Articles | Volume 12, issue 6
https://doi.org/10.5194/amt-12-3417-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-12-3417-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Evaluating biases in filter-based aerosol absorption measurements using photoacoustic spectroscopy
Nicholas W. Davies
College of Engineering, Mathematics and Physical Sciences, University
of Exeter, Exeter, EX4 4QF, UK
Observation Based Research, Met Office, Exeter, EX1 3PB, UK
Cathryn Fox
Observation Based Research, Met Office, Exeter, EX1 3PB, UK
Kate Szpek
Observation Based Research, Met Office, Exeter, EX1 3PB, UK
Michael I. Cotterell
College of Engineering, Mathematics and Physical Sciences, University
of Exeter, Exeter, EX4 4QF, UK
Observation Based Research, Met Office, Exeter, EX1 3PB, UK
Jonathan W. Taylor
Centre for Atmospheric Science, School of Earth and Environmental
Sciences, University of Manchester, Manchester, M13 9PL, UK
James D. Allan
Centre for Atmospheric Science, School of Earth and Environmental
Sciences, University of Manchester, Manchester, M13 9PL, UK
National Centre for Atmospheric Science, University of Manchester,
Manchester, M13 9PL, UK
Paul I. Williams
Centre for Atmospheric Science, School of Earth and Environmental
Sciences, University of Manchester, Manchester, M13 9PL, UK
National Centre for Atmospheric Science, University of Manchester,
Manchester, M13 9PL, UK
Jamie Trembath
Facility for Airborne Atmospheric Measurements, Cranfield, MK43 0AL,
UK
Jim M. Haywood
College of Engineering, Mathematics and Physical Sciences, University
of Exeter, Exeter, EX4 4QF, UK
Earth System and Mitigation Science, Met Office Hadley Centre, Exeter,
EX1 3PB, UK
Justin M. Langridge
CORRESPONDING AUTHOR
Observation Based Research, Met Office, Exeter, EX1 3PB, UK
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Latest update: 14 Dec 2024
Short summary
This research project assesses biases in traditional, filter-based, aerosol absorption measurements by comparison to state-of-the-art, non-filter-based, or in situ, measurements. We assess biases in traditional absorption measurements for three main aerosol types, including dust and fresh and aged biomass burning aerosols. The main results of this study are that the traditional and state-of-the-art absorption measurements are well correlated and that biases in the former are up to 45 %.
This research project assesses biases in traditional, filter-based, aerosol absorption...