September 10, 2013
Journal Article

Modal Bin Hybrid Model: A Surface Area Consistent, Triple Moment Sectional Method for Use in Process-oriented Modeling of Atmospheric Aerosols

Abstract

A triple moment sectional method, Modal Bin Hybrid Model (MBHM), has been developed. In addition to number and mass (volume), surface area is predicted (and preserved), which is important for gas-to-particle mass transfer and light extinction cross section. The performance of MBHM was evaluated against double moment sectional (DMS) methods with various size resolutions up to BIN256 (BINx: x is number of sections over three orders of magnitude in size, ?logD = 3/x) for simulating evolution of particles under simultaneously occurring nucleation, condensation and coagulation processes. Because MBHM gives a physically consistent form of the intra-sectional distributions, errors and biases of MBHM at BIN4-8 resolution were almost equivalent to those of DMS at BIN16-32 resolution for various important variables such as the moments Mk (k: 0, 2, 3), dMk/dt, and the number and volume of particles larger than a certain diameter. Another important feature of MBHM is that only a single bin is adequate to simulate full aerosol dynamics for particles whose size distribution can be approximated by a single lognormal mode. This flexibility is useful for process-oriented (multi category and/or mixing state) modeling: primary aerosols whose size parameters would not differ substantially in time and space can be expressed by a single or a small number of modes, whereas secondary aerosols whose size changes drastically from one to several hundred nanometers can be expressed by a number of modes. Added dimensions can be applied to MBHM to represent mixing state or photo-chemical age for aerosol mixing state studies.

Revised: May 2, 2014 | Published: September 10, 2013

Citation

Kajino M., R.C. Easter, and S.J. Ghan. 2013. Modal Bin Hybrid Model: A Surface Area Consistent, Triple Moment Sectional Method for Use in Process-oriented Modeling of Atmospheric Aerosols. Journal of Geophysical Research: Atmospheres 118, no. 17:10,011-10,040. PNNL-SA-93195. doi:10.1002/jgrd.50685