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Atmospheric deposition represents a major input of mercury to surface environments. The phase of mercury (gas or particle) has important implications for its removal from the atmosphere. We use long-term observations of reactive gaseous mercury (RGM), particle-bound mercury (PBM), fine particulate matter (PM2.5), and temperature at five sites in North America to derive an empirical gas-particle partitioning relationship log10(K-1) = (10 ± 1) − (2500 ± 300)/T where K = (PBM/PM2.5)/RGM with PBM and RGM in common mixing ratio units, PM2.5 in μg m−3, and T in Kelvin. This relationship is in the range of previous work but is based on far more extensive data from multiple sites. We implement this empirical relationship in the GEOS-Chem global 3-D Hg model to partition divalent mercury (Hg(II)). The resulting gas-phase fraction of Hg(II) ranges from over 90% in warm air with little aerosol to less than 10% in cold air with high aerosol. Hg deposition to high latitudes increases because of more efficient scavenging of particulate Hg(II) by snow. Model comparison to Hg observations at surface sites suggests that subsidence from the free troposphere (warm air, low aerosol) is a major factor driving the seasonality of RGM, while elevated PBM is mostly associated with high aerosol loads. This and other model updates, including the correction of an outstanding algorithm error, to wet deposition improve the simulation of Hg wet deposition fluxes in the US relative to the previous version of the model. The observed wintertime minimum in wet deposition fluxes is attributed to inefficient snow scavenging of gas-phase Hg(II).

We use GEOS-Chem chemical transport model simulations of sulfate–ammonium aerosol data from the NASA ARCTAS and NOAA ARCPAC aircraft campaigns in the North American Arctic in April 2008, together with longer-term data from surface sites, to better understand aerosol sources in the Arctic in winter–spring and the implications for aerosol acidity. Arctic pollution is dominated by transport from mid-latitudes, and we test the relevant ammonia and sulfur dioxide emission inventories in the model by comparison with wet deposition flux data over the source continents. We find that a complicated mix of natural and anthropogenic sources with different vertical signatures is responsible for sulfate concentrations in the Arctic. East Asian pollution influence is weak in winter but becomes important in spring through transport in the free troposphere. European influence is important at all altitudes but never dominant. West Asia (non-Arctic Russia and Kazakhstan) is the largest contributor to Arctic sulfate in surface air in winter, reflecting a southward extension of the Arctic front over that region. Ammonium in Arctic spring mostly originates from anthropogenic sources in East Asia and Europe, with added contribution from boreal fires, resulting in a more neutralized aerosol in the free troposphere than at the surface. The ARCTAS and ARCPAC data indicate a median aerosol neutralization fraction [NH4+]/(2[SO42−] + [NO3−]) of 0.5 mol mol−1 below 2 km and 0.7 mol mol−1 above. We find that East Asian and European aerosol transported to the Arctic is mostly neutralized, whereas West Asian and North American aerosol is highly acidic. Growth of sulfur emissions in West Asia may be responsible for the observed increase in aerosol acidity at Barrow over the past decade. As global sulfur emissions decline over the next decades, increasing aerosol neutralization in the Arctic is expected, potentially accelerating Arctic warming through indirect radiative forcing and feedbacks.

We combine CO column measurements from the MOPITT, AIRS, SCIAMACHY, and TES satellite instruments in a full-year (May 2004–April 2005) global inversion of CO sources at 4◦ ×5◦ spatial resolution and monthly temporal resolution. The inversion uses the GEOS-Chem chemical transport model (CTM) and its adjoint applied to MOPITT, AIRS, and SCIAMACHY. Observations from TES, surface sites (NOAA/GMD), and aircraft (MOZAIC) are used for evaluation of the a posteriori solution. Using GEOSChem as a common intercomparison platform shows global consistency between the different satellite datasets and with the in situ data. Differences can be largely explained by different averaging kernels and a priori information. The global CO emission from combustion as constrained in the inversion is 1350 Tg a−1 . This is much higher than current bottomup emission inventories. A large fraction of the correction results from a seasonal underestimate of CO sources at northern mid-latitudes in winter and suggests a larger-thanexpected CO source from vehicle cold starts and residential heating. Implementing this seasonal variation of emissions solves the long-standing problem of models underestimating CO in the northern extratropics in winter-spring. A posteriori emissions also indicate a general underestimation of biomass burning in the GFED2 inventory. However, the tropical biomass burning constraints are not quantitatively consistent across the different datasets.

We use observations from the April 2008 NASA ARCTAS aircraft campaign to the North American Arctic, interpreted with a global 3-D chemical transport model (GEOS-Chem), to better understand the sources and cycling of hydrogen oxide radicals (HOx≡H+OH+peroxy radicals) and their reservoirs (HOy≡HOx+peroxides) in the springtime Arctic atmosphere. We find that a standard gas-phase chemical mechanism overestimates the observed HO2 and H2O2 concentrations. Computation of HOx and HOy gas-phase chemical budgets on the basis of the aircraft observations also indicates a large missing sink for both. We hypothesize that this could reflect HO2 uptake by aerosols, favored by low temperatures and relatively high aerosol loadings, through a mechanism that does not produce H2O2. We implemented such an uptake of HO2 by aerosol in the model using a standard reactive uptake coefficient parameterization with γ(HO2) values ranging from 0.02 at 275 K to 0.5 at 220 K. This successfully reproduces the concentrations and vertical distributions of the different HOx species and HOy reservoirs. HO2 uptake by aerosol is then a major HOx and HOy sink, decreasing mean OH and HO2 concentrations in the Arctic troposphere by 32% and 31% respectively. Better rate and product data for HO2 uptake by aerosol are needed to understand this role of aerosols in limiting the oxidizing power of the Arctic atmosphere.

We combine CO column measurements from the MOPITT, AIRS, SCIAMACHY, and TES satellite instruments in a full-year (May 2004-April 2005) global inversion of CO sources at 4 degrees x 5 degrees spatial resolution and monthly temporal resolution. The inversion uses the GEOS-Chem chemical transport model (CTM) and its adjoint applied to MOPITT, AIRS, and SCIAMACHY. Observations from TES, surface sites (NOAA/GMD), and aircraft (MOZAIC) are used for evaluation of the a posteriori solution. Using GEOS-Chem as a common intercomparison platform shows global consistency between the different satellite datasets and with the in situ data. Differences can be largely explained by different averaging kernels and a priori information. The global CO emission from combustion as constrained in the inversion is 1350 Tg a(-1). This is much higher than current bottom-up emission inventories. A large fraction of the correction results from a seasonal underestimate of CO sources at northern mid-latitudes in winter and suggests a larger-than-expected CO source from vehicle cold starts and residential heating. Implementing this seasonal variation of emissions solves the long-standing problem of models underestimating CO in the northern extratropics in winter-spring. A posteriori emissions also indicate a general underestimation of biomass burning in the GFED2 inventory. However, the tropical biomass burning constraints are not quantitatively consistent across the different datasets.

We use aircraft observations of carbon monoxide (CO) from the NASA ARCTAS and NOAA ARCPAC campaigns in April 2008 together with multiyear (2003– 2008) CO satellite data from the AIRS instrument and a global chemical transport model (GEOS-Chem) to better understand the sources, transport, and interannual variability of pollution in the Arctic in spring. Model simulation of the aircraft data gives best estimates of CO emissions in April 2008 of 26 Tg month−1 for Asian anthropogenic, 9.4 for European anthropogenic, 4.1 for North American anthropogenic, 15 for Russian biomass burning (anomalously large that year), and 23 for Southeast Asian biomass burning. We find that Asian anthropogenic emissions are the dominant source of Arctic CO pollution everywhere except in surface air where European anthropogenic emissions are of similar importance. Russian biomass burning makes little contribution to mean CO (reflecting the long CO lifetime) but makes a large contribution to CO variability in the form of combustion plumes. Analysis of two pollution events sampled by the aircraft demonstrates that AIRS can successfully observe pollution transport to the Arctic in the mid-troposphere. The 2003–2008 record of CO from AIRS shows that interannual variability averaged over the Arctic cap is very small. AIRS CO columns over Alaska are highly correlated with the Ocean Niño Index, suggesting a link between El Niño and Asian pollution transport to the Arctic. AIRS shows lowerthan-average CO columns over Alaska during April 2008, despite the Russian fires, due to a weakened Aleutian Low hindering transport from Asia and associated with the moderate 2007–2008 La Niña. This suggests that Asian pollution influence over the Arctic may be particularly large under strong El Niño conditions.

We combine CO column measurements from the MOPITT, AIRS, SCIAMACHY, and TES satellite instruments in a full-year (May 2004-April 2005) global inversion of CO sources at 4 degrees x 5 degrees spatial resolution and monthly temporal resolution. The inversion uses the GEOS-Chem chemical transport model (CTM) and its adjoint applied to MOPITT, AIRS, and SCIAMACHY. Observations from TES, surface sites (NOAA/GMD), and aircraft (MOZAIC) are used for evaluation of the a posteriori solution. Using GEOS-Chem as a common intercomparison platform shows global consistency between the different satellite datasets and with the in situ data. Differences can be largely explained by different averaging kernels and a priori information. The global CO emission from combustion as constrained in the inversion is 1350 Tg a(-1). This is much higher than current bottom-up emission inventories. A large fraction of the correction results from a seasonal underestimate of CO sources at northern mid-latitudes in winter and suggests a larger-than-expected CO source from vehicle cold starts and residential heating. Implementing this seasonal variation of emissions solves the long-standing problem of models underestimating CO in the northern extratropics in winter-spring. A posteriori emissions also indicate a general underestimation of biomass burning in the GFED2 inventory. However, the tropical biomass burning constraints are not quantitatively consistent across the different datasets.

We present a model study of carbon monoxide for 1988-1997 using the GEOS-Chem 3-D model driven by assimilated meteorological data, with time-varying emissions from biomass burning and from fossil fuel and industry, overhead ozone columns, and methane. The hydroxyl radical is calculated interactively using a chemical parameterization to capture chemical feedbacks. We document the inventory for fossil fuels/industry and discuss major uncertainties and the causes of differences with other inventories that give significantly lower emissions. We find that emissions hardly change from 1988 to 1997, as increases in Asia are offset by decreases elsewhere. The model reproduces the 20% decrease in CO at high northern latitudes and the 10% decrease in the North Pacific, caused primarily by the decrease in European emissions. The model compares well with observations at sites impacted by fossil fuel emissions from North America, Europe, and east Asia suggesting that the emissions from this source are reliable to 25%, and we argue that bottom-up emission estimates are likely to be too low rather than too high. The model is too low at the seasonal maximum in spring in the southern tropics, except for locations in the Atlantic Ocean. This problem may be caused by an overestimate of the frequency of tropical deep convection, a common problem in models that use assimilated meteorological data. We argue that the yield of CO from methane oxidation is near unity, contrary to some other studies, based on removal rates of intermediate species.