We construct global budgets of atmospheric glyoxal and methylglyoxal with the goal of quantifying their potential for global secondary organic aerosol (SOA) formation via irreversible uptake by aqueous aerosols and clouds. We conduct a detailed simulation of glyoxal and methylglyoxal in the GEOS‐Chem global 3‐D chemical transport model including our best knowledge of source and sink processes. Our resulting best estimates of the global sources of glyoxal and methylglyoxal are 45 Tg a⁻¹ and 140 Tg a⁻¹, respectively. Oxidation of biogenic isoprene contributes globally 47% of glyoxal and 79% of methylglyoxal. The second most important precursors are acetylene (mostly anthropogenic) for glyoxal and acetone (mostly biogenic) for methylglyoxal. Both acetylene and acetone have long lifetimes and provide a source of dicarbonyls in the free troposphere. Atmospheric lifetimes of glyoxal and methylglyoxal in the model are 2.9 h and 1.6 h, respectively, mostly determined by photolysis. Simulated dicarbonyl concentrations in continental surface air at northern midlatitudes are in the range 10–100 ppt, consistent with in situ measurements. On a global scale, the highest concentrations are over biomass burning regions, in agreement with glyoxal column observations from the SCIAMACHY satellite instrument. SCIAMACHY and a few ship cruises also suggest a large marine source of dicarbonyls missing from our model. The global source of SOA from the irreversible uptake of dicarbonyls in GEOS‐Chem is 11 Tg C a⁻¹, including 2.6 Tg C a⁻¹ from glyoxal and 8 Tg C a⁻¹ from methylglyoxal; 90% of this source takes place in clouds. The magnitude of the global SOA source from dicarbonyls is comparable to that computed in GEOS‐Chem from the standard mechanism involving reversible partitioning of semivolatile products from the oxidation of monoterpenes, sesquiterpenes, isoprene, and aromatics.

The first global simultaneous observations of glyoxal (CHOCHO) and formaldehyde (HCHO) columns retrieved from measurements by the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) satellite instrument are presented and compared to model calculations. The global pattern of the distribution of CHOCHO is similar to that of HCHO. High values are observed over areas with large biogenic isoprene emissions (Central Africa, parts of South America, and Indonesia). Also regions with biomass burning and anthropogenic pollution exhibit elevated levels of CHOCHO. The ratio of the columns of CHOCHO to HCHO is generally of the order of 0.05 in regions having biogenic emissions, which is in reasonable agreement with the current understanding of the oxidation of hydrocarbons emitted by the biosphere. However and in contrast to our model, high values of both HCHO and CHOCHO are also observed over areas of the tropical oceans. This is tentatively attributed to outflow from the continents and local oceanic biogenic sources of the precursors of HCHO and CHOCHO.

Measurements from the Global Ozone Monitoring Experiment GOME have been analysed for tropospheric BrO in the northern hemispheric spring and summer 1997. Tropospheric excess columns have been determined by subtracting measurements from a longitude range which is assumed to represent background conditions. From February until the end of May enhanced tropospheric BrO columns are observed over the Hudson Bay area and parts of the Canadian Arctic. This large and persistent event has not been reported before and can only be explained by a large local source of bromine. In addition, from March to May other smaller and shorter tropospheric BrO events are detectable along the coast lines of the Arctic Sea and over the polar ice. They correspond to the ground‐based observations of enhanced tropospheric BrO reported from several stations in the high Arctic.

A new approach to derive tropospheric concentrations of some atmospheric trace gases from ground-based UV/vis measurements is described. The instrument, referred to as the MAX-DOAS, is based on the well-known UV/vis instruments, which use the sunlight scattered in the zenith sky as the light source and the method of Differential Optical Absorption Spectroscopy (DOAS) to derive column amounts of absorbers like ozone and nitrogen dioxide. Substantial enhancements have been applied to this standard setup to use different lines of sight near to the horizon as additional light sources (MAX - multi axis). Results from measurements at Ny-Ålesund (79° N, 12° E) are presented and interpreted with the full-spherical radiative transfer model SCIATRAN. In particular, measurements of the oxygen dimer O₄ which has a known column and vertical distribution in the atmosphere are used to evaluate the sensitivity of the retrieval to parameters such as multiple scattering, solar azimuth, surface albedo and refraction in the atmosphere and also to validate the radiative transfer model. As a first application, measurements of NO₂ emissions from a ship lying in Ny-Ålesund harbour are presented. The results of this study demonstrate the feasibility of long term UV/vis multi axis measurement that can be used to derive not only column amounts of different trace gases but also some information on the vertical location of these absorbers.

We review the standard nitrogen dioxide (NO₂) data product (Version 1.0.), which is based on measurements made in the spectral region 415–465 nm by the Ozone Monitoring Instrument (OMI) on the NASA Earth Observing System‐Aura satellite. A number of ground‐ and aircraft‐based measurements have been used to validate the data product's three principal quantities: stratospheric, tropospheric, and total NO₂ column densities under nearly or completely cloud‐free conditions. The validation of OMI NO₂ is complicated by a number of factors, the greatest of which is that the OMI observations effectively average the NO₂ over its field of view (minimum 340 km²), while a ground‐based instrument samples at a single point. The tropospheric NO₂ field is often very inhomogeneous, varying significantly over tens to hundreds of meters, and ranges from 10¹⁶ cm⁻² over urban and industrial areas. Because of OMI's areal averaging, when validation measurements are made near NO₂ sources the OMI measurements are expected to underestimate the ground‐based, and this is indeed seen. Further, we use several different instruments, both new and mature, which might give inconsistent NO₂ amounts; the correlations between nearby instruments is 0.8–0.9. Finally, many of the validation data sets are quite small and span a very short length of time; this limits the statistical conclusions that can be drawn from them. Despite these factors, good agreement is generally seen between the OMI and ground‐based measurements, with OMI stratospheric NO₂ underestimated by about 14% and total and tropospheric columns underestimated by 15–30%. Typical correlations between OMI NO₂ and ground‐based measurements are generally >0.6.