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.

Severe surface ozone pollution over major Chinese cities has become an emerging air quality concern, raising a new challenge for emission control measures in China. In this study, we explore the source contributions to surface daily maximum 8 h average (MDA8) ozone over China in 2016 and 2017, the 2 years with the highest surface ozone averaged over Chinese cities in record. We estimate the contributions of anthropogenic, background, and individual natural sources to surface ozone over China using the GEOS-Chem chemical transport model at $\mathrm{0.25}{}^{\circ }\times \mathrm{0.3125}{}^{\circ }$ horizontal resolution with the most up-to-date Chinese anthropogenic emission inventory. Model results are evaluated with concurrent surface ozone measurements at 169 cities over China and show generally good agreement. We find that background ozone (defined as ozone that would be present in the absence of all Chinese anthropogenic emissions) accounts for 90 % (49.4 ppbv) of the national March–April mean surface MDA8 ozone over China and 80 % (44.5 ppbv) for May–August. It includes large contributions from natural sources (80 % in March–April and 72 % in May–August). Among them, biogenic volatile organic compound (BVOC) emissions enhance MDA8 ozone by more than 15 ppbv in eastern China during July–August, while lightning NO_x emissions and ozone transport from the stratosphere both lead to ozone enhancements of over 20 ppbv in western China during March–April. Over major Chinese city clusters, domestic anthropogenic sources account for about 30 % of the May–August mean surface MDA8 ozone and reach 39–73 ppbv (38 %–69 %) for days with simulated MDA8 ozone > 100 ppbv in the North China Plain, Fenwei Plain, Yangtze River Delta, and Pearl River Delta city clusters. These high ozone episodes are usually associated with high temperatures, which induce large BVOC emissions and enhance ozone chemical production. Our results indicate that there would be no days with MDA8 ozone > 80 ppbv in these major Chinese cities in the absence of domestic anthropogenic emissions. We find that the 2017 ozone increases relative to 2016 are largely due to higher background ozone driven by hotter and drier weather conditions, while changes in domestic anthropogenic emissions alone would have led to ozone decreases in 2017. Meteorological conditions in 2017 favor natural source contributions (particularly soil NO_x and BVOC ozone enhancements) and ozone chemical production, increase the thermal decomposition of peroxyacetyl nitrate (PAN), and further decrease ozone dry deposition velocity. More stringent emission control measures are thus required to offset the adverse effects of unfavorable meteorology, such as high temperature, on surface ozone air quality.

Formation of SOA from the aromatic species toluene, xylene, and, for the first time, benzene, is added to a global chemical transport model. A simple mechanism is presented that accounts for competition between low and high-yield pathways of SOA formation, wherein secondary gas-phase products react further with either nitric oxide (NO) or hydroperoxy radical (HO₂) to yield semi- or non-volatile products, respectively. Aromatic species yield more SOA when they react with OH in regions where the [NO]/[HO₂] ratios are lower. The SOA yield thus depends upon the distribution of aromatic emissions, with biomass burning emissions being in areas with lower [NO]/[HO₂] ratios, and the reactivity of the aromatic with respect to OH, as a lower initial reactivity allows transport away from industrial source regions, where [NO]/[HO₂] ratios are higher, to more remote regions, where this ratio is lower and, hence, the ultimate yield of SOA is higher. As a result, benzene is estimated to be the most important aromatic species with regards to global formation of SOA, with a total production nearly equal that of toluene and xylene combined. Global production of SOA from aromatic sources via the mechanisms identified here is estimated at 3.5 Tg/yr, resulting in a global burden of 0.08 Tg, twice as large as previous estimates. The contribution of these largely anthropogenic sources to global SOA is still small relative to biogenic sources, which are estimated to comprise 90% of the global SOA burden, about half of which comes from isoprene. Uncertainty in these estimates owing to factors ranging from the atmospheric relevance of chamber conditions to model deficiencies result in an estimated range of SOA production from aromatics of 2–12 Tg/yr. Though this uncertainty range affords a significant anthropogenic contribution to global SOA, it is evident from comparisons to recent observations that additional pathways for production of anthropogenic SOA still exist beyond those accounted for here. Nevertheless, owing to differences in spatial distributions of sources and seasons of peak production, regions exist in which aromatic SOA produced via the mechanisms identified here are predicted to contribute substantially to, and even dominate, the local SOA concentrations, such as outflow regions from North America and South East Asia during the wintertime, though total modeled SOA concentrations there are small (~0.1 μg/m³).

Space‐borne formaldehyde (HCHO) column measurements from the Ozone Monitoring Instrument (OMI), with 13 × 24 km² nadir footprint and daily global coverage, provide new constraints on the spatial distribution of biogenic isoprene emission from North America. OMI HCHO columns for June‐August 2006 are consistent with measurements from the earlier GOME satellite sensor (1996–2001) but OMI is 2–14% lower. The spatial distribution of OMI HCHO columns follows that of isoprene emission; anthropogenic hydrocarbon emissions are undetectable except in Houston. We develop updated relationships between HCHO columns and isoprene emission from a chemical transport model (GEOS‐Chem), and use these to infer top‐down constraints on isoprene emissions from the OMI data. We compare the OMI‐derived emissions to a state‐of‐science bottom‐up isoprene emission inventory (MEGAN) driven by two land cover databases, and use the results to optimize the MEGAN emission factors (EFs) for broadleaf trees (the main isoprene source). The OMI‐derived isoprene emissions in North America (June–August 2006) with 1° × 1° resolution are spatially consistent with MEGAN (R² = 0.48–0.68) but are lower (by 4–25% on average). MEGAN overestimates emissions in the Ozarks and the Upper South. A better fit to OMI (R² = 0.73) is obtained in MEGAN by using a uniform isoprene EF from broadleaf trees rather than variable EFs. Thus MEGAN may overestimate emissions in areas where it specifies particularly high EFs. Within‐canopy isoprene oxidation may also lead to significant differences between the effective isoprene emission to the atmosphere seen by OMI and the actual isoprene emission determined by MEGAN.

Quantifying isoprene emissions using satellite observations of the formaldehyde (HCHO) columns is subject to errors involving the column retrieval and the assumed relationship between HCHO columns and isoprene emissions, taken here from the GEOS‐CHEM chemical transport model. Here we use a 6‐year (1996–2001) HCHO column data set from the Global Ozone Monitoring Experiment (GOME) satellite instrument to (1) quantify these errors, (2) evaluate GOME‐derived isoprene emissions with in situ flux measurements and a process‐based emission inventory (Model of Emissions of Gases and Aerosols from Nature, MEGAN), and (3) investigate the factors driving the seasonal and interannual variability of North American isoprene emissions. The error in the GOME HCHO column retrieval is estimated to be 40%. We use the Master Chemical Mechanism (MCM) to quantify the time‐dependent HCHO production from isoprene, α‐ and β‐pinenes, and methylbutenol and show that only emissions of isoprene are detectable by GOME. The time‐dependent HCHO yield from isoprene oxidation calculated by MCM is 20–30% larger than in GEOS‐CHEM. GOME‐derived isoprene fluxes track the observed seasonal variation of in situ measurements at a Michigan forest site with a −30% bias. The seasonal variation of North American isoprene emissions during 2001 inferred from GOME is similar to MEGAN, with GOME emissions typically 25% higher (lower) at the beginning (end) of the growing season. GOME and MEGAN both show a maximum over the southeastern United States, but they differ in the precise location. The observed interannual variability of this maximum is 20–30%, depending on month. The MEGAN isoprene emission dependence on surface air temperature explains 75% of the month‐to‐month variability in GOME‐derived isoprene emissions over the southeastern United States during May–September 1996–2001.

We use a continuous 6‐year record (1996–2001) of GOME satellite measurements of formaldehyde (HCHO) columns over east and south Asia to improve regional emission estimates of reactive nonmethane volatile organic compounds (NMVOCs), including isoprene, alkenes, HCHO, and xylenes. Mean monthly HCHO observations are compared to simulated HCHO columns from the GEOS‐Chem chemical transport model using state‐of‐science, “bottom‐up” emission inventories from Streets et al. (2003a) for anthropogenic and biomass burning emissions and Guenther et al. (2006) for biogenic emissions (MEGAN). We find that wintertime GOME observations can diagnose anthropogenic reactive NMVOC emissions from China, leading to an estimate 25% higher than Streets et al. (2003a). We attribute the difference to vehicular emissions. The biomass burning source for east and south Asia is almost 5 times the estimate of Streets et al. (2003a). GOME reveals a large source from agricultural burning in the North China Plain in June missing from current inventories. This source may reflect a recent trend toward in‐field burning of crop residues as the need for biofuels diminishes. Biogenic isoprene emission in east and south Asia derived from GOME is 56 ± 30 Tg yr⁻¹, similar to 52 Tg yr⁻¹ from MEGAN. We find, however, that MEGAN underestimates emissions in China and overestimates emissions in the tropics. The higher Chinese biogenic and biomass burning emissions revealed by GOME have important implications for ozone pollution. We find 5 to 20 ppb seasonal increases in surface ozone in GEOS‐Chem for central and northern China when using GOME‐derived versus bottom‐up emissions. Our methodology can be adapted for other regions of the world to provide top‐down constraints on NMVOC emissions where multiple emission source types overlap in space and time.