Modelling the chemically aged and mixed aerosols over the eastern central Atlantic Ocean – potential impacts

Detailed information on the chemical and physical properties of aerosols is important for assessing their role in air quality and climate. This work explores the origin and fate of continental aerosols transported over the Central Atlantic Ocean, in terms of chemical composition, number and size distribution, using chemistry-transport models, satellite data and in situ measurements. We focus on August 2005, a period with intense hurricane and tropical storm activity over the Atlantic Ocean. A mixture of anthropogenic (sulphates, nitrates), natural (desert dust, sea salt) and chemically aged (sulphate and nitrate on dust) aerosols is found entering the hurricane genesis region, most likely interacting with clouds in the area. Results from our modelling study suggest rather small amounts of accumulation mode desert dust, sea salt and chemically aged dust aerosols in this Atlantic Ocean region. Aerosols of smaller size (Aitken mode) are more abundant in the area and in some occasions sulphates of anthropogenic origin and desert dust are of the same magnitude in terms of number concentrations. Typical aerosol number concentrations are derived for the vertical layers near shallow cloud formation regimes, indicating that the aerosol number concentration can reach several thousand particles per cubic centimetre. The vertical distribution of the aerosols shows that the desert dust particles are often transported near the top of the marine cloud layer as they enter into the region where deep convection is initiated. The anthropogenic sulphate aerosol can be transported within a thick layer and enter the cloud deck through multiple ways (from the top, the base of the cloud, and by entrainment). The sodium (sea salt related) aerosol is mostly found below the cloud base. The results of this work may provide insights relevant for studies that consider aerosol influences on cloud processes and storm development in the Central Atlantic region

Kinetic comparison of tissue non-specific and placental human alkaline phosphatases expressed in baculovirus infected cells: application to screening for Down's syndrome

BACKGROUND: In humans, there are four alkaline phosphatases, and each form exibits a characteristic pattern of tissue distribution. The availability of an easy method to reveal their activity has resulted in large amount of data reporting correlations between variations in activity and illnesses. For example, alkaline phosphatase from neutrophils of mothers pregnent with a trisomy 21 fetus (Down's syndrome) displays significant differences both in its biochemical and immunological properties, and in its affinity for some specific inhibitors. RESULTS: To analyse these differences, the biochemical characteristics of two isozymes (non specific and placental alkaline phosphatases) were expressed in baculovirus infected cells. Comparative analysis of the two proteins allowed us to estimate the kinetic constants of denaturation and sensitivity to two inhibitors (L-p-bromotetramisole and thiophosphate), allowing better discrimination between the two enzymes. These parameters were then used to estimate the ratio of the two isoenzymes in neutrophils of pregnant mothers with or without a trisomy 21 fetus. It appeared that the placental isozyme represented 13% of the total activity of neutrophils of non pregnant women. This proportion did not significantly increase with normal pregnancy. By contrast, in pregnancies with trisomy 21 fetus, the proportion reached 60–80% of activity. CONCLUSION: Over-expression of the placental isozyme compared with the tissue-nonspecific form in neutrophils of mother with a trisomy 21 fetus may explain why the characteristics of the alkaline phosphatase in these cells is different from normal. Application of this knowledge could improve the potential of using alkaline phosphatase measurements to screen for Down's syndrome

Recurrent myelitis after allogeneic stem cell transplantation. Report of two cases

<p>Abstract</p> <p>Background</p> <p>Allogeneic and autologous haematopoietic stem cell transplantation are established treatment options for haematological malignancies and may possibly be employed to treat a range of genetic and autoimmune diseases.</p> <p>Case presentation</p> <p>We report two patients who developed an acute myelitis within their thoracic spinal cord after allogeneic stem cell transplantation. Myelitis in these patients was not related to graft versus host disease or immune reconstitution and was responsive to intravenous methylprednisolone and cyclophosphamide.</p> <p>Conclusions</p> <p>Myelitis is a possibly disabling consequence of haematopoietic stem cell transplantation.</p

Optimizing a dynamic fossil fuel CO2 emission model with CTDAS (CarbonTracker Data Assimilation Shell, v1.0) for an urban area using atmospheric observations of CO2, CO, NOx, and SO2

We present a modelling framework for fossil fuel CO2 emissions in an urban environment, which allows constraints from emission inventories to be combined with atmospheric observations of CO2 and its co-emitted species CO, NOx , and SO2. Rather than a static assignment of average emission rates to each unit area of the urban domain, the fossil fuel emissions we use are dynamic: they vary in time and space in relation to data that describe or approximate the activity within a sector, such as traffic density, power demand, 2m temperature (as proxy for heating demand), and sunlight and wind speed (as proxies for renewable energy supply). Through inverse modelling, we optimize the relationships between these activity data and the resulting emissions of all species within the dynamic fossil fuel emission model, based on atmospheric mole fraction observations. The advantage of this novel approach is that the optimized parameters (emission factors and emission ratios, N D 44) in this dynamic emission model (a) vary much less over space and time, (b) allow for a physical interpretation of mean and uncertainty, and (c) have better defined uncertainties and covariance structure. This makes them more suited to extrapolate, optimize, and interpret than the gridded emissions themselves. The merits of this approach are investigated using a pseudo-observation-based ensemble Kalman filter inversion set-up for the Dutch Rijnmond area at 1km-1km resolution. We find that the fossil fuel emission model approximates the gridded emissions well (annual mean differences < 2 %, hourly temporal r2 D 0:21-0.95), while reported errors in the underlying parameters allow a full covariance structure to be created readily. Propagating this error structure into atmospheric mole fractions shows a strong dominance of a few large sectors and a few dominant uncertainties, most notably the emission ratios of the various gases considered. If the prior emission ratios are either sufficiently well-known or well constrained from a dense observation network, we find that including observations of co-emitted species improves our ability to estimate emissions per sector relative to using CO2 mole fractions only. Nevertheless, the total CO2 emissions can be well constrained with CO2 as the only tracer in the inversion. Because some sectors are sampled only sparsely over a day, we find that propagating solutions from day-to-day leads to largest uncertainty reduction and smallest CO2 residuals over the 14 consecutive days considered. Although we can technically estimate the temporal distribution of some emission categories like shipping separate from their total magnitude, the controlling parameters are difficult to distinguish. Overall, we conclude that our new system looks promising for application in verification studies, provided that reliable urban atmospheric transport fields and reasonable a priori emission ratios for CO2 and its co-emitted species can be produced

Evaluation of a three-dimensional chemical transport model (PMCAMx) in the European domain during the EUCAARI May 2008 campaign

PMCAMx-2008, a detailed three-dimensional chemical transport model (CTM), was applied to Europe to simulate the mass concentration and chemical composition of particulate matter (PM) during May 2008. The model includes a state-of-the-art organic aerosol module which is based on the volatility basis set framework treating both primary and secondary organic components as semivolatile and photochemically reactive. The model performance is evaluated against high time resolution aerosol mass spectrometer (AMS) ground and airborne measurements. Overall, organic aerosol is predicted to account for 32% of total PM&lt;sub&gt;1&lt;/sub&gt; at ground level during May 2008, followed by sulfate (30%), crustal material and sea-salt (14%), ammonium (13%), nitrate (7%), and elemental carbon (4%). The model predicts that fresh primary OA (POA) is a small contributor to organic PM concentrations in Europe during late spring, and that oxygenated species (oxidized primary and biogenic secondary) dominate the ambient OA. The Mediterranean region is the only area in Europe where sulfate concentrations are predicted to be much higher than the OA, while organic matter is predicted to be the dominant PM&lt;sub&gt;1&lt;/sub&gt; species in central and northern Europe. The comparison of the model predictions with the ground measurements in four measurement stations is encouraging. The model reproduces more than 94% of the daily averaged data and more than 87% of the hourly data within a factor of 2 for PM&lt;sub&gt;1&lt;/sub&gt; OA. The model tends to predict relatively flat diurnal profiles for PM&lt;sub&gt;1&lt;/sub&gt; OA in many areas, both rural and urban in agreement with the available measurements. The model performance against the high time resolution airborne measurements at multiple altitudes and locations is as good as its performance against the ground level hourly measurements. There is no evidence of missing sources of OA aloft over Europe during this period

Novel KRIT1/CCM1 mutation in a patient with retinal cavernous hemangioma and cerebral cavernous malformation

Retinal cavernous hemangiomas are rare vascular anomalies, and can be associated with cerebral cavernous malformations (CCM). Distinct mutations have been reported in patients who have both CCMs and retinal cavernous hemangiomas. Fluorescein angiography, spectral domain optical coherence tomography, and genetic testing were performed on a patient with a retinal cavernous hemangioma and a CCM. Our patient was heterozygous in the KRIT1/CCM1 gene for a frameshift mutation, c.1088delC. This would be predicted to result in premature protein termination. We have identified a novel mutation in the KRIT1/CCM1 gene in a patient with both CCM and retinal cavernous hemangioma. We hypothesize that the occurrence of retinal cavernous hemangiomas and CCMs is underlaid by a common mechanism present in the KRIT1/CCM1 gene

Methane and ethane emission scenarios for potential shale gas production in Europe

A main concern surrounding (shale) gas production and exploitation is the leakage of methane, a potent greenhouse gas. High leakage rates have been observed outside of Europe but the representativeness of these observations for Europe is unknown. To facilitate the monitoring of methane leakage from a future shale gas industry in Europe we developed potential production scenarios for ten major shale gas plays and identified a suitable tracer in (shale) gas to distinguish oil and gas related emissions from other methane sources. To distinguish gas leakage from other methane sources we propose ethane, a known tracer for leakage from oil and gas production but absent in emissions from other important methane sources in Europe. Ethane contents for the ten plays are estimated from a European gas composition database and shale gas composition and reservoir data from the US, resulting in three different classes of ethane to methane ratios in the raw gas (0.015, 0.04 and 0.1). The ethane content classes have a relation with the average thermal maturity, a basic shale gas reservoir characteristic, which is known for all ten European shale gas plays. By assuming different production scenarios in addition to a range of possible gas leakage rates, we estimate potential ethane tracer release by shale gas play. Ethane emissions are estimated by play following a low, medium or high gas production scenario in combination with leakage rates ranging from 0.2&thinsp;%–10&thinsp;% based on observed leakage rates in the US.</p

Organic aerosol concentration and composition over Europe: insights from comparison of regional model predictions with aerosol mass spectrometer factor analysis

A detailed three-dimensional regional chemical transport model (Particulate Matter Comprehensive Air Quality Model with Extensions, PMCAMx) was applied over Europe, focusing on the formation and chemical transformation of organic matter. Three periods representative of different seasons were simulated, corresponding to intensive field campaigns. An extensive set of AMS measurements was used to evaluate the model and, using factor-analysis results, gain more insight into the sources and transformations of organic aerosol (OA). Overall, the agreement between predictions and measurements for OA concentration is encouraging, with the model reproducing two-thirds of the data (daily average mass concentrations) within a factor of 2. Oxygenated OA (OOA) is predicted to contribute 93% to total OA during May, 87% during winter and 96% during autumn, with the rest consisting of fresh primary OA (POA). Predicted OOA concentrations compare well with the observed OOA values for all periods, with an average fractional error of 0.53 and a bias equal to −0.07 (mean error = 0.9 μg m−3, mean bias = −0.2 μg m−3). The model systematically underpredicts fresh POA at most sites during late spring and autumn (mean bias up to −0.8 μg m−3). Based on results from a source apportionment algorithm running in parallel with PMCAMx, most of the POA originates from biomass burning (fires and residential wood combustion), and therefore biomass burning OA is most likely underestimated in the emission inventory. The sensitivity of POA predictions to the corresponding emissions' volatility distribution is discussed. The model performs well at all sites when the Positive Matrix Factorization (PMF)-estimated low-volatility OOA is compared against the OA with saturation concentrations of the OA surrogate species C* ≤ 0.1 μg m−3 and semivolatile OOA against the OA with C* > 0.1 μg m−3