65 research outputs found
New observations of NO2 in the upper troposphere from TROPOMI
Nitrogen oxides (NOxâĄNO+NO2) in the NOx-limited upper troposphere (UT) are long-lived and so have a large influence on the oxidizing capacity of the troposphere and formation of the greenhouse gas ozone. Models misrepresent NOx in the UT, and observations to address deficiencies in models are sparse. Here we obtain a year of near-global seasonal mean mixing ratios of NO2 in the UT (450â180âhPa) at 1âĂ1â by applying cloud-slicing to partial columns of NO2 from TROPOMI. This follows refinement of the cloud-slicing algorithm with synthetic partial columns from the GEOS-Chem chemical transport model. TROPOMI, prior to cloud-slicing, is corrected for a 13â% underestimate in stratospheric NO2 variance and a 50â% overestimate in free-tropospheric NO2 determined by comparison to Pandora total columns at high-altitude free-tropospheric sites at Mauna Loa, Izaña, and Altzomoni and MAX-DOAS and Pandora tropospheric columns at Izaña. Two cloud-sliced seasonal mean UT NO2 products for June 2019 to May 2020 are retrieved from corrected TROPOMI total columns using distinct TROPOMI cloud products that assume clouds are reflective boundaries (FRESCO-S) or water droplet layers (ROCINN-CAL). TROPOMI UT NO2 typically ranges from 20â30âpptv over remote oceans to >80âpptv over locations with intense seasonal lightning. Spatial coverage is mostly in the tropics and subtropics with FRESCO-S and extends to the midlatitudes and polar regions with ROCINN-CAL, due to its greater abundance of optically thick clouds and wider cloud-top altitude range. TROPOMI UT NO2 seasonal means are spatially consistent (R=0.6â0.8) with an existing coarser spatial resolution (5â latitudeâĂâ8â longitude) UT NO2 product from the Ozone Monitoring Instrument (OMI). UT NO2 from TROPOMI is 12â26âpptv more than that from OMI due to increase in NO2 with altitude from the OMI pressure ceiling (280âhPa) to that for TROPOMI (180âhPa), but possibly also due to altitude differences in TROPOMI and OMI cloud products and NO2 retrieval algorithms. The TROPOMI UT NO2 product offers potential to evaluate and improve representation of UT NOx in models and supplement aircraft observations that are sporadic and susceptible to large biases in the UT.This research has been supported by the European
Research Council under the European Unionâs Horizon 2020
research and innovation programme (through the Starting Grant
awarded to Eloise A. Marais, UpTrop (grant no. 851854))
Validation of Sentinel-5P TROPOMI tropospheric NO2 products by comparison with NO2 measurements from airborne imaging, ground-based stationary, and mobile car DOAS measurements during the S5P-VAL-DE-Ruhr campaign
Airborne imaging differential optical absorption spectroscopy (DOAS), ground-based stationary and car DOAS measurements were conducted during the S5P-VAL-DE-Ruhr campaign in September 2020. The campaign area is located in the Rhine-Ruhr region of North Rhine-Westphalia, Western Germany, which is a pollution hotspot in Europe comprising urban and large industrial emitters. The measurements are used to validate space-borne NO2 tropospheric vertical column density data products from the Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI). Seven flights were performed with the airborne imaging DOAS instrument for measurements of atmospheric pollution (AirMAP), providing measurements which were used to create continuous maps of NO2 in the layer below the aircraft. These flights cover many S5P ground pixels within an area of 30 km x 35 km and were accompanied by ground-based stationary measurements and three mobile car DOAS instruments. Stationary measurements were conducted by two Pandora, two zenith-sky and two MAX-DOAS instruments distributed over three target areas. Ground-based stationary and car DOAS measurements are used to evaluate the AirMAP tropospheric NO2 vertical column densities and show high Pearson correlation coefficients of 0.87 and 0.89 and slopes of 0.93 ± 0.09 and 0.98 ± 0.02 for the stationary and car DOAS, respectively. Having a spatial resolution of about 100 m x 30 m, the AirMAP tropospheric NO2 vertical column density (VCD) data creates a link between the ground-based and the TROPOMI measurements with a resolution of 3.5 km x 5.5 km and is therefore well suited to validate the TROPOMI tropospheric NO2 VCD. The measurements on the seven flight days show strong NO2 variability, which is dependent on the different target areas, the weekday, and the meteorological conditions. The AirMAP campaign dataset is compared to the TROPOMI NO2 operational off-line (OFFL) V01.03.02 data product, the reprocessed NO2 data, using the V02.03.01 of the official L2 processor, provided by the Product Algorithm Laboratory (PAL), and several scientific TROPOMI NO2 data products. The TROPOMI data products and the AirMAP data are highly correlated with correlation coefficients between 0.72 and 0.87, and slopes of 0.38 ± 0.02 to 1.02 ± 0.07. On average, TROPOMI tropospheric NO2 VCDs are lower than the AirMAP NO2 results. The slope increased from 0.38 ± 0.02 for the operational OFFL V01.03.02 product to 0.83 ± 0.06 after the improvements in the retrieval of the PAL V02.03.01 product were implemented. Different auxiliary data, such as spatially higher resolved a priori NO2 vertical profiles, surface reflectivity and the cloud treatment, are investigated using scientific TROPOMI tropospheric NO2 VCD data products to evaluate their impact on the operational TROPOMI NO2 VCD data product. The comparison of the AirMAP campaign dataset to the scientific data products shows that the choice of surface reflectivity data base has a minor impact on the tropospheric NO2 VCD retrieval in the campaign region and season. In comparison, the replacement of the a priori NO2 profile in combination with the improvements in the retrieval of the PAL V02.03.01 product regarding cloud heights has a major impact on the tropospheric NO2 VCD retrieval and increases the slope from 0.88 ± 0.06 to 1.00 ± 0.07. This study demonstrates that the underestimation of the TROPOMI tropospheric NO2 VCD product with respect to the validation dataset has been and can be further significantly improved.</p
Intercomparison of Sentinel-5P TROPOMI cloud products for tropospheric trace gas retrievals
Clouds have a strong impact on satellite measurements of tropospheric trace gases in the ultraviolet, visible, and near-infrared spectral ranges from space. Therefore, trace gas retrievals rely on information on cloud fraction, cloud albedo, and cloud height from cloud products. In this study, the cloud parameters from different cloud retrieval algorithms for the Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI) are compared: the Optical Cloud Recognition Algorithm (OCRA) a priori cloud fraction, the Retrieval Of Cloud Information using Neural Networks (ROCINN) CAL (Clouds-As-Layers) cloud fraction and cloud top and base height, the ROCINN CRB (Clouds-as-Reflecting-Boundaries) cloud fraction and cloud height, the Fast Retrieval Scheme for Clouds from the Oxygen A-band (FRESCO) cloud fraction, the interpolated FRESCO cloud height from the TROPOMI NO2 product, the cloud fraction from the NO2 fitting window, the O2âO2 cloud fraction and cloud height, the Mainz Iterative Cloud Retrieval Utilities (MICRU) cloud fraction, and the Visible Infrared Imaging Radiometer Suite (VIIRS) cloud fraction. Two different versions of the TROPOMI cloud products OCRA/ROCINN, FRESCO, and the TROPOMI NO2 product are included in the comparisons (processor version 1.x and 2.x). Overall, the cloud parameters retrieved by the different algorithms show qualitative consistency in version 1.x and good agreement in version 2.x with the exception of the VIIRS cloud fraction, which cannot be directly compared to the other data. Differences between the cloud retrievals are found especially for small cloud heights with a cloud fraction threshold of 0.2, i.e. clouds that are particularly relevant for tropospheric trace gas retrievals. The cloud fractions of the different version 2 cloud products primarily differ over snow- and ice-covered pixels and scenes with sun glint, for which only MICRU includes an explicit treatment. All cloud parameters show some systematic problems related to the across-track dependence, where larger values are found at the edges of the satellite view. The consistency between the cloud parameters from different algorithms depends strongly on how the data are filtered for the comparison, for example, what quality value is used or whether snow- and ice-covered pixels are excluded from the analysis. In summary, clear differences were found between the results of various algorithms, but these differences are reduced in the most recent versions of the cloud data
From the Ethnic History of Asia â the DĆnghĂș, WĆ«huĂĄn and XiÄnbÄi Proto-Mongolian Tribes
Cilj je ovog Älanka prikazati povijest protomongolskih plemena DĆnghĂș, WĆ«huĂĄn i XiÄnbÄi od 4. stoljeÄa pr. Kr. do kraja 3. stoljeÄa po. Kr. Povijest drevnih nomadskih naroda koji su ĆŸivjeli sjeverno od Kine zapisana je u kineskim dinastijskim kronikama. Protomongolska plemena 1. tisuÄljeÄa pr. Kr. u kineskim se izvorima nazivaju DĆnghĂș. Najstarije vijesti o njima potjeÄu iz razdoblja ZaraÄenih drĆŸava (4. â 3. st. pr. Kr.), a govore o sukobu sa sjevernim kineskim drĆŸavama. Druga vrsta izvora za povijest protomongolskih plemena arheoloĆĄki su nalazi, koji mongolsku etnogenezu povezuju s kulturama ploÄastih grobova, i MlaÄi XiĂ jiÄdiĂ n. Lingvisti graÄu za istraĆŸivanje mongolske etnogeneze pronalaze u altajskoj jeziÄnoj porodici, kojoj pripada i mongolski jezik. U radu se na temelju navedenih izvora opisuje promjena politiÄke situacije u stepi krajem 3. stoljeÄa pr. Kr., kada narod XiĆngnĂș stvara moÄnu drĆŸavu i pokorava DĆnghĂșe. Ostatke razbijenih DĆnghĂșa, koji su najveÄim dijelom migrirali na sjever, kineske kronike biljeĆŸe pod novim topoetnonimima â XiÄnbÄi i WĆ«huĂĄn. Slabljenje i pad drĆŸave XiĆngnĂșa omoguÄili su protomongolskim plemenima ponovni izlazak na povijesnu scenu. Kinesko carstvo HĂ n uspostavilo je krajem 1. stoljeÄa pr. Kr. najprije odnose s plemenima WĆ«huĂĄn, a sredinom 1. stoljeÄa po. Kr. i s plemenima XiÄnbÄi. Oba plemenska saveza u poÄetku su priznavala vrhovnu vlast Kine i obavljala graniÄarsku sluĆŸbu. Pod vodstvom plemenskih starjeĆĄina u 2. stoljeÄu po. Kr. poÄela su voditi samostalnu politiku i napadati pograniÄna kineska podruÄja. U zakljuÄnom dijelu rada govori se o vremenu kada su plemena WĆ«huĂĄn i XiÄnbÄi bila na vrhuncu moÄi. No veÄ poÄetkom 3. stoljeÄa WĆ«huĂĄni su potpali pod vlast Kineza i XiÄnbÄija; plemenski savez XiÄnbÄi raspao se u drugoj polovini 3. stoljeÄa.The aim of this paper is to present the history of the DĆnghĂș, WĆ«huĂĄn and XiÄnbÄi Proto-Mongolian tribes in the period from the 4th century B.C. to the end of the 3rd century A.D. The history of the ancient nomadic peoples who lived north of China is written in Chinese dynasty chronicles. Proto-Mongolian tribes from the 1st century B.C. are called DĆnghĂș in Chinese sources. The earliest news on them originates from the Warring States Period (4th â 3rd century B.C.), and tells of a conflict with the northern Chinese states. Other types of sources on the history of the Proto-Mongolian tribes are archaeological findings, which associate Mongolian ethnogenesis with slab grave cultures and the Lower XiĂ jiÄdiĂ n. Linguists find the materials for the research on Mongolian ethnogenesis in the Altaic linguistic family, which the Mongolian language belongs to as well. Based on the mentioned sources, the change in the political situation in the steppes at the end of the 3rd century B.C., when the people of XiĆngnĂș created a powerful state and conquered the DĆnghĂșes, is described in the paper. The remains of the shattered DĆnghĂșes, who had mostly migrated to the north, have been recorded in Chinese chronicles under new topoethnonyms: XiÄnbÄi and WĆ«huĂĄn. The weakening and fall of the XiĆngnĂșesâ state enabled the Proto-Mongolian tribes to re-enter the historical scene. At the end of the 1st century B.C. the Chinese HĂ n Empire firstly established relations with the WĆ«huĂĄn tribes and in the middle of the 1st century A.D. with the XiÄnbÄi tribes, too. In the beginning both tribal alliances acknowledged the supreme authority of China and carried out frontier service. Under the guidance of tribal chiefs the tribes started to run an independent policy and attack Chinaâs border areas during the 2nd century A.D. In the conclusion, the author describes the period when the WĆ«huĂĄn and XiÄnbÄi tribes were at the peak of their power. However, already at the beginning of the 3rd century, the WĆ«huĂĄns fell under the authorities of China and XiÄnbÄi, but the XiÄnbÄi tribal alliance fell apart in the second half of the 3rd century
Mechanisms Used for Genomic Proliferation by Thermophilic Group II Introns
Studies of mobile group II introns from a thermophilic cyanobacterium reveal how these introns proliferate within genomes and might explain the origin of introns and retroelements in higher organisms
Etude des paramÚtres génétiques de la production et de caractÚres associés à partir d'un plan de croisement diallÚle chez Coffea arabica
Les paramĂštres gĂ©nĂ©tiques de plusieurs caractĂšres agronomiques et morphologiques chez Coffea arabica ont Ă©tĂ© estimĂ©s dans un essai diallĂšle situĂ© dans la station de Foumbot de l'IRAD, dans la rĂ©gion ouest du Cameroun. Il s'agit d'un plan de croisements de type demi diallĂšle 7x7 avec les autofĂ©condations, soit 21 croisements hybrides et 7 lignĂ©es autofĂ©condĂ©es. AprĂšs une comparaison des deux types de matĂ©riel vĂ©gĂ©tal, une estimation des hĂ©ritabilitĂ©s et des corrĂ©lations gĂ©nĂ©tiques entre caractĂšres est proposĂ©e Ă partir de l'analyse du diallĂšle sans les autofĂ©condations. Il apparaĂźt que les hybrides sont globalement supĂ©rieurs aux lignĂ©es pour la plupart des caractĂ©ristiques agonomiques et en particulier pour la production. Il n'existe pas de relation nette entre la valeur propre des lignĂ©es et les aptitudes gĂ©nĂ©rales Ă la combinaison. Le Caturra est une variĂ©tĂ© performante et un bon gĂ©niteur; en revanche la variĂ©tĂ© Java se comporte trĂšs bien en tant que variĂ©tĂ©, mais elle s'avĂšre ĂȘtre un mauvais gĂ©niteur. Certains caractĂšres, comme le nombre de branches primaires, corrĂ©lĂ©s gĂ©nĂ©tiquement Ă la production, pourraient ĂȘtre utilisĂ©s pour amĂ©liorer la prĂ©diction de ce caractĂšre. Une estimation des Ă©covalences associĂ©es Ă chaque gĂ©niteur a permis de quantifier leur participation respective Ă l'Aptitude SpĂ©cifique Ă la Combinaison. Le gĂ©niteur Jal apparaĂźt comme le plus intĂ©ractif pour la plupart des caractĂšres considĂ©rĂ©s, ce qui peut indiquer un niveau d'hĂ©tĂ©rozygotie Ă©lĂ©vĂ©e de cette variĂ©tĂ©. (RĂ©sumĂ© d'auteur
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