An improved glyoxal retrieval from OMI measurements

Alvarado, Leonardo M. A.; Richter, Andreas; Vrekoussis, Mihalis; Wittrock, F.; Hilboll, Andreas; Schreier, Stefan F.; Burrows, J. P.

doi:10.5194/amt-7-4133-2014

Cited by 51 publications

(68 citation statements)

References 61 publications

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“…The increase in H 2 CO columns between 09:30 and 13:30 appears to be largest over southern Europe, southern Australia, north-eastern China or central Siberia, while an inverse diurnal variation, of equivalent magnitude, is observed over the equatorial forests of the Amazon, Africa and Indonesia. The same effect has been reported for glyoxal columns, another important indicator of NMVOC emissions (Alvarado et al, 2014). The observed diurnal variations will be further discussed in Sect.…”

Section: Continental Emission Regionssupporting

confidence: 55%

“…Since 2004, complementary early afternoon H 2 CO columns have also been available from the OMI imaging spectrometer on Aura Millet et al, 2008;González Abad et al, 2015a), and since 2011 from OMPS on SUOMI-NPP González Abad et al, 2015b). In addition to formaldehyde, glyoxal -another short-lived NMVOC -has also successfully been retrieved from SCIAMACHY (Wittrock et al, 2006), GOME-2 (Vrekoussis et al, 2010; Lerot et al, 2010) and OMI (Alvarado et al, 2014;Chan Miller et al, 2014).…”

Section: De Smedt Et Almentioning

confidence: 99%

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Diurnal, seasonal and long-term variations of global formaldehyde columns inferred from combined OMI and GOME-2 observations

et al. 2015

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Abstract. We present the new version (v14) of the BIRA-IASB algorithm for the retrieval of formaldehyde (H 2 CO) columns from spaceborne UV-visible sensors. Applied to OMI measurements from Aura and to GOME-2 measurements from MetOp-A and MetOp-B, this algorithm is used to produce global distributions of H 2 CO representative of midmorning and early afternoon conditions. Its main features include (1) a new iterative DOAS scheme involving three fitting intervals to better account for the O 2 -O 2 absorption, (2) the use of earthshine radiances averaged in the equatorial Pacific as reference spectra, and (3) a destriping correction and background normalisation resolved in the across-swath position. For the air mass factor calculation, a priori vertical profiles calculated by the IMAGES chemistry transport model at 09:30 and 13:30 LT are used. Although the resulting GOME-2 and OMI H 2 CO vertical columns are found to be highly correlated, some systematic differences are observed. Afternoon columns are generally larger than morning ones, especially in mid-latitude regions. In contrast, over tropical rainforests, morning H 2 CO columns significantly exceed those observed in the afternoon. These differences are discussed in terms of the H 2 CO column variation between mid-morning and early afternoon, using ground-based MAX-DOAS measurements available from seven stations in Europe, China and Africa. Validation results confirm the capacity of the combined satellite measurements to resolve diurnal variations in H 2 CO columns. Furthermore, vertical profiles derived from MAX-DOAS measurements in the Beijing area and in Bujumbura are used for a more detailed validation exercise. In both regions, we find an agreement better than 15 % when MAX-DOAS profiles are used as a priori for the satellite retrievals. Finally, regional trends in H 2 CO columns are estimated for the 2004-2014 period using SCIAMACHY and GOME-2 data for morning conditions, and OMI for early afternoon conditions. Consistent features are observed, such as an increase of the columns in India and central-eastern China, and a decrease in the eastern US and Europe. We find that the higher horizontal resolution of OMI combined with a better sampling and a more favourable illumination at midday allow for more significant trend estimates, especially over Europe and North America. Importantly, in some parts of the Amazonian forest, we observe with both time series a significant downward trend in H 2 CO columns, spatially correlated with areas affected by deforestation.

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Section: Continental Emission Regionssupporting

confidence: 55%

Section: De Smedt Et Almentioning

confidence: 99%

Diurnal, seasonal and long-term variations of global formaldehyde columns inferred from combined OMI and GOME-2 observations

et al. 2015

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“…An independent OMI CHOCHO retrieval by Alvarado et al (2014) is also systematically lower than SCIAMACHY. This calls for revisiting the interpretation of CHOCHO data from space.…”

Section: Chan Miller Et Al: Hotspot Of Glyoxal Over the Pearl Rivmentioning

confidence: 99%

Hotspot of glyoxal over the Pearl River delta seen from the OMI satellite instrument: implications for emissions of aromatic hydrocarbons

et al. 2016

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Abstract. The Pearl River delta (PRD) is a densely populated hub of industrial activity located in southern China. OMI (Ozone Monitoring Instrument) satellite observations reveal a large hotspot of glyoxal (CHOCHO) over the PRD that is almost twice as large as any other in Asia. Formaldehyde (HCHO) and NO 2 observed by OMI are also high in the PRD but no more than in other urban/industrial areas of China. The CHOCHO hotspot over the PRD can be explained by industrial paint and solvent emissions of aromatic volatile organic compounds (VOCs), with toluene being a dominant contributor. By contrast, HCHO in the PRD originates mostly from VOCs emitted by combustion (principally vehicles). By applying a plume transport model to wind-segregated OMI data, we show that the CHOCHO and HCHO enhancements over the PRD observed by OMI are consistent with current VOC emission inventories. Prior work using CHOCHO retrievals from the SCIAMACHY satellite instrument suggested that emission inventories for aromatic VOCs in the PRD were too low by a factor of 10-20; we attribute this result in part to bias in the SCIAMACHY data and in part to underestimated CHOCHO yields from oxidation of aromatics. Our work points to the importance of better understanding CHOCHO yields from the oxidation of aromatics in order to interpret space-based CHOCHO observations in polluted environments.

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“…Satellite observations of HCHO have been widely used as a proxy to estimate isoprene emissions (Abbot et al, 2003;Palmer et al, 2006;Millet et al, 2008;Curci et al, 2010;Barkley et al, 2013), but there are uncertainties related to the HCHO yield from isoprene oxidation (Marais et al, 2012) and the role of other NMVOCs as HCHO precursors (Fu et al, 2007). CHOCHO observations from space could provide a complementary constraint (Vrekoussis et al, 2009(Vrekoussis et al, , 2010Alvarado et al, 2014;Chan Miller et al, 2014). Here we use CHO-CHO and HCHO aircraft observations over the southeast US from the summer 2013 Southeast Nexus (SENEX) campaign , interpreted with the Goddard Earth Observing System chemical transport model (GEOSChem), to test understanding of the CHOCHO yield from isoprene oxidation, its dependence on nitrogen oxide radicals (NO x ≡ NO + NO 2 ), and the combined value of the CHOCHO-HCHO pair measured from space to constrain isoprene emissions and chemistry.…”

Section: Introductionmentioning

confidence: 99%

Glyoxal yield from isoprene oxidation and relation to formaldehyde: chemical mechanism, constraints from SENEX aircraft observations, and interpretation of OMI satellite data

et al. 2017

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Abstract. Glyoxal (CHOCHO) is produced in the atmosphere by the oxidation of volatile organic compounds (VOCs). Like formaldehyde (HCHO), another VOC oxidation product, it is measurable from space by solar backscatter. Isoprene emitted by vegetation is the dominant source of CHOCHO and HCHO in most of the world. We use aircraft observations of CHOCHO and HCHO from the SENEX campaign over the southeast US in summer 2013 to better understand the CHOCHO time-dependent yield from isoprene oxidation, its dependence on nitrogen oxides (NO x ≡ NO + NO 2 ), the behavior of the CHOCHO-HCHO relationship, the quality of OMI CHOCHO satellite observations, and the implications for using CHOCHO observations from space as constraints on isoprene emissions. We simulate the SENEX and OMI observations with the Goddard Earth Observing System chemical transport model (GEOSChem) featuring a new chemical mechanism for CHOCHO formation from isoprene. The mechanism includes prompt CHOCHO formation under low-NO x conditions following the isomerization of the isoprene peroxy radical (ISOPO 2 ). The SENEX observations provide support for this prompt CHOCHO formation pathway, and are generally consistent with the GEOS-Chem mechanism. Boundary layer CHO-CHO and HCHO are strongly correlated in the observations and the model, with some departure under low-NO x conditions due to prompt CHOCHO formation. SENEX vertical profiles indicate a free-tropospheric CHOCHO background that is absent from the model. The OMI CHOCHO data provide some support for this free-tropospheric background and show southeast US enhancements consistent with the isoPublished by Copernicus Publications on behalf of the European Geosciences Union. 8726 C. Chan Miller et al.: Glyoxal yield from isoprene prene source but a factor of 2 too low. Part of this OMI bias is due to excessive surface reflectivities assumed in the retrieval. The OMI CHOCHO and HCHO seasonal data over the southeast US are tightly correlated and provide redundant proxies of isoprene emissions. Higher temporal resolution in future geostationary satellite observations may enable detection of the prompt CHOCHO production under low-NO x conditions apparent in the SENEX data.

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An improved glyoxal retrieval from OMI measurements

Cited by 51 publications

References 61 publications

Diurnal, seasonal and long-term variations of global formaldehyde columns inferred from combined OMI and GOME-2 observations

Diurnal, seasonal and long-term variations of global formaldehyde columns inferred from combined OMI and GOME-2 observations

Hotspot of glyoxal over the Pearl River delta seen from the OMI satellite instrument: implications for emissions of aromatic hydrocarbons

Glyoxal yield from isoprene oxidation and relation to formaldehyde: chemical mechanism, constraints from SENEX aircraft observations, and interpretation of OMI satellite data

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