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This content will become publicly available on July 26, 2018

Title: Multivariate quadrature for representing cloud condensation nuclei activity of aerosol populations

Here, sparse representations of atmospheric aerosols are needed for efficient regional- and global-scale chemical transport models. Here we introduce a new framework for representing aerosol distributions, based on the quadrature method of moments. Given a set of moment constraints, we show how linear programming, combined with an entropy-inspired cost function, can be used to construct optimized quadrature representations of aerosol distributions. The sparse representations derived from this approach accurately reproduce cloud condensation nuclei (CCN) activity for realistically complex distributions simulated by a particleresolved model. Additionally, the linear programming techniques described in this study can be used to bound key aerosol properties, such as the number concentration of CCN. Unlike the commonly used sparse representations, such as modal and sectional schemes, the maximum-entropy approach described here is not constrained to pre-determined size bins or assumed distribution shapes. This study is a first step toward a particle-based aerosol scheme that will track multivariate aerosol distributions with sufficient computational efficiency for large-scale simulations.
ORCiD logo [1] ;  [1]
  1. Brookhaven National Lab. (BNL), Upton, NY (United States)
Publication Date:
Report Number(s):
Journal ID: ISSN 2169-897X; R&D Project: 2016-BNL-EE630EECA-Budg; KP1701000
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Journal of Geophysical Research: Atmospheres
Additional Journal Information:
Journal Name: Journal of Geophysical Research: Atmospheres; Journal ID: ISSN 2169-897X
American Geophysical Union
Research Org:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Country of Publication:
United States
54 ENVIRONMENTAL SCIENCES; aerosol modeling; cloud condensation nuclei; particle-based modeling; quadrature method of moments
OSTI Identifier: