectory. We discuss applications of this framework to a set of wildfire events that impacted the city of Montreal from 2010 to 2021. Measurements from the Canadian air pollution monitoring network were used both to estimate the initial concentrations of fire-emitted species as well as to compare our simulations with measured PM
2.5, ozone, and sulfur dioxide.
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