skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Uncertainty in counting ice nucleating particles with continuous flow diffusion chambers

Abstract

This study investigates the measurement of ice nucleating particle (INP) concentrations and sizing of crystals using continuous flow diffusion chambers (CFDCs). CFDCs have been deployed for decades to measure the formation of INPs under controlled humidity and temperature conditions in laboratory studies and by ambient aerosol populations. These measurements have, in turn, been used to construct parameterizations for use in models by relating the formation of ice crystals to state variables such as temperature and humidity as well as aerosol particle properties such as composition and number. We show here that assumptions of ideal instrument behavior are not supported by measurements made with a commercially available CFDC, the SPectrometer for Ice Nucleation (SPIN), and the instrument on which it is based, the Zurich Ice Nucleation Chamber (ZINC). Non-ideal instrument behavior, which is likely inherent to varying degrees in all CFDCs, is caused by exposure of particles to different humidities and/or temperatures than predicated from instrument theory of operation. This can result in a systematic, and variable, underestimation of reported INP concentrations. Here we find here variable correction factors from 1.5 to 9.5, consistent with previous literature values. We use a machine learning approach to show that non-ideality is most likely due to small-scale flowmore » features where the aerosols are combined with sheath flows. Machine learning is also used to minimize the uncertainty in measured INP concentrations. Finally, we suggest that detailed measurement, on an instrument-by-instrument basis, be performed to characterize this uncertainty.« less

Authors:
 [1]; ORCiD logo [1];  [1]; ORCiD logo [2]; ORCiD logo [2]; ORCiD logo [1]; ORCiD logo [1];  [3]
  1. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Dept. of Earth, Atmospheric and Planetary Sciences
  2. Federal Inst. of Technology, Zurich (Switzerland). Inst. for Atmospheric and Climate Science
  3. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Dept. of Earth, Atmospheric and Planetary Sciences, and Dept. of Civil and Environmental Engineering
Publication Date:
Research Org.:
Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
Sponsoring Org.:
USDOE; National Science Foundation (NSF); National Aeronautic and Space Administration (NASA)
OSTI Identifier:
1425936
Grant/Contract Number:  
SC0014487; NNX13AO15G; AGS-1461347; AGS-1339264; 200021_156581
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Atmospheric Chemistry and Physics (Online)
Additional Journal Information:
Journal Name: Atmospheric Chemistry and Physics (Online); Journal Volume: 17; Journal Issue: 17; Journal ID: ISSN 1680-7324
Publisher:
European Geosciences Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Garimella, Sarvesh, Rothenberg, Daniel A., Wolf, Martin J., David, Robert O., Kanji, Zamin A., Wang, Chien, Rösch, Michael, and Cziczo, Daniel J. Uncertainty in counting ice nucleating particles with continuous flow diffusion chambers. United States: N. p., 2017. Web. doi:10.5194/acp-17-10855-2017.
Garimella, Sarvesh, Rothenberg, Daniel A., Wolf, Martin J., David, Robert O., Kanji, Zamin A., Wang, Chien, Rösch, Michael, & Cziczo, Daniel J. Uncertainty in counting ice nucleating particles with continuous flow diffusion chambers. United States. doi:10.5194/acp-17-10855-2017.
Garimella, Sarvesh, Rothenberg, Daniel A., Wolf, Martin J., David, Robert O., Kanji, Zamin A., Wang, Chien, Rösch, Michael, and Cziczo, Daniel J. Thu . "Uncertainty in counting ice nucleating particles with continuous flow diffusion chambers". United States. doi:10.5194/acp-17-10855-2017. https://www.osti.gov/servlets/purl/1425936.
@article{osti_1425936,
title = {Uncertainty in counting ice nucleating particles with continuous flow diffusion chambers},
author = {Garimella, Sarvesh and Rothenberg, Daniel A. and Wolf, Martin J. and David, Robert O. and Kanji, Zamin A. and Wang, Chien and Rösch, Michael and Cziczo, Daniel J.},
abstractNote = {This study investigates the measurement of ice nucleating particle (INP) concentrations and sizing of crystals using continuous flow diffusion chambers (CFDCs). CFDCs have been deployed for decades to measure the formation of INPs under controlled humidity and temperature conditions in laboratory studies and by ambient aerosol populations. These measurements have, in turn, been used to construct parameterizations for use in models by relating the formation of ice crystals to state variables such as temperature and humidity as well as aerosol particle properties such as composition and number. We show here that assumptions of ideal instrument behavior are not supported by measurements made with a commercially available CFDC, the SPectrometer for Ice Nucleation (SPIN), and the instrument on which it is based, the Zurich Ice Nucleation Chamber (ZINC). Non-ideal instrument behavior, which is likely inherent to varying degrees in all CFDCs, is caused by exposure of particles to different humidities and/or temperatures than predicated from instrument theory of operation. This can result in a systematic, and variable, underestimation of reported INP concentrations. Here we find here variable correction factors from 1.5 to 9.5, consistent with previous literature values. We use a machine learning approach to show that non-ideality is most likely due to small-scale flow features where the aerosols are combined with sheath flows. Machine learning is also used to minimize the uncertainty in measured INP concentrations. Finally, we suggest that detailed measurement, on an instrument-by-instrument basis, be performed to characterize this uncertainty.},
doi = {10.5194/acp-17-10855-2017},
journal = {Atmospheric Chemistry and Physics (Online)},
number = 17,
volume = 17,
place = {United States},
year = {Thu Sep 14 00:00:00 EDT 2017},
month = {Thu Sep 14 00:00:00 EDT 2017}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Citation Metrics:
Cited by: 3 works
Citation information provided by
Web of Science

Save / Share:

Works referenced in this record:

Random Forests
journal, January 2001