1. ABOUT THE DATASET -------------------- Title: Dataset for Airborne observations of ice-nucleating particles during the 2022 DCMEX campaign, New Mexico. [Dataset] Creator(s): Martin I. Daily, Joseph Robinson, Declan Finney, Erin Raif, James B. McQuaid, Benjamin J Murray and Alan Blyth Organisation(s): University of Leeds Rights-holder(s): Copyright 2024 University of Leeds Publication Year: 2024 Description: Aerosol filter data from the 2022 DCMEX aircraft campaign in New Mexico, USA, sampled from BAe-146 FAAM research aircraft. The dataset contains the sampling metadata, INP concentrations (both concentrations and freezing temperatures obtained in the experiments) and SEM-EDS data (size distributions from both SEM and optical probes, as well as EDS size-resolved composition fractions). Cite as: Martin I. Daily, Joseph Robinson, Declan Finney, Erin Raif, James B. McQuaid, Benjamin J Murray and Alan Blyth (2024): Dataset for Airborne observations of ice-nucleating particles during the 2022 DCMEX campaign, New Mexico. [Dataset]. https://doi.org/10.5518/1476 Contact: Martin I. Daily, m.i.daily@leeds.ac.uk / Ben J. Murray, b.j.murray@leeds.ac.uk 2. TERMS OF USE --------------- Copyright 2024 University of Leeds. Unless otherwise stated, this dataset is licensed under a Creative Commons Attribution 4.0 International Licence: https://creativecommons.org/licenses/by/4.0/. 3. PROJECT AND FUNDING INFORMATION ---------------------------------- Title: DCMEX -- Deep Convective Microphysics Experiment Dates: 1 Feb 2020 - 31 Mar 2025 Funding organisation: Natural Environment Research Council Grant no.: NE/T006420/1 4. CONTENTS ----------- File listing - 01_filters_metadata.csv: This file contains metadata for each aerosol run and the filters collected during them including: date, time of start and end of run, mean altitude during run (metres above sea level), volume of air sampled (litres), mean air sampling rate (litres/min). - 02_INP_data_teflon.csv. Droplet freezing assay results for Teflon filter samples (droplet freezing temperatures) and calculated INP value (per litre air) with errors. - 03_INP_data_polycarbonate.csv: Droplet freezing assay results for polycarbonate filter samples (droplet freezing temperatures) and calculated INP value (per litre air) with errors. - 04_INP_handlingblanks_teflon.csv: Droplet freezing assay results for Teflon filter handling blanks (droplet freezing temperatures). - 05_INP_handlingblanks_polycarbonate.csv: Droplet freezing assay results for polycarbonate filter handling blanks (droplet freezing temperatures). - 06_SEM_particlesizedist.csv: Binned aerosol particle size distribution (dnlogDp/logDp) in the range 0.3 – 20 micrometres, with errors, derived from scanning electron microscope analysis of selected polycarbonate filters. - 07_SEM_sizedcomposition.csv: Tables of binned fractional composition of aerosol in the range 0.3 – 20 micrometres, derived from scanning electron microscope analysis of selected polycarbonate filters. 5. METHODS ---------- - Filter collection: Collected using the dual filter inlet sampling system on the BAe-146 FAAM research aircraft. Filters were collected during aerosol runs, during which the aircraft was flying level and at constant altitude in cloud-free air. Typically a pair of filters, one Teflon(PTFE) 1.2 micrometre pore size and one polycarbonate 0.4 micrometre pore size was taken during each filter run. - INP concentrations: These were generated from PTFE filter aerosol samples collected on board of the BAe-146 FAAM research aircraft. The filters were analysed using a droplet freezing assay on a Nucleation by Immersed Particle Instrument (NIPI, Whale et al., 2015). Teflon filter droplet assays used a ‘drop-on’ technique (Price et al., 2018) while polycarbonate filters were washed into a suspension. - SEM-EDS size-resolved composition and particle size distribution. This data was generated using aerosol samples collected on top of polycarbonate filters on board of the BAe-146 FAAM research aircraft. The filters were analysed using our SEM-EDS approach (Sanchez-Marroquin et al., 2019). Each particle detected by the microscope software was sized and analysed for fractional elemental composition by EDS, then classified post-hoc by a previously published algorithm (Sanchez-Marroquin et al., 2019).