2,004 research outputs found
Changes in dissolved iron deposition to the oceans driven by human activity: a 3-D global modelling study
The global atmospheric iron (Fe) cycle is parameterized in the global 3-D chemical transport model TM4-ECPL to simulate the proton- and the organic ligand-promoted mineral-Fe dissolution as well as the aqueous-phase photochemical reactions between the oxidative states of Fe (III/II). Primary emissions of total (TFe) and dissolved (DFe) Fe associated with dust and combustion processes are also taken into account, with TFe mineral emissions calculated to amount to ~ 35 Tg-Fe yrâ1 and TFe emissions from combustion sources of ~ 2 Tg-Fe yrâ1. The model reasonably simulates the available Fe observations, supporting the reliability of the results of this study. Proton- and organic ligand-promoted Fe dissolution in present-day TM4-ECPL simulations is calculated to be ~ 0.175 Tg-Fe yrâ1, approximately half of the calculated total primary DFe emissions from mineral and combustion sources in the model (~ 0.322 Tg-Fe yrâ1). The atmospheric burden of DFe is calculated to be ~ 0.024 Tg-Fe. DFe deposition presents strong spatial and temporal variability with an annual flux of ~ 0.496 Tg-Fe yrâ1, from which about 40 % (~ 0.191 Tg-Fe yrâ1) is deposited over the ocean. The impact of air quality on Fe deposition is studied by performing sensitivity simulations using preindustrial (year 1850), present (year 2008) and future (year 2100) emission scenarios. These simulations indicate that about a 3 times increase in Fe dissolution may have occurred in the past 150 years due to increasing anthropogenic emissions and thus atmospheric acidity. Air-quality regulations of anthropogenic emissions are projected to decrease atmospheric acidity in the near future, reducing to about half the dust-Fe dissolution relative to the present day. The organic ligand contribution to Fe dissolution shows an inverse relationship to the atmospheric acidity, thus its importance has decreased since the preindustrial period but is projected to increase in the future. The calculated changes also show that the atmospheric DFe supply to the globe has more than doubled since the preindustrial period due to 8-fold increases in the primary non-dust emissions and about a 3-fold increase in the dust-Fe dissolution flux. However, in the future the DFe deposition flux is expected to decrease (by about 25 %) due to reductions in the primary non-dust emissions (about 15 %) and in the dust-Fe dissolution flux (about 55 %). The present level of atmospheric deposition of DFe over the global ocean is calculated to be about 3 times higher than for 1850 emissions, and about a 30 % decrease is projected for 2100 emissions. These changes are expected to impact most on the high-nutrientâlow-chlorophyll oceanic regions
ÎÎAÎÎ΄ΊÎÎ ÎŁÎYΊÎÎ ÎΠΠ΀ÎÎ ÎΥΧÎIÎ ÎAÎ Î Î (ÎÎĄÎ΄ΥÎYÎ ÎÎÎ) Σ΀ΠΥEΞ΄ÎÎÎ
This article examines the skyphoi with relief decoration retrieved from the rescue excavation of the Voughioukalaki area, which is located within ancient Lappa, in the territory of modern Argyroupolis near Rethymno. The two hundred and thirty six sherds found in a domestic context enrich the available documentation on the socio-economic conditions of Lappa during the Hellenistic period, highlighting the commercial relationships of the city with the other trade-centres of that period. The morphological, technical and iconographic analysis of these skyphoi with relief decoration aims to complete the existing bibliography concerning this particular Cretan class of pottery
Formation and growth of atmospheric nanoparticles in the eastern Mediterranean : results from long-term measurements and process simulations
Atmospheric new particle formation (NPF) is a common phenomenon all over the world. In this study we present the longest time series of NPF records in the eastern Mediterranean region by analyzing 10 years of aerosol number size distribution data obtained with a mobility particle sizer. The measurements were performed at the Finokalia environmental research station on Crete, Greece, during the period June 2008-June 2018. We found that NPF took place on 27% of the available days, undefined days were 23% and non-event days 50 %. NPF is more frequent in April and May probably due to the terrestrial biogenic activity and is less frequent in August. Throughout the period under study, nucleation was observed also during the night. Nucleation mode particles had the highest concentration in winter and early spring, mainly because of the minimum sinks, and their average contribution to the total particle number concentration was 8 %. Nucleation mode particle concentrations were low outside periods of active NPF and growth, so there are hardly any other local sources of sub-25 nm particles. Additional atmospheric ion size distribution data simultaneously collected for more than 2 years were also analyzed. Classification of NPF events based on ion spectrometer measurements differed from the corresponding classification based on a mobility spectrometer, possibly indicating a different representation of local and regional NPF events between these two measurement data sets. We used the MALTE-Box model for simulating a case study of NPF in the eastern Mediterranean region. Monoterpenes contributing to NPF can explain a large fraction of the observed NPF events according to our model simulations. However the adjusted parameterization resulting from our sensitivity tests was significantly different from the initial one that had been determined for the boreal environment.Peer reviewe
Chemical and dynamical identification of emission outflows during the HALO campaign EMeRGe in Europe and Asia
The number of large urban agglomerations is steadily increasing worldwide. At a local scale, their emissions lead to air pollution, directly affecting people\u27s health. On a global scale, their emissions lead to an increase of greenhouse gases, affecting climate. In this context, in 2017 and 2018, the airborne campaign EMeRGe (Effect of Megacities on the transport and transformation of pollutants on the Regional to Global scales) investigated emissions of European and Asian major population centres (MPCs) to improve the understanding and predictability of pollution outflows. Here, we present two methods to identify and characterise pollution outflows probed during EMeRGe. First, we use a set of volatile organic compounds (VOCs) as chemical tracers to characterise air masses by specific source signals, i.e. benzene from anthropogenic pollution of targeted regions, acetonitrile from biomass burning (BB, primarily during EMeRGe-Asia), and isoprene from fresh biogenic signals (primarily during EMeRGe-Europe. Second, we attribute probed air masses to source regions and estimate their individual contribution by constructing and applying a simple emission uptake scheme for the boundary layer which combines FLEXTRA back trajectories and EDGAR carbon monoxide (CO) emission rates (acronyms are provided in the Appendix). During EMeRGe-Europe, we identified anthropogenic pollution outflows from northern Italy, southern Great Britain, the BelgiumâNetherlandsâRuhr (BNR) area and the Iberian Peninsula. Additionally, our uptake scheme indicates significant long-range transport of pollution from the USA and Canada. During EMeRGe-Asia, the pollution outflow is dominated by sources in China and Taiwan, but BB signals from Southeast Asia and India contribute as well. Outflows of pre-selected MPC targets are identified in less than 20â% of the sampling time, due to restrictions in flight planning and constraints of the measurement platform itself. Still, EMeRGe combines in a unique way near- and far-field measurements, which show signatures of local and distant sources, transport and conversion fingerprints, and complex air mass compositions. Our approach provides a valuable classification and characterisation of the EMeRGe dataset, e.g. for BB and anthropogenic influence of potential source regions and paves the way for a more comprehensive analysis and various model studies
Observation- and model-based estimates of particulate dry nitrogen deposition to the oceans
Anthropogenic nitrogen (N) emissions to the atmosphere have increased significantly the deposition of nitrate (NO3-) and ammonium (NH4+) to the surface waters of the open ocean, with potential impacts on marine productivity and the global carbon cycle. Global-scale understanding of the impacts of N deposition to the oceans is reliant on our ability to produce and validate models of nitrogen emission, atmospheric chemistry, transport and deposition. In this work, ~2900 observations of aerosol NO3- and NH4+ concentrations, acquired from sampling aboard ships in the period 1995 - 2012, are used to assess the performance of modelled N concentration and deposition fields over the remote ocean. Three ocean regions (the eastern tropical North Atlantic, the northern Indian Ocean and northwest Pacific) were selected, in which the density and distribution of observational data were considered sufficient to provide effective comparison to model products. All of these study regions are affected by transport and deposition of mineral dust, which alters the deposition of N, due to uptake of nitrogen oxides (NOx) on mineral surfaces. Assessment of the impacts of atmospheric N deposition on the ocean requires atmospheric chemical transport models to report deposition fluxes, however these fluxes cannot be measured over the ocean. Modelling studies such as the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP), which only report deposition flux are therefore very difficult to validate for dry deposition. Here the available observational data were averaged over a 5° x 5° grid and compared to ACCMIP dry deposition fluxes (ModDep) of oxidised N (NOy) and reduced N (NHx) and to the following parameters from the TM4-ECPL (TM4) model: ModDep for NOy, NHx and particulate NO3- and NH4+, and surface-level particulate NO3- and NH4+ concentrations. As a model ensemble, ACCMIP can be expected to be more robust than TM4, while TM4 gives access to speciated parameters (NO3- and NH4+) that are more relevant to the observed parameters and which are not available in ACCMIP. Dry deposition fluxes (CalDep) were calculated from the observed concentrations using estimates of dry deposition velocities. Model â observation ratios, weighted by grid-cell area and numbers of observations, (RA,n) were used to assess the performance of the models. Comparison in the three study regions suggests that TM4 over-estimates NO3- concentrations (RA,n = 1.4 â 2.9) and under-estimates NH4+ concentrations (RA,n = 0.5 â 0.7), with spatial distributions in the tropical Atlantic and northern Indian Ocean not being reproduced by the model. In the case of NH4+ in the Indian Ocean, this discrepancy was probably due to seasonal biases in the sampling. Similar patterns were observed in the various comparisons of CalDep to ModDep (RA,n = 0.6 â 2.6 for NO3-, 0.6 â 3.1 for NH4+). Values of RA,n for NHx CalDep - ModDep comparisons were approximately double the corresponding values for NH4+ CalDep - ModDep comparisons due to the significant fraction of gas-phase NH3 deposition incorporated in the TM4 and ACCMIP NHx model products. All of the comparisons suffered due to the scarcity of observational data and the large uncertainty in dry deposition velocities used to derive deposition fluxes from concentrations. These uncertainties have been a major limitation on estimates of the flux of material to the oceans for several decades. Recommendations are made for improvements in N deposition estimation through changes in observations, modelling and model â observation comparison procedures. Validation of modelled dry deposition requires effective comparisons to observable aerosol-phase species concentrations and this cannot be achieved if model products only report dry deposition flux over the ocean
Chemical and dynamical identification of emission outflows during the HALO campaign EMeRGe in Europe and Asia
The airborne megacity campaign EMeRGe provided an unprecedented amount of trace gas measurements. We combine measured volatile organic compounds (VOCs) with trajectory-modelled emission uptakes to identify potential source regions of pollution. We also characterise the chemical fingerprints (e.g. biomass burning and anthropogenic signatures) of the probed air masses to corroborate the contributing source regions. Our approach is the first large-scale study of VOCs originating from megacities
High temperature sensitivity of monoterpene emissions from global vegetation
AbstractTerrestrial vegetation emits vast amounts of monoterpenes into the atmosphere, influencing ecological interactions and atmospheric chemistry. Global emissions are simulated as a function of temperature with a fixed exponential relationship (ÎČ coefficient) across forest ecosystems and environmental conditions. We applied meta-analysis algorithms on 40 years of published monoterpene emission data and show that relationship between emissions and temperature is more sensitive and intricate than previously thought. Considering the entire dataset, a higher temperature sensitivity (ÎČâ=â0.13â±â0.01â°Câ1) is derived but with a linear increase with the reported coefficients of determination (R2), indicating that co-occurring environmental factors modify the temperature sensitivity of the emissions that is primarily related to the specific plant functional type (PFT). Implementing a PFT-dependent ÎČ in a biogenic emission model, coupled with a chemistry â climate model, demonstrated that atmospheric processes are exceptionally dependent on monoterpene emissions which are subject to amplified variations under rising temperatures.</jats:p
Evaluation of global simulations of aerosol particle and cloud condensation nuclei number, with implications for cloud droplet formation
A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011-2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of -24 % and -35 % for particles with dry diameters > 50 and > 120 nm, as well as -36 % and -34 % for CCN at supersaturations of 0.2 % and 1.0 %, respectively. However, they seem to behave differently for particles activating at very low supersaturations (<0.1 %) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N-3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2 % (CCN0.2) compared to that for N-3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120 nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40 % during winter and 20 % in summer. In contrast to the large spread in simulated aerosol particle and CCN number concentrations, the CDNC derived from simulated CCN spectra is less diverse and in better agreement with CDNC estimates consistently derived from the observations (average NMB -13 % and -22 % for updraft velocities 0.3 and 0.6 m s(-1), respectively). In addition, simulated CDNC is in slightly better agreement with observationally derived values at lower than at higher updraft velocities (index of agreement 0.64 vs. 0.65). The reduced spread of CDNC compared to that of CCN is attributed to the sublinear response of CDNC to aerosol particle number variations and the negative correlation between the sensitivities of CDNC to aerosol particle number concentration (partial derivative N-d/partial derivative N-a) and to updraft velocity (partial derivative N-d/partial derivative w). Overall, we find that while CCN is controlled by both aerosol particle number and composition, CDNC is sensitive to CCN at low and moderate CCN concentrations and to the updraft velocity when CCN levels are high. Discrepancies are found in sensitivities partial derivative N-d/partial derivative N-a and partial derivative N-d/partial derivative w; models may be predisposed to be too "aerosol sensitive" or "aerosol insensitive" in aerosol-cloud-climate interaction studies, even if they may capture average droplet numbers well. This is a subtle but profound finding that only the sensitivities can clearly reveal and may explain intermodel biases on the aerosol indirect effect.Peer reviewe
- âŠ