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  • 1
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 14, No. 19 ( 2014-10-15), p. 10845-10895
    Abstract: Abstract. This paper evaluates the current status of global modeling of the organic aerosol (OA) in the troposphere and analyzes the differences between models as well as between models and observations. Thirty-one global chemistry transport models (CTMs) and general circulation models (GCMs) have participated in this intercomparison, in the framework of AeroCom phase II. The simulation of OA varies greatly between models in terms of the magnitude of primary emissions, secondary OA (SOA) formation, the number of OA species used (2 to 62), the complexity of OA parameterizations (gas-particle partitioning, chemical aging, multiphase chemistry, aerosol microphysics), and the OA physical, chemical and optical properties. The diversity of the global OA simulation results has increased since earlier AeroCom experiments, mainly due to the increasing complexity of the SOA parameterization in models, and the implementation of new, highly uncertain, OA sources. Diversity of over one order of magnitude exists in the modeled vertical distribution of OA concentrations that deserves a dedicated future study. Furthermore, although the OA / OC ratio depends on OA sources and atmospheric processing, and is important for model evaluation against OA and OC observations, it is resolved only by a few global models. The median global primary OA (POA) source strength is 56 Tg a−1 (range 34–144 Tg a−1) and the median SOA source strength (natural and anthropogenic) is 19 Tg a−1 (range 13–121 Tg a−1). Among the models that take into account the semi-volatile SOA nature, the median source is calculated to be 51 Tg a−1 (range 16–121 Tg a−1), much larger than the median value of the models that calculate SOA in a more simplistic way (19 Tg a−1; range 13–20 Tg a−1, with one model at 37 Tg a−1). The median atmospheric burden of OA is 1.4 Tg (24 models in the range of 0.6–2.0 Tg and 4 between 2.0 and 3.8 Tg), with a median OA lifetime of 5.4 days (range 3.8–9.6 days). In models that reported both OA and sulfate burdens, the median value of the OA/sulfate burden ratio is calculated to be 0.77; 13 models calculate a ratio lower than 1, and 9 models higher than 1. For 26 models that reported OA deposition fluxes, the median wet removal is 70 Tg a−1 (range 28–209 Tg a−1), which is on average 85% of the total OA deposition. Fine aerosol organic carbon (OC) and OA observations from continuous monitoring networks and individual field campaigns have been used for model evaluation. At urban locations, the model–observation comparison indicates missing knowledge on anthropogenic OA sources, both strength and seasonality. The combined model–measurements analysis suggests the existence of increased OA levels during summer due to biogenic SOA formation over large areas of the USA that can be of the same order of magnitude as the POA, even at urban locations, and contribute to the measured urban seasonal pattern. Global models are able to simulate the high secondary character of OA observed in the atmosphere as a result of SOA formation and POA aging, although the amount of OA present in the atmosphere remains largely underestimated, with a mean normalized bias (MNB) equal to −0.62 (−0.51) based on the comparison against OC (OA) urban data of all models at the surface, −0.15 (+0.51) when compared with remote measurements, and −0.30 for marine locations with OC data. The mean temporal correlations across all stations are low when compared with OC (OA) measurements: 0.47 (0.52) for urban stations, 0.39 (0.37) for remote stations, and 0.25 for marine stations with OC data. The combination of high (negative) MNB and higher correlation at urban stations when compared with the low MNB and lower correlation at remote sites suggests that knowledge about the processes that govern aerosol processing, transport and removal, on top of their sources, is important at the remote stations. There is no clear change in model skill with increasing model complexity with regard to OC or OA mass concentration. However, the complexity is needed in models in order to distinguish between anthropogenic and natural OA as needed for climate mitigation, and to calculate the impact of OA on climate accurately.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2014
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  • 2
    In: Climate Dynamics, Springer Science and Business Media LLC, Vol. 39, No. 11 ( 2012-12), p. 2611-2629
    Type of Medium: Online Resource
    ISSN: 0930-7575 , 1432-0894
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2012
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  • 3
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 6, No. 10 ( 2006-07-17), p. 2943-2979
    Abstract: Abstract. 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.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2006
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  • 4
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 13, No. 4 ( 2013-02-19), p. 1853-1877
    Abstract: Abstract. We report on the AeroCom Phase II direct aerosol effect (DAE) experiment where 16 detailed global aerosol models have been used to simulate the changes in the aerosol distribution over the industrial era. All 16 models have estimated the radiative forcing (RF) of the anthropogenic DAE, and have taken into account anthropogenic sulphate, black carbon (BC) and organic aerosols (OA) from fossil fuel, biofuel, and biomass burning emissions. In addition several models have simulated the DAE of anthropogenic nitrate and anthropogenic influenced secondary organic aerosols (SOA). The model simulated all-sky RF of the DAE from total anthropogenic aerosols has a range from −0.58 to −0.02 Wm−2, with a mean of −0.27 Wm−2 for the 16 models. Several models did not include nitrate or SOA and modifying the estimate by accounting for this with information from the other AeroCom models reduces the range and slightly strengthens the mean. Modifying the model estimates for missing aerosol components and for the time period 1750 to 2010 results in a mean RF for the DAE of −0.35 Wm−2. Compared to AeroCom Phase I (Schulz et al., 2006) we find very similar spreads in both total DAE and aerosol component RF. However, the RF of the total DAE is stronger negative and RF from BC from fossil fuel and biofuel emissions are stronger positive in the present study than in the previous AeroCom study. We find a tendency for models having a strong (positive) BC RF to also have strong (negative) sulphate or OA RF. This relationship leads to smaller uncertainty in the total RF of the DAE compared to the RF of the sum of the individual aerosol components. The spread in results for the individual aerosol components is substantial, and can be divided into diversities in burden, mass extinction coefficient (MEC), and normalized RF with respect to AOD. We find that these three factors give similar contributions to the spread in results.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2013
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  • 5
    In: Journal of Geophysical Research, American Geophysical Union (AGU), Vol. 113, No. D4 ( 2008-02-22)
    Type of Medium: Online Resource
    ISSN: 0148-0227
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2008
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  • 6
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 14, No. 12 ( 2014-06-16), p. 5893-5904
    Abstract: Abstract. Belgium is one of the areas within Europe experiencing the highest levels of air pollution. A high-resolution (3 km) modelling experiment is employed to provide guidance to policymakers about expected air quality changes in the near future (2026–2035). The regional air quality model AURORA (Air quality modelling in Urban Regions using an Optimal Resolution Approach), driven by output from a regional climate model, is used to simulate several 10-year time slices to investigate the impact of climatic changes and different emission scenarios on near-surface O3 concentrations, one of the key indices for air quality. Evaluation of the model against measurements from 34 observation stations shows that the AURORA model is capable of reproducing 10-year mean concentrations, daily cycles and spatial patterns. The results for the Representative Concentration Pathways (RCP)4.5 emission scenario indicate that the mean surface O3 concentrations are expected to increase significantly in the near future due to less O3 titration by reduced NOx emissions. Applying an alternative emission scenario for Europe is found to have only a minor impact on the overall concentrations, which are dominated by the background changes. Climate change alone has a much smaller effect on the near-surface O3 concentrations over Belgium than the projected emission changes. The very high horizontal resolution that is used in this study results in much improved spatial correlations and simulated peak concentrations compared to a standard 25 km simulation. An analysis of the number of peak episodes during summer revealed that the emission reductions in RCP4.5 result in a 25% decrease of these peak episodes.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2014
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  • 7
    In: Geoscientific Model Development, Copernicus GmbH, Vol. 3, No. 2 ( 2010-10-06), p. 445-473
    Abstract: Abstract. We present a comprehensive description and benchmark evaluation of the tropospheric chemistry version of the global chemistry transport model TM5 (Tracer Model 5, version TM5-chem-v3.0). A full description is given concerning the photochemical mechanism, the interaction with aerosol, the treatment of the stratosphere, the wet and dry deposition parameterizations, and the applied emissions. We evaluate the model against a suite of ground-based, satellite, and aircraft measurements of components critical for understanding global photochemistry for the year 2006. The model exhibits a realistic oxidative capacity at a global scale. The methane lifetime is ~8.9 years with an associated lifetime of methyl chloroform of 5.86 years, which is similar to that derived using an optimized hydroxyl radical field. The seasonal cycle in observed carbon monoxide (CO) is well simulated at different regions across the globe. In the Northern Hemisphere CO concentrations are underestimated by about 20 ppbv in spring and 10 ppbv in summer, which is related to missing chemistry and underestimated emissions from higher hydrocarbons, as well as to uncertainties in the seasonal variation of CO emissions. The model also captures the spatial and seasonal variation in formaldehyde tropospheric columns as observed by SCIAMACHY. Positive model biases over the Amazon and eastern United States point to uncertainties in the isoprene emissions as well as its chemical breakdown. Simulated tropospheric nitrogen dioxide columns correspond well to observations from the Ozone Monitoring Instrument in terms of its seasonal and spatial variability (with a global spatial correlation coefficient of 0.89), but TM5 fields are lower by 25–40%. This is consistent with earlier studies pointing to a high bias of 0–30% in the OMI retrievals, but uncertainties in the emission inventories have probably also contributed to the discrepancy. TM5 tropospheric nitrogen dioxide profiles are in good agreement (within ~0.1 ppbv) with in situ aircraft observations from the INTEX-B campaign over (the Gulf of) Mexico. The model reproduces the spatial and seasonal variation in background surface ozone concentrations and tropospheric ozone profiles from the World Ozone and Ultraviolet Radiation Data Centre to within 10 ppbv, but at several tropical stations the model tends to underestimate ozone in the free troposphere. The presented model results benchmark the TM5 tropospheric chemistry version, which is currently in use in several international cooperation activities, and upon which future model improvements will take place.
    Type of Medium: Online Resource
    ISSN: 1991-9603
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2010
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  • 8
    In: Journal of Geophysical Research, American Geophysical Union (AGU), Vol. 111, No. D8 ( 2006)
    Type of Medium: Online Resource
    ISSN: 0148-0227
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2006
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  • 9
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 14, No. 9 ( 2014-05-13), p. 4679-4713
    Abstract: Abstract. Many of the next generation of global climate models will include aerosol schemes which explicitly simulate the microphysical processes that determine the particle size distribution. These models enable aerosol optical properties and cloud condensation nuclei (CCN) concentrations to be determined by fundamental aerosol processes, which should lead to a more physically based simulation of aerosol direct and indirect radiative forcings. This study examines the global variation in particle size distribution simulated by 12 global aerosol microphysics models to quantify model diversity and to identify any common biases against observations. Evaluation against size distribution measurements from a new European network of aerosol supersites shows that the mean model agrees quite well with the observations at many sites on the annual mean, but there are some seasonal biases common to many sites. In particular, at many of these European sites, the accumulation mode number concentration is biased low during winter and Aitken mode concentrations tend to be overestimated in winter and underestimated in summer. At high northern latitudes, the models strongly underpredict Aitken and accumulation particle concentrations compared to the measurements, consistent with previous studies that have highlighted the poor performance of global aerosol models in the Arctic. In the marine boundary layer, the models capture the observed meridional variation in the size distribution, which is dominated by the Aitken mode at high latitudes, with an increasing concentration of accumulation particles with decreasing latitude. Considering vertical profiles, the models reproduce the observed peak in total particle concentrations in the upper troposphere due to new particle formation, although modelled peak concentrations tend to be biased high over Europe. Overall, the multi-model-mean data set simulates the global variation of the particle size distribution with a good degree of skill, suggesting that most of the individual global aerosol microphysics models are performing well, although the large model diversity indicates that some models are in poor agreement with the observations. Further work is required to better constrain size-resolved primary and secondary particle number sources, and an improved understanding of nucleation and growth (e.g. the role of nitrate and secondary organics) will improve the fidelity of simulated particle size distributions.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2014
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  • 10
    Online Resource
    Online Resource
    Copernicus GmbH ; 2013
    In:  Atmospheric Chemistry and Physics Vol. 13, No. 4 ( 2013-02-27), p. 2267-2281
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 13, No. 4 ( 2013-02-27), p. 2267-2281
    Abstract: Abstract. The global methane (CH4) growth rate showed large variations after the eruption of Mount Pinatubo in June 1991. Both sources and sinks of tropospheric CH4 were altered following the eruption, by feedback processes between climate and tropospheric photochemistry. Such processes include Ultra Violet (UV) radiative changes due to the presence of volcanic sulfur dioxide (SO2) and sulphate aerosols in the stratosphere, and due to stratospheric ozone depletion. Changes in temperature and water vapour in the following years caused changes in tropospheric chemistry, as well as in natural emissions. We present a sensitivity study that investigates the relative effects that these processes had on tropospheric CH4 concentrations, using a simple one-dimensional chemistry model representative for the global tropospheric column. To infer the changes in UV radiative fluxes, the chemistry model is coupled to a radiative transfer model. We find that the overall effect of natural processes after the eruption on the CH4 growth rate is dominated by the reduction in CH4 lifetime due to stratospheric ozone depletion. However, all the other processes are found to have non-negligible effects, and should therefore be taken into account in order to obtain a good estimate of CH4 concentrations after Pinatubo. We find that the overall effect was a small initial increase in the CH4 growth rate after the eruption, followed by a decrease of about 7 ppb yr−1 by mid-1993. When changes in anthropogenic emissions are employed according to emission inventories, an additional decrease of about 5 ppb yr−1 in the CH4 growth rate is obtained between the years 1991 and 1993. The results using the simplified single column model are in good qualitative agreement with observed changes in the CH4 growth rate. Further analysis, taking into account changes in the dynamics of the atmosphere, variations in emissions from biomass burning, and in biogenic emissions of non-methane volatile organic compounds (NMVOC), requires the use of a full three-dimensional model.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2013
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