Anthropogenic mercury emissions are transported through the atmosphere as gaseous elemental mercury (Hg(0)) prior to deposition to Earth's surface. Strong seasonality in atmospheric Hg(0) concentrations in the Northern Hemisphere has been explained by two factors: anthropogenic Hg(0) emissions are thought to peak in winter due to higher energy consumption, and atmospheric oxidation rates of Hg(0) are faster in summer. Oxidationdriven Hg(0) seasonality should be equally pronounced in the Southern Hemisphere, which is inconsistent with observations of constant year-round Hg(0) levels. Here, we assess the role of Hg(0) uptake by vegetation as an alternative mechanism for driving Hg(0) seasonality. We find that at terrestrial sites in the Northern Hemisphere, Hg(0) co-varies with CO2, which is

The vertical allocation of emissions has a major impact on results of Chemistry Transport Models. However, in Europe it is still common to use fixed vertical profiles based on rough estimates to determine the emission height of point sources. This publication introduces a set of new vertical profiles for the use in chemistry transport modeling that were created from hourly gridded emissions calculated by the SMOKE for Europe emission model. SMOKE uses plume rise calculations to determine effective emission heights. Out of more than 40 000 different vertical emission profiles 73 have been chosen by means of hierarchical cluster analysis. These profiles show large differences to those currently used in many emission models. Emissions from combustion processes are released in much lower altitudes while those from production processes are allocated to higher altitudes. The profiles have a high temporal and spatial variability which is not represented by currently used profiles.

Mercury (Hg), a global contaminant, is emitted mainly in its elemental form Hg0 to the atmosphere where it is oxidized to reactive HgII compounds, which efficiently deposit to surface ecosystems. Therefore, the chemical cycling between the elemental and oxidized Hg forms in the atmosphere determines the scale and geographical pattern of global Hg deposition. Recent advances in the photochemistry of gas-phase oxidized HgI and HgII species postulate their photodissociation back to Hg0 as a crucial step in the atmospheric Hg redox cycle. However, the significance of these photodissociation mechanisms on atmospheric Hg chemistry, lifetime, and surface deposition remains uncertain. Here we implement a comprehensive and quantitative mechanism of the photochemical and thermal atmospheric reactions between Hg0, HgI, and HgII species in a global model and evaluate the results against atmospheric Hg observations. We find that the photochemistry of HgI and HgII leads to insufficient Hg oxidation globally. The combined efficient photoreduction of HgI and HgII to Hg0 competes with thermal oxidation of Hg0, resulting in a large model overestimation of 99% of measured Hg0 and underestimation of 51% of oxidized Hg and ∼66% of HgII wet deposition. This in turn leads to a significant increase in the calculated global atmospheric Hg lifetime of 20 mo, which is unrealistically longer than the 3–6-mo range based on observed atmospheric Hg variability. These results show that the HgI and HgII photoreduction processes largely offset the efficiency of bromine-initiated Hg0 oxidation and reveal missing Hg oxidation processes in the troposphere.

Abstract. The EURODELTA III exercise has facilitated a comprehensive intercomparison and evaluation of chemistry transport model performances. Participating models performed calculations for four 1-month periods in different seasons in the years 2006 to 2009, allowing the influence of different meteorological conditions on model performances to be evaluated. The exercise was performed with strict requirements for the input data, with few exceptions. As a consequence, most of differences in the outputs will be attributed to the differences in model formulations of chemical and physical processes. The models were evaluated mainly for background rural stations in Europe. The performance was assessed in terms of bias, root mean square error and correlation with respect to the concentrations of air pollutants (NO2, O3, SO2, PM10 and PM2.5), as well as key meteorological variables. Though most of meteorological parameters were prescribed, some variables like the planetary boundary layer (PBL) height and the vertical diffusion coefficient were derived in the model preprocessors and can partly explain the spread in model results. In general, the daytime PBL height is underestimated by all models. The largest variability of predicted PBL is observed over the ocean and seas. For ozone, this study shows the importance of proper boundary conditions for accurate model calculations and then on the regime of the gas and particle chemistry. The models show similar and quite good performance for nitrogen dioxide, whereas they struggle to accurately reproduce measured sulfur dioxide concentrations (for which the agreement with observations is the poorest). In general, the models provide a close-to-observations map of particulate matter (PM2.5 and PM10) concentrations over Europe rather with correlations in the range 0.4–0.7 and a systematic underestimation reaching −10 µg m−3 for PM10. The highest concentrations are much more underestimated, particularly in wintertime. Further evaluation of the mean diurnal cycles of PM reveals a general model tendency to overestimate the effect of the PBL height rise on PM levels in the morning, while the intensity of afternoon chemistry leads formation of secondary species to be underestimated. This results in larger modelled PM diurnal variations than the observations for all seasons. The models tend to be too sensitive to the daily variation of the PBL. All in all, in most cases model performances are more influenced by the model setup than the season. The good representation of temporal evolution of wind speed is the most responsible for models' skillfulness in reproducing the daily variability of pollutant concentrations (e.g. the development of peak episodes), while the reconstruction of the PBL diurnal cycle seems to play a larger role in driving the corresponding pollutant diurnal cycle and hence determines the presence of systematic positive and negative biases detectable on daily basis.