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HCOOH measurements from space: TES retrieval algorithm and observed global distribution.

K E Cady-Pereira1, S Chaliyakunnel2, M W Shephard3

  • 1Atmospheric and Environmental Research, Inc., Lexington, Massachusetts, USA.

Atmospheric Measurement Techniques
|March 15, 2021
PubMed
Summary
This summary is machine-generated.

The Tropospheric Emission Spectrometer (TES) satellite provides new data on formic acid (HCOOH) distribution. Global HCOOH levels are higher than models predict, suggesting missing sources from biogenic emissions and fires.

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Area of Science:

  • Atmospheric Chemistry
  • Remote Sensing
  • Satellite Observations

Background:

  • Formic acid (HCOOH) is a significant atmospheric carboxylic acid.
  • Understanding its global distribution is crucial for atmospheric chemistry.
  • Previous measurements have had limitations in global coverage and resolution.

Purpose of the Study:

  • To describe the retrieval algorithm for formic acid (HCOOH) from the Tropospheric Emission Spectrometer (TES) satellite.
  • To quantify the global distribution of tropospheric HCOOH using TES data.
  • To compare TES HCOOH measurements with chemical transport model (GEOS-Chem) predictions.

Main Methods:

  • Optimal estimation methodology for spectral retrieval.
  • Analysis of spectral microwindows and a priori constraints.
  • Comprehensive error, sensitivity, and performance analysis of the HCOOH retrieval.

Main Results:

  • TES HCOOH retrievals offer limited vertical sensitivity, primarily between 900-600 hPa with ~2 km resolution.
  • Detection limits for HCOOH are around 0.5 ppbv, dependent on thermal contrast.
  • TES-derived global HCOOH distribution shows seasonality broadly matching GEOS-Chem CTM but with higher overall concentrations.

Conclusions:

  • TES satellite data reveals higher atmospheric formic acid (HCOOH) concentrations than current models simulate.
  • Discrepancies are pronounced in summer and over biomass burning regions.
  • This suggests significant underestimation of HCOOH sources, likely from biogenic emissions and fires, in atmospheric models.