Abstract
Atmospheric aerosol and the cloud droplets and ice crystals that grow on them remain major sources of uncertainty in global climate models. A subset of aerosol, ice nucleating particles, catalyze the freezing of water droplets at temperatures warmer than −38 °C. Here we show that RuBisCO, one of the most abundant proteins in plants and phytoplankton, is one of the most efficient known immersion ice nucleating particles with a mean freezing temperature of −7.9 ± 0.3 °C. Further, we demonstrate RuBisCO is present in ambient continental aerosol where it can serve as an ice nucleating particle. Other biogenic molecules act as immersion ice nucleating particles, in the range of −19 to −26 °C. In addition, our results indicate heat denaturation is not a universal indicator of the proteinaceous origin of ice nucleating particles, suggesting current studies may fail to accurately quantify biological ice nucleating particle concentrations and their global importance.
Original language | English |
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Article number | 51 |
Journal | Communications Earth and Environment |
Volume | 4 |
Issue number | 1 |
DOIs | |
State | Published - Dec 2023 |
Externally published | Yes |
Funding
Financial support was provided by NSF Atmospheric Chemistry Program (Award # AGS-2128133) to D.C.O.T. and S.D.B.. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. We thank Shawn M. Doyle and Jason B. Sylvan of the Department of Oceanography, Texas A&M University, for their guidance on RNA sample preparation and the use of the plate reader for RuBisCO quantification. The authors gratefully acknowledge the NOAA Air Resources Laboratory (ARL) for the provision of the HYSPLIT transport and dispersion model and READY website ( https://www.ready.noaa.gov ) used in this publication. Financial support was provided by NSF Atmospheric Chemistry Program (Award # AGS-2128133) to D.C.O.T. and S.D.B. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. We thank Shawn M. Doyle and Jason B. Sylvan of the Department of Oceanography, Texas A&M University, for their guidance on RNA sample preparation and the use of the plate reader for RuBisCO quantification. The authors gratefully acknowledge the NOAA Air Resources Laboratory (ARL) for the provision of the HYSPLIT transport and dispersion model and READY website (https://www.ready.noaa.gov) used in this publication.
Funders | Funder number |
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Department of Oceanography, Texas A&M University | |
NOAA Air Resources Laboratory | |
National Science Foundation | AGS-2128133 |
Army Research Laboratory |