![]() In order to calculate the other properties of atmospheric aerosol, e.g., number and size distribution, aerosol dynamic processes such as nucleation, condensation and coagulation have to be described in the model. Until recently, the EMEP (Co-operative Programme for Monitoring and Evaluation of the Long-Range Transmission of Air Pollutants in Europe) Eulerian transport model allows only for the first estimate on aerosol mass and chemical composition distribution in Europe. Therefore measurements of aerosol number concentration were initiated. These particles are characterized by a large number density but their contribution to the PM 2.5 and PM 10 mass is negligible. Recently, fine and ultra-fine particles due to their ability to penetrate deeper into the respiratory system have become the focus of research interest. Most of available epidemiological studies are based on the measurements of the mass concentration of particles smaller than 2.5 μm (PM 2.5) or 10 μm (PM 10) in diameter. The acute and chronic health effects of particles have lately been a matter of growing public concern and one of the topic research areas. To estimate the radiative forcing of atmospheric aerosols, information on their number, size and surface area is quite essential. They influence the climate directly by absorbing incoming solar radiation or scattering it back to space, and indirectly by enhancing cloud formation and modifying the clouds characteristics. Atmospheric aerosols affect air quality, human health and climate change through many different processes. Therefore it is recommended for implementation and further testing in the regional three-dimensional Eulerian model. MONO32 showed an acceptable accuracy for long-range transport modeling in describing aerosol dynamics while being computationally efficient. However, the results appeared to be quite sensitive to the hygroscopic properties of the condensable organic vapor. Deviations in the resulting nucleation mode diameter were 11–16%. Two typical nucleation episodes were chosen for testing, and by using the nucleation rate and the condensable vapor source rate calculated from the measurements, MONO32 was able to predict the evolution of the total number concentration and the growth rate of the nucleation mode quantitatively in good agreement with the observations. MONO32 was also verified against measurements available from the Biogenic Aerosol Formation in the Boreal Forest 3 (BIOFOR3) campaign. MONO32 compared reasonably well with the sectional model AEROFOR2 with 54 sections for example, difference in the total number concentration after 24-hour simulation was less than 15–25%. A mode-merging method was implemented in MONO32 to account for the transfer of aerosol mass and number to a larger mode as particles grow by condensation and coagulation. ![]() Both integration methods showed the same accuracy in calculating particle number and size evolution, while the two-step scheme was computationally much more efficient. Two different time integration schemes, a FORTRAN NAG-library routine and a two-step scheme, were tested. MONO32 accounts for nucleation, condensation, and coagulation processes. The module presents aerosol size distribution with four monodisperse modes and characterizes aerosol chemical composition with seven components, so 32 prognostic equations are needed to describe particle mass and number concentration. In this work, we present and evaluate an aerosol dynamics module MONO32, which is designed for use in regional air pollution models. Air quality models used as a scientific basis for air pollution strategy development need physically sound and computationally efficient schemes to describe aerosol formation, interaction, and evolution.
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