Search

Your search keyword '"Wittrock, Folkard"' showing total 150 results
Start Over Author "Wittrock, Folkard"
150 results on '"Wittrock, Folkard"'

1. Investigating the Link Between Glyoxal and Biogenic Activities

Author

Alvarado, Leonardo M. A., Richter, Andreas, Vrekoussis, Mihalis, Wittrock, Folkard, Hilboll, Andreas, Schreier, Stefan F., Burrows, John P., Blondel, Philippe, Series editor, Guilyardi, Eric, Series editor, Rabassa, Jorge, Series editor, Horwood, Clive, Series editor, Lohmann, Gerrit, editor, Meggers, Helge, editor, Unnithan, Vikram, editor, Wolf-Gladrow, Dieter, editor, Notholt, Justus, editor, and Bracher, Astrid, editor

Published
2015
Full Text
View/download PDF

5. 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

Author

Lange, Kezia, primary, Richter, Andreas, additional, Schönhardt, Anja, additional, Meier, Andreas C., additional, Bösch, Tim, additional, Seyler, André, additional, Krause, Kai, additional, Behrens, Lisa K., additional, Wittrock, Folkard, additional, Merlaud, Alexis, additional, Tack, Frederik, additional, Fayt, Caroline, additional, Friedrich, Martina M., additional, Dimitropoulou, Ermioni, additional, Van Roozendael, Michel, additional, Kumar, Vinod, additional, Donner, Sebastian, additional, Dörner, Steffen, additional, Lauster, Bianca, additional, Razi, Maria, additional, Borger, Christian, additional, Uhlmannsiek, Katharina, additional, Wagner, Thomas, additional, Ruhtz, Thomas, additional, Eskes, Henk, additional, Bohn, Birger, additional, Santana Diaz, Daniel, additional, Abuhassan, Nader, additional, Schüttemeyer, Dirk, additional, and Burrows, John P., additional

Published
2022
Full Text
View/download PDF

7. Ground-based validation of the MetOp-A and MetOp-B GOME-2 OClO measurements

Author

Pinardi, Gaia, primary, Van Roozendael, Michel, additional, Hendrick, François, additional, Richter, Andreas, additional, Valks, Pieter, additional, Alwarda, Ramina, additional, Bognar, Kristof, additional, Frieß, Udo, additional, Granville, José, additional, Gu, Myojeong, additional, Johnston, Paul, additional, Prados-Roman, Cristina, additional, Querel, Richard, additional, Strong, Kimberly, additional, Wagner, Thomas, additional, Wittrock, Folkard, additional, and Yela Gonzalez, Margarita, additional

Published
2022
Full Text
View/download PDF

8. Determination of NOx emission rates of inland ships from onshore measurements.

Author

Krause, Kai, Wittrock, Folkard, Richter, Andreas, Busch, Dieter, Bergen, Anton, Burrows, John P., Freitag, Steffen, and Halbherr, Olesia

Subjects
*INLAND water transportation, *SHIPPING rates, *WATERWAYS, *TRAFFIC density, *ENERGY consumption, *AIR traffic
Abstract

Inland ships are an important source of NOx , especially for cities along busy waterways. The amount and effect of such emissions depend on the traffic density and NOx emission rates of individual vessels. Ship emission rates are typically derived using in situ land measurements in relation to NOx emission factors (e.g. the number of pollutants emitted by ships per unit of burnt fuel). In this study, a different approach is taken, and NOx emission rates are obtained (in gs-1). Within the EU LIFE project, CLean INland SHipping (CLINSH), a new approach to calculating the NOx emission rates from data of in situ measurement stations has been developed and is presented in this study. Peaks (i.e. elevated concentrations) of NOx were assigned to the corresponding source ships, using the AIS (automated identification system) signals they transmit. Each ship passage was simulated, using a Gaussian puff model, in order to derive the emission rate of the respective source ship. In total, over 32 900 ship passages have been monitored over the course of 4 years. The emission rates of NOx were investigated with respect to ship speed, ship size, and direction of travel. Comparisons of the onshore-derived emission rates and those on board for selected CLINSH ships show good agreement. The derived emission rates are of a similar magnitude to emission factors from previous studies. Most ships comply with existing limits due to grandfathering. The emission rates (in gs-1) can be directly used to investigate the effect of ship traffic on air quality, as the absolute emitted number of pollutants per unit of time is known. In contrast, for relative emission factors (in gkg-1 fuel), further knowledge about the fuel consumption of the individual ships is needed to calculate the number of pollutants emitted per unit of time. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

9. Validation of Sentinel-5P TROPOMI tropospheric NO2 products by comparison with NO2 measurements from airborne imaging DOAS, ground-based stationary DOAS, and mobile car DOAS measurements during the S5P-VAL-DE-Ruhr campaign.

Author

Lange, Kezia, Richter, Andreas, Schönhardt, Anja, Meier, Andreas C., Bösch, Tim, Seyler, André, Krause, Kai, Behrens, Lisa K., Wittrock, Folkard, Merlaud, Alexis, Tack, Frederik, Fayt, Caroline, Friedrich, Martina M., Dimitropoulou, Ermioni, Van Roozendael, Michel, Kumar, Vinod, Donner, Sebastian, Dörner, Steffen, Lauster, Bianca, and Razi, Maria

Subjects
RESEARCH aircraft, AIR pollution, AIRBORNE-based remote sensing, PEARSON correlation (Statistics), OPTICAL spectroscopy, LIGHT absorption, POLLUTION measurement
Abstract

Airborne imaging differential optical absorption spectroscopy (DOAS), ground-based stationary DOAS, 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 sources. The DOAS measurements are used to validate spaceborne NO 2 tropospheric vertical column density (VCD) 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 that were used to create continuous maps of NO 2 in the layer below the aircraft. These flights cover many S5P ground pixels within an area of 30 km × 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-DOAS, and two MAX-DOAS instruments. Ground-based stationary and car DOAS measurements are used to evaluate the AirMAP tropospheric NO 2 VCDs and show high Pearson correlation coefficients of 0.88 and 0.89 and slopes of 0.90 ± 0.09 and 0.89 ± 0.02 for the stationary and car DOAS, respectively. Having a spatial resolution of about 100 m × 30 m, the AirMAP tropospheric NO 2 VCD data create a link between the ground-based and the TROPOMI measurements with a nadir resolution of 3.5 km × 5.5 km and are therefore well suited to validate the TROPOMI tropospheric NO 2 VCD. The observations on the 7 flight days show strong NO 2 variability, which is dependent on the three target areas, the day of the week, and the meteorological conditions. The AirMAP campaign data set is compared to the TROPOMI NO 2 operational offline (OFFL) V01.03.02 data product, the reprocessed NO 2 data using the V02.03.01 of the official level-2 processor provided by the Product Algorithm Laboratory (PAL), and several scientific TROPOMI NO 2 data products. The AirMAP and TROPOMI OFFL V01.03.02 data are highly correlated (r=0.87) but show an underestimation of the TROPOMI data with a slope of 0.38 ± 0.02 and a median relative difference of - 9 %. With the modifications in the NO 2 retrieval implemented in the PAL V02.03.01 product, the slope and median relative difference increased to 0.83 ± 0.06 and + 20 %. However, the modifications resulted in larger scatter and the correlation decreased significantly to r=0.72. The results can be improved by not applying a cloud correction for the TROPOMI data in conditions with high aerosol load and when cloud pressures are retrieved close to the surface. The influence of spatially more highly resolved a priori NO 2 vertical profiles and surface reflectivity are investigated using scientific TROPOMI tropospheric NO 2 VCD data products. The comparison of the AirMAP campaign data set to the scientific data products shows that the choice of surface reflectivity database has a minor impact on the tropospheric NO 2 VCD retrieval in the campaign region and season. In comparison, the replacement of the a priori NO 2 profile in combination with the improvements in the retrieval of the PAL V02.03.01 product regarding cloud heights can further increase the tropospheric NO 2 VCDs. This study demonstrates that the underestimation of the TROPOMI tropospheric NO 2 VCD product with respect to the validation data set has been and can be further significantly improved. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

12. Estimation of ship emission rates at a major shipping lane by long-path DOAS measurements

Author

Krause, Kai, Wittrock, Folkard, Richter, Andreas, Schmitt, Stefan, Pöhler, Denis, Weigelt, Andreas, and Burrows, John P.

Abstract

Ships are an important source of SO2 and NOx, which are key parameters of air quality. Monitoring of ship emissions is usually carried out using in situ instruments on land, which depend on favourable wind conditions to transport the emitted substances to the measurement site. Remote sensing techniques such as long-path differential optical absorption spectroscopy (LP-DOAS) measurements can supplement those measurements, especially in unfavourable meteorological conditions. In this study 1 year of LP-DOAS measurements made across the river Elbe close to Hamburg (Germany) have been evaluated. Peaks (i.e. elevated concentrations) in the NO2 and SO2 time series were assigned to passing ships, and a method to derive emission rates of SO2, NO2 and NOx from those measurements using a Gaussian plume model is presented. A total of 7402 individual ship passages have been monitored, and their respective NOx, SO2 and NO2 emission rates have been derived. The emission rates, coupled with the knowledge of the ship type, ship size and ship speed, have been analysed. Emission rates are compared to emission factors from previous studies and show good agreement. In contrast to emission factors (in grams per kilogram fuel), the derived emission rates (in grams per second) do not need further knowledge about the fuel consumption of the ship. To our knowledge this is the first time emission rates of air pollutants from individual ships have been derived from LP-DOAS measurements.

Published
2021

13. Ground-based validation of the MetopA and B GOME-2 OClO measurements

Author

Pinardi, Gaia, primary, Van Roozendael, Michel, additional, Hendrick, François, additional, Richter, Andreas, additional, Valks, Pieter, additional, Alwarda, Ramina, additional, Bognar, Kristof, additional, Frieß, Udo, additional, Granville, José, additional, Gu, Myojeong, additional, Johnston, Paul, additional, Prados-Roman, Cristina, additional, Querel, Richard, additional, Strong, Kimberly, additional, Wagner, Thomas, additional, Wittrock, Folkard, additional, and Yela Gonzalez, Margarita, additional

Published
2021
Full Text
View/download PDF

14. 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.

Author

Lange, Kezia, Richter, Andreas, Schönhardt, Anja, Meier, Andreas C., Bösch, Tim, Seyler, André, Krause, Kai, Behrens, Lisa K., Wittrock, Folkard, Merlaud, Alexis, Tack, Frederik, Fayt, Caroline, Friedrich, Martina M., Dimitropoulou, Ermioni, Van Roozendael, Michel, Kumar, Vinod, Donner, Sebastian, Dörner, Steffen, Lauster, Bianca, and Razi, Maria

Subjects
RESEARCH aircraft, AIRBORNE-based remote sensing, PEARSON correlation (Statistics), AIR pollution, OPTICAL spectroscopy, LIGHT absorption, COLUMNS
Abstract

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 formeasurements 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 kmx 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 100mx 30m, 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 kmx 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. [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

16. Ground-based validation of the Copernicus Sentinel-5P TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks

Author

Verhoelst, Tijl, Compernolle, Steven, Pinardi, Gaia, Lambert, Jean Christopher, Eskes, Henk J., Eichmann, Kai Uwe, Fjæraa, Ann Mari, Granville, José, Niemeijer, Sander, Cede, Alexander, Tiefengraber, Martin, Hendrick, François, Pazmiño, Andrea, Bais, Alkiviadis, Bazureau, Ariane, Boersma, K.F., Bognar, Kristof, Dehn, Angelika, Donner, Sebastian, Elokhov, Aleksandr, Gebetsberger, Manuel, Goutail, Florence, Grutter De La Mora, Michel, Gruzdev, Aleksandr, Gratsea, Myrto, Hansen, Georg H., Irie, Hitoshi, Jepsen, Nis, Kanaya, Yugo, Karagkiozidis, Dimitris, Kivi, Rigel, Kreher, Karin, Levelt, Pieternel F., Liu, Cheng, Müller, Moritz, Navarro Comas, Monica, Piters, Ankie J.M., Pommereau, Jean Pierre, Portafaix, Thierry, Prados-Roman, Cristina, Puentedura, Olga, Querel, Richard, Remmers, Julia, Richter, Andreas, Rimmer, John, Cárdenas, Claudia Rivera, De Miguel, Lidia Saavedra, Sinyakov, Valery P., Stremme, Wolfgang, Strong, Kimberly, Van Roozendael, Michel, Veefkind, J.P., Wagner, Thomas, Wittrock, Folkard, Yela González, Margarita, Zehner, Claus, Verhoelst, T. [0000-0003-0163-9984], Compernolle, S. [0000-0003-0872-0961], Pinardi, G. [0000-0001-5428-916X], Eskes, H. [0000-0002-8743-4455], Bais, A. [0000-0003-3899-2001], Folkert Boersma, K. [0000-0002-4591-7635], Bognar, K. [0000-0003-4619-2020], Donner, S. [0000-0001-8868-167X], Elokhov, A. [0000-0003-4725-9186], Grutter de la Mora, M. [0000-0001-9800-5878], Gruzdev, A. [0000-0003-3224-1012], Karagkiozidis, D. [0000-0002-3595-0538], Kivi, R. [0000-0001-8828-2759], Liu, C. [0000-0002-3759-9219], Müller, M. [0000-0001-5284-5425], Pommereau, J. P. [0000-0002-8285-9526], Prados Roman, C. [0000-0001-8332-0226], Puentedura, O. [0000-0002-4286-1867], Querel, R. [0000-0001-8792-2486], Richter, A. [0000-0003-3339-212X], Rivera Cárdenas, C. [0000-0002-8617-265X], Stremme, W. [0000-0003-0791-3833], Strong, K. [0000-0001-9947-1053], Pepijn Veefkind, J. [0000-0003-0336-6406], European Space Agency (ESA), French Institut National des Sciences de l'Univers (INSU), Centre National D'Etudes Spatiales (CNES), Centre National de la Recherche Scientifique (CNRS), Institut polaire français Paul Emile Victor (IPEV), and Belgian Science Policy Office (BELSPO)

Subjects
Meteorologie en Luchtkwaliteit, WIMEK, Meteorology and Air Quality, Copernicus Sentinel 5P, Life Science, Pandonia global networks
Abstract

This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOspheric Monitoring Instrument (TROPOMI) on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5P) satellite. Tropospheric, stratospheric, and total NO2 column data from S5P are compared to correlative measurements collected from, respectively, 19 Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS), 26 Network for the Detection of Atmospheric Composition Change (NDACC) Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 Pandonia Global Network (PGN)/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatio-temporal co-location of the satellite and correlative data, e.g. by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5P data show, on average, (i) a negative bias for the tropospheric column data, of typically −23 % to −37 % in clean to slightly polluted conditions but reaching values as high as −51 % over highly polluted areas; (ii) a slight negative median difference for the stratospheric column data, of about −0.2 Pmolec cm−2, i.e. approx. −2 % in summer to −15 % in winter; and (iii) a bias ranging from zero to −50 % for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6 Pmolec cm−2 and negative values above. The dispersion between S5P and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5 Pmolec cm−2) but exceed those for the tropospheric column data (0.7 Pmolec cm−2). While a part of the biases and dispersion may be due to representativeness differences such as different area averaging and measurement times, it is known that errors in the S5P tropospheric columns exist due to shortcomings in the (horizontally coarse) a priori profile representation in the TM5-MP chemical transport model used in the S5P retrieval and, to a lesser extent, to the treatment of cloud effects and aerosols. Although considerable differences (up to 2 Pmolec cm−2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and offline (OFFL) versions of the S5P NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79 % larger than the OFFL values. This research has been supported by the ESA/ESRIN (grant no. 4000117151/16/I-LG) and the BELSPO/ESA ProDEx (TROVA-E2 (PEA grant no. 4000116692)). Part of the reported work was carried out in the framework of the Copernicus Sentinel-5 Precursor Mission Performance Centre (S5P MPC), contracted by the European Space Agency and supported by the Belgian Federal Science Policy Office (BELSPO), the Royal Belgian Institute for Space Aeronomy (BIRA-IASB), the Netherlands Space Office (NSO), and the German Aerospace Centre (DLR). Part of this work was carried out also in the framework of the S5P Validation Team (S5PVT) AO projects NIDFORVAL (ID no. 28607, PI Gaia Pinardi, BIRA-IASB) and CESAR (ID no. 28596, PI Arnoud Apituley, KNMI). The authors express special thanks to Ann Mari Fjæraa, José Granville, Sander Niemeijer, and Olivier Rasson for post-processing of the network and satellite data and for their dedication to the S5P operational validation. The LATMOS real-time processing facility is acknowledged for fast delivery of ZSL-DOAS SAOZ data. Fast delivery of MAX-DOAS data tailored to the S5P validation was organized through the S5PVT AO project NIDFORVAL. The authors are grateful to ESA/ESRIN for supporting the ESA Validation Data Centre (EVDC) established at NILU and for running the Fiducial Reference Measurements (FRM) programme and in particular the FRM4DOAS and Pandonia projects. The PGN is a bilateral project between NASA and ESA, and the NASA funding for the PGN is provided through the NASA Tropospheric Composition Program and Goddard Space Flight Center Pandora project. The MAX-DOAS, ZSL-DOAS, and PGN instrument PIs and staff at the stations are thanked warmly for their sustained effort on maintaining high-quality measurements and for valuable scientific discussions. Aleksandr Elokhov and Aleksandr Gruzdev acknowledge national funding from RFBR through the project 20-95-00274. IUP Bremen acknowledges DLR Bonn for funding received through project 50EE1709A. The SAOZ network acknowledges funding from the French Institut National des Sciences de l'Univers (INSU) of the Centre National de la Recherche Scientifique (CNRS), Centre National d'Etudes Spatiales (CNES), and Institut polaire français Paul Emile Victor (IPEV). Work done by Hitoshi Irie was supported by the Environment Research and Technology Development Fund (2-1901) of the Environmental Restoration and Conservation Agency of Japan, JSPS KAKENHI (grant nos. JP19H04235 and JP17K00529), the JAXA 2nd Research Announcement on the Earth Observations (grant no. 19RT000351), and JST CREST (grant no. JPMJCR15K4). The University of Toronto ZSL-DOAS measurements at Eureka were made at the Polar Environment Atmospheric Research Laboratory (PEARL) by the Canadian Network for the Detection of Atmospheric Change (CANDAC), with support from the Canadian Space Agency (AVATARS project), the Natural Sciences and Engineering Research Council (PAHA project), and Environment and Climate Change Canada. Peerreview

Published
2021

17. Determination of NOx emission rates of sailing inland ships from on-shore measurements.

Author

Krause, Kai, Wittrock, Folkard, Richter, Andreas, Busch, Dieter, Bergen, Anton, and Burrows, John P.

Subjects
*INLAND water transportation, *SAILING ships, *TRAFFIC density, *WATERWAYS, *SHIP fuel, *ENERGY consumption
Abstract

Inland ships are an important source of NOx, especially for cities along busy waterways. The amount and effect of these emissions depends on the traffic density and the NOx emission rates of the individual vessels. Monitoring of ship emissions is usually carried out using in situ instruments on land and often relative NOx emission factors, e.g. the amount of emitted pollutants per amount of burnt fuel is reported, but in this study, NOx emission rates in g s-1 are investigated. Within the EU Life project Clean Inland Shipping (CLINSH), a new approach to calculate NOx emission rates from data of in situ measurement stations has been developed and is presented in this study. Peaks (i.e. elevated concentrations) of NOx were assigned to the corresponding source ships and each ship passage was simulated using a Gaussian-puff-model in order to derive the emission rate. In total over 32900 ship passages have been monitored over the course of 4 years. The emission rates of NOx were investigated with respect to ship speed, ship size and direction of travel. Individual comparisons of the on-shore emission rates and those made on-board of selected CLINSH ships show good agreement. Also the emission rates are of similar magnitude as emission factors from previous studies. In contrast to relative emission factors (in grams per kilogram fuel), the emission rates (in grams per second) do not need further knowledge about the fuel consumption of the ship and can therefore be used directly to investigate the effect of ship traffic on air quality. [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

18. Determination of NO x emission rates of sailing inland ships from on-shore measurements.

Author

Krause, Kai, Wittrock, Folkard, Richter, Andreas, Busch, Dieter, Bergen, Anton, and Burrows, John P.

Subjects
ATMOSPHERIC nitrous oxide, INLAND water transportation, AIR quality, SHIP fuel
Abstract

Inland ships are an important source of NO x , especially for cities along busy waterways. The amount and effect of these emissions depends on the traffic density and the NO x emission rates of the individual vessels. Monitoring of ship emissions is usually carried out using in situ instruments on land and often relative NO x emission factors, e.g. the amount of emitted pollutants per amount of burnt fuel is reported, but in this study, NO x emission rates in g s-1 are investigated. Within the EU Life project Clean Inland Shipping (CLINSH), a new approach to calculate NO x emission rates from data of in situ measurement stations has been developed and is presented in this study. Peaks (i.e. elevated concentrations) of NO x were assigned to the corresponding source ships and each ship passage was simulated using a Gaussian-puff-model in order to derive the emission rate. In total over 32900 ship passages have been monitored over the course of 4 years. The emission rates of NO x were investigated with respect to ship speed, ship size and direction of travel. Individual comparisons of the on-shore emission rates and those made on-board of selected CLINSH ships show good agreement. Also the emission rates are of similar magnitude as emission factors from previous studies. In contrast to relative emission factors (in grams per kilogram fuel), the emission rates (in grams per second) do not need further knowledge about the fuel consumption of the ship and can therefore be used directly to investigate the effect of ship traffic on air quality. [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

20. Ground-based validation of the Copernicus Sentinel-5p TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks

Author

Verhoelst, Tiji, Compernolle, Steven, Pinardi, Gala, Lambert, Jean-Christopher, Eskes, Henk J., Eichmann, Kai-Uwe, Fjæraa, Ann Mari, Granville, José, Niemeijer, Sander, Cede, Alexander, Tiefengraber, Martin, Hendrick, François, Pazmino, Andrea, Bais, Alkiviadis, Bazureau, Ariane, Boersma, Klaas Folkert, Bognar, Kristof, Dehn, Angelika, Donner, Sebastian, Elokhov, Aleksandr, Gebetsberger, Manuel, Goutail, Florence, Grutter de la Mora, Michel, Gruzdev, Aleksandr, Gratsea, Myrto, Hansen, Georg, Irie, Hitoshi, Jepsen, Nis, Kanaya, Yugo, Karagkiozidis, Dimitris, Kivi, Rigel, Kreher, Karin, Levelt, Pieternel F., Liu, Cheng, Müller, Moritz, Navarro-Comas, Monica, Piters, Ankie J. M., Pommereau, Jean-Pierre, Portafaix, Thierry, Puentedura, Olga, Querel, Richard, Remmers, Julia, Richter, Andreas, Rimmer, John, Rivera Cárdenas, Claudia, Saavedra De Miguel, Lidia, Sinyakov, Valery P., Strong, Kimberley, Van Roozendaël, Michel, Veefkind, Pepijn J., Wagner, Thomas, Wittrock, Folkard, Yela-González, Margarita, Zehner, Claus, Belgian Institute for Space Aeronomy / Institut d'Aéronomie Spatiale de Belgique (BIRA-IASB), Royal Netherlands Meteorological Institute (KNMI), Institut für Umweltphysik [Bremen] (IUP), Universität Bremen, Norsk Institutt for Luftforskning (NILU), Science [&] Technology Corporation [Delft] (S [&] T), NASA Goddard Space Flight Center (GSFC), Institute of Meteorology and Geophysics [Innsbruck], University of Innsbruck, STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), Laboratory of Atmospheric Physics [Thessaloniki], Aristotle University of Thessaloniki, Meteorology and Air Quality Group, Wageningen University and Research [Wageningen] (WUR), Department of Physics [Toronto], University of Toronto, European Space Research Institute (ESRIN), European Space Agency (ESA), Max-Planck-Institut für Chemie (MPIC), Max-Planck-Gesellschaft, A.M.Obukhov Institute of Atmospheric Physics (IAP), Russian Academy of Sciences [Moscow] (RAS), Centro de Ciencias de la Atmosfera [Mexico], Universidad Nacional Autónoma de México (UNAM), National Observatory of Athens (NOA), Center for Environmental Remote Sensing [Chiba] (CEReS), Chiba University, Danish Meteorological Institute (DMI), Research Institute for Global Change (RIGC), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Space and Earth Observation Centre [Sodankylä], Finnish Meteorological Institute (FMI), BK Scientific GmbH, Delft University of Technology (TU Delft), Department of Precision Machinery and Precision Instrumentation [Hefei], University of Science and Technology of China [Hefei] (USTC), Instituto Nacional de Técnica Aeroespacial (INTA), Laboratoire de l'Atmosphère et des Cyclones (LACy), Météo France-Université de La Réunion (UR)-Centre National de la Recherche Scientifique (CNRS), National Institute of Water and Atmospheric Research [Lauder] (NIWA), University of Manchester [Manchester], Kyrgyz National University, Institute of Environmental Physics [Bremen] (IUP), and University of Bremen

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere
Abstract

This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOMI instrument on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5p) satellite. Tropospheric, stratospheric, and total NO2 column data from S5p are compared to correlative measurements collected from, respectively, 19 Multi-Axis DOAS (MAX-DOAS), 26 NDACC Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 PGN/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatio-temporal co-location of the satellite and correlative data, e.g., by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability, and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5p data show, on an average: (i) a negative bias for the tropospheric column data, of typically −23 to −37 % in clean to slightly polluted conditions, but reaching values as high as −51 % over highly polluted areas; (ii) a slight negative bias for the stratospheric column data, of about −0.2 Pmolec/cm2, i.e. approx. −2 % in summer to −15 % in winter; and (iii) a bias ranging from zero to −50 % for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6 Pmolec/cm2 and negative values above. The dispersion between S5p and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5 Pmolec/cm2), but exceed those for the tropospheric column data (0.7 Pmolec/cm2). While a part of the biases and dispersion may be due to representativeness differences, it is known that errors in the S5p tropospheric columns exist due to shortcomings in the (horizontally coarse) a-priori profile representation in the TM5-MP chemistry transport model used in the S5p retrieval, and to a lesser extent, to the treatment of cloud effects. Although considerable differences (up to 2 Pmolec/cm2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and off-line (OFFL) versions of the S5p NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79 % larger than the OFFL values.

Published
2020

21. Intercomparison of NO2, O-4, O-3 and HCHO slant column measurements by MAX-DOAS and zenith-sky UV-visible spectrometers during CINDI-2

Author

Kreher, Karin, Van Roozendael, Michel, Hendrick, Francois, Apituley, Arnoud, Dimitropoulou, Ermioni, Friess, Udo, Richter, Andreas, Wagner, Thomas, Lampel, Johannes, Abuhassan, Nader, Ang, Li, Anguas, Monica, Bais, Alkis, Benavent, Nuria, Boesch, Tim, Bognar, Kristof, Borovski, Alexander, Bruchkouski, Ilya, Cede, Alexander, Chan, Ka Lok, Donner, Sebastian, Drosoglou, Theano, Fayt, Caroline, Finkenzeller, Henning, Garcia-Nieto, David, Gielen, Clio, Gomez-Martin, Laura, Hao, Nan, Henzing, Bas, Herman, Jay R., Hermans, Christian, Hoque, Syedul, Irie, Hitoshi, Jin, Junli, Johnston, Paul, Butt, Junaid Khayyam, Khokhar, Fahim, Koenig, Theodore K., Kuhn, Jonas, Kumar, Vinod, Liu, Cheng, Ma, Jianzhong, Merlaud, Alexis, Mishra, Abhishek K., Mueller, Moritz, Navarro-Comas, Monica, Ostendorf, Mareike, Pazmino, Andrea, Peters, Enno, Pinardi, Gaia, Pinharanda, Manuel, Piters, Ankie, Platt, Ulrich, Postylyakov, Oleg, Prados-Roman, Cristina, Puentedura, Olga, Querel, Richard, Saiz-Lopez, Alfonso, Schoenhardt, Anja, Schreier, Stefan F., Seyler, Andre, Sinha, Vinayak, Spinei, Elena, Strong, Kimberly, Tack, Frederik, Tian, Xin, Tiefengraber, Martin, Tirpitz, Jan-Lukas, van Gent, Jeron, Volkamer, Rainer, Vrekoussis, Mihalis, Wang, Shanshan, Wang, Zhuoru, Wenig, Mark, Wittrock, Folkard, Xie, Pinhua H., Xu, Jin, Yela, Margarita, Zhang, Chengxin, Zhao, Xiaoyi, BK Scientific GmbH, Belgian Institute for Space Aeronomy / Institut d'Aéronomie Spatiale de Belgique (BIRA-IASB), Royal Netherlands Meteorological Institute (KNMI), Institut für Umweltphysik [Heidelberg], Universität Heidelberg [Heidelberg], Institute of Environmental Physics [Bremen] (IUP), University of Bremen, Max-Planck-Institut für Chemie (MPIC), Max-Planck-Gesellschaft, NASA Goddard Space Flight Center (GSFC), Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences [Changchun Branch] (CAS), Instituto de Química Física Rocasolano (IQFR), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Laboratory of Atmospheric Physics [Thessaloniki], Aristotle University of Thessaloniki, Department of Physics [Toronto], University of Toronto, A.M.Obukhov Institute of Atmospheric Physics (IAP), Russian Academy of Sciences [Moscow] (RAS), Belarusian State University, Meteorologisches Institut München (MIM), Ludwig-Maximilians-Universität München (LMU), School of Earth and Space Sciences [Hefei], University of Science and Technology of China [Hefei] (USTC), Department of Chemistry and Biochemistry [Boulder], University of Colorado [Boulder], Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado [Boulder]-National Oceanic and Atmospheric Administration (NOAA), Instituto Nacional de Técnica Aeroespacial (INTA), European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), The Netherlands Organisation for Applied Scientific Research (TNO), Center for Environmental Remote Sensing [Chiba] (CEReS), Chiba University, Chinese Academy of Meteorological Sciences (CAMS), National Institute of Water and Atmospheric Research [Lauder] (NIWA), National University of Sciences and Technology [Islamabad] (NUST), Institute of Environmental Physics [Heidelberg] (IUP), Indian Institute of Science Education and Research Mohali (IISER Mohali), Department of Earth and Environmental Sciences [Mohali], Department of Atmospheric and Cryospheric Sciences [Innsbruck] (ACINN), Universität Innsbruck [Innsbruck], STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), Institute for the Protection of Maritime Infrastructures, Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institute for Meteorology and Climatology [Vienna] (BOKU-Met), University of Natural Resources and Life Sciences (BOKU), Virginia Polytechnic Institute and State University [Blacksburg], Center for Marine Environmental Sciences [Bremen] (MARUM), Universität Bremen, Energy, Environment and Water Research Center (EEWRC), Cyprus Institute (CyI), Liaoning Technical University [Huludao], Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Fudan University [Shanghai], DLR Institut für Methodik der Fernerkundung / DLR Remote Sensing Technology Institute (IMF), Deutsches Zentrum für Luft- und Raumfahrt [Oberpfaffenhofen-Wessling] (DLR), Environment and Climate Change Canada, and Electrical and Computer Engineering

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Science & Technology, RAMAN-SCATTERING, RETRIEVAL, CROSS-SECTIONS, BRO, RADIATIVE-TRANSFER, Physical Sciences, Meteorology & Atmospheric Sciences, OPTICAL-ABSORPTION SPECTROSCOPY, FORMALDEHYDE, CAMPAIGN, NITROGEN-DIOXIDE, AEROSOL EXTINCTION
Abstract

In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 d during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, the Netherlands (51.97 degrees N, 4.93 degrees E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were (1) to characterise and better understand the differences between a large number of multi-axis differential optical absorption spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, (2) to define a robust methodology for performance assessment of all participating instruments, and (3) to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation. The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO2), the oxygen collision complex (O-4) and ozone (O-3) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region, and NO2 in an additional (smaller) wavelength range in the visible region. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in a unique set of measurements made under highly comparable air mass conditions. The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the selected reference (which is obtained from the median of either all data sets or a subset), and the rms error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the consistency between all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques. Netherlands Space Office (NSO); ESA through the CINDI-2 (ESA) project [4000118533/16/I-Sbo]; ESA through the FRM4DOAS (ESA) project [4000118181/16/I-EF]; EU 7th Framework Programme QA4ECV projectEuropean Union (EU) [607405]; Austrian Science Fund (FWF)Austrian Science Fund (FWF) [I 2296-N29]; Canadian Space Agency (AVATARS project); Natural Sciences and Engineering Research Council (PAHA project); Canada Foundation for InnovationCanada Foundation for Innovation; UVAS ("Ultraviolet and Visible Atmospheric Sounder") projects SEOSAT/INGENIO [ESP2015-71299-R]; DFG project RAPSODI [PL 193/17-1]; Centre National de la Recherche Scientifique (CNRS)Centre National de la Recherche Scientifique (CNRS); Centre National d'Etudes Spatiales (CNES)Centre National D'etudes Spatiales; National funding project HELADO [CTM2013-41311-P]; National funding project AVATAR [CGL2014-55230-R]; Russian Science FoundationRussian Science Foundation (RSF) [16-17-10275]; Russian Foundation for Basic ResearchRussian Foundation for Basic Research (RFBR) [16-05-01062, 18-35-00682]; ACTRIS-2 (H2020 grant) [654109]; NASA's Atmospheric Composition ProgramNational Aeronautics & Space Administration (NASA) [NASA-16-NUP2016-0001]; US National Science FoundationNational Science Foundation (NSF) [AGS-1620530]; NASANational Aeronautics & Space Administration (NASA); University of Bremen; DFG Research Center/Cluster of Excellence "The Ocean in the Earth System-MARUM"German Research Foundation (DFG); University of Bremen Institutional Strategy of the DFG; Luftblick through the ESA Pandonia Project; NASA Pandora Project at the Goddard Space Flight Center under NASA Headquarters' Tropospheric Composition Program CINDI-2 received funding from the Netherlands Space Office (NSO). Funding for this study was provided by ESA through the CINDI-2 (ESA contract no. 4000118533/16/I-Sbo) and FRM4DOAS (ESA contract no. 4000118181/16/I-EF) projects and partly within the EU 7th Framework Programme QA4ECV project (grant agreement no. 607405). The BOKU MAX-DOAS instrument was funded and the participation of Stefan F. Schreier was supported by the Austrian Science Fund (FWF): I 2296-N29. The participation of the University of Toronto team was supported by the Canadian Space Agency (through the AVATARS project) and the Natural Sciences and Engineering Research Council (through the PAHA project). The instrument was primarily funded by the Canada Foundation for Innovation and is usually operated at the Polar Environment Atmospheric Research Laboratory (PEARL) by the Canadian Network for the Detection of Atmospheric Change (CANDAC). Funding for CISC was provided by the UVAS ("Ultraviolet and Visible Atmospheric Sounder") projects SEOSAT/INGENIO, ESP2015-71299-R, MINECO-FEDER and UE. The activities of the IUP-Heidelberg were supported by the DFG project RAPSODI (grant no. PL 193/17-1). SAOZ and Mini-SAOZ instruments are supported by the Centre National de la Recherche Scientifique (CNRS) and the Centre National d'Etudes Spatiales (CNES). INTA recognises support from the National funding projects HELADO (CTM2013-41311-P) and AVATAR (CGL2014-55230-R). AMOIAP recognises support from the Russian Science Foundation (grant no. 16-17-10275) and the Russian Foundation for Basic Research (grant nos. 16-05-01062 and 18-35-00682). Ka L. Chan received transnational access funding from ACTRIS-2 (H2020 grant agreement no. 654109). Rainer Volkamer recognises funding from NASA's Atmospheric Composition Program (NASA-16-NUP2016-0001) and the US National Science Foundation (award AGS-1620530). Henning Finkenzeller is the recipient of a NASA graduate fellowship. Mihalis Vrekoussis recognises support from the University of Bremen and the DFG Research Center/Cluster of Excellence "The Ocean in the Earth System-MARUM". Financial support through the University of Bremen Institutional Strategy in the framework of the DFG Excellence Initiative is gratefully appreciated for Anja Schonhardt. Pandora instrument deployment was supported by Luftblick through the ESA Pandonia Project and NASA Pandora Project at the Goddard Space Flight Center under NASA Headquarters' Tropospheric Composition Program. The article processing charges for this open-access publication were covered by BK Scientific.

Published
2020

22. Validation of tropospheric NO2 column measurements of GOME-2A and OMI using MAX-DOAS and direct sun network observations

Author

Pinardi, Gaia, Roozendael, Michel, Hendrick, François, Theys, Nicolas, Abuhassan, Nader, Bais, Alkiviadis, Boersma, Folkert, Cede, Alexander, Chong, Jihyo, Donner, Sebastian, Drosoglou, Theano, Frieß, Udo, Granville, José, Herman, Jay R., Eskes, Henk, Holla, Robert, Hovila, Jari, Irie, Hitoshi, Kanaya, Yugo, Karagkiozidis, Dimitris, Kouremeti, Natalia, Lambert, Jean-Christopher, Ma, Jianzhong, Peters, Enno, Piters, Ankie, Postylyakov, Oleg, Richter, Andreas, Remmers, Julia, Takashima, Hisahiro, Tiefengraber, Martin, Valks, Pieter, Vlemmix, Tim, Wagner, Thomas, and Wittrock, Folkard

Abstract

MAX-DOAS and direct sun NO2 vertical column network data are used to investigate the accuracy of tropospheric NO2 column measurements of the GOME-2 instrument on the MetOP-A satellite platform and the OMI instrument on Aura. The study is based on 23 MAX-DOAS and 16 direct sun instruments at stations distributed worldwide. A method to quantify and correct for horizontal dilution effects in heterogeneous NO2 field conditions is proposed. After systematic application of this correction to urban sites, satellite measurements are found to present smaller biases compared to ground-based reference data in almost all cases. We investigate the seasonal dependence of the validation results, as well as the impact of using different approaches to select satellite ground pixels in coincidence with ground-based data. In optimal comparison conditions (satellite pixels containing the station) the median bias between satellite tropospheric NO2 column measurements and the ensemble of MAX-DOAS and direct sun measurements is found to be significant and equal to −36 % for GOME-2A and −20 % for OMI. These biases are further reduced to −24 % and −8 % respectively, after application of the dilution correction. Comparisons with the QA4ECV satellite product for both GOME-2A and OMI is also performed, showing less scatter but also a slightly larger median tropospheric NO2 column bias with respect to the ensemble of MAX-DOAS and direct sun measurements.

Published
2020

23. Intercomparison of NO2, O4, O3 and HCHO slant column measurements by MAX-DOAS and zenith-sky UV–visible spectrometers during CINDI-2

Author

Electrical and Computer Engineering, Kreher, Karin, Van Roozendael, Michel, Hendrick, Francois, Apituley, Arnoud, Dimitropoulou, Ermioni, Friess, Udo, Richter, Andreas, Wagner, Thomas, Lampel, Johannes, Abuhassan, Nader, Ang, Li, Anguas, Monica, Bais, Alkis, Benavent, Nuria, Boesch, Tim, Bognar, Kristof, Borovski, Alexander, Bruchkouski, Ilya, Cede, Alexander, Chan, Ka Lok, Donner, Sebastian, Drosoglou, Theano, Fayt, Caroline, Finkenzeller, Henning, Garcia-Nieto, David, Gielen, Clio, Gomez-Martin, Laura, Hao, Nan, Henzing, Bas, Herman, Jay R., Hermans, Christian, Hoque, Syedul, Irie, Hitoshi, Jin, Junli, Johnston, Paul, Butt, Junaid Khayyam, Khokhar, Fahim, Koenig, Theodore K., Kuhn, Jonas, Kumar, Vinod, Liu, Cheng, Ma, Jianzhong, Merlaud, Alexis, Mishra, Abhishek K., Mueller, Moritz, Navarro-Comas, Monica, Ostendorf, Mareike, Pazmino, Andrea, Peters, Enno, Pinardi, Gaia, Pinharanda, Manuel, Piters, Ankie, Platt, Ulrich, Postylyakov, Oleg, Prados-Roman, Cristina, Puentedura, Olga, Querel, Richard, Saiz-Lopez, Alfonso, Schoenhardt, Anja, Schreier, Stefan F., Seyler, Andre, Sinha, Vinayak, Spinei, Elena, Strong, Kimberly, Tack, Frederik, Tian, Xin, Tiefengraber, Martin, Tirpitz, Jan-Lukas, van Gent, Jeron, Volkamer, Rainer, Vrekoussis, Mihalis, Wang, Shanshan, Wang, Zhuoru, Wenig, Mark, Wittrock, Folkard, Xie, Pinhua H., Xu, Jin, Yela, Margarita, Zhang, Chengxin, Zhao, Xiaoyi, Electrical and Computer Engineering, Kreher, Karin, Van Roozendael, Michel, Hendrick, Francois, Apituley, Arnoud, Dimitropoulou, Ermioni, Friess, Udo, Richter, Andreas, Wagner, Thomas, Lampel, Johannes, Abuhassan, Nader, Ang, Li, Anguas, Monica, Bais, Alkis, Benavent, Nuria, Boesch, Tim, Bognar, Kristof, Borovski, Alexander, Bruchkouski, Ilya, Cede, Alexander, Chan, Ka Lok, Donner, Sebastian, Drosoglou, Theano, Fayt, Caroline, Finkenzeller, Henning, Garcia-Nieto, David, Gielen, Clio, Gomez-Martin, Laura, Hao, Nan, Henzing, Bas, Herman, Jay R., Hermans, Christian, Hoque, Syedul, Irie, Hitoshi, Jin, Junli, Johnston, Paul, Butt, Junaid Khayyam, Khokhar, Fahim, Koenig, Theodore K., Kuhn, Jonas, Kumar, Vinod, Liu, Cheng, Ma, Jianzhong, Merlaud, Alexis, Mishra, Abhishek K., Mueller, Moritz, Navarro-Comas, Monica, Ostendorf, Mareike, Pazmino, Andrea, Peters, Enno, Pinardi, Gaia, Pinharanda, Manuel, Piters, Ankie, Platt, Ulrich, Postylyakov, Oleg, Prados-Roman, Cristina, Puentedura, Olga, Querel, Richard, Saiz-Lopez, Alfonso, Schoenhardt, Anja, Schreier, Stefan F., Seyler, Andre, Sinha, Vinayak, Spinei, Elena, Strong, Kimberly, Tack, Frederik, Tian, Xin, Tiefengraber, Martin, Tirpitz, Jan-Lukas, van Gent, Jeron, Volkamer, Rainer, Vrekoussis, Mihalis, Wang, Shanshan, Wang, Zhuoru, Wenig, Mark, Wittrock, Folkard, Xie, Pinhua H., Xu, Jin, Yela, Margarita, Zhang, Chengxin, and Zhao, Xiaoyi

Abstract

In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 d during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, the Netherlands (51.97 degrees N, 4.93 degrees E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were (1) to characterise and better understand the differences between a large number of multi-axis differential optical absorption spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, (2) to define a robust methodology for performance assessment of all participating instruments, and (3) to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation. The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO2), the oxygen collision complex (O-4) and ozone (O-3) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region, and NO2 in an additional (smaller) wavelength range in the visible region. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in a unique set of measurements made under highly comparable air mass conditions. The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by

Published
2020

24. Intercomparison of MAX-DOAS vertical profile retrieval algorithms: studies on field data from the CINDI-2 campaign

Author

Tirpitz, Jan-Lukas, primary, Frieß, Udo, additional, Hendrick, François, additional, Alberti, Carlos, additional, Allaart, Marc, additional, Apituley, Arnoud, additional, Bais, Alkis, additional, Beirle, Steffen, additional, Berkhout, Stijn, additional, Bognar, Kristof, additional, Bösch, Tim, additional, Bruchkouski, Ilya, additional, Cede, Alexander, additional, Chan, Ka Lok, additional, den Hoed, Mirjam, additional, Donner, Sebastian, additional, Drosoglou, Theano, additional, Fayt, Caroline, additional, Friedrich, Martina M., additional, Frumau, Arnoud, additional, Gast, Lou, additional, Gielen, Clio, additional, Gomez-Martín, Laura, additional, Hao, Nan, additional, Hensen, Arjan, additional, Henzing, Bas, additional, Hermans, Christian, additional, Jin, Junli, additional, Kreher, Karin, additional, Kuhn, Jonas, additional, Lampel, Johannes, additional, Li, Ang, additional, Liu, Cheng, additional, Liu, Haoran, additional, Ma, Jianzhong, additional, Merlaud, Alexis, additional, Peters, Enno, additional, Pinardi, Gaia, additional, Piters, Ankie, additional, Platt, Ulrich, additional, Puentedura, Olga, additional, Richter, Andreas, additional, Schmitt, Stefan, additional, Spinei, Elena, additional, Stein Zweers, Deborah, additional, Strong, Kimberly, additional, Swart, Daan, additional, Tack, Frederik, additional, Tiefengraber, Martin, additional, van der Hoff, René, additional, van Roozendael, Michel, additional, Vlemmix, Tim, additional, Vonk, Jan, additional, Wagner, Thomas, additional, Wang, Yang, additional, Wang, Zhuoru, additional, Wenig, Mark, additional, Wiegner, Matthias, additional, Wittrock, Folkard, additional, Xie, Pinhua, additional, Xing, Chengzhi, additional, Xu, Jin, additional, Yela, Margarita, additional, Zhang, Chengxin, additional, and Zhao, Xiaoyi, additional

Published
2021
Full Text
View/download PDF

25. GOME observations of stratospheric trace gas distributions during the splitting vortex event in the Antarctic winter of 2002. Part 1: measurements

Author

Richter, Andreas, Wittrock, Folkard, Weber, Mark, Beirle, Steffen, Kuhl, Sven, Platt, Ulrich, Wagner, Thomas, Wilms-Grabe, Walburga, and Burrows, John P.

Subjects
Global warming -- Research, Ozone layer depletion -- Research, Atmosphere -- Research, Earth -- Atmosphere, Earth -- Research, Earth sciences, Science and technology
Abstract

Measurements from the Global Ozone Monitoring Experiment (GOME) are used to study the chemical evolution of the stratosphere during the unusual 2002 winter in the Southern Hemisphere. The results show that chlorine activation as indicated by OCIO columns was similar to previous years in the vortex until the major warming on 26 September 2002 after which it decreased rapidly. Similarly, N[O.sub.2] columns were only slightly larger than in previous years before the warming, indicating strong denoxification and probably also denitrification. After the warming, very large N[O.sub.2] columns were observed for a few days, which then decreased again as the vortex reestablished itself until the final warming. Ozone columns were much larger than in any previous year from September onward, mainly as a result of the unusual dynamical situation. Analysis of the global long-term time series of GOME measurements since 1996 provides a unique opportunity to set the austral winter 2002 into perspective. The GOME data reveal the large difference in variability of chlorine activation between the two hemispheres, whereas denoxification shows surprisingly little variation from year to year in both hemispheres. However, N[O.sub.2] depletion in the Southern Hemisphere is usually sustained for about one month longer in the Antarctic stratosphere as a result of the stable vortex. Compared to the observations in the Northern Hemisphere, the austral winter 2002 was still stable and cold and had a high potential for chemical ozone destruction.

Published
2005

27. Validation of tropospheric NO<sub>2</sub> column measurements of GOME-2A and OMI using MAX-DOAS and direct sun network observations

Author

Pinardi, Gaia, primary, Van Roozendael, Michel, additional, Hendrick, François, additional, Theys, Nicolas, additional, Abuhassan, Nader, additional, Bais, Alkiviadis, additional, Boersma, Folkert, additional, Cede, Alexander, additional, Chong, Jihyo, additional, Donner, Sebastian, additional, Drosoglou, Theano, additional, Dzhola, Anatoly, additional, Eskes, Henk, additional, Frieß, Udo, additional, Granville, José, additional, Herman, Jay R., additional, Holla, Robert, additional, Hovila, Jari, additional, Irie, Hitoshi, additional, Kanaya, Yugo, additional, Karagkiozidis, Dimitris, additional, Kouremeti, Natalia, additional, Lambert, Jean-Christopher, additional, Ma, Jianzhong, additional, Peters, Enno, additional, Piters, Ankie, additional, Postylyakov, Oleg, additional, Richter, Andreas, additional, Remmers, Julia, additional, Takashima, Hisahiro, additional, Tiefengraber, Martin, additional, Valks, Pieter, additional, Vlemmix, Tim, additional, Wagner, Thomas, additional, and Wittrock, Folkard, additional

Published
2020
Full Text
View/download PDF

28. Ground-based validation of the Copernicus Sentinel-5p TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks

Author

Verhoelst, Tijl, primary, Compernolle, Steven, additional, Pinardi, Gaia, additional, Lambert, Jean-Christopher, additional, Eskes, Henk J., additional, Eichmann, Kai-Uwe, additional, Fjæraa, Ann Mari, additional, Granville, José, additional, Niemeijer, Sander, additional, Cede, Alexander, additional, Tiefengraber, Martin, additional, Hendrick, François, additional, Pazmiño, Andrea, additional, Bais, Alkiviadis, additional, Bazureau, Ariane, additional, Boersma, K. Folkert, additional, Bognar, Kristof, additional, Dehn, Angelika, additional, Donner, Sebastian, additional, Elokhov, Aleksandr, additional, Gebetsberger, Manuel, additional, Goutail, Florence, additional, Grutter de la Mora, Michel, additional, Gruzdev, Aleksandr, additional, Gratsea, Myrto, additional, Hansen, Georg H., additional, Irie, Hitoshi, additional, Jepsen, Nis, additional, Kanaya, Yugo, additional, Karagkiozidis, Dimitris, additional, Kivi, Rigel, additional, Kreher, Karin, additional, Levelt, Pieternel F., additional, Liu, Cheng, additional, Müller, Moritz, additional, Navarro Comas, Monica, additional, Piters, Ankie J. M., additional, Pommereau, Jean-Pierre, additional, Portafaix, Thierry, additional, Puentedura, Olga, additional, Querel, Richard, additional, Remmers, Julia, additional, Richter, Andreas, additional, Rimmer, John, additional, Rivera Cárdenas, Claudia, additional, Saavedra de Miguel, Lidia, additional, Sinyakov, Valery P., additional, Strong, Kimberley, additional, Van Roozendael, Michel, additional, Veefkind, J. Pepijn, additional, Wagner, Thomas, additional, Wittrock, Folkard, additional, Yela González, Margarita, additional, and Zehner, Claus, additional

Published
2020
Full Text
View/download PDF

29. Intercomparison of NO<sub>2</sub>, O<sub>4</sub>, O<sub>3</sub> and HCHO slant column measurements by MAX-DOAS and zenith-sky UV–visible spectrometers during CINDI-2

Author

Kreher, Karin, primary, Van Roozendael, Michel, additional, Hendrick, Francois, additional, Apituley, Arnoud, additional, Dimitropoulou, Ermioni, additional, Frieß, Udo, additional, Richter, Andreas, additional, Wagner, Thomas, additional, Lampel, Johannes, additional, Abuhassan, Nader, additional, Ang, Li, additional, Anguas, Monica, additional, Bais, Alkis, additional, Benavent, Nuria, additional, Bösch, Tim, additional, Bognar, Kristof, additional, Borovski, Alexander, additional, Bruchkouski, Ilya, additional, Cede, Alexander, additional, Chan, Ka Lok, additional, Donner, Sebastian, additional, Drosoglou, Theano, additional, Fayt, Caroline, additional, Finkenzeller, Henning, additional, Garcia-Nieto, David, additional, Gielen, Clio, additional, Gómez-Martín, Laura, additional, Hao, Nan, additional, Henzing, Bas, additional, Herman, Jay R., additional, Hermans, Christian, additional, Hoque, Syedul, additional, Irie, Hitoshi, additional, Jin, Junli, additional, Johnston, Paul, additional, Khayyam Butt, Junaid, additional, Khokhar, Fahim, additional, Koenig, Theodore K., additional, Kuhn, Jonas, additional, Kumar, Vinod, additional, Liu, Cheng, additional, Ma, Jianzhong, additional, Merlaud, Alexis, additional, Mishra, Abhishek K., additional, Müller, Moritz, additional, Navarro-Comas, Monica, additional, Ostendorf, Mareike, additional, Pazmino, Andrea, additional, Peters, Enno, additional, Pinardi, Gaia, additional, Pinharanda, Manuel, additional, Piters, Ankie, additional, Platt, Ulrich, additional, Postylyakov, Oleg, additional, Prados-Roman, Cristina, additional, Puentedura, Olga, additional, Querel, Richard, additional, Saiz-Lopez, Alfonso, additional, Schönhardt, Anja, additional, Schreier, Stefan F., additional, Seyler, André, additional, Sinha, Vinayak, additional, Spinei, Elena, additional, Strong, Kimberly, additional, Tack, Frederik, additional, Tian, Xin, additional, Tiefengraber, Martin, additional, Tirpitz, Jan-Lukas, additional, van Gent, Jeroen, additional, Volkamer, Rainer, additional, Vrekoussis, Mihalis, additional, Wang, Shanshan, additional, Wang, Zhuoru, additional, Wenig, Mark, additional, Wittrock, Folkard, additional, Xie, Pinhua H., additional, Xu, Jin, additional, Yela, Margarita, additional, Zhang, Chengxin, additional, and Zhao, Xiaoyi, additional

Published
2020
Full Text
View/download PDF

30. Supplementary material to "Validation of tropospheric NO2 column measurements of GOME-2A and OMI using MAX-DOAS and direct sun network observations"

Author

Pinardi, Gaia, primary, Van Roozendael, Michel, additional, Hendrick, François, additional, Theys, Nicolas, additional, Abuhassan, Nader, additional, Bais, Alkiviadis, additional, Boersma, Folkert, additional, Cede, Alexander, additional, Chong, Jihyo, additional, Donner, Sebastian, additional, Drosoglou, Theano, additional, Frieß, Udo, additional, Granville, José, additional, Herman, Jay R., additional, Eskes, Henk, additional, Holla, Robert, additional, Hovila, Jari, additional, Irie, Hitoshi, additional, Kanaya, Yugo, additional, Karagkiozidis, Dimitris, additional, Kouremeti, Natalia, additional, Lambert, Jean-Christopher, additional, Ma, Jianzhong, additional, Peters, Enno, additional, Piters, Ankie, additional, Postylyakov, Oleg, additional, Richter, Andreas, additional, Remmers, Julia, additional, Takashima, Hisahiro, additional, Tiefengraber, Martin, additional, Valks, Pieter, additional, Vlemmix, Tim, additional, Wagner, Thomas, additional, and Wittrock, Folkard, additional

Published
2020
Full Text
View/download PDF

33. Intercomparison of MAX-DOAS vertical profile retrieval algorithms: studies on field data from the CINDI-2 campaign

Author

Tirpitz, Jan-Lukas, primary, Frieß, Udo, additional, Hendrick, François, additional, Alberti, Carlos, additional, Allaart, Marc, additional, Apituley, Arnoud, additional, Bais, Alkis, additional, Beirle, Steffen, additional, Berkhout, Stijn, additional, Bognar, Kristof, additional, Bösch, Tim, additional, Bruchkouski, Ilya, additional, Cede, Alexander, additional, Chan, Ka Lok, additional, den Hoed, Mirjam, additional, Donner, Sebastian, additional, Drosoglou, Theano, additional, Fayt, Caroline, additional, Friedrich, Martina M., additional, Frumau, Arnoud, additional, Gast, Lou, additional, Gielen, Clio, additional, Gomez-Martín, Laura, additional, Hao, Nan, additional, Hensen, Arjen, additional, Henzing, Bas, additional, Hermans, Christian, additional, Jin, Junli, additional, Kreher, Karin, additional, Kuhn, Jonas, additional, Lampel, Johannes, additional, Li, Ang, additional, Liu, Cheng, additional, Liu, Haoran, additional, Ma, Jianzhong, additional, Merlaud, Alexis, additional, Peters, Enno, additional, Pinardi, Gaia, additional, Piters, Ankie, additional, Platt, Ulrich, additional, Puentedura, Olga, additional, Richter, Andreas, additional, Schmitt, Stefan, additional, Spinei, Elena, additional, Stein Zweers, Deborah, additional, Strong, Kimberly, additional, Swart, Daan, additional, Tack, Frederick, additional, Tiefengraber, Martin, additional, van der Hoff, René, additional, van Roozendael, Michel, additional, Vlemmix, Tim, additional, Vonk, Jan, additional, Wagner, Thomas, additional, Wang, Yang, additional, Wang, Zhuoru, additional, Wenig, Mark, additional, Wiegner, Matthias, additional, Wittrock, Folkard, additional, Xie, Pinhua, additional, Xing, Chengzhi, additional, Xu, Jin, additional, Yela, Margarita, additional, Zhang, Chengxin, additional, and Zhao, Xiaoyi, additional

Published
2020
Full Text
View/download PDF

34. Supplementary material to "Intercomparison of MAX-DOAS vertical profile retrieval algorithms: studies on field data from the CINDI-2 campaign"

Author

Tirpitz, Jan-Lukas, primary, Frieß, Udo, additional, Hendrick, François, additional, Alberti, Carlos, additional, Allaart, Marc, additional, Apituley, Arnoud, additional, Bais, Alkis, additional, Beirle, Steffen, additional, Berkhout, Stijn, additional, Bognar, Kristof, additional, Bösch, Tim, additional, Bruchkouski, Ilya, additional, Cede, Alexander, additional, Chan, Ka Lok, additional, den Hoed, Mirjam, additional, Donner, Sebastian, additional, Drosoglou, Theano, additional, Fayt, Caroline, additional, Friedrich, Martina M., additional, Frumau, Arnoud, additional, Gast, Lou, additional, Gielen, Clio, additional, Gomez-Martín, Laura, additional, Hao, Nan, additional, Hensen, Arjen, additional, Henzing, Bas, additional, Hermans, Christian, additional, Jin, Junli, additional, Kreher, Karin, additional, Kuhn, Jonas, additional, Lampel, Johannes, additional, Li, Ang, additional, Liu, Cheng, additional, Liu, Haoran, additional, Ma, Jianzhong, additional, Merlaud, Alexis, additional, Peters, Enno, additional, Pinardi, Gaia, additional, Piters, Ankie, additional, Platt, Ulrich, additional, Puentedura, Olga, additional, Richter, Andreas, additional, Schmitt, Stefan, additional, Spinei, Elena, additional, Stein Zweers, Deborah, additional, Strong, Kimberly, additional, Swart, Daan, additional, Tack, Frederick, additional, Tiefengraber, Martin, additional, van der Hoff, René, additional, van Roozendael, Michel, additional, Vlemmix, Tim, additional, Vonk, Jan, additional, Wagner, Thomas, additional, Wang, Yang, additional, Wang, Zhuoru, additional, Wenig, Mark, additional, Wiegner, Matthias, additional, Wittrock, Folkard, additional, Xie, Pinhua, additional, Xing, Chengzhi, additional, Xu, Jin, additional, Yela, Margarita, additional, Zhang, Chengxin, additional, and Zhao, Xiaoyi, additional

Published
2020
Full Text
View/download PDF

35. Intercomparison of NO2, O4, O3 and HCHO slant column measurements by MAX-DOAS and zenith-sky UV-Visible spectrometers during the CINDI-2 campaign

Author

Kreher, Karin, Roozendael, Michel, Hendrick, Francois, Apituley, Arnoud, Dimitropoulou, Ermioni, Frieß, Udo, Richter, Andreas, Wagner, Thomas, Abuhassan, Nader, Ang, Li, Anguas, Monica, Bais, Alkis, Benavent, Nuria, Bösch, Tim, Bognar, Kristof, Borovski, Alexander, Bruchkouski, Ilya, Cede, Alexander, Chan, Ka L., Donner, Sebastian, Drosoglou, Theano, Fayt, Caroline, Finkenzeller, Henning, Garcia-Nieto, David, Gielen, Clio, Gómez-Martín, Laura, Hao, Nan, Herman, Jay R., Hermans, Christian, Hoque, Syedul, Irie, Hitoshi, Jin, Junli, Johnston, Paul, Khayyam Butt, Junaid, Khokhar, Fahim, Koenig, Theodore K., Kuhn, Jonas, Kumar, Vinod, Lampel, Johannes, Liu, Cheng, Ma, Jianzhong, Merlaud, Alexis, Mishra, Abhishek K., Müller, Moritz, Navarro-Comas, Monica, Ostendorf, Mareike, Pazmino, Andrea, Peters, Enno, Pinardi, Gaia, Pinharanda, Manuel, Piters, Ankie, Platt, Ulrich, Postylyakov, Oleg, Prados-Roman, Cristina, Puentedura, Olga, Querel, Richard, Saiz-Lopez, Alfonso, Schönhardt, Anja, Schreier, Stefan F., Seyler, Andre, Sinha, Vinayak, Spinei, Elena, Strong, Kimberly, Tack, Frederik, Tian, Xin, Tiefengraber, Martin, Tirpitz, Jan-Lukas, Gent, Jeron, Volkamer, Rainer, Vrekoussis, Mihalis, Wang, Shanshan, Wang, Zhuoru, Wenig, Mark, Wittrock, Folkard, Xie, Pinhua H., Xu, Jin, Yela, Margarita, Zhang, Chengxin, and Zhao, Xiaoyi

Abstract

In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 days during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, The Netherlands (51.97° N, 4.93° E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were to characterise and better understand the differences between a large number of Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, to discuss the performance of the various types of instruments and to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation. The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO2), the oxygen dimer (O4) and ozone (O3) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region and NO2 in an additional (smaller) wavelength range in the visible. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in an unprecedented set of measurements made under highly comparable air mass conditions. The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the reference, and the RMS error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the measurement performance of all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques.

Published
2019

36. Studies of the horizontal inhomogeneities in NO2 concentrations above a shipping lane using ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements and validation with airborne imaging DOAS measurements

Author

Seyler, André, Meier, Andreas C., Wittrock, Folkard, Kattner, Lisa, Mathieu-Üffing, Barbara, Peters, Enno, Richter, Andreas, Ruhtz, Thomas, Schönhardt, Anja, Schmolke, Stefan, and Burrows, John P.

Subjects
NO2 concentration, 500 Naturwissenschaften und Mathematik::500 Naturwissenschaften::500 Naturwissenschaften und Mathematik, multi-axis differential optical absorption spectroscopy (MAX-DOAS)
Abstract

This study describes a novel application of an “onion-peeling” approach to multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements of shipping emissions aiming at investigating the strong horizontal inhomogeneities in NO2 over a shipping lane. To monitor ship emissions on the main shipping route towards the port of Hamburg, a two-channel (UV and visible) MAX-DOAS instrument was deployed on the island Neuwerk in the German Bight, 6–7 km south of the main shipping lane. Utilizing the fact that the effective light path length in the atmosphere depends systematically on wavelength, simultaneous measurements and DOAS retrievals in the UV and visible spectral ranges are used to probe air masses at different horizontal distances to the instrument to estimate two-dimensional pollutant distributions. Two case studies have been selected to demonstrate the ability to derive the approximate plume positions in the observed area. A situation with northerly wind shows high NO2 concentrations close to the measurement site and low values in the north of the shipping lane. The opposite situation with southerly wind, unfavorable for the on-site in situ instrumentation, demonstrates the ability to detect enhanced NO2 concentrations several kilometers away from the instrument. Using a Gaussian plume model, in-plume NO2 volume mixing ratios can be derived from the MAX-DOAS measurements. For validation, a comparison to airborne imaging DOAS measurements during the NOSE campaign in July 2013 is performed, showing good agreement between the approximate plume position derived from the onion-peeling MAX-DOAS and the airborne measurements as well as between the derived in-plume NO2 volume mixing ratios (VMRs).

Published
2019

37. Studies of the horizontal inhomogeneities in NO2 concentrations above a shipping lane using ground-based MAX-DOAS and airborne imaging DOAS measurements

Author

Seyler, André, Meier, Andreas C., Wittrock, Folkard, Kattner, Lisa, Mathieu-Üffing, Barbara, Peters, Enno, Richter, Andreas, Ruhtz, Thomas, Schönhardt, Anja, Schmolke, Stefan, and Burrows, John P.

Abstract

This study describes a novel application of an onion peeling like approach to MAX-DOAS measurements of shipping emissions aiming at investigating the strong horizontal inhomogeneities in NO2 over a shipping lane. To monitor ship emissions on the main shipping route towards the port of Hamburg, a two-channel (UV and visible) MAX-DOAS instrument was deployed on the island Neuwerk in the German Bight, 6–7 km south of the main shipping lane. Utilizing the fact that the effective light path length in the atmosphere depends systematically on wavelength, simultaneous measurements and DOAS retrievals in the UV and visible spectral range are used to probe air masses at different horizontal distances to the instrument to estimate two-dimensional pollutant distributions. Two case-studies have been selected to demonstrate the ability to derive the approximate plume positions in the observed area. A situation with northerly wind shows high NO2 concentrations close to the measurement site and low values in the north of the shipping lane. The opposite situation with southerly wind, unfavorable for the on-site in situ instrumentation, demonstrates the ability to detect enhanced NO2 concentrations several kilometers away from the instrument. To validate the approach, a comparison to air-borne imaging DOAS measurements during the NOSE campaign in July 2013 is performed, showing good agreement between the approximate plume position derived from the onion peeling MAX-DOAS and the air-borne measurements. Combining synergistically information about the plume width from the air-borne measurements and about the vertical plume extent from MAX-DOAS, yields NO2 concentrations in the plume from both measurements which agree very well.

Published
2018

38. Ground-based validation of the MetopA and B GOME-2 OClO measurements.

Author

Pinardi, Gaia, Van Roozendael, Michel, Hendrick, François, Richter, Andreas, Valks, Pieter, Alwarda, Ramina, Bognar, Kristof, Frieß, Udo, Granville, José, Myojeong Gu, Johnston, Paul, Prados-Roman, Cristina, Querel, Richard, Strong, Kimberly, Wagner, Thomas, Wittrock, Folkard, and Gonzalez, Margarita Yela

Subjects
ATMOSPHERIC chemistry, REGRESSION analysis, LINEAR statistical models, SEASONS, STATISTICAL correlation
Abstract

This paper reports on ground-based validation of the atmospheric OClO data record produced in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC SAF) using the GOME2-A and -B instruments over the 2007-2016 and 2013-2016 periods, respectively. OClO slant column densities are compared to correlative measurements collected from 9 NDACC Zenith-Scattered-Light DOAS (ZSL-DOAS) instruments distributed in both the Arctic and Antarctic. Sensitivity tests are performed on the ground-based data to estimate the impact of the different OClO DOAS analysis settings. On this basis, we infer systematic uncertainties of about 25 % between the different ground-based data analysis, reaching total uncertainties ranging from about 26 % to 33 % for the different stations. Time-series at the different sites show good agreement between satellite and ground-based data, both for the inter-annual variability and the overall OClO seasonal behavior. GOME-2A results are found to be nosier than those of GOME-2B, especially after 2011, probably due to instrumental degradation effects. Daily linear regression analysis for OClO activated periods yield correlation coefficients of 0.8 for GOME-2A and 0.87 for GOME-2B, with slopes of 0.64 and 0.72, respectively. Biases are within 8 x 1013 molec/cm2 with some differences between GOME-2A and GOME- 2B, depending on the station. Overall, considering all the stations, a median bias of about -2.2 x 1013 molec/cm2 is found for both GOME-2 instruments. [ABSTRACT FROM AUTHOR]

Published
2021
Full Text
View/download PDF

39. Studies of the horizontal inhomogeneities in NO<sub>2</sub> concentrations above a shipping lane using ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements and validation with airborne imaging DOAS measurements

Author

Seyler, André, primary, Meier, Andreas C., additional, Wittrock, Folkard, additional, Kattner, Lisa, additional, Mathieu-Üffing, Barbara, additional, Peters, Enno, additional, Richter, Andreas, additional, Ruhtz, Thomas, additional, Schönhardt, Anja, additional, Schmolke, Stefan, additional, and Burrows, John P., additional

Published
2019
Full Text
View/download PDF

41. Full-azimuthal imaging-DOAS observations of NO2 and O4 during CINDI-2

Author

Peters, Enno, primary, Ostendorf, Mareike, additional, Bösch, Tim, additional, Seyler, André, additional, Schönhardt, Anja, additional, Schreier, Stefan F., additional, Henzing, Jeroen Sebastiaan, additional, Wittrock, Folkard, additional, Richter, Andreas, additional, Vrekoussis, Mihalis, additional, and Burrows, John P., additional

Published
2019
Full Text
View/download PDF

42. Intercomparison of NO2, O4, O3 and HCHO slant column measurements by MAX-DOAS and zenith-sky UV-Visible spectrometers during the CINDI-2 campaign

Author

Kreher, Karin, primary, Van Roozendael, Michel, additional, Hendrick, Francois, additional, Apituley, Arnoud, additional, Dimitropoulou, Ermioni, additional, Frieß, Udo, additional, Richter, Andreas, additional, Wagner, Thomas, additional, Abuhassan, Nader, additional, Ang, Li, additional, Anguas, Monica, additional, Bais, Alkis, additional, Benavent, Nuria, additional, Bösch, Tim, additional, Bognar, Kristof, additional, Borovski, Alexander, additional, Bruchkouski, Ilya, additional, Cede, Alexander, additional, Chan, Ka L., additional, Donner, Sebastian, additional, Drosoglou, Theano, additional, Fayt, Caroline, additional, Finkenzeller, Henning, additional, Garcia-Nieto, David, additional, Gielen, Clio, additional, Gómez-Martín, Laura, additional, Hao, Nan, additional, Herman, Jay R., additional, Hermans, Christian, additional, Hoque, Syedul, additional, Irie, Hitoshi, additional, Jin, Junli, additional, Johnston, Paul, additional, Khayyam Butt, Junaid, additional, Khokhar, Fahim, additional, Koenig, Theodore K., additional, Kuhn, Jonas, additional, Kumar, Vinod, additional, Lampel, Johannes, additional, Liu, Cheng, additional, Ma, Jianzhong, additional, Merlaud, Alexis, additional, Mishra, Abhishek K., additional, Müller, Moritz, additional, Navarro-Comas, Monica, additional, Ostendorf, Mareike, additional, Pazmino, Andrea, additional, Peters, Enno, additional, Pinardi, Gaia, additional, Pinharanda, Manuel, additional, Piters, Ankie, additional, Platt, Ulrich, additional, Postylyakov, Oleg, additional, Prados-Roman, Cristina, additional, Puentedura, Olga, additional, Querel, Richard, additional, Saiz-Lopez, Alfonso, additional, Schönhardt, Anja, additional, Schreier, Stefan F., additional, Seyler, Andre, additional, Sinha, Vinayak, additional, Spinei, Elena, additional, Strong, Kimberly, additional, Tack, Frederik, additional, Tian, Xin, additional, Tiefengraber, Martin, additional, Tirpitz, Jan-Lukas, additional, van Gent, Jeron, additional, Volkamer, Rainer, additional, Vrekoussis, Mihalis, additional, Wang, Shanshan, additional, Wang, Zhuoru, additional, Wenig, Mark, additional, Wittrock, Folkard, additional, Xie, Pinhua H., additional, Xu, Jin, additional, Yela, Margarita, additional, Zhang, Chengxin, additional, and Zhao, Xiaoyi, additional

Published
2019
Full Text
View/download PDF

43. Supplementary material to "Intercomparison of NO2, O4, O3 and HCHO slant column measurements by MAX-DOAS and zenith-sky UV-Visible spectrometers during the CINDI-2 campaign"

Author

Kreher, Karin, primary, Van Roozendael, Michel, additional, Hendrick, Francois, additional, Apituley, Arnoud, additional, Dimitropoulou, Ermioni, additional, Frieß, Udo, additional, Richter, Andreas, additional, Wagner, Thomas, additional, Abuhassan, Nader, additional, Ang, Li, additional, Anguas, Monica, additional, Bais, Alkis, additional, Benavent, Nuria, additional, Bösch, Tim, additional, Bognar, Kristof, additional, Borovski, Alexander, additional, Bruchkouski, Ilya, additional, Cede, Alexander, additional, Chan, Ka L., additional, Donner, Sebastian, additional, Drosoglou, Theano, additional, Fayt, Caroline, additional, Finkenzeller, Henning, additional, Garcia-Nieto, David, additional, Gielen, Clio, additional, Gómez-Martín, Laura, additional, Hao, Nan, additional, Herman, Jay R., additional, Hermans, Christian, additional, Hoque, Syedul, additional, Irie, Hitoshi, additional, Jin, Junli, additional, Johnston, Paul, additional, Khayyam Butt, Junaid, additional, Khokhar, Fahim, additional, Koenig, Theodore K., additional, Kuhn, Jonas, additional, Kumar, Vinod, additional, Lampel, Johannes, additional, Liu, Cheng, additional, Ma, Jianzhong, additional, Merlaud, Alexis, additional, Mishra, Abhishek K., additional, Müller, Moritz, additional, Navarro-Comas, Monica, additional, Ostendorf, Mareike, additional, Pazmino, Andrea, additional, Peters, Enno, additional, Pinardi, Gaia, additional, Pinharanda, Manuel, additional, Piters, Ankie, additional, Platt, Ulrich, additional, Postylyakov, Oleg, additional, Prados-Roman, Cristina, additional, Puentedura, Olga, additional, Querel, Richard, additional, Saiz-Lopez, Alfonso, additional, Schönhardt, Anja, additional, Schreier, Stefan F., additional, Seyler, Andre, additional, Sinha, Vinayak, additional, Spinei, Elena, additional, Strong, Kimberly, additional, Tack, Frederik, additional, Tian, Xin, additional, Tiefengraber, Martin, additional, Tirpitz, Jan-Lukas, additional, van Gent, Jeron, additional, Volkamer, Rainer, additional, Vrekoussis, Mihalis, additional, Wang, Shanshan, additional, Wang, Zhuoru, additional, Wenig, Mark, additional, Wittrock, Folkard, additional, Xie, Pinhua H., additional, Xu, Jin, additional, Yela, Margarita, additional, Zhang, Chengxin, additional, and Zhao, Xiaoyi, additional

Published
2019
Full Text
View/download PDF

44. BOREAS – a new MAX-DOAS profile retrieval algorithm for aerosols and trace gases

Author

Bösch, Tim, primary, Rozanov, Vladimir, additional, Richter, Andreas, additional, Peters, Enno, additional, Rozanov, Alexei, additional, Wittrock, Folkard, additional, Merlaud, Alexis, additional, Lampel, Johannes, additional, Schmitt, Stefan, additional, de Haij, Marijn, additional, Berkhout, Stijn, additional, Henzing, Bas, additional, Apituley, Arnoud, additional, den Hoed, Mirjam, additional, Vonk, Jan, additional, Tiefengraber, Martin, additional, Müller, Moritz, additional, and Burrows, John Philip, additional

Published
2018
Full Text
View/download PDF

45. Studies of the horizontal inhomogeneities in NO2 concentrations above a shipping lane using ground-based MAX-DOAS and airborne imaging DOAS measurements

Author

Seyler, André, primary, Meier, Andreas C., additional, Wittrock, Folkard, additional, Kattner, Lisa, additional, Mathieu-Üffing, Barbara, additional, Peters, Enno, additional, Richter, Andreas, additional, Ruhtz, Thomas, additional, Schönhardt, Anja, additional, Schmolke, Stefan, additional, and Burrows, John P., additional

Published
2018
Full Text
View/download PDF

46. Satellite nadir NO2 validation based on zenith-sky, direct-sun and MAXDOAS network observations

Author

Pinardi, Gaia, Van Roozendael, Michel, Lambert, Jean-Christopher, Granville, José, Hendrick, François, Gielen, Clio, Cede, Alexander, Kanaya, Ygo, Irie, Hitoshi, Wittrock, Folkard, Richter, Andreas, Peters, Enno, Wagner, Thomas, Gu, Myojeong, Remmers, Julia, Lampel, Johannes, Friess, Udo, Vlemmix, Tim, Piters, Ankie, Hao, Nan, Tiefengraber, Martin, Herman, Jay, Abuhassan, Nader, Holla, Robert, Bais, Alkis, Balis, Dimitris, Drosoglou, Theano, Kouremeti, Natalia, Hovila, Jari, Chong, J., Postylyakov, Oleg, Ma, Jianzhong, Goutail, Florence, Pommereau, Jean-Pierre, Pazmino, Andrea, Navarro, Monica, Puentedura, Olga, Yu, Huan, Belgian Institute for Space Aeronomy / Institut d'Aéronomie Spatiale de Belgique (BIRA-IASB), NASA Goddard Space Flight Center (GSFC), Research Institute for Global Change (RIGC), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Center for Environmental Remote Sensing [Chiba] (CEReS), Chiba University, Institute of Environmental Physics [Bremen] (IUP), University of Bremen, Max Planck Institute for Chemistry (MPIC), Max-Planck-Gesellschaft, Institut für Umweltphysik [Heidelberg], Universität Heidelberg [Heidelberg], Department of Geoscience and Remote Sensing [Delft], Delft University of Technology (TU Delft), Royal Netherlands Meteorological Institute (KNMI), DLR Institut für Methodik der Fernerkundung / DLR Remote Sensing Technology Institute (IMF), Deutsches Zentrum für Luft- und Raumfahrt [Oberpfaffenhofen-Wessling] (DLR), Institute of Meteorology and Geophysics [Innsbruck], University of Innsbruck, Joint Center for Earth Systems Technology [Baltimore] (JCET), NASA Goddard Space Flight Center (GSFC)-University of Maryland [Baltimore County] (UMBC), University of Maryland System-University of Maryland System, Meteorologisches Observatorium Hohenpeißenberg (MOHp), Deutscher Wetterdienst [Offenbach] (DWD), Laboratory of Atmospheric Physics [Thessaloniki], Aristotle University of Thessaloniki, Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC), Finnish Meteorological Institute (FMI), Gwangju Institute of Science and Technology (GIST), A.M.Obukhov Institute of Atmospheric Physics (IAP), Russian Academy of Sciences [Moscow] (RAS), Chinese Academy of Meteorological Sciences (CAMS), STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Instituto Nacional de Técnica Aeroespacial (INTA), Cardon, Catherine, Universität Heidelberg [Heidelberg] = Heidelberg University, and Leopold Franzens Universität Innsbruck - University of Innsbruck

Subjects
[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [SDU.OCEAN] Sciences of the Universe [physics]/Ocean, Atmosphere, [PHYS.PHYS.PHYS-AO-PH] Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph]
Abstract

International audience; Since more than fifteen years, total and tropospheric NO2 columns have been retrieved from nadir space-borne sensors such as SCIAMACHY on ENVISAT, OMI on AURA and GOME-2 on MetOp platforms. The NO2 data products are generally retrieved in three main steps: (1) a DOAS spectral analysis yielding the total column amount of NO2 along the slant optical path, (2) an estimation of the stratospheric NO2 column, to be subtracted from the total column to derive the tropospheric contribution, and (3) a conversion of the total and tropospheric slant columns into vertical columns based on airmass factor calculations which require a-priori knowledge of the NO2 vertical distribution and surface albedo, as well as information on cloud cover and height.In this study we combine correlative measurements available from several ground-based remote sensing networks to address the validation of (1) the GOME-2 GDP 4.8 NO2 products generated within the EUMETSAT O3M-SAF project, and (2) the SCIAMACHY, OMI and GOME-2 TEMIS product. Zenith-sky DOAS/SAOZ measurements from the NDACC network are used to assess the stratospheric NO2 columns retrieved from the satellite, while the consistency of the total and tropospheric NO2 columns in urban, sub-urban and back-ground conditions is investigated using direct-sun Pandora and multi-axis MAXDOAS data sets from about 40 stations. Where available, vertical profile information from MAXDOAS measurements is used to assess the reliability of the different satellite a-priori profile shapes.Results are discussed in terms of observed biases between satellite and ground-based data sets, their dependence on location, season and cloud conditions. For stratospheric columns, the uncertainty related to the correction applied for ensuring the photochemical matching between satellite and ground-based observations is also evaluated. The satellite pixels resolution effect is statistically explored in relation to the typical extent of the emission sources at urban site locations, using data from SCIAMACHY 60x30 km², GOME-2 40x80 km² and OMI 13x24 km².

Published
2016

48. Investigating differences in DOAS retrieval codes using MAD-CAT campaign data

Author

Peters, Enno, primary, Pinardi, Gaia, additional, Seyler, André, additional, Richter, Andreas, additional, Wittrock, Folkard, additional, Bösch, Tim, additional, Van Roozendael, Michel, additional, Hendrick, François, additional, Drosoglou, Theano, additional, Bais, Alkiviadis F., additional, Kanaya, Yugo, additional, Zhao, Xiaoyi, additional, Strong, Kimberly, additional, Lampel, Johannes, additional, Volkamer, Rainer, additional, Koenig, Theodore, additional, Ortega, Ivan, additional, Puentedura, Olga, additional, Navarro-Comas, Mónica, additional, Gómez, Laura, additional, Yela González, Margarita, additional, Piters, Ankie, additional, Remmers, Julia, additional, Wang, Yang, additional, Wagner, Thomas, additional, Wang, Shanshan, additional, Saiz-Lopez, Alfonso, additional, García-Nieto, David, additional, Cuevas, Carlos A., additional, Benavent, Nuria, additional, Querel, Richard, additional, Johnston, Paul, additional, Postylyakov, Oleg, additional, Borovski, Alexander, additional, Elokhov, Alexander, additional, Bruchkouski, Ilya, additional, Liu, Haoran, additional, Liu, Cheng, additional, Hong, Qianqian, additional, Rivera, Claudia, additional, Grutter, Michel, additional, Stremme, Wolfgang, additional, Khokhar, M. Fahim, additional, Khayyam, Junaid, additional, and Burrows, John P., additional

Published
2017
Full Text
View/download PDF

49. Enhanced trans-Himalaya pollution transport to the Tibetan Plateau by cut-off low systems

Author

Zhang, Ruixiong, primary, Wang, Yuhang, additional, He, Qiusheng, additional, Chen, Laiguo, additional, Zhang, Yuzhong, additional, Qu, Hang, additional, Smeltzer, Charles, additional, Li, Jianfeng, additional, Alvarado, Leonardo M. A., additional, Vrekoussis, Mihalis, additional, Richter, Andreas, additional, Wittrock, Folkard, additional, and Burrows, John P., additional

Published
2017
Full Text
View/download PDF

50. Assessment of the stratospheric NO2 column using long-term ground-based UV-visible and satellite nadir observations

Author

Pinardi, Gaia, Van Roozendael, Michel, Lambert, Jean-Christopher, Hendrick, Francois, Granville, José, Tack, Frederik, Goutail, Florence, Pommereau, Jean-Pierre, Pazmino, Andrea, Wittrock, Folkard, Richter, Andreas, Wagner, Thomas, Gu, Myojeong, Friess, Udo, Navarro, Monica, Puentedura, Olga, Belgian Institute for Space Aeronomy / Institut d'Aéronomie Spatiale de Belgique (BIRA-IASB), STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Institute of Environmental Physics [Bremen] (IUP), University of Bremen, Max Planck Institute for Chemistry (MPIC), Max-Planck-Gesellschaft, Institut für Umweltphysik [Heidelberg], Universität Heidelberg [Heidelberg] = Heidelberg University, Instituto Nacional de Técnica Aeroespacial (INTA), Cardon, Catherine, and Universität Heidelberg [Heidelberg]

Subjects
[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], [PHYS.PHYS.PHYS-AO-PH] Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph]
Abstract

International audience; Zenith-sky UV-visible instruments have been used to monitor stratospheric NO2 columns from pole to pole for more than 2 decades, as part of the Network for the Detection of Atmospheric Composition Change (NDACC). Long-term monitoring and fit-for-purpose data quality are essential commitments of the network. Recently, recommendations were made for a better harmonization of the retrieval of NO2 stratospheric vertical columns (Van Roozendael and Hendrick 2012, http://ndacc-uvvis-wg.aeronomie.be/tools/NDACC_UVVIS-WG_NO2 settings_v4.pdf). Those include, in addition to the use of harmonized SCD settings, a common approach to the air-mass factor (AMF) calculation, based on pre-calculated look-up tables of climatological AMFs resolved in latitude, time, wavelength, surface albedo, solar zenith angle and station altitude.

Published
2015

Catalog

Books, media, physical & digital resources
See catalog results