The average of atmospheric vertical profiles

A new method to perform averages of atmospheric vertical profiles is presented. The method allows changing a-posteriori the strength of the constraint used in the retrievals of the single profiles with the purpose of optimizing the trade-off between measurement error and vertical resolution. The method is used to calculate averages of HCFC-22 profiles retrieved from MIPAS observations, demonstrating the possibility of correctly obtaining retrievals with smaller constraints (that is: having at least a factor ten greater errors) and more degrees of freedom by up to a factor two

Quality quantifier of indirect measurements

A quality quantifier, referred to as measurement quality quantifier (MQQ), is proposed for indirect measurements. It satisfies the property that the MQQ of the data fusion of two or more independent measurements is the sum of the MQQs of the individual measurements and can also be determined in absolute terms for ill-posed problems. It is calculated from the covariance and Jacobian matrices of the observations, but the same result is also obtained using the covariance and averaging kernel matrices of the retrieved quantities. In the case of measurements of a continuous distribution a quantifier that provides the information distribution can be derived from the MQQ. The proposed quantifiers are herewith used for the quality assessment of atmospheric ozone measurements performed by IASI and MIPAS instruments

Optimal use of the information provided by indirect measurements of atmospheric vertical profiles

A procedure for the optimal utilization and representation of the information retrieved from atmospheric observations is discussed. We show that the "measurement-space solution" exclusively contains the information present in the observations, but is not suitable for a representation of the retrieved profile in the form of a graph. The new method of the "null-space regularization", which provides in a complement space an external constraint and makes the solution compliant with this representation, is presented. In this way the measurement and the constraint are separately determined and are given in a vertical grid that can be freely chosen as fine as desired. The method is applied to simulated measurements and is used to define a procedure for data fusion

Generalization of the complete data fusion to multi-target retrieval of atmospheric parameters and application to FORUM and IASI-NG simulated measurements

Abstract In the context of a growing need for innovatory techniques to take advantage of the largest amount of information from the great number of available remote sensing data, the Complete Data Fusion (CDF) algorithm was presented as a new method to combine independent measurements of the same vertical profile of an atmospheric parameter into a single estimate for a concise and complete characterization of the atmospheric state. The majority of the atmospheric composition measurements determine the altitude distribution of a great number of quantities: multi-target retrievals (MTRs) are increasingly applied to remote sensing observations to determine simultaneously atmospheric constituents with the purpose to reduce the systematic error caused by interfering species. In this work, we optimised the CDF for the application to MTR products. We applied the method to simulated retrievals in the thermal infrared and in the far infrared spectral ranges, considering the instrumental specifications and performances of IASI-NG (Infrared Atmospheric Sounding Interferometer New Generation) and FORUM (Far-Infrared Outgoing Radiation Understanding and Monitoring) instruments, respectively. The obtained results show that the CDF algorithm can cope with state vectors from MTRs, that must share at least one retrieved variable. In particular, the results show that the fused profile has the greatest number of degrees of freedom and the smallest error for all considered cases. The comparison between the CDF products and the synergistic retrieval ones shows the equivalence of the two methods when the linear approximation is adopted to simplify the treatment of the retrieval problem

Phosgene distribution derived from MIPAS ESA v8 data: intercomparisons and trends

The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) measured the middle-infrared limb emission spectrum of the atmosphere from 2002 to 2012 on board ENVISAT, a polar-orbiting satellite. Recently, the European Space Agency (ESA) completed the final reprocessing of MIPAS measurements, using version 8 of the level 1 and level 2 processors, which include more accurate models, processing strategies, and auxiliary data. The list of retrieved gases has been extended, and it now includes a number of new species with weak emission features in the MIPAS spectral range. The new retrieved trace species include carbonyl chloride (COCl2), also called phosgene. Due to its toxicity, its use has been reduced over the years; however, it is still used by chemical industries for several applications. Besides its direct injection in the troposphere, stratospheric phosgene is mainly produced from the photolysis of CCl4, a molecule present in the atmosphere because of human activity. Since phosgene has a long stratospheric lifetime, it must be carefully monitored as it is involved in the ozone destruction cycles, especially over the winter polar regions. In this paper we exploit the ESA MIPAS version 8 data in order to discuss the phosgene distribution, variability, and trends in the middle and lower stratosphere and in the upper troposphere. The zonal averages show that phosgene volume mixing ratio is larger in the stratosphere, with a peak of 40 pptv (parts per trillion by volume) between 50 and 30 hPa at equatorial latitudes, while at middle and polar latitudes it varies from 10 to 25 pptv. A moderate seasonal variability is observed in polar regions, mostly between 80 and 50 hPa. The comparison of MIPAS–ENVISAT COCl2 v8 profiles with the ones retrieved from MIPAS balloon and ACE-FTS (Atmospheric Chemistry Experiment – Fourier Transform Spectrometer) measurements highlights a negative bias of about 2 pptv, mainly in polar and mid-latitude regions. Part of this bias is attributed to the fact that the ESA level 2 v8 processor uses an updated spectroscopic database. For the trend computation, a fixed pressure grid is used to interpolate the phosgene profiles, and, for each pressure level, VMR (volume mixing ratio) monthly averages are computed in pre-defined 10∘ wide latitude bins. Then, for each latitudinal bin and pressure level, a regression model has been fitted to the resulting time series in order to derive the atmospheric trends. We find that the phosgene trends are different in the two hemispheres. The analysis shows that the stratosphere of the Northern Hemisphere is characterized by a negative trend of about −7 pptv per decade, while in the Southern Hemisphere phosgene mixing ratios increase with a rate of the order of +4 pptv per decade. This behavior resembles the stratospheric trend of CCl4, which is the main stratospheric source of COCl2. In the upper troposphere a positive trend is found in both hemispheres.</p

Molecular and Structural Aspects of Clinically Relevant Mutations of SARS-CoV-2 RNA-Dependent RNA Polymerase in Remdesivir-Treated Patients

(1) Background: SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) is a promising therapeutic target to fight COVID-19, and many RdRp inhibitors nucleotide/nucleoside analogs, such as remdesivir, have been identified or are in clinical studies. However, the appearance of resistant mutations could reduce their efficacy. In the present work, we structurally evaluated the impact of RdRp mutations found at baseline in 39 patients treated with remdesivir and associated with a different degree of antiviral response in vivo. (2) Methods: A refined bioinformatics approach was applied to assign SARS-CoV-2 clade and lineage, and to define RdRp mutational profiles. In line with such a method, the same mutations were built and analyzed by combining docking and thermodynamics evaluations with both molecular dynamics and representative pharmacophore models. (3) Results: Clinical studies revealed that patients bearing the most prevalent triple mutant P323L+671S+M899I, which was present in 41% of patients, or the more complex mutational profile P323L+G671S+L838I+D738Y+K91E, which was found with a prevalence of 2.6%, showed a delayed reduced response to remdesivir, as confirmed by the increase in SARS-CoV-2 viral load and by a reduced theoretical binding affinity versus RdRp ( Delta Gbind(WT) = 122.70 kcal/mol; Delta Gbind(P323L+ 671S+M899I) = 84.78 kcal/mol; Delta Gbind(P323L+ G671S+L838I+D738Y+K91E) = 96.74 kcal/mol). Combined computational approaches helped to rationalize such clinical observations, offering a mechanistic understanding of the allosteric effects of mutants on the global motions of the viral RNA synthesis machine and in the changes of the interactions patterns of remdesivir during its binding

External quality assessment of HIV-1 DNA quantification assays used in the clinical setting in Italy

none18no: Total cell-associated HIV-1 DNA is a surrogate marker of the HIV-1 reservoir, however, certified systems for its quantification are not available. The Italian HIV DNA Network was launched to validate HIV-1 DNA quantification methods in use at University and Hospital labs. A quality control panel including HIV-1 DNA standards, reconstructed blood samples (RBSs) and DNA from different HIV-1 subtypes was blindly tested by 12 participating labs by quantitative real-time PCR (n = 6), droplet digital PCR (n = 3) or both (n = 3). The median 95% hit rate was 4.6 (3.7-5.5) copies per test and linearity in the tested range was excellent (R2 = 1.000 [1.000-1.000]). The median values obtained across labs were 3,370 (2,287-4,245), 445 (299-498), 59 (40-81) and 7 (6-11) HIV-1 DNA copies, for the 3,584, 448, 56 and 7-copy standards, respectively. With RBSs, measured values were within twofold with respect to the median in two thirds of cases. HIV-1 subtypes were missed (CRF01_AE by 3 labs) or underestimated by > 1 log (subtypes A, C, D, F by one lab; CRF01_AE by one lab; CRF02_AG by one lab). The overall performance was excellent with HIV-1 DNA standards, however detection of different HIV-1 subtypes must be improved.openVicenti, Ilaria; Dragoni, Filippo; Giannini, Alessia; Casabianca, Anna; Lombardi, Francesca; Di Sante, Laura; Turriziani, Ombretta; Racca, Sara; Paolucci, Stefania; Lai, Alessia; Bon, Isabella; Abbate, Isabella; Rozera, Gabriella; Belmonti, Simone; Scutari, Rossana; Alteri, Claudia; Saladini, Francesco; Zazzi, MaurizioVicenti, Ilaria; Dragoni, Filippo; Giannini, Alessia; Casabianca, Anna; Lombardi, Francesca; Di Sante, Laura; Turriziani, Ombretta; Racca, Sara; Paolucci, Stefania; Lai, Alessia; Bon, Isabella; Abbate, Isabella; Rozera, Gabriella; Belmonti, Simone; Scutari, Rossana; Alteri, Claudia; Saladini, Francesco; Zazzi, Maurizi

The ESA MIPAS/Envisat level2-v8 dataset: 10 years of measurements retrieved with ORM v8.22

The observations acquired during the full mission of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument, aboard the European Space Agency Environmental Satellite (Envisat), have been analysed with version 8.22 of the Optimised Retrieval Model (ORM), originally developed as the scientific prototype of the ESA level-2 processor for MIPAS observations. The results of the analyses have been included into the MIPAS level-2 version 8 (level2-v8) database containing atmospheric fields of pressure, temperature, and volume mixing ratio (VMR) of MIPAS main targets H$_{2}$O, O$_{3}$, HNO$_{3}$, CH$_{4}$, N$_{2}$O, and NO$_{2}$, along with the minor gases CFC-11, ClONO$_{2}$, N$_{2}$O$_{5}$, CFC-12, COF$_{2}$, CCl$_{4}$, CF$_{4}$, HCFC-22, C$_{2}$H$_{2}$, CH$_{3}$Cl, COCl$_{2}$, C$_{2}$H$_{6}$, OCS, and HDO. The database covers all the measurements acquired by MIPAS in the nominal measurement mode of the full resolution (FR) part of the mission (from July 2002 to March 2004) and all the observation modes of the optimised resolution (OR) part (from January 2005 to April 2012). The number of species included in the MIPAS level2-v8 dataset makes it of particular importance for the studies of stratospheric chemistry. The database is considered by ESA the final release of the MIPAS level-2 products. The ORM algorithm is operated at the vertical grid coincident to the tangent altitudes of the observations or to a subset of them, spanning (in the nominal mode) the altitude range from 6 to 68 km in the FR phase and from 6 to 70 km in the OR period. In the latitude domain, FR profiles are spaced by about 4.7∘, while the OR profiles are spaced by about 3.7∘. For each retrieved species, the auxiliary data and the retrieval choices are described. Each product is characterised in terms of the retrieval error, spatial resolution, and “useful” vertical range in both phases of the MIPAS mission. These depend on the characteristics of the measurements (spectral and vertical resolution of the measurements), the retrieval choices (number of spectral points included in the analyses, number of altitudes included in the vertical retrieval grid), and the information content of the measurements for each trace species. For temperature, water vapour, ozone, and nitric acid, the number of degrees of freedom is significantly larger in the OR phase than in the FR one, mainly due to the finer vertical measurement grid. In the FR phase, some trace species are characterised by a smaller retrieval error with respect to the OR phase, mainly due to the larger number of spectral points used in the analyses, along with the reduced vertical resolution. The way of handling possible caveats (negative VMR, vertical grid representation) is discussed. The quality of the retrieved profiles is assessed through four criteria, two providing information on the successful convergence of the retrieval iterations, one on the capability of the retrieval to reproduce the measurements, and one on the presence of outliers. An easy way to identify and filter the problematic profiles with the information contained in the output files is provided. MIPAS level2-v8 data are available to the scientific community through the ESA portal (https://doi.org/10.5270/EN1-c8hgqx4)