Gas Transfer Across Air‐Water Interfaces in Inland Waters: From Micro‐Eddies to Super‐Statistics
Abstract In inland water covering lakes, reservoirs, and ponds, the gas exchange of slightly soluble gases such as carbon dioxide, dimethyl sulfide, methane, or oxygen across a clean and nearly flat air‐water interface is routinely described using a water‐side mean gas transfer velocity kL‾, where o...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-11-01
|
| Series: | Water Resources Research |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2023WR036615 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849227269592055808 |
|---|---|
| author | Gabriel Katul Andrew Bragg Ivan Mammarella Heping Liu Qi Li Elie Bou‐Zeid |
| author_facet | Gabriel Katul Andrew Bragg Ivan Mammarella Heping Liu Qi Li Elie Bou‐Zeid |
| author_sort | Gabriel Katul |
| collection | DOAJ |
| description | Abstract In inland water covering lakes, reservoirs, and ponds, the gas exchange of slightly soluble gases such as carbon dioxide, dimethyl sulfide, methane, or oxygen across a clean and nearly flat air‐water interface is routinely described using a water‐side mean gas transfer velocity kL‾, where overline indicates time or ensemble averaging. The micro‐eddy surface renewal model predicts kL‾=αoSc−1/2νϵ‾1/4, where Sc is the molecular Schmidt number, ν is the water kinematic viscosity, and ϵ‾ is the waterside mean turbulent kinetic energy dissipation rate at or near the interface. While αo=0.39−0.46 has been reported across a number of data sets, others report large scatter or variability around this value range. It is shown here that this scatter can be partly explained by high temporal variability in instantaneous ϵ around ϵ‾, a mechanism that was not previously considered. As the coefficient of variation CVe in ϵ increases, αo must be adjusted by a multiplier 1+CVe2−3/32 that was derived from a log‐normal model for the probability density function of ϵ. Reported variations in αo with a macro‐scale Reynolds number can also be partly attributed to intermittency effects in ϵ. Such intermittency is characterized by the long‐range (i.e., power‐law decay) spatial auto‐correlation function of ϵ. That αo varies with a macro‐scale Reynolds number does not necessarily violate the micro‐eddy model. Instead, it points to a coordination between the macro‐ and micro‐scales arising from the transfer of energy across scales in the energy cascade. |
| format | Article |
| id | doaj-art-14cdc302e7ea46528fd496668ecb6454 |
| institution | Kabale University |
| issn | 0043-1397 1944-7973 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Wiley |
| record_format | Article |
| series | Water Resources Research |
| spelling | doaj-art-14cdc302e7ea46528fd496668ecb64542025-08-23T13:05:51ZengWileyWater Resources Research0043-13971944-79732024-11-016011n/an/a10.1029/2023WR036615Gas Transfer Across Air‐Water Interfaces in Inland Waters: From Micro‐Eddies to Super‐StatisticsGabriel Katul0Andrew Bragg1Ivan Mammarella2Heping Liu3Qi Li4Elie Bou‐Zeid5Department of Civil and Environmental Engineering Duke University Durham NC USADepartment of Civil and Environmental Engineering Duke University Durham NC USAFaculty of Science Institute for Atmospheric and Earth System Research/Physics University of Helsinki Helsinki FinlandDepartment of Civil and Environmental Engineering Washington State University Pullman WA USADepartment of Civil and Environmental Engineering Cornell University Ithaca NY USADepartment of Civil and Environmental Engineering Princeton University Princeton NJ USAAbstract In inland water covering lakes, reservoirs, and ponds, the gas exchange of slightly soluble gases such as carbon dioxide, dimethyl sulfide, methane, or oxygen across a clean and nearly flat air‐water interface is routinely described using a water‐side mean gas transfer velocity kL‾, where overline indicates time or ensemble averaging. The micro‐eddy surface renewal model predicts kL‾=αoSc−1/2νϵ‾1/4, where Sc is the molecular Schmidt number, ν is the water kinematic viscosity, and ϵ‾ is the waterside mean turbulent kinetic energy dissipation rate at or near the interface. While αo=0.39−0.46 has been reported across a number of data sets, others report large scatter or variability around this value range. It is shown here that this scatter can be partly explained by high temporal variability in instantaneous ϵ around ϵ‾, a mechanism that was not previously considered. As the coefficient of variation CVe in ϵ increases, αo must be adjusted by a multiplier 1+CVe2−3/32 that was derived from a log‐normal model for the probability density function of ϵ. Reported variations in αo with a macro‐scale Reynolds number can also be partly attributed to intermittency effects in ϵ. Such intermittency is characterized by the long‐range (i.e., power‐law decay) spatial auto‐correlation function of ϵ. That αo varies with a macro‐scale Reynolds number does not necessarily violate the micro‐eddy model. Instead, it points to a coordination between the macro‐ and micro‐scales arising from the transfer of energy across scales in the energy cascade.https://doi.org/10.1029/2023WR036615Batchelor scalemicro‐eddy modelgas transfer velocitysuperstatisticsair‐water exchangeintermittency |
| spellingShingle | Gabriel Katul Andrew Bragg Ivan Mammarella Heping Liu Qi Li Elie Bou‐Zeid Gas Transfer Across Air‐Water Interfaces in Inland Waters: From Micro‐Eddies to Super‐Statistics Water Resources Research Batchelor scale micro‐eddy model gas transfer velocity superstatistics air‐water exchange intermittency |
| title | Gas Transfer Across Air‐Water Interfaces in Inland Waters: From Micro‐Eddies to Super‐Statistics |
| title_full | Gas Transfer Across Air‐Water Interfaces in Inland Waters: From Micro‐Eddies to Super‐Statistics |
| title_fullStr | Gas Transfer Across Air‐Water Interfaces in Inland Waters: From Micro‐Eddies to Super‐Statistics |
| title_full_unstemmed | Gas Transfer Across Air‐Water Interfaces in Inland Waters: From Micro‐Eddies to Super‐Statistics |
| title_short | Gas Transfer Across Air‐Water Interfaces in Inland Waters: From Micro‐Eddies to Super‐Statistics |
| title_sort | gas transfer across air water interfaces in inland waters from micro eddies to super statistics |
| topic | Batchelor scale micro‐eddy model gas transfer velocity superstatistics air‐water exchange intermittency |
| url | https://doi.org/10.1029/2023WR036615 |
| work_keys_str_mv | AT gabrielkatul gastransferacrossairwaterinterfacesininlandwatersfrommicroeddiestosuperstatistics AT andrewbragg gastransferacrossairwaterinterfacesininlandwatersfrommicroeddiestosuperstatistics AT ivanmammarella gastransferacrossairwaterinterfacesininlandwatersfrommicroeddiestosuperstatistics AT hepingliu gastransferacrossairwaterinterfacesininlandwatersfrommicroeddiestosuperstatistics AT qili gastransferacrossairwaterinterfacesininlandwatersfrommicroeddiestosuperstatistics AT eliebouzeid gastransferacrossairwaterinterfacesininlandwatersfrommicroeddiestosuperstatistics |