Abstract. Biogenic NOx emissions from soils are a large natural source with substantial uncertainties in global bottom-up estimates (ranging from 4 to 15 Tg N yr−1). We reduce this range in emission estimates, and present a top-down soil NOx emission inventory for 2005 based on retrieved tropospheric NO2 columns from the Ozone Monitoring Instrument (OMI). We use a state-of-science soil NOx emission inventory (Hudman et al., 2012) as a priori in the GEOS-Chem chemistry transport model to identify 11 regions where tropospheric NO2 columns are dominated by soil NOx emissions. Strong correlations between soil NOx emissions and simulated NO2 columns indicate that spatial patterns in simulated NO2 columns in these regions indeed reflect the underlying soil NOx emissions. Subsequently, we use a mass-balance approach to constrain emissions for these 11 regions on all major continents using OMI observed and GEOS-Chem simulated tropospheric NO2 columns. We find that responses of simulated NO2 columns to changing NOx emissions are suppressed over low NOx regions, and account for these non-linearities in our inversion approach. In general, our approach suggests that emissions need to be increased in most regions. Our OMI top-down soil NOx inventory amounts to 10.0 Tg N for 2005 when only constraining the 11 regions, and 12.9 Tg N when extrapolating the constraints globally. Substantial regional differences exist (ranging from −40% to +90%), and globally our top-down inventory is 4–35% higher than the GEOS-Chem a priori (9.6 Tg N yr−1). We evaluate NO2 concentrations simulated with our new OMI top-down inventory against surface NO2 measurements from monitoring stations in Africa, the USA and Europe. Although this comparison is complicated by several factors, we find an encouraging improved agreement when using the OMI top-down inventory compared to using the a priori inventory. To our knowledge, this study provides, for the first time, specific constraints on soil NOx emissions on all major continents using OMI NO2 columns. Our results rule out the low end of reported soil NOx emission estimates, and suggest that global emissions are most likely around 12.9 ± 3.9 Tg N yr−1.

Abstract. We present a computationally efficient approach to account for the non-linear chemistry occurring during the dispersion of ship exhaust plumes in a global 3-D model of atmospheric chemistry (GEOS-Chem). We use a plume-ingrid formulation where ship emissions age chemically for 5 h before being released in the global model grid. Besides reducing the original ship NO x emissions in GEOS-Chem, our approach also releases the secondary compounds ozone and HNO 3 , produced during the 5 h after the original emissions, into the model. We applied our improved method and also the widely used "instant dilution" approach to a 1-yr GEOS-Chem simulation of global tropospheric ozone-NO x -VOC-aerosol chemistry. We also ran simulations with the standard model (emitting 10 molecules O 3 and 1 molecule HNO 3 per ship NO x molecule), and a model without any ship emissions at all. The model without any ship emissions simulates up to 0.1 ppbv (or 50 %) lower NO x concentrations over the North Atlantic in July than our improved GEOS-Chem model. "Instant dilution" overestimates NO x concentrations by 0.1 ppbv (50 %) and ozone by 3-5 ppbv (10-25 %), compared to our improved model over this region. These conclusions are supported by comparing simulated and observed NO x and ozone concentrations in the lower troposphere over the Pacific Ocean. The comparisons show that the improved GEOS-Chem model simulates NO x concentrations in between the instant dilution model and the model without ship emissions, which results in lower O 3 conCorrespondence to: G. C. M. Vinken (g.c.m.vinken@tue.nl) centrations than the instant dilution model. The relative differences in simulated NO x and ozone between our improved approach and instant dilution are smallest over strongly polluted seas (e.g. North Sea), suggesting that accounting for inplume chemistry is most relevant for pristine marine areas.

Abstract. We present a top-down ship NO x emission inventory for the Baltic Sea, the North Sea, the Bay of Biscay and the Mediterranean Sea based on satellite-observed tropospheric NO 2 columns of the Ozone Monitoring Instrument (OMI) for [2005][2006]. We improved the representation of ship emissions in the GEOS-Chem chemistry transport model, and compared simulated NO 2 columns to consistent satellite observations. Relative differences between simulated and observed NO 2 columns have been used to constrain ship emissions in four European seas (the Baltic Sea, the North Sea, the Bay of Biscay and the Mediterranean Sea) using a mass-balance approach, and accounting for nonlinear sensitivities to changing emissions in both model and satellite retrieval. These constraints are applied to 39 % of total top-down European ship NO x emissions, which amount to 0.96 Tg N for 2005, and 1.0 Tg N for 2006 (11-15 % lower than the bottom-up EMEP ship emission inventory). Our results indicate that EMEP emissions in the Mediterranean Sea are too high (by 60 %) and misplaced by up to 150 km, which can have important consequences for local air quality simulations. In the North Sea ship track, our top-down emissions amount to 0.05 Tg N for 2005 (35 % lower than EMEP). Increased top-down emissions were found for the Baltic Sea and the Bay of Biscay ship tracks, with totals in these tracks of 0.05 Tg N (131 % higher than EMEP) and 0.08 Tg N for 2005 (128 % higher than EMEP), respectively. Our study explicitly accounts for the (non-linear) sensitivity of satellite retrievals to changes in the a priori NO 2 profiles, as satellite observations are never fully independent of model information (i.e. assumptions on vertical NO 2 profiles). Our study provides for the first time a space-based, top-down ship NO x emission inventory, and can serve as a framework for future studies to constrain ship emissions using satellite NO 2 observations in other seas.

Abstract. Ultraviolet–visible (UV–Vis) satellite retrievals of trace gas columns of nitrogen dioxide (NO2), sulfur dioxide (SO2), and formaldehyde (HCHO) are useful to test and improve models of atmospheric composition, for data assimilation, air quality hindcasting and forecasting, and to provide top-down constraints on emissions. However, because models and satellite measurements do not represent the exact same geophysical quantities, the process of confronting model fields with satellite measurements is complicated by representativeness errors, which degrade the quality of the comparison beyond contributions from modelling and measurement errors alone. Here we discuss three types of representativeness errors that arise from the act of carrying out a model–satellite comparison: (1) horizontal representativeness errors due to imperfect collocation of the model grid cell and an ensemble of satellite pixels called superobservation, (2) temporal representativeness errors originating mostly from differences in cloud cover between the modelled and observed state, and (3) vertical representativeness errors because of reduced satellite sensitivity towards the surface accompanied with necessary retrieval assumptions on the state of the atmosphere. To minimize the impact of these representativeness errors, we recommend that models and satellite measurements be sampled as consistently as possible, and our paper provides a number of recipes to do so. A practical confrontation of tropospheric NO2 columns simulated by the TM5 chemistry transport model (CTM) with Ozone Monitoring Instrument (OMI) tropospheric NO2 retrievals suggests that horizontal representativeness errors, while unavoidable, are limited to within 5–10 % in most cases and of random nature. These errors should be included along with the individual retrieval errors in the overall superobservation error. Temporal sampling errors from mismatches in cloud cover, and, consequently, in photolysis rates, are of the order of 10 % for NO2 and HCHO, and systematic, but partly avoidable. In the case of air pollution applications where sensitivity down to the ground is required, we recommend that models should be sampled on the same mostly cloud-free days as the satellite retrievals. The most relevant representativeness error is associated with the vertical sensitivity of UV–Vis satellite retrievals. Simple vertical integration of modelled profiles leads to systematically different model columns compared to application of the appropriate averaging kernel. In comparing OMI NO2 to GEOS-Chem NO2 simulations, these systematic differences are as large as 15–20 % in summer, but, again, avoidable.

Nitrogen oxide (NO x ) emissions from maritime shipping produce ozone (O 3 ) and hydroxyl radicals (OH), which in turn destroy methane (CH 4 ). The balance between this warming (due to O 3 ) and cooling (due to CH 4 ) determines the net effect of ship NO x on climate. Previous estimates of the chemical impact and radiative forcing (RF) of ship NO x have generally assumed that plumes of ship exhaust are instantly diluted into model grid cells spanning hundreds of kilometers, even though this is known to produce biased results. Here we improve the parametric representation of exhaust-gas chemistry developed in the GEOS-Chem chemical transport model (CTM) to provide the first estimate of RF from shipping that accounts for sub-grid-scale ship plume chemistry. The CTM now calculates O 3 production and CH 4 loss both within and outside the exhaust plumes and also accounts for the effect of wind speed. With the improved modeling of plumes, ship NO x perturbations are smaller than suggested by the ensemble of past global modeling studies, but if we assume instant dilution of ship NO x on the grid scale, the CTM reproduces previous model results. Our best estimates of the RF components from increasing ship NO x emissions by 1 Tg(N) yr −1 are smaller than that given in the past literature: +3.4 ± 0.85 mW m −2 (1σ confidence interval) from the short-lived ozone increase, −5.7±1.3 mW m −2 from the CH 4 decrease, and −1.7 ± 0.7 mW m −2 from the long-lived O 3 decrease that accompanies the CH 4 change. The resulting net RF is −4.0 ± 2.0 mW m −2 for emissions of 1 Tg(N) yr −1 . Due to non-linearity in O 3 production as a function of background NO x , RF from large changes in ship NO x emissions, such as the increase since preindustrial times, is about 20 % larger than this RF value for small marginal emission changes. Using sensitivity tests in one CTM, we quantify sources of uncertainty in the RF components and causes of the ±30 % spread in past model results; the main source of uncertainty is the composition of the background atmosphere in the CTM, which is driven by model formulation (±10 to 20 %) and the plausible range of anthropogenic emissions (±10 %).