Measuring Arctic Ice-Nucleating Particle Concentrations from Preserved Filters
Year: 2025
Type: article
Abstract: Cloud feedback mechanisms from mixed-phase clouds in the Arctic contribute significantly to the uncertainty in projecting Arctic Amplification and its global climate impacts. A key factor in this process is the presence of ice-nucleating particles (INPs), but their measurements in the Arctic have been spatially and temporally scarce, especially during the 2000s. This thesis aims to provide a method for addressing logistical challenges associated with both the vast area of interest and the complexities of measurement techniques. Archived aerosol glass and quartz fibre filters collected during two summer ship expeditions in 2001 and 2008, along with filters from the Zeppelin Observatory in Ny-Ålesund, Norway (from summers 2001, 2008, 2017, and 2020), were analysed to expand existing INP concentration datasets and create new ones. The INP measurement method using preserved filters was validated by comparison with ship-based INP data from 2001 and ground-based data from Svalbard in 2017 and 2020. Validation results show that the method produces INP concentrations within one order of magnitude of uncertainty, consistent with intercomparison studies in the literature. The new datasets provide valuable insights into INP variability under diverse meteorological conditions. Although long-term trends in INP concentrations appear smaller than short-term variability, the occurrence of highly active INPs increased notably from 2001 to 2020. This study demonstrates the viability of using preserved aerosol filters to retrieve historical INP data. It suggests the potential for developing a 20-year continuous INP record from a remote Arctic location, supporting long-term research on Arctic mixed-phase cloud processes.
Source: Työväentutkimus Vuosikirja
Author: Mustonen, Linnea
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: green
OpenAlex ID: W7199847449
