Aircraft Infrared Remote Sensing of Formic Acid

Abstract

The principle aim of this MSc thesis was to create and evaluate novel retrievals of atmospheric formic acid (HCOOH) partial-column weighted-mean concentrations using optimal estimation methods via the Manchester Airborne Retrieval Scheme (MARS) algorithm and nadir high-resolution spectroscopic data measured from the UK FAAM aircraft. The data used here was recorded by the Met Office Airborne Research Interferometer Evaluation System (ARIES) Fourier Transform spectrometer during two flights conducted as part of the NERC Greenhouse gAs Uk and Global Emissions (GAUGE) project. The retrieval of HCOOH is of interest due to its role in the oxidising capacity of the atmosphere and a known over-estimation in chemical transport models and association with biomass burning. HCOOH shows high global variability in atmospheric concentrations typically averaging around 200 pptv in the lower troposphere. Retrievals are reported here as partial-column weighted-mean concentrations and evaluated in terms of retrieval uncertainty, error, and performance against available in situ data measured by a chemical ionization mass spectrometer, also operated on the FAAM aircraft during GAUGE flights. It has been shown here that ARIES has the capacity to record spectra useful for the retrieval of HCOOH using MARS, which now incorporates an operational retrieval method for HCOOH as a result of this work. The results shown here are the first known attempt to understand the potential for meaningful retrievals of HCOOH concentrations from airborne FTS. In future work, ARIES data from other FAAM flights over source regions (i.e. biomass burning zones), where the CIMS instrument is also operated may help to better understand the range of errors and biases under a range of altitudes and nadir scenes. No such flights have yet been conducted, however such missions are planned as part of the NERC Global Methane Project in Uganda in early 2019.

Date of Award	1 Aug 2019
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Martin Gallagher (Supervisor) & Grant Allen (Supervisor)