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  1. AU="Buchwitz, Michael"
  2. AU="Sadrozinski, H-F W."
  3. AU="Allan, Rachel"
  4. AU="Ma, Jiele"
  5. AU="Bizjak, Isabella"
  6. AU="Pelucchi, Paride"
  7. AU="Krug, Anne Barbara"
  8. AU="Pikridas, M"
  9. AU="Adams, Jonathan D"
  10. AU="Esquivel-Muelbert, A."
  11. AU="Khan, Meraj Alam"
  12. AU="Bullard, Stevan"
  13. AU="Wang, Peter H"
  14. AU="Preto, Jordane"
  15. AU="Pierce, Shaketha"
  16. AU="Sankar, Jishnu"
  17. AU="Yahagi, Naohisa"
  18. AU=Pinho Juliana
  19. AU="Brennan, Anna"
  20. AU="Lee, Theresa M"
  21. AU="Chunqing Ou"
  22. AU="Gwynn, Simon"
  23. AU="Holper, Sarah"
  24. AU="Haider, Farag Ibrahim"
  25. AU="Rice, Jordin L"
  26. AU="Gong, Xingguo"
  27. AU=Rother Magdalena B.
  28. AU="Petrov, Ksenia"
  29. AU="Rijneveld, R"
  30. AU=Lopez-Martinez Briceida
  31. AU=Astone Pia
  32. AU="Amaral, V"

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  1. Buch ; Online: Zonal variability of methane trends derived from satellite data

    Hachmeister, Jonas / Schneising, Oliver / Buchwitz, Michael / Burrows, John P. / Notholt, Justus / Buschmann, Matthias

    eISSN: 1680-7324

    2024  

    Abstract: The Tropospheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor (S5P) satellite is part of the latest generation of trace gas monitoring satellites and provides a new level of spatio-temporal information with daily global coverage, ... ...

    Abstract The Tropospheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor (S5P) satellite is part of the latest generation of trace gas monitoring satellites and provides a new level of spatio-temporal information with daily global coverage, which enables the calculation of daily globally averaged CH 4 concentrations. To investigate changes in atmospheric methane, the background CH 4 level (i.e. the CH 4 concentration without seasonal and short-term variations) has to be determined. CH 4 growth rates vary in a complex manner and high-latitude zonal averages may have gaps in the time series, and thus simple fitting methods do not produce reliable results. In this paper we present an approach based on fitting an ensemble of dynamic linear models (DLMs) to TROPOMI data, from which the best model is chosen with the help of cross-validation to prevent overfitting. This method is computationally fast and is not dependent on additional inputs, allowing for fast and continuous analysis of the most recent time series data. We present results of global annual methane increases (AMIs) for the first 4.5 years of S5P/TROPOMI data, which show good agreement with AMIs from other sources. Additionally, we investigated what information can be derived from zonal bands. Due to the fast meridional mixing within hemispheres, we use zonal growth rates instead of AMIs, since they provide a higher temporal resolution. Clear differences can be observed between Northern Hemisphere and Southern Hemisphere growth rates, especially during 2019 and 2022. The growth rates show similar patterns within the hemispheres and show no short-term variations during the years, indicating that air masses within a hemisphere are well-mixed during a year. Additionally, the growth rates derived from S5P/TROPOMI data are largely consistent with growth rates derived from Copernicus Atmospheric Monitoring Service (CAMS) global-inversion-optimized (CAMS/INV) data, which use surface observations. In 2019 a reduction in growth rates can be observed for ...
    Thema/Rubrik (Code) 551
    Sprache Englisch
    Erscheinungsdatum 2024-01-15
    Erscheinungsland de
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  2. Buch ; Online: Zonal variability of methane trends derived from satellite data

    Hachmeister, Jonas / Schneising, Oliver / Buchwitz, Michael / Burrows, John P. / Notholt, Justus / Buschmann, Matthias

    eISSN:

    2024  

    Abstract: The Tropospheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor (S5P) satellite is part of the latest generation of trace gas monitoring satellites and provides a new level of spatio-temporal information with daily global coverage, ... ...

    Abstract The Tropospheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor (S5P) satellite is part of the latest generation of trace gas monitoring satellites and provides a new level of spatio-temporal information with daily global coverage, which enables the calculation of daily globally averaged CH 4 concentrations. To investigate changes in atmospheric methane, the background CH 4 level (i.e. the CH 4 concentration without seasonal and short-term variations) has to be determined. CH 4 growth rates vary in a complex manner and high-latitude zonal averages may have gaps in the time series, and thus simple fitting methods do not produce reliable results. In this paper we present an approach based on fitting an ensemble of dynamic linear models (DLMs) to TROPOMI data, from which the best model is chosen with the help of cross-validation to prevent overfitting. This method is computationally fast and is not dependent on additional inputs, allowing for fast and continuous analysis of the most recent time series data. We present results of global annual methane increases (AMIs) for the first 4.5 years of S5P/TROPOMI data, which show good agreement with AMIs from other sources. Additionally, we investigated what information can be derived from zonal bands. Due to the fast meridional mixing within hemispheres, we use zonal growth rates instead of AMIs, since they provide a higher temporal resolution. Clear differences can be observed between Northern Hemisphere and Southern Hemisphere growth rates, especially during 2019 and 2022. The growth rates show similar patterns within the hemispheres and show no short-term variations during the years, indicating that air masses within a hemisphere are well-mixed during a year. Additionally, the growth rates derived from S5P/TROPOMI data are largely consistent with growth rates derived from Copernicus Atmospheric Monitoring Service (CAMS) global-inversion-optimized (CAMS/INV) data, which use surface observations. In 2019 a reduction in growth rates can be observed for ...
    Thema/Rubrik (Code) 551
    Sprache Englisch
    Erscheinungsdatum 2024-01-15
    Erscheinungsland de
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  3. Artikel: On the morphological variability of

    Buchwitz, Michael / Voigt, Sebastian

    PeerJ

    2018  Band 6, Seite(n) e4346

    Abstract: ... ...

    Abstract Ichniotherium
    Sprache Englisch
    Erscheinungsdatum 2018-01-31
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ZDB-ID 2703241-3
    ISSN 2167-8359
    ISSN 2167-8359
    DOI 10.7717/peerj.4346
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  4. Buch ; Online: Advances in retrieving XCH4 and XCO from Sentinel-5 Precursor

    Schneising, Oliver / Buchwitz, Michael / Hachmeister, Jonas / Vanselow, Steffen / Reuter, Maximilian / Buschmann, Matthias / Bovensmann, Heinrich / Burrows, John P.

    eISSN: 1867-8548

    improvements in the scientific TROPOMI/WFMD algorithm

    2023  

    Abstract: The TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor satellite enables the accurate determination of atmospheric methane ( CH 4 ) and carbon monoxide ( CO ) abundances at high spatial resolution and global daily sampling. ... ...

    Abstract The TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor satellite enables the accurate determination of atmospheric methane ( CH 4 ) and carbon monoxide ( CO ) abundances at high spatial resolution and global daily sampling. Due to its wide swath and sampling, the global distribution of both gases can be determined in unprecedented detail. The scientific retrieval algorithm Weighting Function Modified Differential Optical Absorption Spectroscopy (WFMD) has proven valuable in simultaneously retrieving the atmospheric column-averaged dry-air mole fractions XCH 4 and XCO from TROPOMI's radiance measurements in the shortwave infrared (SWIR) spectral range. Here we present recent improvements of the algorithm which have been incorporated into the current version (v1.8) of the TROPOMI/WFMD product. This includes processing adjustments such as increasing the polynomial degree to 3 in the fitting procedure to better account for possible spectral albedo variations within the fitting window and updating the digital elevation model to minimise topography-related biases. In the post-processing, the machine-learning-based quality filter has been refined using additional data when training the random forest classifier to further reduce scenes with residual cloudiness that are incorrectly classified as good. In particular, the cloud filtering over the Arctic ocean is considerably improved. Furthermore, the machine learning calibration, addressing systematic errors due to simplifications in the forward model or instrumental issues, has been optimised. By including an additional feature associated with the fitted polynomial when training the corresponding random forest regressor, spectral albedo variations are better accounted for. To remove vertical stripes in the XCH 4 and XCO data, an efficient orbit-wise destriping filter based on combined wavelet–Fourier filtering has been implemented, while optimally preserving the original spatial trace gas features. The temporal coverage of the data records has ...
    Thema/Rubrik (Code) 551
    Sprache Englisch
    Erscheinungsdatum 2023-02-03
    Erscheinungsland de
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  5. Buch ; Online: Using TROPOspheric Monitoring Instrument (TROPOMI) measurements and Weather Research and Forecasting (WRF) CO modelling to understand the contribution of meteorology and emissions to an extreme air pollution event in India

    Vellalassery, Ashique / Pillai, Dhanyalekshmi / Marshall, Julia / Gerbig, Christoph / Buchwitz, Michael / Schneising, Oliver / Ravi, Aparnna

    eISSN: 1680-7324

    2021  

    Abstract: Several ambient air quality records corroborate the severe and persistent degradation of air quality over northern India during the winter months, with evidence of a continued, increasing trend of pollution across the Indo-Gangetic Plain (IGP) over the ... ...

    Abstract Several ambient air quality records corroborate the severe and persistent degradation of air quality over northern India during the winter months, with evidence of a continued, increasing trend of pollution across the Indo-Gangetic Plain (IGP) over the past decade. A combination of atmospheric dynamics and uncertain emissions, including the post-monsoon agricultural stubble burning, make it challenging to resolve the role of each individual factor. Here we demonstrate the potential use of an atmospheric transport model, the Weather Research and Forecasting model coupled with chemistry (WRF–Chem) to identify and quantify the role of transport mechanisms and emissions on the occurrence of the pollution events. The investigation is based on the use of carbon monoxide (CO) observations from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor satellite and the surface measurement network, as well as the WRF–Chem simulations, to investigate the factors contributing to CO enhancement over India during November 2018. We show that the simulated column-averaged dry air mole fraction (XCO) is largely consistent with TROPOMI observations, with a spatial correlation coefficient of 0.87. The surface-level CO concentrations show larger sensitivities to boundary layer dynamics, wind speed, and diverging source regions, leading to a complex concentration pattern and reducing the observation-model agreement with a correlation coefficient ranging from 0.41 to 0.60 for measurement locations across the IGP. We find that daily satellite observations can provide a first-order inference of the CO transport pathways during the enhanced burning period, and this transport pattern is reproduced well in the model. By using the observations and employing the model at a comparable resolution, we confirm the significant role of atmospheric dynamics and residential, industrial, and commercial emissions in the production of the exorbitant level of air pollutants in northern India. We find that biomass burning plays only a minimal role in both column and surface enhancements of CO, except for the state of Punjab during the high pollution episodes. While the model reproduces observations reasonably well, a better understanding of the factors controlling the model uncertainties is essential for relating the observed concentrations to the underlying emissions. Overall, our study emphasizes the importance of undertaking rigorous policy measures, mainly focusing on reducing residential, commercial, and industrial emissions in addition to actions already underway in the agricultural sectors.
    Thema/Rubrik (Code) 551
    Sprache Englisch
    Erscheinungsdatum 2021-04-08
    Erscheinungsland de
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  6. Buch ; Online: Data and scripts for manuscript "Efficacy of high-resolution satellite observations in inverse modeling of carbon monoxide emissions"

    Nüß, Johann Rasmus / Daskalakis, Nikos / Piwowarczyk, Fabian Günther / Gkouvousis, Angelos / Schneising, Oliver / Buchwitz, Michael / Kanakidou, Maria / Krol, Maarten C. / Vrekoussis, Mihalis

    2022  

    Abstract: Collection of analysis and plotting scripts and model in- and output needed to reproduce the simulations, figures and analysis for the manuscript "Efficacy of high-resolution satellite observations in inverse modeling of carbon monoxide emissions" ... ...

    Abstract Collection of analysis and plotting scripts and model in- and output needed to reproduce the simulations, figures and analysis for the manuscript "Efficacy of high-resolution satellite observations in inverse modeling of carbon monoxide emissions" authored by Nüß et al. See the included README for more information on what each file includes.
    Schlagwörter Life Science
    Verlag University of Bremen
    Erscheinungsland nl
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

    Volltext online

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  7. Buch ; Online: Severe Californian wildfires in November 2018 observed from space

    Schneising, Oliver / Buchwitz, Michael / Reuter, Maximilian / Bovensmann, Heinrich / Burrows, John P.

    eISSN: 1680-7324

    the carbon monoxide perspective

    2020  

    Abstract: Due to proceeding climate change, some regions such as California face rising weather extremes with dry periods becoming warmer and drier, entailing the risk that wildfires and associated air pollution episodes will continue to increase. November 2018 ... ...

    Abstract Due to proceeding climate change, some regions such as California face rising weather extremes with dry periods becoming warmer and drier, entailing the risk that wildfires and associated air pollution episodes will continue to increase. November 2018 turned into one of the most severe wildfire episodes on record in California, with two particularly destructive wildfires spreading concurrently through the north and the south of the state. Both fires ignited at the wildland–urban interface, causing many civilian fatalities and forcing the total evacuation of several cities and communities. Here we demonstrate that the inherent carbon monoxide ( CO ) emissions of the wildfires and subsequent transport can be observed from space by analysing radiance measurements of the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite in the shortwave infrared spectral range. From the determined CO distribution we assess the corresponding air quality burden in major Californian cities caused by the fires and discuss the associated uncertainties. As a result of the prevailing wind conditions, the largest CO load during the first days of the fires is found in Sacramento and San Francisco, with city area averages reaching boundary layer concentration anomalies of about 2.5 mg CO m −3 . Even the most polluted city scenes likely comply with the national ambient air quality standards ( 10 mg CO m −3 with 8 h averaging time). This finding based on dense daily recurrent satellite monitoring is consistent with isolated ground-based air quality measurements.
    Thema/Rubrik (Code) 333
    Sprache Englisch
    Erscheinungsdatum 2020-03-20
    Erscheinungsland de
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  8. Buch ; Online: Using satellite measurements and mesoscale modelling to understand the contribution to an extreme air pollution event in India

    Vellalassery, Ashique / Pillai, Dhanyalekshmi / Marshall, Julia / Gerbig, Christoph / Buchwitz, Michael / Schneising, Oliver

    eISSN: 1680-7324

    2020  

    Abstract: Several ambient air quality records corroborate severe and persistent degradation of air quality over North India during the winter months with evidence of a continued increasing trend of pollution across the Indo-Gangetic Plain (IGP) over the past ... ...

    Abstract Several ambient air quality records corroborate severe and persistent degradation of air quality over North India during the winter months with evidence of a continued increasing trend of pollution across the Indo-Gangetic Plain (IGP) over the past decade. A combination of atmospheric dynamics and uncertain emissions, including the post-monsoon agricultural stubble burning, make it challenging to resolve the role of each individual factor. Here we demonstrate the potential use of an atmospheric transport model, the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) to identify and quantify the role of transport mechanisms and emissions on the occurrence of the pollution events. The investigation is based on the use of CO observations from TROPOspheric Monitoring Instrument (TROPOMI), onboard the Sentinel 5-Precursor satellite, and the surface measurement network as well as WRF-Chem simulations to investigate the factors contributing to CO enhancement over India during November 2018. We show that the simulated column-averaged dry air mole fraction (XCO) is largely consistent with TROPOMI observations with a spatial correlation coefficient of 0.87. The surface-level CO concentrations show larger sensitivities to boundary layer dynamics, wind speed, and diverging source regions, leading to a complex concentration pattern and reducing the observation-model agreement with a correlation coefficient ranging from 0.41 to 0.60 for measurement locations across the IGP. We find that daily satellite observations can provide a first-order inference of the CO transport pathways during the enhanced burning period, and this transport pattern is reproduced well in the model. By using the observations and employing the model at a comparable resolution, we confirm the significant role of atmospheric dynamics as well as residential, industrial and commercial emissions in the production of the exorbitant level of air pollutants in North India. We find that biomass burning plays only a minimal role in both column and surface enhancements of CO, except for in the state of Punjab during the high pollution episodes. While the model reproduces observations reasonably well, a better understanding of the factors controlling the model uncertainties is essential to relate the observed concentrations to the underlying emissions. Overall, our study emphasizes the importance of undertaking rigorous policy measures, mainly focusing on reducing residential, commercial and industrial emissions in addition to actions already underway in the agricultural sectors.
    Thema/Rubrik (Code) 551
    Sprache Englisch
    Erscheinungsdatum 2020-10-26
    Erscheinungsland de
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

    Volltext online

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  9. Buch ; Online: Spatially resolved evaluation of Earth system models with satellite column-averaged CO2

    Gier, Bettina K. / Buchwitz, Michael / Reuter, Maximilian / Cox, Peter M. / Friedlingstein, Pierre / Eyring, Veronika

    eISSN: 1726-4189

    2020  

    Abstract: Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) showed large uncertainties in simulating atmospheric CO 2 concentrations. We utilize the Earth System Model Evaluation Tool (ESMValTool) to evaluate ... ...

    Abstract Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) showed large uncertainties in simulating atmospheric CO 2 concentrations. We utilize the Earth System Model Evaluation Tool (ESMValTool) to evaluate emission-driven CMIP5 and CMIP6 simulations with satellite data of column-average CO 2 mole fractions (XCO 2 ). XCO 2 time series show a large spread among the model ensembles both in CMIP5 and CMIP6. Compared to the satellite observations, the models have a bias of + 25 to − 20 ppmv in CMIP5 and + 20 to − 15 ppmv in CMIP6, with the multi-model mean biases at + 10 and + 2 ppmv, respectively. The derived mean atmospheric XCO 2 growth rate (GR) of 2.0 ppmv yr −1 is overestimated by 0.4 ppmv yr −1 in CMIP5 and 0.3 ppmv yr −1 in CMIP6 for the multi-model mean, with a good reproduction of the interannual variability. All models capture the expected increase of the seasonal cycle amplitude (SCA) with increasing latitude, but most models underestimate the SCA. Any SCA derived from data with missing values can only be considered an “effective” SCA, as the missing values could occur at the peaks or troughs. The satellite data are a combined data product covering the period 2003–2014 based on the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY)/Envisat (2003–2012) and Thermal And Near infrared Sensor for carbon Observation Fourier transform spectrometer/Greenhouse Gases Observing Satellite (TANSO-FTS/GOSAT) (2009–2014) instruments. While the combined satellite product shows a strong negative trend of decreasing effective SCA with increasing XCO 2 in the northern midlatitudes, both CMIP ensembles instead show a non-significant positive trend in the multi-model mean. The negative trend is reproduced by the models when sampling them as the observations, attributing it to sampling characteristics. Applying a mask of the mean data coverage of each satellite to the models, the effective SCA is higher for the SCIAMACHY/Envisat mask than when using the TANSO-FTS/GOSAT mask. This induces an artificial negative trend when using observational sampling over the full period, as SCIAMACHY/Envisat covers the early period until 2012, with TANSO-FTS/GOSAT measurements starting in 2009. Overall, the CMIP6 ensemble shows better agreement with the satellite data than the CMIP5 ensemble in all considered quantities (XCO 2 , GR, SCA and trend in SCA). This study shows that the availability of column-integral CO 2 from satellite provides a promising new way to evaluate the performance of Earth system models on a global scale, complementing existing studies that are based on in situ measurements from single ground-based stations.
    Thema/Rubrik (Code) 333
    Sprache Englisch
    Erscheinungsdatum 2020-12-08
    Erscheinungsland de
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  10. Artikel: The potential of a constellation of low earth orbit satellite imagers to monitor worldwide fossil fuel CO2 emissions from large cities and point sources

    Lespinas, Franck / Wang, Yilong / Broquet, Grégoire / Bréon, François-Marie / Buchwitz, Michael / Reuter, Maximilian / Meijer, Yasjka / Loescher, Armin / Janssens-Maenhout, Greet / Zheng, Bo / Ciais, Philippe

    Carbon balance and management. 2020 Dec., v. 15, no. 1

    2020  

    Abstract: BACKGROUND: Satellite imagery will offer unparalleled global spatial coverage at high-resolution for long term cost-effective monitoring of CO₂ concentration plumes generated by emission hotspots. CO₂ emissions can then be estimated from the magnitude of ...

    Abstract BACKGROUND: Satellite imagery will offer unparalleled global spatial coverage at high-resolution for long term cost-effective monitoring of CO₂ concentration plumes generated by emission hotspots. CO₂ emissions can then be estimated from the magnitude of these plumes. In this paper, we assimilate pseudo-observations in a global atmospheric inversion system to assess the performance of a constellation of one to four sun-synchronous low-Earth orbit (LEO) imagers to monitor anthropogenic CO₂ emissions. The constellation of imagers follows the specifications from the European Spatial Agency (ESA) for the Copernicus Anthropogenic Carbon Dioxide Monitoring (CO2M) concept for a future operational mission dedicated to the monitoring of anthropogenic CO₂ emissions. This study assesses the uncertainties in the inversion estimates of emissions (“posterior uncertainties”). RESULTS: The posterior uncertainties of emissions for individual cities and power plants are estimated for the 3 h before satellite overpasses, and extrapolated at annual scale assuming temporal auto-correlations in the uncertainties in the emission products that are used as a prior knowledge on the emissions by the Bayesian framework of the inversion. The results indicate that (i) the number of satellites has a proportional impact on the number of 3 h time windows for which emissions are constrained to better than 20%, but it has a small impact on the posterior uncertainties in annual emissions; (ii) having one satellite with wide swath would provide full images of the XCO₂ plumes, and is more beneficial than having two satellites with half the width of reference swath; and (iii) an increase in the precision of XCO₂ retrievals from 0.7 ppm to 0.35 ppm has a marginal impact on the emission monitoring performance. CONCLUSIONS: For all constellation configurations, only the cities and power plants with an annual emission higher than 0.5 MtC per year can have at least one 8:30–11:30 time window during one year when the emissions can be constrained to better than 20%. The potential of satellite imagers to constrain annual emissions not only depend on the design of the imagers, but also strongly depend on the temporal error structure in the prior uncertainties, which is needed to be objectively assessed in the bottom-up emission maps.
    Schlagwörter Bayesian theory ; administrative management ; carbon ; carbon dioxide ; cost effectiveness ; fossil fuels ; remote sensing ; satellites
    Sprache Englisch
    Erscheinungsverlauf 2020-12
    Umfang p. 18.
    Erscheinungsort Springer International Publishing
    Dokumenttyp Artikel
    Anmerkung NAL-AP-2-clean
    ISSN 1750-0680
    DOI 10.1186/s13021-020-00153-4
    Datenquelle NAL Katalog (AGRICOLA)

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