Operational satellite validation with data from the Pandonia Global Network (PGN)

2020 ◽  
Author(s):  
Alexander Cede ◽  
Martin Tiefengraber ◽  
Angelika Dehn ◽  
Barry Lefer ◽  
Jonas von Bismarck ◽  
...  
Keyword(s):  
Program Planning ◽  
Low Earth Orbit ◽  
Global Network ◽  
High Temporal Resolution ◽  
Vertical Column ◽  
Validation Data ◽  
Passive Remote Sensing ◽  
Satellite Validation ◽  
Data Products ◽  
Planning Group

<p>The Pandonia Global Network (PGN) is a worldwide operating network of passive remote sensing spectrometer systems named “Pandora”. PGN is measuring atmospheric trace gases at high temporal resolution with the purpose of air quality monitoring and satellite validation. PGN is an activity carried out jointly by NASA, through the Pandora project at Goddard Space Flight Center, and ESA, through the Austrian contractor LuftBlick, as part of their Joint Program Planning Group Subgroup on calibration and validation and field activities. Many of the more than 50 actual PGN instruments are directly owned by NASA or ESA, another part belongs to other collaborating governmental and academic institutions. A major objective of the PGN is to support the validation and verification of more than a dozen low-earth orbit and geostationary orbit based UV-visible sensors, most notably Sentinel 5P, TEMPO, GEMS and Sentinel 4. PGN instruments are homogeneously calibrated and their data are centrally processed in real-time. Starting in June 2019, the PGN team has made more and more network locations “official PGN sites”, which means all required technical and logistical steps for this purpose have been performed. At the end of 2019 there are 18 such official network sites, where quality assured data are uploaded daily to EVDC (ESA Atmospheric Validation Data Centre), where they are used for operational validation of Sentinel 5P retrievals (see e.g. http://mpc-vdaf-server.tropomi.eu/no2/no2-offl-pandora). The current official PGN data products are total vertical column amounts of NO2 and O3 from direct sun observations. Research data products include total vertical columns amounts of SO2 and HCHO from direct sun observations as well as surface concentrations, tropospheric columns amounts, and vertical profiles for NO2 and HCHO from sky observations. These named research products are planned to become official over the course of the year 2020.</p>

New and improved data from the Pandonia Global Network for satellite validation

2021 ◽  
Author(s):  
Alexander Cede ◽  
Martin Tiefengraber ◽  
Manuel Gebetsberger ◽  
Michel Van Roozendael ◽  
Henk Eskes ◽  
...  
Keyword(s):  
Environmental Protection Agency ◽  
Program Planning ◽  
Global Network ◽  
High Temporal Resolution ◽  
Validation Data ◽  
Total Uncertainty ◽  
Satellite Validation ◽  
Initial Comparison ◽  
New Feature ◽  
Planning Group

<p>The worldwide operating Pandonia Global Network (PGN) is measuring atmospheric trace gases at high temporal resolution with the purpose of air quality monitoring and satellite validation. It is an activity carried out jointly by NASA and ESA as part of their “Joint Program Planning Group Subgroup” on calibration and validation and field activities, with additional collaboration from other institutions, most notably a strongly growing participation of the US Environmental Protection Agency (EPA). The more than 50 official PGN instruments are homogeneously calibrated and their data are centrally processed in real-time. Since 2019, total NO2 column amounts from the PGN are uploaded daily to the ESA Atmospheric Validation Data Centre (EVDC), where they are used for operational validation of Sentinel 5P (S5P) retrievals. During 2020, a new processor version 1.8 has been developed, which produces improved total NO2 column amounts and also the following new PGN products: total columns of O3, SO2 and HCHO based on direct sun observations and tropospheric columns, surface concentrations and tropospheric profiles of NO2 and HCHO based on sky observations. In this presentation we show some first examples of comparisons of the new PGN products with S5P data. Compared to the total NO2 columns from the previous processor version 1.7, the 1.8 data use better estimations for the effective NO2 temperature and the air mass factor. The effect of this improvement on the comparison with S5P retrievals is shown for some remote and high-altitude PGN sites. The new PGN total O3 column algorithm also retrieves the effective O3 temperature, which is a rather unique feature for ground-based direct sun retrievals. This allows us to analyze whether potential differences to satellite O3 columns might be influenced by the O3 temperature. Including the O3 temperature in the spectral fitting has also allowed the retrieval of accurate total SO2 columns. This PGN data product is of particular interest for satellite validation, as ground-based total SO2 column amounts are hardly measured by other instrumentation. An initial comparison of the PGN SO2 columns with S5P retrievals at selected PGN sites around the world is shown. PGN total HCHO columns from direct sun measurements are now possible for those PGN instruments, where the hardware parts made of Delrin, which outgasses HCHO, have been replaced by Nylon pieces. An initial comparison to HCHO retrievals from S5P is shown for locations with these upgraded instruments. Another new feature in the 1.8 PGN data is that they come with comprehensive uncertainty estimations, separated in the output files as independent, structured, common and total uncertainty.</p>

Quality assessment of two years of Sentinel-5p TROPOMI NO2 data

2020 ◽  
Author(s):  
Tijl Verhoelst ◽  
Steven Compernolle ◽  
José Granville ◽  
Arno Keppens ◽  
Gaia Pinardi ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Quality Indicators ◽  
Scattered Light ◽  
Global Network ◽  
Visible Range ◽  
Network Data ◽  
Random Errors ◽  
Validation Data ◽  
Comparison Results ◽  
Data Products

<p>For more than two years now the first atmospheric satellite of the Copernicus EO programme, Sentinel-5p (S5P) TROPOMI, has acquired spectral measurements of the Earth radiance in the visible range, from which near-real-time (NRTI) and offline (OFFL) processors retrieve operationally the total, tropospheric and stratospheric  column abundance of atmospheric NO<sub>2</sub>.  In support of these routine operations, the S5P Mission Performance Centre (MPC) performs continuous QA/QC of these data products and produces key Quality Indicators enabling users to verify the fitness-for-purpose of the S5P data. Quality Indicators are derived from comparisons to ground-based reference data, both station-by-station in monitoring mode in the S5P Automated Validation Server (AVS) and globally in more complex in-depth analyses.  Complementary quality information is obtained from product intercomparisons (NRTI vs. OFFL) and from satellite-to-satellite comparisons.  After two years of successful operation we present here a consolidated overview of the quality of the S5P TROPOMI NO<sub>2</sub> data products delivered publicly.</p><p>S5P NO2 data are compared routinely to ground-based network measurements collected through either the ESA Validation Data Centre (EVDC) or network data archives (NDACC, PGN). Direct-sun measurements from the Pandonia Global Network (PGN) serve as a reference for total NO<sub>2</sub> validation, Multi-Axis DOAS network data for tropospheric  NO<sub>2</sub> validation, and NDACC zenith-scattered-light DOAS network data for stratospheric NO<sub>2</sub> validation.  Comparison methods are optimized to limit spatial and temporal mismatch to a minimum (information-based spatial co-location strategy, photochemical adjustment to account for local time measurement difference). Comparison results are analyzed to derive Quality Indicators and to conclude on the compliance w.r.t. the mission requirements. This include estimates of: (1) the bias, as proxy for systematic errors, (2) the dispersion of the differences, which combines random errors with seasonal and irreducible mismatch errors, and (3) the dependence of bias and dispersion on key influence quantities (surface albedo, cloud cover…)</p><p>Intercomparison of S5P products (NRTI vs. OFFL) and comparison to other satellite data, including a similar processing of OMI measurements, complement the ground-based validation with relative biases and spatio-temporal patterns/artefacts related to instrumental issues (e.g. striping) and to the sensitivity to geophysical features (e.g. clouds and sea/ice albedo contrast).  </p><p>Overall, the MPC quality assessment of S5P NO<sub>2</sub> data concludes to an excellent performance for the stratospheric column data (bias2 vs. ground-based data. This dispersion larger than the mission requirement on data precision can partly be attributed to comparisons errors such as those due to differences in horizontal resolution. Total column data are found to be biased low by 20%, with a 30% station-to-station scatter. After gridding to monthly means on a 0.8°x0.4° grid, comparisons to OMI data yield a much smaller dispersion (within the requirement of 0.7Pmolec/cm<sup>2</sup>), and a minor relative bias. NRTI and OFFL perform similarly, even if they occasionally differ in specific cases of direct comparisons.       </p>

Quality assessment of three years of Sentinel-5p TROPOMI NO2 data 

2021 ◽  
Author(s):  
Tijl Verhoelst ◽  
Steven Compernolle ◽  
Gaia Pinardi ◽  
José Granville ◽  
Jean-Christopher Lambert ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Quality Indicators ◽  
Reference Data ◽  
Scattered Light ◽  
Global Network ◽  
Validation Data ◽  
Data Set ◽  
Comparison Results ◽  
Data Products ◽  
The Impact

<p>For more than three years now, the first atmospheric satellite of the Copernicus EO programme, Sentinel-5p (S5P) TROPOMI, has acquired spectral measurements of the Earth radiance in the visible range, from which near-real-time (NRTI) and offline (OFFL) processors retrieve the total, tropospheric and stratospheric  column abundance of  NO<sub>2</sub>.   The S5P Mission Performance Centre  performs continuous QA/QC of these data products enabling users to verify the fitness-for-purpose of the S5P data. Quality Indicators are derived from comparisons to ground-based reference data, both station-by-station in the S5P Automated Validation Server (AVS), and globally in more in-depth analyses.  Complementary quality information is obtained from product intercomparisons (NRTI vs. OFFL) and from satellite-to-satellite comparisons.  After three years of successful operation we present here a consolidated overview of the quality of the S5P TROPOMI NO<sub>2</sub> data products, with particular attention paid to the impact of the various processor improvements, especially in the latest version (v1.4), activated on 2 December 2020, which introduces an updated cloud retrieval resulting in higher NO<sub>2</sub> columns in polluted regions. Also the upcoming v2, due in April 2021 but already used to produce a Diagnostic Data Set, is discussed. </p><p>S5P NO<sub>2</sub> data are compared to ground-based measurements collected through either the ESA Validation Data Centre (EVDC) or network data archives (NDACC, PGN). Measurements from the Pandonia Global Network (PGN) serve as a reference for total NO<sub>2</sub> validation, Multi-Axis DOAS data for tropospheric  NO<sub>2</sub> validation, and NDACC zenith-scattered-light DOAS data for stratospheric NO<sub>2</sub> validation.  Comparison methods are optimized to limit spatial and temporal mismatch errors (co-location strategy, photochemical adjustment to account for local time difference). Comparison results are analyzed to derive Quality Indicators and to conclude on the compliance w.r.t. the mission requirements.  This include estimates of: (1) the bias, as proxy for systematic errors, (2) the dispersion of the differences, which combines random errors with seasonal and mismatch errors, and (3) the dependence of these on key influence quantities (surface albedo, cloud cover…)</p><p>Overall, the MPC quality assessment of S5P NO<sub>2</sub> data concludes to an excellent performance for the stratospheric data (bias<5%, dispersion<10%). The tropospheric data show a negative bias of -30% and a dispersion of 3Pmolec/cm<sup>2</sup> vs. ground-based data. This dispersion is larger than the mission requirement on data precision, but it can partly be attributed to comparison errors such as those due to differences in resolution. Total column data are found to be biased low by 20%, with a 30% station-to-station scatter. After gridding to monthly means on a 0.8°x0.4° grid, comparisons to OMI data yield a much smaller dispersion (within the requirement of 0.7Pmolec/cm<sup>2</sup>), and a minor relative bias. NRTI and OFFL perform similarly, even if they occasionally differ over specific scenes. Besides the impact of the processor upgrade to v1.4 on the bias in polluted scenes, we discuss the implications of the reported negative biases in S5P tropospheric (and total) columns on NO<sub>2</sub> reduction estimates, e.g. in the context of SARS-CoV-2 lockdown measures. Feedback from this work on the ground-based reference data is also briefly reported.         </p>

scholarly journals Tropospheric NO<sub>2</sub> column densities deduced from zenith-sky DOAS measurements in Shanghai, China, and their application to satellite validation

2009 ◽  
Vol 9 (11) ◽  
pp. 3641-3662 ◽  
Author(s):  
D. Chen ◽  
B. Zhou ◽  
S. Beirle ◽  
L. M. Chen ◽  
T. Wagner
Keyword(s):  
Satellite Data ◽  
Urban Site ◽  
Optical Absorption Spectroscopy ◽  
Vertical Column ◽  
Error Sources ◽  
Satellite Validation ◽  
Tropospheric No2 ◽  
Realistic Information ◽  
Good Agreement

Abstract. Zenith-sky scattered sunlight observations using differential optical absorption spectroscopy (DOAS) technique were carried out in Shanghai, China (31.3° N, 121.5° E) since December 2006. At this polluted urban site, the measurements provided NO2 total columns in the daytime. Here, we present a new method to extract time series of tropospheric vertical column densities (VCDs) of NO2 from these observations. The derived tropospheric NO2 VCDs are important quantities for the estimation of emissions and for the validation of satellite observations. Our method makes use of assumptions on the relative NO2 height profiles and the diurnal variation of stratospheric NO2 VCDs. The main error sources arise from the uncertainties in the estimated stratospheric slant column densities (SCDs) and the determination of tropospheric NO2 air mass factor (AMF). For a polluted site like Shanghai, the accuracy of our method is conservatively estimated to be <25% for solar zenith angle (SZA) lower than 70°. From simultaneously performed long-path DOAS measurements, the NO2 surface concentrations at the same site were observed and the corresponding tropospheric NO2 VCDs were estimated using the assumed seasonal NO2 profiles in the planetary boundary layer (PBL). By making a comparison between the tropospheric NO2 VCDs from zenith-sky and long-path DOAS measurements, it is found that the former provides more realistic information about total tropospheric pollution than the latter, so it's more suitable for satellite data validation. A comparison between the tropospheric NO2 VCDs from ground-based zenith-sky measurements and SCIAMACHY was also made. Satellite validation for a strongly polluted area is highly needed, but exhibits also a great challenge. Our comparison shows good agreement, considering in particular the different spatial resolutions between the two measurements. Remaining systematic deviations are most probably related to the uncertainties of satellite data caused by the assumptions on aerosol properties as well as the layer heights of aerosols and NO2.

scholarly journals Impact of synthetic space-borne NO<sub>2</sub> observations from the Sentinel-4 and Sentinel-5P missions on tropospheric NO<sub>2</sub> analyses

2019 ◽  
Vol 19 (19) ◽  
pp. 12811-12833 ◽  
Author(s):  
Renske Timmermans ◽  
Arjo Segers ◽  
Lyana Curier ◽  
Rachid Abida ◽  
Jean-Luc Attié ◽  
...  
Keyword(s):  
Error Estimates ◽  
Temporal Resolution ◽  
Transport Model ◽  
Surface Ozone ◽  
Low Earth Orbit ◽  
Added Value ◽  
High Temporal Resolution ◽  
Chemistry Transport Model ◽  
European Continent ◽  
Global Coverage

Abstract. We present an Observing System Simulation Experiment (OSSE) dedicated to the evaluation of the added value of the Sentinel-4 and Sentinel-5P missions for tropospheric nitrogen dioxide (NO2). Sentinel-4 is a geostationary (GEO) mission covering the European continent, providing observations with high temporal resolution (hourly). Sentinel-5P is a low Earth orbit (LEO) mission providing daily observations with a global coverage. The OSSE experiment has been carefully designed, with separate models for the simulation of observations and for the assimilation experiments and with conservative estimates of the total observation uncertainties. In the experiment we simulate Sentinel-4 and Sentinel-5P tropospheric NO2 columns and surface ozone concentrations at 7 by 7 km resolution over Europe for two 3-month summer and winter periods. The synthetic observations are based on a nature run (NR) from a chemistry transport model (MOCAGE) and error estimates using instrument characteristics. We assimilate the simulated observations into a chemistry transport model (LOTOS-EUROS) independent of the NR to evaluate their impact on modelled NO2 tropospheric columns and surface concentrations. The results are compared to an operational system where only ground-based ozone observations are ingested. Both instruments have an added value to analysed NO2 columns and surface values, reflected in decreased biases and improved correlations. The Sentinel-4 NO2 observations with hourly temporal resolution benefit modelled NO2 analyses throughout the entire day where the daily Sentinel-5P NO2 observations have a slightly lower impact that lasts up to 3–6 h after overpass. The evaluated benefits may be even higher in reality as the applied error estimates were shown to be higher than actual errors in the now operational Sentinel-5P NO2 products. We show that an accurate representation of the NO2 profile is crucial for the benefit of the column observations on surface values. The results support the need for having a combination of GEO and LEO missions for NO2 analyses in view of the complementary benefits of hourly temporal resolution (GEO, Sentinel-4) and global coverage (LEO, Sentinel-5P).

scholarly journals Evaluating the impact of spatial resolution on tropospheric NO<sub>2</sub> column comparisons within urban areas using high-resolution airborne data

2019 ◽  
Vol 12 (11) ◽  
pp. 6091-6111 ◽  
Author(s):  
Laura M. Judd ◽  
Jassim A. Al-Saadi ◽  
Scott J. Janz ◽  
Matthew G. Kowalewski ◽  
R. Bradley Pierce ◽  
...  
Keyword(s):  
High Resolution ◽  
Los Angeles ◽  
Spatial Heterogeneity ◽  
Spatial Resolution ◽  
Urban Areas ◽  
High Temporal Resolution ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Monitoring Instrument ◽  
The Impact

Abstract. NASA deployed the GeoTASO airborne UV–visible spectrometer in May–June 2017 to produce high-resolution (approximately 250 m×250 m) gapless NO2 datasets over the western shore of Lake Michigan and over the Los Angeles Basin. The results collected show that the airborne tropospheric vertical column retrievals compare well with ground-based Pandora spectrometer column NO2 observations (r2=0.91 and slope of 1.03). Apparent disagreements between the two measurements can be sensitive to the coincidence criteria and are often associated with large local variability, including rapid temporal changes and spatial heterogeneity that may be observed differently by the sunward-viewing Pandora observations. The gapless mapping strategy executed during the 2017 GeoTASO flights provides data suitable for averaging to coarser areal resolutions to simulate satellite retrievals. As simulated satellite pixel area increases to values typical of TEMPO (Tropospheric Emissions: Monitoring Pollution), TROPOMI (TROPOspheric Monitoring Instrument), and OMI (Ozone Monitoring Instrument), the agreement with Pandora measurements degraded, particularly for the most polluted columns as localized large pollution enhancements observed by Pandora and GeoTASO are spatially averaged with nearby less-polluted locations within the larger area representative of the satellite spatial resolutions (aircraft-to-Pandora slope: TEMPO scale =0.88; TROPOMI scale =0.77; OMI scale =0.57). In these two regions, Pandora and TEMPO or TROPOMI have the potential to compare well at least up to pollution scales of 30×1015 molecules cm−2. Two publicly available OMI tropospheric NO2 retrievals are found to be biased low with respect to these Pandora observations. However, the agreement improves when higher-resolution a priori inputs are used for the tropospheric air mass factor calculation (NASA V3 standard product slope =0.18 and Berkeley High Resolution product slope =0.30). Overall, this work explores best practices for satellite validation strategies with Pandora direct-sun observations by showing the sensitivity to product spatial resolution and demonstrating how the high-spatial-resolution NO2 data retrieved from airborne spectrometers, such as GeoTASO, can be used with high-temporal-resolution ground-based column observations to evaluate the influence of spatial heterogeneity on validation results.

scholarly journals Comparisons of aerosol optical depth provided by seviri satellite observations and CAMx air quality modelling

2015 ◽  
Vol XL-7/W3 ◽  
pp. 187-193 ◽  
Author(s):  
A. Fernandes ◽  
M. Riffler ◽  
J. Ferreira ◽  
S. Wunderle ◽  
C. Borrego ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Satellite Data ◽  
Spatial Variations ◽  
Transport Processes ◽  
Satellite Observations ◽  
High Temporal Resolution ◽  
Vertical Column ◽  
Air Pollution Modelling ◽  
Spatial Coverage

Satellite data provide high spatial coverage and characterization of atmospheric components for vertical column. Additionally, the use of air pollution modelling in combination with satellite data opens the challenging perspective to analyse the contribution of different pollution sources and transport processes. The main objective of this work is to study the AOD over Portugal using satellite observations in combination with air pollution modelling. For this purpose, satellite data provided by Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) on-board the geostationary Meteosat-9 satellite on AOD at 550 nm and modelling results from the Chemical Transport Model (CAMx - Comprehensive Air quality Model) were analysed. The study period was May 2011 and the aim was to analyse the spatial variations of AOD over Portugal. In this study, a multi-temporal technique to retrieve AOD over land from SEVIRI was used. The proposed method takes advantage of SEVIRI's high temporal resolution of 15 minutes and high spatial resolution. <br><br> CAMx provides the size distribution of each aerosol constituent among a number of fixed size sections. For post processing, CAMx output species per size bin have been grouped into total particulate sulphate (PSO4), total primary and secondary organic aerosols (POA + SOA), total primary elemental carbon (PEC) and primary inert material per size bin (CRST_1 to CRST_4) to be used in AOD quantification. The AOD was calculated by integration of aerosol extinction coefficient (Qext) on the vertical column. The results were analysed in terms of temporal and spatial variations. The analysis points out that the implemented methodology provides a good spatial agreement between modelling results and satellite observation for dust outbreak studied (10th -17th of May 2011). A correlation coefficient of r=0.79 was found between the two datasets. This work provides relevant background to start the integration of these two different types of the data in order to improve air pollution assessment.

scholarly journals Carbon monoxide column retrieval for clear-sky and cloudy atmospheres: a full-mission data set from SCIAMACHY 2.3 μm reflectance measurements

2017 ◽  
Author(s):  
Tobias Borsdorff ◽  
Joost aan de Brugh ◽  
Haili Hu ◽  
Philippe Nédélec ◽  
Ilse Aben ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Data Processing ◽  
Pearson Correlation ◽  
Retrieval Algorithm ◽  
Vertical Column ◽  
Validation Data ◽  
Data Set ◽  
Airborne Measurements ◽  
Clear Sky ◽  
Infrared Measurements

Abstract. We discuss the retrieval of carbon monoxide (CO) vertical column densities from clear-sky and cloud contaminated 2311–2338 nm reflectance spectra measured by the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) from January 2003 until the end of the mission in April 2012. These data was processed with the Shortwave Infrared CO Retrieval algorithm SICOR that we developed for the operational data processing of the Tropospheric Monitoring Instrument (TROPOMI) that will be launched on ESA’s Sentinel-5 Precursor (S5P) mission. This study complements previous work that was limited to clear-sky observations over land. Over the oceans, CO is estimated from cloudy-sky measurements only, which is an important addition to the SCIAMACHY clear-sky CO data set as shown by NDACC and TCCON measurements at coastal sites. For Ny-Ålesund, Lauder, Mauna Loa, and Reunion, a validation of SCIAMACHY clear-sky retrievals is not meaningful because of the high retrieval noise and the few collocations at these sites. This improves significantly when considering cloudy-sky observations, where we find a low mean bias b = ±6.0 ppb and a strong correlation between the validation data set and the SCIAMACHY data sets with a mean Pearson correlation coefficient r = 0.7. Also for land observations, cloudy-sky CO retrievals present an interesting complement to the clear-sky data set, which is less sensitive to the spatial representativeness of the satellite and validation measurement. For example, at the cities Teheran and Beijing the agreement of SCIAMACHY clear-sky CO observations with MOZAIC/IAGOS airborne measurements is poor with a mean bias of b = 171.2 ppb and 57.9 ppb because of local CO pollution, which cannot be captured by SCIAMACHY. The validation improves significantly for cloudy sky retrievals with b = 52.3 ppb and 5.0 ppb, respectively. This is due to a reduced retrieval sensitivity to CO below the cloud and so to the altitude range, which is mostly affected by strong local surface emissions. At the less urbanized region around the airportWindhoek, local CO pollution is less prominent and so MOZAIC/IAGOS measurements agree well with SCIAMACHY clear-sky retrievals with a mean bias of b = 15.5 ppb, but can be even further improved considering cloudy SCIAMACHY observations with a mean CO bias of b = 0.2 ppb. Overall the cloudy-sky CO retrievals from SCIAMACHY short wave infrared measurements present a valuable addition to the clear-sky only data set. Moreover, the study represents the first application of the S5P algorithm for operational CO data processing on cloudy observations prior to the launch of the S5P mission.

scholarly journals Ultrasound functional neuroimaging reveals propagation of task-related brain activity in behaving primates

2018 ◽  
Author(s):  
Alexandre Dizeux ◽  
Marc Gesnik ◽  
Harry Ahnine ◽  
Kevin Blaize ◽  
Fabrice Arcizet ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Large Scale ◽  
Functional Neuroimaging ◽  
Anterior Cingulate ◽  
Global Network ◽  
High Temporal Resolution ◽  
Wide Field ◽  
Spatiotemporal Resolution ◽  
Macro Scale ◽  
The Brain

ABSTRACTIn recent decades, neuroimaging has played an invaluable role in improving the fundamental understanding of the brain. At the macro scale, neuroimaging modalities such as MRI, EEG, and MEG, exploit a wide field of view to explore the brain as a global network of interacting regions. However, this comes at the price of either limited spatiotemporal resolution or limited sensitivity. At the micro scale, electrophysiology is used to explore the dynamic aspects of neuronal activity with a very high temporal resolution. However, this modality requires a statistical averaging of several tens of single task responses. A large-scale neuroimaging modality of sufficient spatial and temporal resolution and sensitivity to study brain region activation dynamically would open new territories of possibility in neuroscienceWe show that neurofunctional ultrasound imaging (fUS) is both able to assess brain activation during single cognitive tasks within superficial and deeper areas of the frontal cortex areas, and image the directional propagation of information within and between these regions. Equipped with an fUS device, two macaque rhesus monkeys were instructed before a stimulus appeared to rest (fixation) or to look towards (saccade) or away (antisaccade) from a stimulus. Our results identified an abrupt transient change in activity for all acquisitions in the supplementary eye field (SEF) when the animals were required to change a rule regarding the task cued by a stimulus. Simultaneous imaging in the anterior cingulate cortex and SEF revealed a time delay in the directional functional connectivity of 0.27 ± 0.07 s and 0.9 ± 0.2 s for animals S and Y, respectively. These results provide initial evidence that recording cerebral hemodynamics over large brain areas at a high spatiotemporal resolution and sensitivity with neurofunctional ultrasound can reveal instantaneous monitoring of endogenous brain signals and behavior.

scholarly journals Tropospheric NO<sub>2</sub> column densities deduced from zenith-sky DOAS measurements in Shanghai, China, and their application to satellite validation

2008 ◽  
Vol 8 (4) ◽  
pp. 16713-16762 ◽  
Author(s):  
D. Chen ◽  
B. Zhou ◽  
S. Beirle ◽  
L. M. Chen ◽  
T. Wagner
Keyword(s):  
Solar Zenith Angle ◽  
Surface Concentration ◽  
Urban Site ◽  
Optical Absorption Spectroscopy ◽  
Vertical Column ◽  
Satellite Validation ◽  
Tropospheric No2 ◽  
Realistic Information ◽  
Good Agreement

Abstract. Zenith-sky scattered sunlight observations using differential optical absorption spectroscopy (DOAS) technique were carried out in Shanghai, China (31.3° N, 121.5° E) since December 2006. At this polluted urban site, the measurement provided NO2 total columns in the daytime. Here, we present a new method to extract time series of tropospheric vertical column densities (VCD) of NO2 from these observations. The derived tropospheric NO2 VCD is an important quantity for the estimation of emissions and for the validation of satellite observations. Our method makes use of assumptions on the relative NO2 height profiles and on the diurnal variation of the stratospheric NO2 VCD. The influence of these parameters on the retrieved tropospheric NO2 VCD is discussed; for a polluted site like Shanghai, the accuracy of our method is estimated to be <20% for solar zenith angle (SZA) lower than 85°. From simultaneously performed long-path DOAS measurement, the NO2 surface concentration at the same site was observed and the corresponding tropospheric NO2 VCD was estimated using the assumed seasonal NO2 profiles in the planetary boundary layer (PBL). By making a comparison between the tropospheric NO2 VCD from zenith-sky and long-path DOAS measurements, it was found that the former provided more realistic information about total tropospheric pollution than the latter, so it's more suitable for satellite data validation than the in situ measurement. A comparison between the tropospheric NO2 VCD from ground-based zenith-sky measurement and SCIAMACHY was also made. Satellite validation for a strongly polluted area is highly needed, but exhibits also a great challenge. Our comparison showed good agreement, considering in particular the different spatial resolutions between the two measurements.

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