Abstract

Abstract. We present the first global glyoxal (CHOCHO) tropospheric column product derived from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor satellite. Atmospheric glyoxal results from the oxidation of other non-methane volatile organic compounds (NMVOCs) and from direct emissions caused by combustion processes. Therefore, this product is a useful indicator of VOC emissions. It is generated with an improved version of the BIRA-IASB scientific retrieval algorithm relying on the differential optical absorption spectroscopy (DOAS) approach. Among the algorithmic updates, the DOAS fit now includes corrections to mitigate the impact of spectral misfits caused by scene brightness inhomogeneity and strong NO2 absorption. The product comes along with a full error characterization, which allows for providing random and systematic error estimates for every observation. Systematic errors are typically in the range of 1 ×1014–3 ×1014 molec. cm−2 (∼30 %–70 % in emission regimes) and originate mostly from a priori data uncertainties and spectral interferences with other absorbing species. The latter may be at the origin, at least partly, of an enhanced glyoxal signal over equatorial oceans, and further investigation is needed to mitigate them. Random errors are large (>6×1014 molec. cm−2) but can be reduced by averaging observations in space and/or time. Benefiting from a high signal-to-noise ratio and a large number of small-size observations, TROPOMI provides glyoxal tropospheric column fields with an unprecedented level of detail. Using the same retrieval algorithmic baseline, glyoxal column data sets are also generated from the Ozone Monitoring Instrument (OMI) on Aura and from the Global Ozone Monitoring Experiment-2 (GOME-2) on board Metop-A and Metop-B. Those four data sets are intercompared over large-scale regions worldwide and show a high level of consistency. The satellite glyoxal columns are also compared to glyoxal columns retrieved from ground-based Multi-AXis DOAS (MAX-DOAS) instruments at nine stations in Asia and Europe. In general, the satellite and MAX-DOAS instruments provide consistent glyoxal columns both in terms of absolute values and variability. Correlation coefficients between TROPOMI and MAX-DOAS glyoxal columns range between 0.61 and 0.87. The correlation is only poorer at one mid-latitude station, where satellite data appear to be biased low during wintertime. The mean absolute glyoxal columns from satellite and MAX-DOAS generally agree well for low/moderate columns with differences of less than 1×1014 molec. cm−2. A larger bias is identified at two sites where the MAX-DOAS columns are very large. Despite this systematic bias, the consistency of the satellite and MAX-DOAS glyoxal seasonal variability is high.

Highlights

  • Exposure to poor air quality kills millions of people annually (e.g. Vohra et al, 2021; World Health Organization, 2016) due to natural and human emissions of a large range of particulate matter and gases, including among others nitrous oxides (NOx), sulfur dioxide, carbon monoxide, methane and volatile organic compounds (VOCs)

  • Typical monthly-dependent a priori glyoxal vertical profile shapes necessary to perform the air mass factors (AMFs) computations have been calculated at the different satellite overpass times with the global chemical transport model MAGRITTE developed at BIRA-IASB, which inherits from the IMAGES model (Bauwens et al, 2016; Müller and Brasseur, 1995; Stavrakou et al, 2009b, 2013)

  • While the instrumental design of Global Ozone Monitoring Experiment-2 (GOME-2) makes it weakly sensitive to scene heterogeneity, it would be beneficial for Ozone Monitoring Instrument (OMI) to include similar cross-sections but that would imply a reprocessing of the complete slant column data set data with limited addedvalue for the large-scale comparison with TROPOspheric Monitoring Instrument (TROPOMI) that we present in the subsection

Read more

Summary

Introduction

Exposure to poor air quality kills millions of people annually (e.g. Vohra et al, 2021; World Health Organization, 2016) due to natural and human emissions of a large range of particulate matter and gases, including among others nitrous oxides (NOx), sulfur dioxide, carbon monoxide, methane and volatile organic compounds (VOCs). The first global glyoxal tropospheric column observations from space were realized by Wittrock et al (2006) using nadir measurements from the SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) instrument Based on this pioneering work, different glyoxal data products were derived from the Global Ozone Monitoring Experiment-2 (GOME-2) (Lerot et al, 2010; Vrekoussis et al, 2009) and from the Ozone Monitoring Instrument (OMI) (Alvarado et al, 2014; Chan Miller et al, 2014). With an enhanced spatial resolution resulting in a number of observations more than 10 times larger than provided by its predecessor OMI, the TROPOspheric Monitoring Instrument (TROPOMI), operating since 2017, allows for observing weak atmospheric absorbers with an unprecedented level of spatio-temporal detail This has been illustrated by Alvarado et al (2020a), who investigated the large amounts of formaldehyde and glyoxal emitted by the intense North American wildfires in August 2018 as observed by TROPOMI for several days and over long distances.

TROPOMI and other nadir-viewing satellite sensors
Description of the algorithm
DOAS fit
Scene heterogeneity
Empirical correction for strong NO2 absorption
Air mass factor computation
Background correction
Uncertainty estimates
Slant column uncertainties
AMF uncertainties
Background correction uncertainties
Total systematic uncertainties
Comparison with other satellite instruments
Comparison of the noise level
Comparison of mean glyoxal fields
Glyoxal over equatorial oceans
Description of MAX-DOAS data sets and methodology
Validation results
Findings
Conclusions
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call