686 research outputs found
Investigating the quality of modeled aerosol profiles based on combined lidar and sunphotometer data
In this study we present an evaluation of the Comprehensive Air Quality Model with extensions (CAMx) for Thessaloniki using radiometric and lidar data. The aerosol mass concentration profiles of CAMx are compared against the PM2.5 and PM2. 5−10 concentration profiles retrieved by the Lidar-Radiometer Inversion Code (LIRIC). The CAMx model and the LIRIC algorithm results were compared in terms of mean mass concentration profiles, center of mass and integrated mass concentration in the boundary layer and the free troposphere. The mean mass concentration comparison resulted in profiles within the same order of magnitude and similar vertical structure for the PM2. 5 particles. The mean centers of mass values are also close, with a mean bias of 0.57 km. On the opposite side, there are larger differences for the PM2. 5−10 mode, both in the boundary layer and in the free troposphere. In order to grasp the reasons behind the discrepancies, we investigate the effect of aerosol sources that are not properly included in the model's emission inventory and in the boundary conditions such as the wildfires and the desert dust component. The identification of the cases that are affected by wildfires is performed using wind backward trajectories from the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model in conjunction with satellite fire pixel data from MODerate-resolution Imaging Spectroradiometer (MODIS) Terra and Aqua global monthly fire location product MCD14ML. By removing those cases the correlation coefficient improves from 0.69 to 0.87 for the PM2. 5 integrated mass in the boundary layer and from 0.72 to 0.89 in the free troposphere. The PM2.5 center of mass fractional bias also decreases to 0.38 km. Concerning the analysis of the desert dust component, the simulations from the Dust Regional Atmospheric Model (BSC-DREAM8b) were deployed. When only the Saharan dust cases are taken into account, BSC-DREAM8b generally outperforms CAMx when compared with LIRIC, achieving a correlation of 0.91 and a mean bias of −29.1 % for the integrated mass in the free troposphere and a correlation of 0.57 for the center of mass. CAMx, on the other hand, underestimates the integrated mass in the free troposphere. Consequently, the accuracy of CAMx is limited concerning the transported Saharan dust cases. We conclude that the performance of CAMx appears to be best for the PM2.5 particles, both in the boundary layer and in the free troposphere. Sources of particles not properly taken into account by the model are confirmed to negatively affect its performance, especially for the PM2. 5−10 particles.The authors would like to acknowledge the
EU projects MACC-III (Monitoring Atmospheric Composition and Climate – III, grant agreement no. 633080) and MACC-II project
(Monitoring Atmospheric Composition and Climate – Interim Implementation, grant agreement no. 283576). The simulated
results presented in this research paper have been produced using the EGI and HellasGrid infrastructures. The ACTRIS-2 project
from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 654109 is gratefully
acknowledged. The authors would also like to acknowledge the support provided by the Scientific Computing Center at Aristotle
University of Thessaloniki throughout the progress of the work on air quality forecasting. BSC-DREAM8b simulations were performed
on the Mare Nostrum supercomputer hosted by Barcelona Supercomputing Center-Centro Nacional de Supercomputacion (BSC-CNS). S. Basart wants to acknowledge the CICYT project (CGL2013-46736). Elina Giannakaki acknowledges the support of the Academy of Finland (project no. 270108).Peer ReviewedPostprint (published version
Intercomparison of Metop-A SO2 measurements during the 2010- 2011 Icelandic eruptions
The European Space Agency project Satellite Monitoring of Ash and Sulphur Dioxide for the mitigation of Aviation
Hazards, was introduced after the eruption of the Icelandic volcano Eyjafjallajökull in the spring of 2010
to facilitate the development of an optimal EndtoEnd
System for Volcanic Ash Plume Monitoring and Prediction.
The Eyjafjallajökull plume drifted towards Europe and caused major disruptions of European air traffic for
several weeks affecting the everyday life of millions of people. The limitations in volcanic plume monitoring and
prediction capabilities gave birth to this observational system which is based on comprehensive satellitederived
ash plume and sulphur dioxide [SO2] level estimates, as well as a widespread validation using supplementary
satellite, aircraft and groundbased
measurements. Intercomparison
of the volcanic total SO2 column and
plume height observed by GOME2/
MetopA
and IASI/MetopA
are shown before, during and after the Eyjafjallajökull
2010 eruptions as well as for the 2011 Grímsvötn eruption. Colocated
groundbased
Brewer Spectrophotometer
data extracted from the World Ozone and Ultraviolet Radiation Data Centre for de Bilt, the Netherlands,
are also compared to the different satellite estimates. Promising agreement is found for the two different
types of instrument for the SO2 columns with linear regression coefficients ranging around from 0.64 when
comparing the different instruments and 0.85 when comparing the two different IASI algorithms. The agreement
for the plume height is lower, possibly due to the major differences between the height retrieval part of the
GOME2 and IASI algorithms. The comparisons with the Brewer groundbased
station in de Bilt, The Netherlands
show good qualitative agreement for the peak of the event however stronger eruptive signals are required
for a longer quantitative comparison
Nine years of UV aerosol optical depth measurements at Thessaloniki, Greece
Spectral measurements of the aerosol optical depth (AOD) and the Ångström coefficient were conducted at Thessaloniki, Greece (40.5° N, 22.9° E) between January 1997 and December 2005 with a Brewer MKIII double-monochromator spectroradiometer. The dataset was compared with collocated measurements of a second spectroradiometer (Brewer MKII) and a CIMEL sun-photometer, showing correlations of 0.93 and 0.98, respectively. A seasonal variation of the AOD was observed at Thessaloniki, with AOD values at 340 nm of 0.52 and 0.28 for August and December respectively. Back trajectories of air masses for up to 4 days were used to assess the influence of long-range transport from various regions to the aerosol load over Thessaloniki. It is shown that part of the observed seasonality can be attributed to air masses with high AOD originating from North-Eastern and Eastern directions during summertime. The analysis of the long-term record (9 years) of AOD showed a downward tendency. A similar decreasing tendency was found in the record of the PM aerosol measurements, which are conducted near the surface at 4 air-quality monitoring stations in the area of the city of Thessaloniki
Geophysical validation and long-term consistency between GOME-2/MetOp-A total ozone column and measurements from the sensors GOME/ERS-2, SCIAMACHY/ENVISAT and OMI/Aura
The main aim of the paper is to assess the consistency of five years of Global Ozone Monitoring Experiment-2/Metop-A [GOME-2] total ozone columns and the long-term total ozone satellite monitoring database already in existence through an extensive inter-comparison and validation exercise using as reference Brewer and Dobson ground-based measurements. The behaviour of the GOME-2 measurements is being weighed against that of GOME (1995–2011), Ozone Monitoring Experiment [OMI] (since 2004) and the Scanning Imaging Absorption spectroMeter for Atmospheric CartograpHY [SCIAMACHY] (since 2002) total ozone column products. Over the background truth of the ground-based measurements, the total ozone columns are inter-evaluated using a suite of established validation techniques; the GOME-2 time series follow the same patterns as those observed by the other satellite sensors. In particular, on average, GOME-2 data underestimate GOME data by about 0.80%, and underestimate SCIAMACHY data by 0.37% with no seasonal dependence of the differences between GOME-2, GOME and SCIAMACHY. The latter is expected since the three datasets are based on similar DOAS algorithms. This underestimation of GOME-2 is within the uncertainty of the reference data used in the comparisons. Compared to the OMI sensor, on average GOME-2 data underestimate OMI_DOAS (collection 3) data by 1.28%, without any significant seasonal dependence of the differences between them. The lack of seasonality might be expected since both the GOME data processor [GDP] 4.4 and OMI_DOAS are DOAS-type algorithms and both consider the variability of the stratospheric temperatures in their retrievals. Compared to the OMI_TOMS (collection 3) data, no bias was found. We hence conclude that the GOME-2 total ozone columns are well suitable to continue the long-term global total ozone record with the accuracy needed for climate monitoring studies
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EARLINET: 12-year of aerosol profiling over Europe
EARLINET has been collecting high quality aerosol optical profiles over Europe since 2000. The comparison with automatic collected dataset of aerosol optical depth (AOD) from AERONET and MODIS demonstrates the effectiveness of EARLINET regular measurement schedule for climatological studies. The analysis of optical properties in the local boundary layer indicates that the general decrease of AOD observed by different platforms over Europe in the last decade could be due to the modification of aerosol properties (towards less absorbing and larger particles) in the lower troposphere
Four-dimensional distribution of the 2010 Eyjafjallajökull volcanic cloud over Europe observed by EARLINET
© Author(s) 2013. This work is distributed under the Creative Commons Attribution 3.0 License.The eruption of the Icelandic volcano Eyjafjallaj ökull in April-May 2010 represents a "natural experiment" to study the impact of volcanic emissions on a continental scale. For the first time, quantitative data about the presence, altitude, and layering of the volcanic cloud, in conjunction with optical information, are available for most parts of Europe derived from the observations by the European Aerosol Research Lidar NETwork (EARLINET). Based on multi-wavelength Raman lidar systems, EARLINET is the only instrument worldwide that is able to provide dense time series of high-quality optical data to be used for aerosol typing and for the retrieval of particle microphysical properties as a function of altitude. In this work we show the four-dimensional (4-D) distribution of the Eyjafjallajökull volcanic cloud in the troposphere over Europe as observed by EARLINET during the entire volcanic event (15 April-26 May 2010). All optical properties directly measured (backscatter, extinction, and particle linear depolarization ratio) are stored in the EARLINET database available at www.earlinet.org. A specific relational database providing the volcanic mask over Europe, realized ad hoc for this specific event, has been developed and is available on request at www.earlinet.org. During the first days after the eruption, volcanic particles were detected over Central Europe within a wide range of altitudes, from the upper troposphere down to the local planetary boundary layer (PBL). After 19 April 2010, volcanic particles were detected over southern and south-eastern Europe. During the first half of May (5-15 May), material emitted by the Eyjafjallajökull volcano was detected over Spain and Portugal and then over the Mediterranean and the Balkans. The last observations of the event were recorded until 25 May in Central Europe and in the Eastern Mediterranean area. The 4-D distribution of volcanic aerosol layering and optical properties on European scale reported here provides an unprecedented data set for evaluating satellite data and aerosol dispersion models for this kind of volcanic events.Peer reviewe
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LIVAS: A 3-D multi-wavelength aerosol/cloud database based on CALIPSO and EARLINET
We present LIVAS (LIdar climatology of Vertical Aerosol Structure for space-based lidar simulation studies), a 3-D multi-wavelength global aerosol and cloud optical database, optimized to be used for future space-based lidar end-to-end simulations of realistic atmospheric scenarios as well as retrieval algorithm testing activities. The LIVAS database provides averaged profiles of aerosol optical properties for the potential spaceborne laser operating wavelengths of 355, 532, 1064, 1570 and 2050 nm and of cloud optical properties at the wavelength of 532 nm. The global database is based on CALIPSO observations at 532 and 1064 nm and on aerosol-type-dependent backscatter- and extinction-related Ångström exponents, derived from EARLINET (European Aerosol Research Lidar Network) ground-based measurements for the UV and scattering calculations for the IR wavelengths, using a combination of input data from AERONET, suitable aerosol models and recent literature. The required spectral conversions are calculated for each of the CALIPSO aerosol types and are applied to CALIPSO backscatter and extinction data corresponding to the aerosol type retrieved by the CALIPSO aerosol classification scheme. A cloud optical database based on CALIPSO measurements at 532 nm is also provided, neglecting wavelength conversion due to approximately neutral scattering behavior of clouds along the spectral range of LIVAS. Averages of particle linear depolarization ratio profiles at 532 nm are provided as well. Finally, vertical distributions for a set of selected scenes of specific atmospheric phenomena (e.g., dust outbreaks, volcanic eruptions, wild fires, polar stratospheric clouds) are analyzed and spectrally converted so as to be used as case studies for spaceborne lidar performance assessments. The final global data set includes 4-year (1 January 2008–31 December 2011) time-averaged CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) data on a uniform grid of 1° × 1° with the original high vertical resolution of CALIPSO in order to ensure realistic simulations of the atmospheric variability in lidar end-to-end simulations
A Dual-Color Fluorescence-Based Platform to Identify Selective Inhibitors of Akt Signaling
Background: Inhibition of Akt signaling is considered one of the most promising therapeutic strategies for many cancers. However, rational target-orientated approaches to cell based drug screens for anti-cancer agents have historically been compromised by the notorious absence of suitable control cells. Methodology/Principal Findings: In order to address this fundamental problem, we have developed BaFiso, a live-cell screening platform to identify specific inhibitors of this pathway. BaFiso relies on the co-culture of isogenic cell lines that have been engineered to sustain interleukin-3 independent survival of the parental Ba/F3 cells, and that are individually tagged with different fluorescent proteins. Whilst in the first of these two lines cell survival in the absence of IL-3 is dependent on the expression of activated Akt, the cells expressing constitutively-activated Stat5 signaling display IL-3 independent growth and survival in an Akt-independent manner. Small molecules can then be screened in these lines to identify inhibitors that rescue IL-3 dependence. Conclusions/Significance: BaFiso measures differential cell survival using multiparametric live cell imaging and permits selective inhibitors of Akt signaling to be identified. BaFiso is a platform technology suitable for the identification of smal
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