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A group additivity approach for the prediction of wavelength-dependent absorption cross-sections [An article from: Atmospheric Environment]
Book Details
Author(s)S.S. Khan, L.J. Broadbelt
PublisherElsevier
ISBN / ASINB000RR1DLQ
ISBN-13978B000RR1DL9
MarketplaceFrance 🇫🇷
Description
This digital document is a journal article from Atmospheric Environment, published by Elsevier in 2004. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
Photolysis is an important loss process of carbonyl, peroxy, and nitrate species in the atmosphere. In general, photolysis rate coefficients depend on the intensity of radiation, wavelength, temperature, and the specific molecule reacting. One key source of differences in rate coefficients between different molecules is the absorption cross-section, @s, which is specific to the reactive molecule under consideration. In order to calculate rate coefficients for photolytic processes, a value of @s must be specified or estimated. To this end, a group additivity approach was developed that can be used to estimate the values of @s of species that photolyze primarily in the 290-370nm wavelength region. We demonstrate that this approach can be used to predict accurately unknown values of @s of species for which experimental data are not available.
Description:
Photolysis is an important loss process of carbonyl, peroxy, and nitrate species in the atmosphere. In general, photolysis rate coefficients depend on the intensity of radiation, wavelength, temperature, and the specific molecule reacting. One key source of differences in rate coefficients between different molecules is the absorption cross-section, @s, which is specific to the reactive molecule under consideration. In order to calculate rate coefficients for photolytic processes, a value of @s must be specified or estimated. To this end, a group additivity approach was developed that can be used to estimate the values of @s of species that photolyze primarily in the 290-370nm wavelength region. We demonstrate that this approach can be used to predict accurately unknown values of @s of species for which experimental data are not available.
