Details zur Publikation

Kategorie Textpublikation
Referenztyp Zeitschriften
DOI 10.1080/10256016.2022.2153126
Volltext Akzeptiertes Manuskript
Titel (primär) New insights into diffusive kinetic fractionation during liquid condensation under supersaturated environment: an alternative approach for isotope tagging of ground-level water vapour
Autor Ganguly, A.; Padhya, V.; Oza, H.; Strauch, G.; Rajendrakumar, D.
Quelle Isotopes in Environmental and Health Studies
Erscheinungsjahr 2023
Department HDG
Band/Volume 59
Heft 1
Seite von 1
Seite bis 26
Sprache englisch
Topic T5 Future Landscapes
Supplements https://ndownloader.figstatic.com/files/38642925
Keywords Diffusive gradient; hydrogen-2; isotope hydrology; kinetic isotope fractionation; machine learning; oxygen-18; supersaturation; vapour sampling
Abstract Stable water isotopes in ground-level vapour are key to estimating water exchange between geospheres. Their sampling, however, is limited to laser-absorption spectrometers and satellite observations, having inherent shortcomings. This study investigates diffusive kinetic fractionation during liquid condensation under supersaturated environment, providing a cost-effective, reliable way of sampling ground-level vapour isotopes (18O, 2H). Experiments were undertaken at three locations in India with ‘liquid’ samples collected from condensation of ambient air at 0°C. Simultaneously, pristine ‘vapour’ was sampled via cryogenic-trapping using liquid nitrogen–alcohol slush at –78°C. The ‘liquid’ condensed under supersaturation was progressively more depleted in 18O, and less enriched in 2H than expected under equilibrium fractionation, with an increasing degree of supersaturation expressed as saturation index (Si). This study revealed: (1) Si, molecular density, Rh, T together control the extent of isotopic kinetic fractionation. (2) The presence of diffusive concentration gradient inhibits the flow of heavier isotopes during liquid condensation. (3) The stochastic nature of the process cannot be explained using a physics-based model alone. The artificial neural network model is hence deployed to sample δ18O (δ 2H) within –0.24 ± 1.79‰ (0.53 ± 11.23 ‰) of true value. (4) The approach can be extended to ground-validate isotope-enabled general circulation models and satellite observations.
dauerhafte UFZ-Verlinkung https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=25740
Ganguly, A., Padhya, V., Oza, H., Strauch, G., Rajendrakumar, D. (2023):
New insights into diffusive kinetic fractionation during liquid condensation under supersaturated environment: an alternative approach for isotope tagging of ground-level water vapour
Isot. Environ. Health Stud. 59 (1), 1 - 26 10.1080/10256016.2022.2153126