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Carbonyl sulfide (COS), a trace gas in our atmosphere that leads to the formation of aerosols in the stratosphere, is largely taken up by terrestrial ecosystems. Quantifying the biosphere uptake of COS could provide a useful quantity to estimate gross primary productivity (GPP). Some COS sources and sinks still contain large uncertainties, and several top-down estimates of the COS budget point to an underestimation of sources, especially in the tropics. We extended the inverse model TM5-4DVAR to assimilate Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) satellite data, in addition to National Oceanic and Atmospheric Administration (NOAA) surface data as used in a previous study. To resolve possible discrepancies among the two observational data sets, a bias correction scheme is necessary and implemented. A set of inversions is presented that explores the influence of the different measurement streams and the settings of the prior fluxes. To evaluate the performance of the inverse system, the HIAPER Pole-to-Pole Observations (HIPPO) aircraft observations and NOAA airborne profiles are used. All inversions reduce the COS biosphere uptake from a prior value of 1053 GgS a−1 to much smaller values, depending on the inversion settings. These large adjustments of the biosphere uptake often turn parts of Amazonia into a COS source. Only inversions that exclusively use MIPAS observations, or strongly reduce the prior errors on the biosphere flux, maintain the Amazon as a COS sink. Inclusion of MIPAS data in the inversion leads to a better separation of land and ocean fluxes. Over the Amazon, these inversions reduce the biosphere uptake from roughly 300 to 100 GgS a−1, indicating a strongly overestimated prior uptake in this region. Although a recent study also reported reduced COS uptake over the Amazon, we emphasise that a careful construction of prior fluxes and their associated errors remains important. For instance, an inversion that gives large freedom to adjust the anthropogenic and ocean fluxes of CS2, an important COS precursor, also closes the budget satisfactorily with much smaller adjustments to the biosphere. We achieved better characterisation of biosphere prior and uncertainty, better characterisation of combined ocean and land fluxes, and better constraint of both by combining surface and satellite observations. We recommend more COS observations to characterise biosphere and ocean fluxes, especially over the data-poor tropics.

Aerosol formation acts as a sink for gas-phase atmospheric species that controls their atmospheric lifetime and environmental effects. To investigate aerosol formation and evolution in the Netherlands, a hybrid positive matrix factorization (PMF) analysis was conducted using observations from May, June, and September 2021 collected in the rural site of Cabauw in the central part of the Netherlands. The hybrid input matrix consists of the full organic mass spectrum acquired from a time-of-flight aerosol chemical speciation monitor (ToF-ACSM), ACSM inorganic species concentrations, and binned particle size distribution concentrations from a scanning mobility particle sizer (SMPS). These hybrid PMF analyses discerned four factors that describe aerosol composition variations: two size-driven factors that are related to new particle formation (NPF) and growth (F4 and F3), as well as two bulk factors driven by composition, not size (F2 and F1). The distribution of chemical species across these factors shows that different compounds are responsible for nucleation and growth of new particles. The smallest-diameter size factor (F4) contains ammonium sulfate and organics and typically peaks during the daytime. Newly formed particles, represented by F4, are mainly correlated with wind from the southwesterly–westerly and easterly sectors that transport sulfur oxides (SOx), ammonia (NH3), and organic precursors to Cabauw. As the particles grow from F4 to F3 and to bulk factors, nitrate and organics play an increasing role, and the particle loading diurnal cycle shifts from daytime to a nighttime maximum. Greater organics availability makes secondary organic aerosol (SOA) more influential in summertime aerosol growth, principally due to volatility differences produced by seasonal variation in photooxidation and temperature.

Carbonyl sulfide (COS) is a useful tracer to estimate gross primary production (GPP) because it shares part of the uptake pathway with CO2. COS is taken up in plants through hydrolysis, catalyzed by the enzyme carbonic anhydrase (CA), but is not released. The Simple Biosphere model version 4 (SiB4) simulates COS leaf uptake using a conductance approach. SiB4 applies the temperature response of the RuBisCo enzyme (used for photosynthesis) to simulate the COS leaf uptake, but the CA enzyme might respond differently to temperature. We introduce a new temperature response function for CA in SiB4, based on enzyme kinetics with an optimum temperature. Moreover, we determine Ball–Woodrow–Berry (BWB) model parameters for stomatal conductance (gs) using observation-based estimates of COS flux, GPP, and gs along with meteorological measurements in an evergreen needleleaf forest (ENF) and deciduous broadleaf forest (DBF). We find that CA has optimum temperatures of 20 ∘C (ENF) and 36 ∘C (DBF), which is lower than that of RuBisCo (45 ∘C), suggesting that canopy temperature changes can critically affect CA's catalyzation activity. Optimized values for the BWB offset parameter are similar to the original value (0.010 ± 0.003 mol m−2 s−1), and optimized values for the BWB slope parameter (ENF: 16.4, DBF: 11.4) are higher than the original value (9.0) at both sites. The optimization reduces prior errors on all parameters by more than 50 % at both stations. We apply the optimized gi and gs parameters in SiB4 site simulations, thereby improving the timing and peak of COS assimilation. In addition, we show that SiB4 underestimates the leaf humidity stress under conditions where high vapor pressure deficit (VPD) should limit gs in the afternoon, thereby overestimating gs. Furthermore, global COS biosphere sinks with optimized parameters show smaller COS uptake in regions where the air temperature is over 25 ∘C, mostly in the tropics, and larger uptake in regions where the temperature is below 25 ∘C. This change corresponds with reported deficiencies in the global COS fluxes, such as missing sinks at high latitudes and required sources in the tropics. Using our optimization and additional observations of COS uptake over various climate and plant types, we expect further improvements in global COS biosphere flux estimates.

This paper provides a description of ICLASS 1.1, a variational Inverse modelling framework for the Chemistry Land-surface Atmosphere Soil Slab model. This framework can be used to study the atmospheric boundary layer, surface layer, or the exchange of gases, moisture, heat, and momentum between the land surface and the lower atmosphere. The general aim of the framework is to allow the assimilation of various streams of observations (fluxes, mixing ratios at multiple heights, etc.) to estimate model parameters, thereby obtaining a physical model that is consistent with a diverse set of observations. The framework allows the retrieval of parameters in an objective manner and enables the estimation of information that is difficult to obtain directly by observations, for example, free tropospheric mixing ratios or stomatal conductances. Furthermore, it allows the estimation of possible biases in observations. Modelling the carbon cycle at the ecosystem level is one of the main intended fields of application. The physical model around which the framework is constructed is relatively simple yet contains the core physics to simulate the essentials of a well-mixed boundary layer and of the land–atmosphere exchange. The model includes an explicit description of the atmospheric surface layer, a region where scalars show relatively large gradients with height. An important challenge is the strong non-linearity of the model, which complicates the estimation of the best parameter values. The constructed adjoint of the tangent linear model can be used to mitigate this challenge. The adjoint allows for an analytical gradient of the objective cost function, which is used for minimisation of this function. An implemented Monte Carlo way of running ICLASS can further help to handle non-linearity and provides posterior statistics on the estimated parameters. The paper provides a technical description of the framework, includes a validation of the adjoint code, in addition to tests for the full inverse modelling framework, and a successful example application for a grassland in the Netherlands.

A new method is presented for estimating urban hydroxyl radical (OH) concentrations using the downwind decay of the ratio of nitrogen dioxide over carbon monoxide column-mixing ratios (XNO2/XCO) retrieved from the Tropospheric Monitoring Instrument (TROPOMI). The method makes use of plumes simulated by the Weather Research and Forecast model (WRF-Chem) using passive-tracer transport, instead of the encoded chemistry, in combination with auxiliary input variables such as Copernicus Atmospheric Monitoring Service (CAMS) OH, Emission Database for Global Atmospheric Research v4.3.2 (EDGAR) NOx and CO emissions, and National Center for Environmental Protection (NCEP)-based meteorological data. NO2 and CO mixing ratios from the CAMS reanalysis are used as initial and lateral boundary conditions. WRF overestimates NO2 plumes close to the center of the city by 15 % to 30 % in summer and 40 % to 50 % in winter compared to TROPOMI observations over Riyadh. WRF-simulated CO plumes differ by 10 % with TROPOMI in both seasons. The differences between WRF and TROPOMI are used to optimize the OH concentration, NOx, CO emissions and their backgrounds using an iterative least-squares method. To estimate OH, WRF is optimized using (a) TROPOMI XNO2/XCO and (b) TROPOMI-derived XNO2 only. For summer, both the NO2/CO ratio optimization and the XNO2 optimization increase the prior OH from CAMS by 32 ± 5.3 % and 28.3 ± 3.9 %, respectively. EDGAR NOx and CO emissions over Riyadh are increased by 42.1 ± 8.4 % and 101 ± 21 %, respectively, in summer. In winter, the optimization method doubles the CO emissions while increasing OH by ∼ 52 ± 14 % and reducing NOx emissions by 15.5 ± 4.1 %. TROPOMI-derived OH concentrations and the pre-existing exponentially modified Gaussian function fit (EMG) method differ by 10 % in summer and winter, confirming that urban OH concentrations can be reliably estimated using the TROPOMI-observed NO2/CO ratio. Additionally, our method can be applied to a single TROPOMI overpass, allowing one to analyze day-to-day variability in OH, NOx and CO emission.

Understanding how multiphase processes affect the iron-containing aerosol cycle is key to predicting ocean biogeochemistry changes and hence the feedback effects on climate. For this work, the EC-Earth Earth system model in its climate–chemistry configuration is used to simulate the global atmospheric oxalate (OXL), sulfate (SO42-), and iron (Fe) cycles after incorporating a comprehensive representation of the multiphase chemistry in cloud droplets and aerosol water. The model considers a detailed gas-phase chemistry scheme, all major aerosol components, and the partitioning of gases in aerosol and atmospheric water phases. The dissolution of Fe-containing aerosols accounts kinetically for the solution's acidity, oxalic acid, and irradiation. Aerosol acidity is explicitly calculated in the model, both for accumulation and coarse modes, accounting for thermodynamic processes involving inorganic and crustal species from sea salt and dust. Simulations for present-day conditions (2000–2014) have been carried out with both EC-Earth and the atmospheric composition component of the model in standalone mode driven by meteorological fields from ECMWF's ERA-Interim reanalysis. The calculated global budgets are presented and the links between the (1) aqueous-phase processes, (2) aerosol dissolution, and (3) atmospheric composition are demonstrated and quantified. The model results are supported by comparison to available observations. We obtain an average global OXL net chemical production of 12.615 ± 0.064 Tg yr−1 in EC-Earth, with glyoxal being by far the most important precursor of oxalic acid. In comparison to the ERA-Interim simulation, differences in atmospheric dynamics and the simulated weaker oxidizing capacity in EC-Earth overall result in a ∼ 30 % lower OXL source. On the other hand, the more explicit representation of the aqueous-phase chemistry in EC-Earth compared to the previous versions of the model leads to an overall ∼ 20 % higher sulfate production, but this is still well correlated with atmospheric observations. The total Fe dissolution rate in EC-Earth is calculated at 0.806 ± 0.014 Tg yr−1 and is added to the primary dissolved Fe (DFe) sources from dust and combustion aerosols in the model (0.072 ± 0.001 Tg yr−1). The simulated DFe concentrations show a satisfactory comparison with available observations, indicating an atmospheric burden of ∼0.007 Tg, resulting in an overall atmospheric deposition flux into the global ocean of 0.376 ± 0.005 Tg yr−1, which is well within the range reported in the literature. All in all, this work is a first step towards the development of EC-Earth into an Earth system model with fully interactive bioavailable atmospheric Fe inputs to the marine biogeochemistry component of the model.

Dry deposition is an important sink of tropospheric ozone that affects surface concentrations and impacts crop yields, the land carbon sink, and the terrestrial water cycle. Dry deposition pathways include plant uptake via stomata and non-stomatal removal by soils, leaf surfaces, and chemical reactions. Observational studies indicate that ozone deposition exhibits substantial temporal variability that is not reproduced by atmospheric chemistry models due to a simplified representation of vegetation uptake processes in these models. In this study, we explore the importance of stomatal and non-stomatal uptake processes in driving ozone dry deposition variability on diurnal to seasonal timescales. Specifically, we compare two land surface ozone uptake parameterizations – a commonly applied big leaf parameterization (W89; Wesely, 1989) and a multi-layer model (MLC-CHEM) constrained with observations – to multi-year ozone flux observations at two European measurement sites (Ispra, Italy, and Hyytiälä, Finland). We find that W89 cannot reproduce the diurnal cycle in ozone deposition due to a misrepresentation of stomatal and non-stomatal sinks at our two study sites, while MLC-CHEM accurately reproduces the different sink pathways. Evaluation of non-stomatal uptake further corroborates the previously found important roles of wet leaf uptake in the morning under humid conditions and soil uptake during warm conditions. The misrepresentation of stomatal versus non-stomatal uptake in W89 results in an overestimation of growing season cumulative ozone uptake (CUO), a metric for assessments of vegetation ozone damage, by 18 % (Ispra) and 28 % (Hyytiälä), while MLC-CHEM reproduces CUO within 7 % of the observation-inferred values. Our results indicate the need to accurately describe the partitioning of the ozone atmosphere–biosphere flux over the in-canopy stomatal and non-stomatal loss pathways to provide more confidence in atmospheric chemistry model simulations of surface ozone mixing ratios and deposition fluxes for large-scale vegetation ozone impact assessments.

Dry deposition is an important removal mechanism for tropospheric ozone (O3). Currently, O3 deposition to oceans in atmospheric chemistry and transport models (ACTMs) is generally represented using constant surface uptake resistances. This occurs despite the role of solubility, waterside turbulence and O3 reacting with ocean water reactants such as iodide resulting in substantial spatiotemporal variability in O3 deposition and concentrations in marine boundary layers. We hypothesize that O3 deposition to the Arctic Ocean, having a relatively low reactivity, is overestimated in current models with consequences for the tropospheric concentrations, lifetime and long-range transport of O3. We investigate the impact of the representation of oceanic O3 deposition to the simulated magnitude and spatiotemporal variability in Arctic surface O3. We have integrated the Coupled Ocean-Atmosphere Response Experiment Gas transfer algorithm (COAREG) into the mesoscale meteorology and atmospheric chemistry model Polar-WRF-Chem (WRF) which introduces a dependence of O3 deposition on physical and biogeochemical drivers of oceanic O3 deposition. Also, we reduced the O3 deposition to sea ice and snow. Here, we evaluate WRF and CAMS reanalysis data against hourly averaged surface O3 observations at 25 sites (latitudes > 60∘ N). This is the first time such a coupled modeling system has been evaluated against hourly observations at pan-Arctic sites to study the sensitivity of the magnitude and temporal variability in Arctic surface O3 on the deposition scheme. We find that it is important to nudge WRF to the ECMWF ERA5 reanalysis data to ensure adequate meteorological conditions to evaluate surface O3. We show that the mechanistic representation of O3 deposition over oceans and reduced snow/ice deposition improves simulated Arctic O3 mixing ratios both in magnitude and temporal variability compared to the constant resistance approach. Using COAREG, O3 deposition velocities are in the order of 0.01 cm s−1 compared to ∼ 0.05 cm s−1 in the constant resistance approach. The simulated monthly mean spatial variability in the mechanistic approach (0.01 to 0.018 cm s−1) expresses the sensitivity to chemical enhancement with dissolved iodide, whereas the temporal variability (up to ±20 % around the mean) expresses mainly differences in waterside turbulent transport. The mean bias for six sites above 70∘ N reduced from −3.8 to 0.3 ppb with the revision to ocean and snow/ice deposition. Our study confirms that O3 deposition to high-latitude oceans and snow/ice is generally overestimated in ACTMs. We recommend that a mechanistic representation of oceanic O3 deposition is preferred in ACTMs to improve the modeled Arctic surface O3 concentrations in terms of magnitude and temporal variability.

Carbonyl sulfide (COS) has the potential to be used as a climate diagnostic due to its close coupling to the biospheric uptake of CO2 and its role in the formation of stratospheric aerosol. The current understanding of the COS budget, however, lacks COS sources, which have previously been allocated to the tropical ocean. This paper presents a first attempt at global inverse modelling of COS within the 4-dimensional variational data-assimilation system of the TM5 chemistry transport model (TM5-4DVAR) and a comparison of the results with various COS observations. We focus on the global COS budget, including COS production from its precursors carbon disulfide (CS2) and dimethyl sulfide (DMS). To this end, we implemented COS uptake by soil and vegetation from an updated biosphere model (Simple Biosphere Model – SiB4). In the calculation of these fluxes, a fixed atmospheric mole fraction of 500 pmol mol−1 was assumed. We also used new inventories for anthropogenic and biomass burning emissions. The model framework is capable of closing the COS budget by optimizing for missing emissions using NOAA observations in the period 2000–2012. The addition of 432 Gg a−1 (as S equivalents) of COS is required to obtain a good fit with NOAA observations. This missing source shows few year-to-year variations but considerable seasonal variations. We found that the missing sources are likely located in the tropical regions, and an overestimated biospheric sink in the tropics cannot be ruled out due to missing observations in the tropical continental boundary layer. Moreover, high latitudes in the Northern Hemisphere require extra COS uptake or reduced emissions. HIPPO (HIAPER Pole-to-Pole Observations) aircraft observations, NOAA airborne profiles from an ongoing monitoring programme and several satellite data sources are used to evaluate the optimized model results. This evaluation indicates that COS mole fractions in the free troposphere remain underestimated after optimization. Assimilation of HIPPO observations slightly improves this model bias, which implies that additional observations are urgently required to constrain sources and sinks of COS. We finally find that the biosphere flux dependency on the surface COS mole fraction (which was not accounted for in this study) may substantially lower the fluxes of the SiB4 biosphere model over strong-uptake regions. Using COS mole fractions from our inversion, the prior biosphere flux reduces from 1053 to 851 Gg a−1, which is closer to 738 Gg a−1 as was found by Berry et al. (2013). In planned further studies we will implement this biosphere dependency and additionally assimilate satellite data with the aim of better separating the role of the oceans and the biosphere in the global COS budget.

Variations in the atmospheric oxidative capacity, largely determined by variations in the hydroxyl radical (OH), form a key uncertainty in many greenhouse and other pollutant budgets, such as that of methane (CH4). Methyl chloroform (MCF) is an often-adopted tracer to indirectly put observational constraints on large-scale variations in OH. We investigated the budget of MCF in a 4DVAR inversion using the atmospheric transport model TM5, for the period 1998–2018, with the objective to derive information on large-scale, interannual variations in atmospheric OH concentrations. While our main inversion did not fully converge, we did derive interannual variations in the global oxidation of MCF that bring simulated mole fractions of MCF within 1 %–2 % of the assimilated observations from the NOAA-GMD surface network at most sites. Additionally, the posterior simulations better reproduce aircraft observations used for independent validation compared to the prior simulations. The derived OH variations showed robustness with respect to the prior MCF emissions and the prior OH distribution over the 1998 to 2008 period. Although we find a rapid 8 % increase in global mean OH concentrations between 2010 and 2012 that quickly declines afterwards, the derived interannual variations were typically small (< 3 %/yr), with no significant long-term trend in global mean OH concentrations. The inverse system found strong adjustments to the latitudinal distribution of OH, relative to widely used prior distributions, with systematic increases in tropical and decreases in extra-tropical OH concentrations (both up to 30 %). These spatial adjustments were driven by intrahemispheric biases in simulated MCF mole fractions, which have not been identified in previous studies. Given the large amplitude of these adjustments, which exceeds spread between literature estimates, and a residual bias in the MCF intrahemispheric gradients, we suggest a reversal in the extratropical ocean sink of MCF in response to declining atmospheric MCF abundance (as hypothesized in Wennberg et al., 2004). This ocean source provides a more realistic explanation for the biases, possibly complementary to adjustments in the OH distribution. We identified significant added value in the use of a 3D transport model, since it implicitly accounts for variable transport and optimizes the observed spatial gradients of MCF, which is not possible in simpler models. However, we also found a trade-off in computational expense and convergence problems. Despite these convergence problems, the derived OH variations do result in an improved match with MCF observations relative to an interannually repeating prior for OH. Therefore, we consider that variations in OH derived from MCF inversions with 3D models can add value to budget studies of long-lived gases like CH4.

This work documents and evaluates the tropospheric gas-phase chemical mechanism MOGUNTIA in the three-dimensional chemistry transport model TM5-MP. Compared to the modified CB05 (mCB05) chemical mechanism previously used in the model, MOGUNTIA includes a detailed representation of the light hydrocarbons (C1–C4) and isoprene, along with a simplified chemistry representation of terpenes and aromatics. Another feature implemented in TM5-MP for this work is the use of the Rosenbrock solver in the chemistry code, which can replace the classical Euler backward integration method of the model. Global budgets of ozone (O3), carbon monoxide (CO), hydroxyl radicals (OH), nitrogen oxides (NOx), and volatile organic compounds (VOCs) are analyzed, and their mixing ratios are compared with a series of surface, aircraft, and satellite observations for the year 2006. Both mechanisms appear to be able to satisfactorily represent observed mixing ratios of important trace gases, with the MOGUNTIA chemistry configuration yielding lower biases than mCB05 compared to measurements in most of the cases. However, the two chemical mechanisms fail to reproduce the observed mixing ratios of light VOCs, indicating insufficient primary emission source strengths, oxidation that is too fast, and/or a low bias in the secondary contribution to C2–C3 organics via VOC atmospheric oxidation. Relative computational memory and time requirements of the different model configurations are also compared and discussed. Overall, the MOGUNTIA scheme simulates a large suite of oxygenated VOCs that are observed in the atmosphere at significant levels. This significantly expands the possible applications of TM5-MP.

This study investigates the use of co-located nitrogen dioxide (NO2) and carbon monoxide (CO) retrievals from the TROPOMI satellite to improve the quantification of burning efficiency and emission factors (EFs) over the megacities of Tehran, Mexico City, Cairo, Riyadh, Lahore, and Los Angeles. Efficient combustion is characterized by high NOx (NO+NO2) and low CO emissions, making the NO2∕CO ratio a useful proxy for combustion efficiency (CE). The local enhancement of CO and NO2 above megacities is well captured by TROPOMI at short averaging times compared with previous satellite missions. In this study, the upwind background and plume rotation methods are used to investigate the accuracy of satellite-derived ΔNO2∕ΔCO ratios. The column enhancement ratios derived using these two methods vary by 5 % to 20 % across the selected megacities. TROPOMI-derived column enhancement ratios are compared with emission ratios from the EDGAR v4.3.2 (Emission Database for Global Atmospheric Research v4.3.2) and the MACCity (Monitoring Atmospheric Chemistry and Climate and CityZen) 2018 emission inventories. TROPOMI correlates strongly (r=0.85 and 0.7) with EDGAR and MACCity, showing the highest emission ratio for Riyadh and lowest emission ratio for Lahore. However, inventory-derived emission ratios are 60 % to 85 % higher than TROPOMI column enhancement ratios across the six megacities. The short lifetime of NO2 and the different vertical sensitivity of TROPOMI NO2 and CO explain most of this difference. We present a method to translate TROPOMI-retrieved column enhancement ratios into corresponding emission ratios, thereby accounting for these influences. Except for Los Angeles and Lahore, TROPOMI-derived emission ratios are close (within 10 % to 25 %) to MACCity values. For EDGAR, however, emission ratios are ∼65 % higher for Cairo and 35 % higher for Riyadh. For Los Angeles, EDGAR and MACCity are a factor of 2 and 3 higher than TROPOMI respectively. The air quality monitoring networks in Los Angeles and Mexico City are used to validate the use of TROPOMI. For Mexico City and Los Angeles, these measurements are consistent with TROPOMI-derived emission ratios, demonstrating the potential of TROPOMI with respect to monitoring burning efficiency.

In Colombia, industrialization and a shift towards intensified agriculture have led to increased emissions of air pollutants. However, the baseline state of air quality in Colombia is relatively unknown. In this study we aim to assess the baseline state of air quality in Colombia with a focus on the spatial and temporal variability in emissions and atmospheric burden of nitrogen oxides (NOx = NO + NO2) and evaluate surface NOx, ozone (O3) and carbon monoxide (CO) mixing ratios. We quantify the magnitude and spatial distribution of the four major NOx sources (lightning, anthropogenic activities, soil biogenic emissions and biomass burning) by integrating global NOx emission inventories into the mesoscale meteorology and atmospheric chemistry model, namely Weather Research and Forecasting (WRF) coupled with Chemistry (collectively WRF-Chem), at a similar resolution (∼25 km) to the Emission Database for Global Atmospheric Research (EDGAR) anthropogenic emission inventory and the Ozone Monitoring Instrument (OMI) remote sensing observations. The model indicates the largest contribution by lightning emissions (1258 Gg N yr−1), even after already significantly reducing the emissions, followed by anthropogenic (933 Gg N yr−1), soil biogenic (187 Gg N yr−1) and biomass burning emissions (104 Gg N yr−1). The comparison with OMI remote sensing observations indicated a mean bias of tropospheric NO2 columns over the whole domain (WRF-Chem minus OMI) of 0.02 (90 % CI: [−0.43, 0.70]) ×1015 molecules cm−2, which is  % of the mean column. However, the simulated NO2 columns are overestimated and underestimated in regions where lightning and biomass burning emissions dominate, respectively. WRF-Chem was unable to capture NOx and CO urban pollutant mixing ratios, neither in timing nor in magnitude. Yet, WRF-Chem was able to simulate the urban diurnal cycle of O3 satisfactorily but with a systematic overestimation of 10 parts per billion (ppb) due to the equally large underestimation of NO mixing ratios and, consequently, titration. This indicates that these city environments are in the NOx-saturated regime with frequent O3 titration. We conducted sensitivity experiments with an online meteorology–chemistry single-column model (SCM) to evaluate how WRF-Chem subgrid-scale-enhanced emissions could explain an improved representation of the observed O3, CO and NOx diurnal cycles. Interestingly, the SCM simulation, showing especially a shallower nocturnal inversion layer, results in a better representation of the observed diurnal cycle of urban pollutant mixing ratios without an enhancement in emissions. This stresses that, besides application of higher-resolution emission inventories and model experiments, the diurnal cycle in boundary layer dynamics (and advection) should be critically evaluated in models such as WRF-Chem to assess urban air quality. Overall, we present a concise method to quantify air quality in regions with limited surface measurements by integrating in situ and remote sensing observations. This study identifies four distinctly different source regions and shows their interannual and seasonal variability during the last 1.5 decades. It serves as a base to assess scenarios of future air quality in Colombia or similar regions with contrasting emission regimes, complex terrain and a limited air quality monitoring network.

Ozone (O3) is a secondary air pollutant that negatively affects human and ecosystem health. Ozone simulations with regional air quality models suffer from unexplained biases over Europe, and uncertainties in the emissions of ozone precursor group nitrogen oxides (NOx=NO+NO2) contribute to these biases. The goal of this study is to use NO2 column observations from the Ozone Monitoring Instrument (OMI) satellite sensor to infer top-down NOx emissions in the regional Weather Research and Forecasting model with coupled chemistry (WRF-Chem) and to evaluate the impact on simulated surface O3 with in situ observations. We first perform a simulation for July 2015 over Europe and evaluate its performance against in situ observations from the AirBase network. The spatial distribution of mean ozone concentrations is reproduced satisfactorily. However, the simulated maximum daily 8 h ozone concentration (MDA8 O3) is underestimated (mean bias error of −14.2 µg m−3), and its spread is too low. We subsequently derive satellite-constrained surface NOx emissions using a mass balance approach based on the relative difference between OMI and WRF-Chem NO2 columns. The method accounts for feedbacks through OH, NO2's dominant daytime oxidant. Our optimized European NOx emissions amount to 0.50 Tg N (for July 2015), which is 0.18 Tg N higher than the bottom-up emissions (which lacked agricultural soil NOx emissions). Much of the increases occur across Europe, in regions where agricultural soil NOx emissions dominate. Our best estimate of soil NOx emissions in July 2015 is 0.1 Tg N, much higher than the bottom-up 0.02 Tg N natural soil NOx emissions from the Model of Emissions of Gases and Aerosols from Nature (MEGAN). A simulation with satellite-updated NOx emissions reduces the systematic bias between WRF-Chem and OMI NO2 (slope =0.98, r2=0.84) and reduces the low bias against independent surface NO2 measurements by 1.1 µg m−3 (−56 %). Following these NOx emission changes, daytime ozone is strongly affected, since NOx emission changes particularly affect daytime ozone formation. Monthly averaged simulated daytime ozone increases by 6.0 µg m−3, and increases of >10 µg m−3 are seen in regions with large emission increases. With respect to the initial simulation, MDA8 O3 has an improved spatial distribution, expressed by an increase in r2 from 0.40 to 0.53, and a decrease of the mean bias by 7.4 µg m−3 (48 %). Overall, our results highlight the dependence of surface ozone on its precursor NOx and demonstrate that simulations of surface ozone benefit from constraining surface NOx emissions by satellite NO2 column observations.

This work reports on the current status of the global modeling of iron (Fe) deposition fluxes and atmospheric concentrations and the analyses of the differences between models, as well as between models and observations. A total of four global 3-D chemistry transport (CTMs) and general circulation (GCMs) models participated in this intercomparison, in the framework of the United Nations Joint Group of Experts on the Scientific Aspects of Marine Environmental Protection (GESAMP) Working Group 38, The Atmospheric Input of Chemicals to the Ocean. The global total Fe (TFe) emission strength in the models is equal to ∼ 72 Tg Fe yr−1 (38–134 Tg Fe yr−1) from mineral dust sources and around 2.1 Tg Fe yr−1 (1.8–2.7 Tg Fe yr−1) from combustion processes (the sum of anthropogenic combustion/biomass burning and wildfires). The mean global labile Fe (LFe) source strength in the models, considering both the primary emissions and the atmospheric processing, is calculated to be 0.7 (±0.3) Tg Fe yr−1, accounting for both mineral dust and combustion aerosols. The mean global deposition fluxes into the global ocean are estimated to be in the range of 10–30 and 0.2–0.4 Tg Fe yr−1 for TFe and LFe, respectively, which roughly corresponds to a respective 15 and 0.3 Tg Fe yr−1 for the multi-model ensemble model mean.The model intercomparison analysis indicates that the representation of the atmospheric Fe cycle varies among models, in terms of both the magnitude of natural and combustion Fe emissions as well as the complexity of atmospheric processing parameterizations of Fe-containing aerosols. The model comparison with aerosol Fe observations over oceanic regions indicates that most models overestimate surface level TFe mass concentrations near dust source regions and tend to underestimate the low concentrations observed in remote ocean regions. All models are able to simulate the tendency of higher Fe concentrations near and downwind from the dust source regions, with the mean normalized bias for the Northern Hemisphere ( ∼ 14), larger than that of the Southern Hemisphere ( ∼ 2.4) for the ensemble model mean. This model intercomparison and model–observation comparison study reveals two critical issues in LFe simulations that require further exploration: (1) the Fe-containing aerosol size distribution and (2) the relative contribution of dust and combustion sources of Fe to labile Fe in atmospheric aerosols over the remote oceanic regions.

Data assimilation systems are used increasingly to constrain the budgets of reactive and long-lived gases measured in the atmosphere. Each trace gas has its own lifetime, dominant sources and sinks, and observational network (from flask sampling and in situ measurements to space-based remote sensing) and therefore comes with its own optimal configuration of the data assimilation. The CarbonTracker Europe data assimilation system for CO2 estimates global carbon sources and sinks, and updates are released annually and used in carbon cycle studies. CarbonTracker Europe simulations are performed using the new modular implementation of the data assimilation system: the CarbonTracker Data Assimilation Shell (CTDAS). Here, we present and document this redesign of the data assimilation code that forms the heart of CarbonTracker, specifically meant to enable easy extension and modification of the data assimilation system. This paper also presents the setup of the latest version of CarbonTracker Europe (CTE2016), including the use of the gridded state vector, and shows the resulting carbon flux estimates. We present the distribution of the carbon sinks over the hemispheres and between the land biosphere and the oceans. We show that with equal fossil fuel emissions, 2015 has a higher atmospheric CO2 growth rate compared to 2014, due to reduced net land carbon uptake in later year. The European carbon sink is especially present in the forests, and the average net uptake over 2001–2015 was 0. 17 ± 0. 11 PgC yr−1 with reductions to zero during drought years. Finally, we also demonstrate the versatility of CTDAS by presenting an overview of the wide range of applications for which it has been used so far.

We present a global distribution of surface methane (CH4) emission estimates for 2000–2012 derived using the CarbonTracker Europe-CH4 (CTE-CH4) data assimilation system. In CTE-CH4, anthropogenic and biospheric CH4 emissions are simultaneously estimated based on constraints of global atmospheric in situ CH4 observations. The system was configured to either estimate only anthropogenic or biospheric sources per region, or to estimate both categories simultaneously. The latter increased the number of optimizable parameters from 62 to 78. In addition, the differences between two numerical schemes available to perform turbulent vertical mixing in the atmospheric transport model TM5 were examined. Together, the system configurations encompass important axes of uncertainty in inversions and allow us to examine the robustness of the flux estimates. The posterior emission estimates are further evaluated by comparing simulated atmospheric CH4 to surface in situ observations, vertical profiles of CH4 made by aircraft, remotely sensed dry-air total column-averaged mole fraction (XCH4) from the Total Carbon Column Observing Network (TCCON), and XCH4 from the Greenhouse gases Observing Satellite (GOSAT). The evaluation with non-assimilated observations shows that posterior XCH4 is better matched with the retrievals when the vertical mixing scheme with faster interhemispheric exchange is used. Estimated posterior mean total global emissions during 2000–2012 are 516 ± 51 Tg CH4 yr−1, with an increase of 18 Tg CH4 yr−1 from 2000–2006 to 2007–2012. The increase is mainly driven by an increase in emissions from South American temperate, Asian temperate and Asian tropical TransCom regions. In addition, the increase is hardly sensitive to different model configurations ( 4 yr−1 difference), and much smaller than suggested by EDGAR v4.2 FT2010 inventory (33 Tg CH4 yr−1), which was used for prior anthropogenic emission estimates. The result is in good agreement with other published estimates from inverse modelling studies (16–20 Tg CH4 yr−1). However, this study could not conclusively separate a small trend in biospheric emissions (−5 to +6.9 Tg CH4 yr−1) from the much larger trend in anthropogenic emissions (15–27 Tg CH4 yr−1). Finally, we find that the global and North American CH4 balance could be closed over this time period without the previously suggested need to strongly increase anthropogenic CH4 emissions in the United States. With further developments, especially on the treatment of the atmospheric CH4 sink, we expect the data assimilation system presented here will be able to contribute to the ongoing interpretation of changes in this important greenhouse gas budget.

Boreal Eurasia is a region where the interaction between droughts and the carbon cycle may have significant impacts on the global carbon cycle. Yet the region is extremely data sparse with respect to meteorology, soil moisture, and carbon fluxes as compared to e.g. Europe. To better constrain our vegetation model SiBCASA, we increase data usage by assimilating two streams of satellite-derived soil moisture. We study whether the assimilation improved SiBCASA's soil moisture and its effect on the simulated carbon fluxes. By comparing to unique in situ soil moisture observations, we show that the passive microwave soil moisture product did not improve the soil moisture simulated by SiBCASA, but the active data seem promising in some aspects. The match between SiBCASA and ASCAT soil moisture is best in the summer months over low vegetation. Nevertheless, ASCAT failed to detect the major droughts occurring between 2007 and 2013. The performance of ASCAT soil moisture seems to be particularly sensitive to ponding, rather than to biomass. The effect on the simulated carbon fluxes is large, 5–10 % on annual GPP and TER, tens of percent on local NEE, and 2 % on area-integrated NEE, which is the same order of magnitude as the inter-annual variations. Consequently, this study shows that assimilation of satellite-derived soil moisture has potentially large impacts, while at the same time further research is needed to understand under which conditions the satellite-derived soil moisture improves the simulated soil moisture.

We present an enhanced version of the SiBCASA terrestrial biosphere model that is extended with (a) biomass burning emissions from the SiBCASA carbon pools using remotely sensed burned area from the Global Fire Emissions Database (GFED), (b) an isotopic discrimination scheme that calculates 13C signatures of photosynthesis and autotrophic respiration, and (c) a separate set of 13C pools to carry isotope ratios into heterotrophic respiration. We quantify in this study the terrestrial exchange of CO2 and 13CO2 as a function of environmental changes in humidity and biomass burning. The implementation of biomass burning yields similar fluxes as CASA-GFED both in magnitude and spatial patterns. The implementation of isotope exchange gives a global mean discrimination value of 15.2‰, ranges between 4 and 20‰ depending on the photosynthetic pathway in the plant, and compares favorably (annually and seasonally) with other published values. Similarly, the isotopic disequilibrium is similar to other studies that include a small effect of biomass burning as it shortens the turnover of carbon. In comparison to measurements, a newly modified starch/sugar storage pool propagates the isotopic discrimination anomalies to respiration much better. In addition, the amplitude of the drought response by SiBCASA is lower than suggested by the measured isotope ratios. We show that a slight increase in the stomatal closure for large vapor pressure deficit would amplify the respired isotope ratio variability. Our study highlights the importance of isotope ratio observations of 13C to assess and improve biochemical models like SiBCASA, especially with regard to the allocation and turnover of carbon and the responses to drought.

We have integrated the atmospheric chemistry and transport model TM5 into the global climate model EC-Earth version 2.4. We present an overview of the TM5 model and the two-way data exchange between TM5 and the IFS model from the European Centre for Medium-Range Weather Forecasts (ECMWF), the atmospheric general circulation model of EC-Earth. In this paper we evaluate the simulation of tropospheric chemistry and aerosols in a one-way coupled configuration. We have carried out a decadal simulation for present-day conditions and calculated chemical budgets and climatologies of tracer concentrations and aerosol optical depth. For comparison we have also performed offline simulations driven by meteorological fields from ECMWF's ERA-Interim reanalysis and output from the EC-Earth model itself. Compared to the offline simulations, the online-coupled system produces more efficient vertical mixing in the troposphere, which reflects an improvement of the treatment of cumulus convection. The chemistry in the EC-Earth simulations is affected by the fact that the current version of EC-Earth produces a cold bias with too dry air in large parts of the troposphere. Compared to the ERA-Interim driven simulation, the oxidizing capacity in EC-Earth is lower in the tropics and higher in the extratropics. The atmospheric lifetime of methane in EC-Earth is 9.4 years, which is 7% longer than the lifetime obtained with ERA-Interim but remains well within the range reported in the literature. We further evaluate the model by comparing the simulated climatologies of surface radon-222 and carbon monoxide, tropospheric and surface ozone, and aerosol optical depth against observational data. The work presented in this study is the first step in the development of EC-Earth into an Earth system model with fully interactive atmospheric chemistry and aerosols.

Radiocarbon dioxide (14CO2, reported in Δ14CO2) can be used to determine the fossil fuel CO2 addition to the atmosphere, since fossil fuel CO2 no longer contains any 14C. After the release of CO2 at the source, atmospheric transport causes dilution of strong local signals into the background and detectable gradients of Δ14CO2 only remain in areas with high fossil fuel emissions. This fossil fuel signal can moreover be partially masked by the enriching effect that anthropogenic emissions of 14CO2 from the nuclear industry have on the atmospheric Δ14CO2 signature. In this paper, we investigate the regional gradients in 14CO2 over the European continent and quantify the effect of the emissions from nuclear industry. We simulate the emissions and transport of fossil fuel CO2 and nuclear 14CO2 for Western Europe using the Weather Research and Forecast model (WRF-Chem) for a period covering 6 summer months in 2008. We evaluate the expected CO2 gradients and the resulting Δ14CO2 in simulated integrated air samples over this period, as well as in simulated plant samples. We find that the average gradients of fossil fuel CO2 in the lower 1200 m of the atmosphere are close to 15 ppm at a 12 km × 12 km horizontal resolution. The nuclear influence on Δ14CO2 signatures varies considerably over the domain and for large areas in France and the UK it can range from 20 to more than 500% of the influence of fossil fuel emissions. Our simulations suggest that the resulting gradients in Δ14CO2 are well captured in plant samples, but due to their time-varying uptake of CO2, their signature can be different with over 3‰ from the atmospheric samples in some regions. We conclude that the framework presented will be well-suited for the interpretation of actual air and plant 14CO2 samples.

In this study, we identify a biomass-burning signal in molecular hydrogen (H2) over the Amazonian tropical rainforest. To quantify this signal, we measure the mixing ratios of H2 and several other species as well as the H2 isotopic composition in air samples that were collected in the BARCA (Balanço Atmosférico Regional de Carbono na Amazônia) aircraft campaign during the dry season. We derive a relative H2 emission ratio with respect to carbon monoxide (CO) of 0.31 ± 0.04 ppb ppb−1 and an isotopic source signature of −280 ± 41‰ in the air masses influenced by tropical biomass burning. In order to retrieve a clear source signal that is not influenced by the soil uptake of H2, we exclude samples from the atmospheric boundary layer. This procedure is supported by data from a global chemistry transport model. The ΔH2 / ΔCO emission ratio is significantly lower than some earlier estimates for the tropical rainforest. In addition, our results confirm the lower values of the previously conflicting estimates of the H2 isotopic source signature from biomass burning. These values for the emission ratio and isotopic source signatures of H2 from tropical biomass burning can be used in future bottom-up and top-down approaches aiming to constrain the strength of the biomass-burning source for H2. Hitherto, these two quantities relied only on combustion experiments or on statistical relations, since no direct signal had been obtained from in-situ observations.

We studied the atmospheric boundary layer (ABL) dynamics and the impact on atmospheric chemistry during the HUMPPA-COPEC-2010 campaign. We used vertical profiles of potential temperature and specific moisture, obtained from 132 radio soundings, to determine the main boundary layer characteristics during the campaign. We propose a classification according to several main ABL prototypes. Further, we performed a case study of a single day, focusing on the convective boundary layer, to analyse the influence of the dynamics on the chemical evolution of the ABL. We used a mixed layer model, initialized and constrained by observations. In particular, we investigated the role of large scale atmospheric dynamics (subsidence and advection) on the ABL development and the evolution of chemical species concentrations. We find that, if the large scale forcings are taken into account, the ABL dynamics are represented satisfactorily. Subsequently, we studied the impact of mixing with a residual layer aloft during the morning transition on atmospheric chemistry. The time evolution of NOx and O3 concentrations, including morning peaks, can be explained and accurately simulated by incorporating the transition of the ABL dynamics from night to day. We demonstrate the importance of the ABL height evolution for the representation of atmospheric chemistry. Our findings underscore the need to couple the dynamics and chemistry at different spatial scales (from turbulence to mesoscale) in chemistry-transport models and in the interpretation of observational data.

An explanatory model study is presented on semi-volatile secondary inorganic aerosols on three clear days in May 2008 during the IMPACT campaign at the Cabauw tower in the Netherlands. A single column model in combination with the equilibrium aerosol model ISORROPIA is used. This model uses surface observations from IMPACT and calculates the gas-aerosol partitioning of ammonium nitrate. The calculated gas-aerosol equilibrium overestimates the gas phase fraction during daytime, and overestimates the aerosol phase fraction during night-time. This discrepancy can partly be solved when the approach of the gas-aerosol equilibrium is forced to proceed with a delay timescale of up to two hours. Although it is shown that the delay itself has a small effect, the most important effect is caused by the mixing of air from higher altitudes at which the equilibrium is shifted to the aerosol phase. Thus, vertical mixing is shown to have a significant influence on the calculated partitioning at the surface. On some occasions, the correspondence to the observed partitioning improves dramatically. Even though gas-aerosol partitioning of ammonium nitrate is not instantaneous, observations show that a different equilibrium in the upper boundary layer causes aerosol ammonium nitrate concentrations to increase with altitude. Our model calculates similar vertical gradients depending on the assumed speed of gas-aerosol equilibrium. The calculated optical properties of the aerosol show a similar behaviour. The aerosol optical properties depend on the aerosol size distribution both directly, because light scattering depends on particle size, and indirectly, because the equilibration timescale depends on the aerosol sizes. Future studies should therefore focus on a fully size-resolved treatment of the gas-aerosol partitioning. Finally, coarser-resolution models may treat the gas-aerosol equilibrium of ammonium nitrate by calculating the equilibrium with a temperature and humidity sampled at a different altitude. We found that the equilibrium at an altitude of 200 m (night) up to 600 m (day) is representative for the partitioning of ammonium nitrate at the surface in the beginning of May 2008.

Interpretation of observed diurnal carbon dioxide (CO2) mixing ratios near the surface requires knowledge of the local dynamics of the planetary boundary layer. In this paper, we study the relationship between the boundary layer dynamics and the CO2 budget in convective conditions through a newly derived set of analytical equations. From these equations, we are able to quantify how uncertainties in boundary layer dynamical variables or in the morning CO2 distribution in the mixed-layer or in the free atmosphere (FA) influence the bulk CO2 mixing ratio. We find that the largest uncertainty incurred on the mid-day CO2 mixing ratio comes from the prescribed early morning CO2 mixing ratios in the stable boundary layer, and in the free atmosphere. Errors in these values influence CO2 mixing ratios inversely proportional to the boundary layer depth (h), just like uncertainties in the assumed initial boundary layer depth and surface CO2 flux. The influence of uncertainties in the boundary layer depth itself is one order of magnitude smaller. If we "invert" the problem and calculate CO2 surface exchange from observed or simulated CO2 mixing ratios, the sensitivities to errors in boundary layer dynamics also invert: they become linearly proportional to the boundary layer depth. We demonstrate these relations for a typical well characterized situation at the Cabauw site in The Netherlands, and conclude that knowledge of the temperature and carbon dioxide profiles of the atmosphere in the early morning are of vital importance to correctly interpret observed CO2 mixing ratios during midday.

Using a Large-Eddy Simulation model, we have systematically studied the inability of boundary layer turbulence to efficiently mix reactive species. This creates regions where the species are accumulated in a correlated or anti-correlated way, thereby modifying the mean reactivity. We quantify this modification by the intensity of segregation, IS, and analyse the driving mechanisms: heterogeneity of the surface moisture and heat fluxes, various background wind patterns and non-uniform isoprene emissions. The heterogeneous surface conditions are characterized by cool and wet forested patches with high isoprene emissions, alternated with warm and dry patches that represents pasture with relatively low isoprene emissions. For typical conditions in the Amazon rain forest, applying homogeneous surface forcings and in the absence of free tropospheric NOx, the isoprene-OH reaction rate is altered by less than 10%. This is substantially smaller than the previously assumed IS of 50% in recent large-scale model analyses of tropical rain forest chemistry. Spatial heterogeneous surface emissions enhance the segregation of species, leading to alterations of the chemical reaction rates up to 20%. The intensities of segregation are enhanced when the background wind direction is parallel to the borders between the patches and reduced in the case of a perpendicular wind direction. The effects of segregation on trace gas concentrations vary per species. For the highly reactive OH, the differences in concentration averaged over the boundary layer are less than 2% compared to homogeneous surface conditions, while the isoprene concentration is increased by as much as 12% due to the reduced chemical reaction rates. These processes take place at the sub-grid scale of chemistry transport models and therefore need to be parameterized.

This study presents the results of a broad intercomparison of a total of 15 global aerosol models within the AeroCom project. Each model is compared to observations related to desert dust aerosols, their direct radiative effect, and their impact on the biogeochemical cycle, i.e., aerosol optical depth (AOD) and dust deposition. Additional comparisons to Angström exponent (AE), coarse mode AOD and dust surface concentrations are included to extend the assessment of model performance and to identify common biases present in models. These data comprise a benchmark dataset that is proposed for model inspection and future dust model development. There are large differences among the global models that simulate the dust cycle and its impact on climate. In general, models simulate the climatology of vertically integrated parameters (AOD and AE) within a factor of two whereas the total deposition and surface concentration are reproduced within a factor of 10. In addition, smaller mean normalized bias and root mean square errors are obtained for the climatology of AOD and AE than for total deposition and surface concentration. Characteristics of the datasets used and their uncertainties may influence these differences. Large uncertainties still exist with respect to the deposition fluxes in the southern oceans. Further measurements and model studies are necessary to assess the general model performance to reproduce dust deposition in ocean regions sensible to iron contributions. Models overestimate the wet deposition in regions dominated by dry deposition. They generally simulate more realistic surface concentration at stations downwind of the main sources than at remote ones. Most models simulate the gradient in AOD and AE between the different dusty regions. However the seasonality and magnitude of both variables is better simulated at African stations than Middle East ones. The models simulate the offshore transport of West Africa throughout the year but they overestimate the AOD and they transport too fine particles. The models also reproduce the dust transport across the Atlantic in the summer in terms of both AOD and AE but not so well in winter-spring nor the southward displacement of the dust cloud that is responsible of the dust transport into South America. Based on the dependency of AOD on aerosol burden and size distribution we use model bias with respect to AOD and AE to infer the bias of the dust emissions in Africa and the Middle East. According to this analysis we suggest that a range of possible emissions for North Africa is 400 to 2200 Tg yr−1 and in the Middle East 26 to 526 Tg yr−1.

The isotopic composition of molecular hydrogen (H2) contains independent information for constraining the global H2 budget. To explore this, we have implemented hydrogen sources and sinks, including their stable isotopic composition and isotope fractionation constants, into the global chemistry transport model TM5. For the first time, a global model now includes a simplified but explicit isotope reaction scheme for the photochemical production of H2. We present a comparison of modelled results for the H2 mixing ratio and isotope composition with available measurements on seasonal to inter annual time scales for the years 2001–2007. The base model results agree well with observations for H2 mixing ratios. For δD[H2], modelled values are slightly lower than measurements. A detailed sensitivity study is performed to identify the most important parameters for modelling the isotopic composition of H2. The results show that on the global scale, the discrepancy between model and measurements can be closed by adjusting the default values of the isotope effects in deposition, photochemistry and the stratosphere-troposphere exchange within the known range of uncertainty. However, the available isotope data do not provide sufficient information to uniquely constrain the global isotope budget. Therefore, additional studies focussing on the isotopic composition near the tropopause and on the isotope effects in the photochemistry and deposition are recommended.

Inverse modeling techniques used to quantify surface carbon fluxes commonly assume that the uncertainty of fossil fuel CO2 (FFCO2) emissions is negligible and that intra-annual variations can be neglected. To investigate these assumptions, we analyzed the differences between four fossil fuel emission inventories with spatial and temporal differences over Europe and their impact on the model simulated CO2 concentration. Large temporal flux variations characterize the hourly fields (~40 % and ~80 % for the seasonal and diurnal cycles, peak-to-peak) and annual country totals differ by 10 % on average and up to 40 % for some countries (i.e., the Netherlands). These emissions have been prescribed to seven different transport models, resulting in 28 different FFCO2 concentrations fields. The modeled FFCO2 concentration time series at surface sites using time-varying emissions show larger seasonal cycles (+2 ppm at the Hungarian tall tower (HUN)) and smaller diurnal cycles in summer (−1 ppm at HUN) than when using constant emissions. The concentration range spanned by all simulations varies between stations, and is generally larger in winter (up to ~10 ppm peak-to-peak at HUN) than in summer (~5 ppm). The contribution of transport model differences to the simulated concentration std-dev is 2–3 times larger than the contribution of emission differences only, at typical European sites used in global inversions. These contributions to the hourly (monthly) std-dev's amount to ~1.2 (0.8) ppm and ~0.4 (0.3) ppm for transport and emissions, respectively. First comparisons of the modeled concentrations with 14C-based fossil fuel CO2 observations show that the large transport differences still hamper a quantitative evaluation/validation of the emission inventories. Changes in the estimated monthly biosphere flux (Fbio) over Europe, using two inverse modeling approaches, are relatively small (less that 5 %) while changes in annual Fbio (up to ~0.15 % GtC yr−1) are only slightly smaller than the differences in annual emission totals and around 30 % of the mean European ecosystem carbon sink. These results point to an urgent need to improve not only the transport models but also the assumed spatial and temporal distribution of fossil fuel emission inventories.

We apply a four-dimensional variational (4D-VAR) data assimilation system to optimize carbon monoxide (CO) emissions for 2003 and 2004 and to reduce the uncertainty of emission estimates from individual sources using the chemistry transport model TM5. The system is designed to assimilate large (satellite) datasets, but in the current study only a limited amount of surface network observations from the National Oceanic and Atmospheric Administration Earth System Research Laboratory (NOAA/ESRL) Global Monitoring Division (GMD) is used to test the 4D-VAR system. By design, the system is capable to adjust the emissions in such a way that the posterior simulation reproduces background CO mixing ratios and large-scale pollution events at background stations. Uncertainty reduction up to 60 % in yearly emissions is observed over well-constrained regions and the inferred emissions compare well with recent studies for 2004. However, with the limited amount of data from the surface network, the system becomes data sparse resulting in a large solution space. Sensitivity studies have shown that model uncertainties (e.g., vertical distribution of biomass burning emissions and the OH field) and the prior inventories used, influence the inferred emission estimates. Also, since the observations only constrain total CO emissions, the 4D-VAR system has difficulties in separating anthropogenic and biogenic sources in particular. The inferred emissions are validated with NOAA aircraft data over North America and the agreement is significantly improved from the prior to posterior simulation. Validation with the Measurements Of Pollution In The Troposphere (MOPITT) instrument version 4 (V4) shows a slight improved agreement over the well-constrained Northern Hemisphere and in the tropics (except for the African continent). However, the model simulation with posterior emissions underestimates MOPITT CO total columns on the remote Southern Hemisphere (SH) by about 10 %. This is caused by a reduction in SH CO sources mainly due to surface stations on the high southern latitudes.

This paper presents the aerosol budget over Europe in 2006 calculated with the global transport model TM5 coupled to the size-resolved aerosol module M7. Comparison with ground observations indicates that the model reproduces the observed concentrations quite well with an expected slight underestimation of PM10 due to missing emissions (e.g. resuspension). We model that a little less than half of the anthropogenic aerosols emitted in Europe are exported and the rest is removed by deposition. The anthropogenic aerosols are removed mostly by rain (95%) and only 5% is removed by dry deposition. For the larger natural aerosols, especially sea salt, a larger fraction is removed by dry processes (sea salt: 70%, mineral dust: 35%). We model transport of aerosols in the jet stream in the higher atmosphere and an import of Sahara dust from the south at high altitudes. Comparison with optical measurements shows that the model reproduces the Ångström parameter very well, which indicates a correct simulation of the aerosol size distribution. However, we underestimate the aerosol optical depth. Because the surface concentrations are close to the observations, the shortage of aerosol in the model is probably at higher altitudes. We show that the discrepancies are mainly caused by an overestimation of wet-removal rates. To match the observations, the wet-removal rates have to be scaled down by a factor of about 5. In that case the modelled ground-level concentrations of sulphate and sea salt increase by 50% (which deteriorates the match), while other components stay roughly the same. Finally, it is shown that in particular events, improved fire emission estimates may significantly improve the ability of the model to simulate the aerosol optical depth. We stress that discrepancies in aerosol models can be adequately analysed if all models would provide (regional) aerosol budgets, as presented in the current study.

The isotopic composition of molecular hydrogen (H2) produced by photochemical oxidation of methane (CH4) and Volatile Organic Compounds (VOCs) is a key quantity in the global isotope budget of (H2). The many individual reaction steps involved complicate its investigation. Here we present a simplified structure-activity approach to assign isotope effects to the individual elementary reaction steps in the oxidation sequence of CH4 and some other VOCs. The approach builds on and extends the work by Gerst and Quay (2001) and Feilberg et al. (2007b). The description is generalized and allows the application, in principle, also to other compounds. The idea is that the C-H and C-D bonds – seen as reactive sites – have similar relative reaction probabilities in isotopically substituted, but otherwise identical molecules. The limitations of this approach are discussed for the reaction CH4+Cl. The same approach is applied to VOCs, which are important precursors of H2 that need to be included into models. Unfortunately, quantitative information on VOC isotope effects and source isotope signatures is very limited and the isotope scheme at this time is limited to a strongly parameterized statistical approach, which neglects kinetic isotope effects. Using these concepts we implement a full hydrogen isotope scheme in a chemical box model and carry out a sensitivity study to identify those reaction steps and conditions that are most critical for the isotope composition of the final H2 product. The reaction scheme is directly applicable in global chemistry models, which can thus include the isotope pathway of H2 produced from CH4 and VOCs in a consistent way.

A four-dimensional variational (4D-Var) data assimilation system for inverse modelling of atmospheric methane emissions is presented. The system is based on the TM5 atmospheric transport model. It can be used for assimilating large volumes of measurements, in particular satellite observations and quasi-continuous in-situ observations, and at the same time it enables the optimization of a large number of model parameters, specifically grid-scale emission rates. Furthermore, the variational method allows to estimate uncertainties in posterior emissions. Here, the system is applied to optimize monthly methane emissions over a 1-year time window on the basis of surface observations from the NOAA-ESRL network. The results are rigorously compared with an analogous inversion by Bergamaschi et al. (2007), which was based on the traditional synthesis approach. The posterior emissions as well as their uncertainties obtained in both inversions show a high degree of consistency. At the same time we illustrate the advantage of 4D-Var in reducing aggregation errors by optimizing emissions at the grid scale of the transport model. The full potential of the assimilation system is exploited in Meirink et al. (2008), who use satellite observations of column-averaged methane mixing ratios to optimize emissions at high spatial resolution, taking advantage of the zooming capability of the TM5 model.

The possible use of 14CO measurements to constrain hydroxyl radical (OH) concentrations in the atmosphere is investigated. 14CO is mainly produced in the upper atmosphere from cosmic radiation. Measurements of 14CO at the surface show lower concentrations compared to the upper atmospheric source region, which is the result of oxidation by OH. In this paper, the sensitivity of 14CO mixing ratio surface measurements to the 3-D OH distribution is assessed with the TM5 model. Simulated 14CO mixing ratios agree within a few molecules 14CO cm−3 (STP) with existing measurements at five locations worldwide. The simulated cosmogenic 14CO distribution appears mainly sensitive to the assumed upper atmospheric 14C source function, and to a lesser extend to model resolution. As a next step, the sensitivity of 14CO measurements to OH is calculated with the adjoint TM5 model. The results indicate that 14CO measurements taken in the tropics are sensitive to OH in a spatially confined region that varies strongly over time due to meteorological variability. Given measurements with an accuracy of 0.5 molecules 14CO cm−3 STP, a good characterization of the cosmogenic 14CO fraction, and assuming perfect transport modeling, a single 14CO measurement may constrain OH to 0.2–0.3×106 molecules OH cm−3 on time scales of 6 months and spatial scales of 70×70 degrees (latitude×longitude) between the surface and 500 hPa. The sensitivity of 14CO measurements to high latitude OH is about a factor of five higher. This is in contrast with methyl chloroform (MCF) measurements, which show the highest sensitivity to tropical OH, mainly due to the temperature dependent rate constant of the MCF–OH reaction. A logical next step will be the analysis of existing 14CO measurements in an inverse modeling framework. This paper presents the required mathematical framework for such an analysis.

A new multiple-scattering Monte Carlo 3-D radiative transfer model named McSCIA (Monte Carlo for SCIAmachy) is presented. The backward technique is used to efficiently simulate narrow field of view instruments. The McSCIA algorithm has been formulated as a function of the Earth's radius, and can thus perform simulations for both plane-parallel and spherical atmospheres. The latter geometry is essential for the interpretation of limb satellite measurements, as performed by SCIAMACHY on board of ESA's Envisat. The model can simulate UV-vis-NIR radiation. First the ray-tracing algorithm is presented in detail, and then successfully validated against literature references, both in plane-parallel and in spherical geometry. A simple 1-D model is used to explain two different ways of treating absorption. One method uses the single scattering albedo while the other uses the equivalence theorem. The equivalence theorem is based on a separation of absorption and scattering. It is shown that both methods give, in a statistical way, identical results for a wide variety of scenarios. Both absorption methods are included in McSCIA, and it is shown that also for a 3-D case both formulations give identical results. McSCIA limb profiles for atmospheres with and without absorption compare well with the one of the state of the art Monte Carlo radiative transfer model MCC++. A simplification of the photon statistics may lead to very fast calculations of absorption features in the atmosphere. However, these simplifications potentially introduce biases in the results. McSCIA does not use simplifications and is therefore a relatively slow implementation of the equivalence theorem.

We present a systematic comparison of tropospheric NO2 from 17 global atmospheric chemistry models with three state-of-the-art retrievals from the Global Ozone Monitoring Experiment (GOME) for the year 2000. The models used constant anthropogenic emissions from IIASA/EDGAR3.2 and monthly emissions from biomass burning based on the 1997–2002 average carbon emissions from the Global Fire Emissions Database (GFED). Model output is analyzed at 10:30 local time, close to the overpass time of the ERS-2 satellite, and collocated with the measurements to account for sampling biases due to incomplete spatiotemporal coverage of the instrument. We assessed the importance of different contributions to the sampling bias: correlations on seasonal time scale give rise to a positive bias of 30–50% in the retrieved annual means over regions dominated by emissions from biomass burning. Over the industrial regions of the eastern United States, Europe and eastern China the retrieved annual means have a negative bias with significant contributions (between –25% and +10% of the NO2 column) resulting from correlations on time scales from a day to a month. We present global maps of modeled and retrieved annual mean NO2 column densities, together with the corresponding ensemble means and standard deviations for models and retrievals. The spatial correlation between the individual models and retrievals are high, typically in the range 0.81–0.93 after smoothing the data to a common resolution. On average the models underestimate the retrievals in industrial regions, especially over eastern China and over the Highveld region of South Africa, and overestimate the retrievals in regions dominated by biomass burning during the dry season. The discrepancy over South America south of the Amazon disappears when we use the GFED emissions specific to the year 2000. The seasonal cycle is analyzed in detail for eight different continental regions. Over regions dominated by biomass burning, the timing of the seasonal cycle is generally well reproduced by the models. However, over Central Africa south of the Equator the models peak one to two months earlier than the retrievals. We further evaluate a recent proposal to reduce the NOx emission factors for savanna fires by 40% and find that this leads to an improvement of the amplitude of the seasonal cycle over the biomass burning regions of Northern and Central Africa. In these regions the models tend to underestimate the retrievals during the wet season, suggesting that the soil emissions are higher than assumed in the models. In general, the discrepancies between models and retrievals cannot be explained by a priori profile assumptions made in the retrievals, neither by diurnal variations in anthropogenic emissions, which lead to a marginal reduction of the NO2 abundance at 10:30 local time (by 2.5–4.1% over Europe). Overall, there are significant differences among the various models and, in particular, among the three retrievals. The discrepancies among the retrievals (10–50% in the annual mean over polluted regions) indicate that the previously estimated retrieval uncertainties have a large systematic component. Our findings imply that top-down estimations of NOx emissions from satellite retrievals of tropospheric NO2 are strongly dependent on the choice of model and retrieval.

Thousands of megatons natural and anthropogenic gases are released and subsequently removed from the troposphere each year. Photochemical reactions, initiated by hydroxyl (OH) radicals, oxidise most gases to products which are more easily removed by precipitation and dry deposition at the earth's surface. Since human-induced pollution emissions strongly affect OH formation and loss, large global changes in OH concentrations are possible. Global models and observations of trace gas distributions from global networks have been used to study geographical and temporal changes in tropospheric OH. Here we present a synopsis of recent studies, indicating that global mean OH has changed remarkably little in the past century, even though regional changes have probably been substantial. Globally, depletion of OH by reactive carbon gases has been compensated by increased OH formation by nitrogen oxides, an act of 'inadvertent geo-engineering'. However, OH analyses for the past 1-2 decades, partly based on methyl chloroform measurements, are inconclusive. Some work, assuming that methyl chloroform emissions have largely ceased, suggests a very strong downward global OH trend in the 1990s, inconsistent with modelling studies. The discrepancy could be much reduced by assuming continued small emissions of methyl chloroform. We recommend the continuation of high precision monitoring of this compound and improved analyses based on detailed meteorological-chemical models.