(121d) A Computationally Efficient Model for Simulating Aerosol Interactions and Chemistry (MOSAIC)

Atmospheric aerosol particles directly influence the Earth's radiation balance by scattering and absorption of radiation, and indirectly through their impact on cloud microphysical properties and amount. The role of aerosols in climate forcing is, therefore, a critical factor in climate change assessment, as well as an essential element in advancing the state of the art in climate modeling. Urban aerosols are also known to have an adverse effect on human health, especially in urban and industrial areas. As a result, there is an urgent need for developing accurate yet computationally efficient models of aerosol chemistry and microphysics for use in air quality and climate models. This paper describes a new Model for Simulating Aerosol Interactions and Chemistry (MOSAIC), with a special focus on addressing the long-standing issues in solving the dynamic partitioning of semi-volatile inorganic gases (HNO3, HCl, and NH3) to size-distributed atmospheric aerosol particles.

Gas-particle partitioning of semi-volatile species is a highly dynamic and competitive process, and plays an important role in the continuous evolution of atmospheric aerosols and the associated physical and chemical properties relevant for the climate forcing and air quality issues. The coupled ordinary differential equations (ODE) for dynamic gas-particle mass transfer are extremely stiff, and the available numerical techniques are either very expensive or produce oscillatory solutions. These limitations are overcome in MOSAIC with a new dynamic gas-particle partitioning module, which is coupled to an efficient and accurate thermodynamics module. The algorithm includes a new concept of ?dynamic pH,? a novel formulation for mass transfer to mixed-phase and solid particles, and an adaptive time-stepping scheme, which together hold the key to smooth, accurate, and efficient solutions of gas-particle partitioning over the entire relative humidity range. MOSAIC is found to be in excellent agreement with a benchmark version of the model that uses a rigorous solver for integrating the stiff ODEs. The steady-state MOSAIC results for monodisperse aerosol test cases are also in excellent agreement with those obtained with the benchmark equilibrium model AIM. Moreover, the CPU times required for fully dynamic solutions by MOSAIC per size bin per 5 min intervals (typical 3-D model time-steps) are similar to those for bulk equilibrium solutions by the computationally efficient but relatively less accurate model ISORROPIA. Evaluation of the performance of MOSAIC within a 3-D modeling framework for an urban scenario will be presented.