4.7 Article

Development of Heterogeneous Ice Nucleation Rate Coefficient Parameterizations From Ambient Measurements

期刊

GEOPHYSICAL RESEARCH LETTERS
卷 48, 期 23, 页码 -

出版社

AMER GEOPHYSICAL UNION
DOI: 10.1029/2021GL095359

关键词

ice nucleation; CFDC; ATOFMS; dust; SSA; freezing rate coefficients

资金

  1. Department of Energy (DOE), Office of Science, Office of Biological and Environmental Research through the Early Career Research program
  2. Center for Aerosol Impacts on Chemistry of the Environment (CAICE)
  3. National Science Foundation (NSF) Center for Chemical Innovation
  4. CalWater 2015 field campaign - NSF

向作者/读者索取更多资源

Ice nucleating particles (INPs) are a rare subset of particles that can have a significant impact on climate. Models need effective parameterizations to simulate the variability of INPs, with laboratory and field measurement-based parameterizations having their own advantages and disadvantages. Heterogeneous ice nucleation rate coefficients for ambient particles can be measured using a single-particle mass spectrometer.
Ice nucleating particles (INPs) are a rare subset of particles that can have an outsized impact relative to their prevalence. To simulate INP variability, models require parameterizations for the most important sources of INPs. Most parameterizations in the literature were developed from laboratory experiments that used proxies for ambient particles. Whether these laboratory models effectively represent ambient aerosol is still not well understood and parameterizations developed from field measurements may be more atmospherically relevant. Expanding on previous work in which we used an ice chamber and a single-particle mass spectrometer (SPMS) to characterize INP composition, we calculate heterogeneous ice nucleation rate coefficients for ambient particles. We find good agreement between our dust and previous measurements of airborne dust. We also use a Monte Carlo approach to assess the relative contribution of each measurement to the uncertainty and find that the biggest source is the sampling efficiency of the SPMS.

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