Articles | Volume 20, issue 3
https://doi.org/10.5194/acp-20-1795-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-20-1795-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Feb 2020
Research article |
| 14 Feb 2020
| 14 Feb 2020
Uncertainty analysis of a European high-resolution emission inventory of CO2 and CO to support inverse modelling and network design
Department of Climate, Air and Sustainability, TNO, P.O. Box 80015,
3508 TA Utrecht, the Netherlands
Stijn N. C. Dellaert
Department of Climate, Air and Sustainability, TNO, P.O. Box 80015,
3508 TA Utrecht, the Netherlands
Antoon J. H. Visschedijk
Department of Climate, Air and Sustainability, TNO, P.O. Box 80015,
3508 TA Utrecht, the Netherlands
Hugo A. C. Denier van der Gon
Department of Climate, Air and Sustainability, TNO, P.O. Box 80015,
3508 TA Utrecht, the Netherlands
Viewed
Total article views: 3,599 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 25 Sep 2019)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,414 | 1,116 | 69 | 3,599 | 90 | 105 |
- HTML: 2,414
- PDF: 1,116
- XML: 69
- Total: 3,599
- BibTeX: 90
- EndNote: 105
Total article views: 2,925 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 14 Feb 2020)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,073 | 788 | 64 | 2,925 | 81 | 94 |
- HTML: 2,073
- PDF: 788
- XML: 64
- Total: 2,925
- BibTeX: 81
- EndNote: 94
Total article views: 674 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 25 Sep 2019)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 341 | 328 | 5 | 674 | 9 | 11 |
- HTML: 341
- PDF: 328
- XML: 5
- Total: 674
- BibTeX: 9
- EndNote: 11
Viewed (geographical distribution)
Total article views: 3,599 (including HTML, PDF, and XML)
Thereof 3,452 with geography defined
and 147 with unknown origin.
Total article views: 2,925 (including HTML, PDF, and XML)
Thereof 2,855 with geography defined
and 70 with unknown origin.
Total article views: 674 (including HTML, PDF, and XML)
Thereof 597 with geography defined
and 77 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
49 citations as recorded by crossref.
- Determination of the emission rates of CO<sub>2</sub> point sources with airborne lidar S. Wolff et al. 10.5194/amt-14-2717-2021
- Verifying national inventory-based combustion emissions of CO2 across the UK and mainland Europe using satellite observations of atmospheric CO and CO2 T. Scarpelli et al. 10.5194/acp-24-10773-2024
- CAMS-REG-v4: a state-of-the-art high-resolution European emission inventory for air quality modelling J. Kuenen et al. 10.5194/essd-14-491-2022
- Effects of point source emission heights in WRF–STILT: a step towards exploiting nocturnal observations in models F. Maier et al. 10.5194/gmd-15-5391-2022
- Accounting for meteorological biases in simulated plumes using smarter metrics P. Vanderbecken et al. 10.5194/amt-16-1745-2023
- Verifying Methane Inventories and Trends With Atmospheric Methane Data J. Worden et al. 10.1029/2023AV000871
- Quantification of fossil fuel CO2 from combined CO, δ13CO2 and Δ14CO2 observations J. Kim et al. 10.5194/acp-23-14425-2023
- Optimising urban measurement networks for CO2 flux estimation: a high-resolution observing system simulation experiment using GRAMM/GRAL S. Vardag & R. Maiwald 10.5194/gmd-17-1885-2024
- Urban-scale variational flux inversion for CO Using TROPOMI total-column retrievals: A case study of Tehran N. Shahrokhi et al. 10.1016/j.atmosenv.2023.120009
- Understanding greenhouse gas (GHG) column concentrations in Munich using the Weather Research and Forecasting (WRF) model X. Zhao et al. 10.5194/acp-23-14325-2023
- Improved definition of prior uncertainties in CO2 and CO fossil fuel fluxes and its impact on multi-species inversion with GEOS-Chem (v12.5) I. Super et al. 10.5194/gmd-17-7263-2024
- Gridded fossil CO2 emissions and related O2 combustion consistent with national inventories 1959–2018 M. Jones et al. 10.1038/s41597-020-00779-6
- Variational regional inverse modeling of reactive species emissions with PYVAR-CHIMERE-v2019 A. Fortems-Cheiney et al. 10.5194/gmd-14-2939-2021
- Uncertainties in the Emissions Database for Global Atmospheric Research (EDGAR) emission inventory of greenhouse gases E. Solazzo et al. 10.5194/acp-21-5655-2021
- GIS-Based Approach to Spatio-Temporal Interpolation of Atmospheric CO2 Concentrations in Limited Monitoring Dataset Y. Bezyk et al. 10.3390/atmos12030384
- Near-real-time CO2 fluxes from CarbonTracker Europe for high-resolution atmospheric modeling A. van der Woude et al. 10.5194/essd-15-579-2023
- The suitability of atmospheric oxygen measurements to constrain western European fossil-fuel CO2 emissions and their trends C. Rödenbeck et al. 10.5194/acp-23-15767-2023
- Global anthropogenic CO<sub>2</sub> emissions and uncertainties as a prior for Earth system modelling and data assimilation M. Choulga et al. 10.5194/essd-13-5311-2021
- Review of Sources of Uncertainty and Techniques Used in Uncertainty Quantification and Sensitivity Analysis to Estimate Greenhouse Gas Emissions from Ruminants E. Kimei et al. 10.3390/su16052219
- NOx emissions in France in 2019–2021 as estimated by the high-spatial-resolution assimilation of TROPOMI NO2 observations R. Plauchu et al. 10.5194/acp-24-8139-2024
- Uncertainty Analysis of Greenhouse Gas (GHG) Emissions Simulated by the Parametric Monte Carlo Simulation and Nonparametric Bootstrap Method K. Lee et al. 10.3390/en13184965
- A Gradient-Descent Optimization of CO2–CO–NOx Emissions over the Paris Megacity─The Case of the First SARS-CoV-2 Lockdown C. Abdallah et al. 10.1021/acs.est.3c00566
- The impact of temporal variability in prior emissions on the optimization of urban anthropogenic emissions of CO2, CH4 and CO using in-situ observations I. Super et al. 10.1016/j.aeaoa.2021.100119
- Analysis of Air Pollutants for a Small Paintshop by Means of a Mobile Platform and Geostatistical Methods I. Sówka et al. 10.3390/en16237716
- Real-world emission and impact of three wheeler electric auto-rickshaw in India T. Bagul et al. 10.1007/s11356-021-14805-6
- Vertical distribution and transport characteristics of ozone pollution based on lidar observation network and data assimilation over the Pearl River Delta, China Y. Pan et al. 10.1016/j.atmosres.2024.107643
- CO anthropogenic emissions in Europe from 2011 to 2021: insights from Measurement of Pollution in the Troposphere (MOPITT) satellite data A. Fortems-Cheiney et al. 10.5194/acp-24-4635-2024
- Quantifying CO<sub>2</sub> emissions of a city with the Copernicus Anthropogenic CO<sub>2</sub> Monitoring satellite mission G. Kuhlmann et al. 10.5194/amt-13-6733-2020
- Spatially resolved hourly traffic emission over megacity Delhi using advanced traffic flow data A. Biswal et al. 10.5194/essd-15-661-2023
- The CO2 Human Emissions (CHE) Project: First Steps Towards a European Operational Capacity to Monitor Anthropogenic CO2 Emissions G. Balsamo et al. 10.3389/frsen.2021.707247
- Impacts of Horizontal Resolution on Global Data Assimilation of Satellite Measurements for Tropospheric Chemistry Analysis T. Sekiya et al. 10.1029/2020MS002180
- Quantification of methane emissions in Hamburg using a network of FTIR spectrometers and an inverse modeling approach A. Forstmaier et al. 10.5194/acp-23-6897-2023
- An online emission module for atmospheric chemistry transport models: implementation in COSMO-GHG v5.6a and COSMO-ART v5.1-3.1 M. Jähn et al. 10.5194/gmd-13-2379-2020
- Analysis of the Anthropogenic and Biogenic NOx Emissions Over 2008–2017: Assessment of the Trends in the 30 Most Populated Urban Areas in Europe A. Fortems‐Cheiney et al. 10.1029/2020GL092206
- Multiple-Criteria Fuzzy Optimization of the Heat Treatment Processes for Two Steel Rolled Products L. Dymova et al. 10.3390/app11052324
- Improving urban CO2 spatial distribution modelling using multi-source data E. Sun et al. 10.1016/j.uclim.2024.101902
- Optimizing a dynamic fossil fuel CO<sub>2</sub> emission model with CTDAS (CarbonTracker Data Assimilation Shell, v1.0) for an urban area using atmospheric observations of CO<sub>2</sub>, CO, NO<sub><i>x</i></sub>, and SO<sub>2</sub> I. Super et al. 10.5194/gmd-13-2695-2020
- Evaluation of the GRAMM/GRAL model for high-resolution wind fields in Heidelberg, Germany M. May et al. 10.1016/j.atmosres.2023.107207
- Complementing XCO2 imagery with ground-based CO2 and 14CO2 measurements to monitor CO2 emissions from fossil fuels on a regional to local scale E. Potier et al. 10.5194/amt-15-5261-2022
- Assessing the Impact of Atmospheric CO2 and NO2 Measurements From Space on Estimating City-Scale Fossil Fuel CO2 Emissions in a Data Assimilation System T. Kaminski et al. 10.3389/frsen.2022.887456
- Identifying a Country’s Freight Transport-Intensive Economic Sectors and Their Logistics Emissions—Method Development and Exemplary Evaluation with Austria P. Miklautsch et al. 10.3390/su142215050
- Potential of 14C-based vs. ΔCO-based ΔffCO2 observations to estimate urban fossil fuel CO2 (ffCO2) emissions F. Maier et al. 10.5194/acp-24-8183-2024
- European pollen reanalysis, 1980–2022, for alder, birch, and olive M. Sofiev et al. 10.1038/s41597-024-03686-2
- Quantifying uncertainty in carbon emission estimation: Metrics and methodologies K. Lee et al. 10.1016/j.jclepro.2024.142141
- Comparison of OCO-2 target observations to MUCCnet – is it possible to capture urban XCO2 gradients from space? M. Rißmann et al. 10.5194/amt-15-6605-2022
- Quantifying CO2 Emissions of Power Plants With CO2 and NO2 Imaging Satellites G. Kuhlmann et al. 10.3389/frsen.2021.689838
- A local- to national-scale inverse modeling system to assess the potential of spaceborne CO<sub>2</sub> measurements for the monitoring of anthropogenic emissions D. Santaren et al. 10.5194/amt-14-403-2021
- Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO): global and European emission temporal profile maps for atmospheric chemistry modelling M. Guevara et al. 10.5194/essd-13-367-2021
- Assessment of Urban CO2 Measurement and Source Attribution in Munich Based on TDLAS-WMS and Trajectory Analysis L. Lan et al. 10.3390/atmos11010058
48 citations as recorded by crossref.
- Determination of the emission rates of CO<sub>2</sub> point sources with airborne lidar S. Wolff et al. 10.5194/amt-14-2717-2021
- Verifying national inventory-based combustion emissions of CO2 across the UK and mainland Europe using satellite observations of atmospheric CO and CO2 T. Scarpelli et al. 10.5194/acp-24-10773-2024
- CAMS-REG-v4: a state-of-the-art high-resolution European emission inventory for air quality modelling J. Kuenen et al. 10.5194/essd-14-491-2022
- Effects of point source emission heights in WRF–STILT: a step towards exploiting nocturnal observations in models F. Maier et al. 10.5194/gmd-15-5391-2022
- Accounting for meteorological biases in simulated plumes using smarter metrics P. Vanderbecken et al. 10.5194/amt-16-1745-2023
- Verifying Methane Inventories and Trends With Atmospheric Methane Data J. Worden et al. 10.1029/2023AV000871
- Quantification of fossil fuel CO2 from combined CO, δ13CO2 and Δ14CO2 observations J. Kim et al. 10.5194/acp-23-14425-2023
- Optimising urban measurement networks for CO2 flux estimation: a high-resolution observing system simulation experiment using GRAMM/GRAL S. Vardag & R. Maiwald 10.5194/gmd-17-1885-2024
- Urban-scale variational flux inversion for CO Using TROPOMI total-column retrievals: A case study of Tehran N. Shahrokhi et al. 10.1016/j.atmosenv.2023.120009
- Understanding greenhouse gas (GHG) column concentrations in Munich using the Weather Research and Forecasting (WRF) model X. Zhao et al. 10.5194/acp-23-14325-2023
- Improved definition of prior uncertainties in CO2 and CO fossil fuel fluxes and its impact on multi-species inversion with GEOS-Chem (v12.5) I. Super et al. 10.5194/gmd-17-7263-2024
- Gridded fossil CO2 emissions and related O2 combustion consistent with national inventories 1959–2018 M. Jones et al. 10.1038/s41597-020-00779-6
- Variational regional inverse modeling of reactive species emissions with PYVAR-CHIMERE-v2019 A. Fortems-Cheiney et al. 10.5194/gmd-14-2939-2021
- Uncertainties in the Emissions Database for Global Atmospheric Research (EDGAR) emission inventory of greenhouse gases E. Solazzo et al. 10.5194/acp-21-5655-2021
- GIS-Based Approach to Spatio-Temporal Interpolation of Atmospheric CO2 Concentrations in Limited Monitoring Dataset Y. Bezyk et al. 10.3390/atmos12030384
- Near-real-time CO2 fluxes from CarbonTracker Europe for high-resolution atmospheric modeling A. van der Woude et al. 10.5194/essd-15-579-2023
- The suitability of atmospheric oxygen measurements to constrain western European fossil-fuel CO2 emissions and their trends C. Rödenbeck et al. 10.5194/acp-23-15767-2023
- Global anthropogenic CO<sub>2</sub> emissions and uncertainties as a prior for Earth system modelling and data assimilation M. Choulga et al. 10.5194/essd-13-5311-2021
- Review of Sources of Uncertainty and Techniques Used in Uncertainty Quantification and Sensitivity Analysis to Estimate Greenhouse Gas Emissions from Ruminants E. Kimei et al. 10.3390/su16052219
- NOx emissions in France in 2019–2021 as estimated by the high-spatial-resolution assimilation of TROPOMI NO2 observations R. Plauchu et al. 10.5194/acp-24-8139-2024
- Uncertainty Analysis of Greenhouse Gas (GHG) Emissions Simulated by the Parametric Monte Carlo Simulation and Nonparametric Bootstrap Method K. Lee et al. 10.3390/en13184965
- A Gradient-Descent Optimization of CO2–CO–NOx Emissions over the Paris Megacity─The Case of the First SARS-CoV-2 Lockdown C. Abdallah et al. 10.1021/acs.est.3c00566
- The impact of temporal variability in prior emissions on the optimization of urban anthropogenic emissions of CO2, CH4 and CO using in-situ observations I. Super et al. 10.1016/j.aeaoa.2021.100119
- Analysis of Air Pollutants for a Small Paintshop by Means of a Mobile Platform and Geostatistical Methods I. Sówka et al. 10.3390/en16237716
- Real-world emission and impact of three wheeler electric auto-rickshaw in India T. Bagul et al. 10.1007/s11356-021-14805-6
- Vertical distribution and transport characteristics of ozone pollution based on lidar observation network and data assimilation over the Pearl River Delta, China Y. Pan et al. 10.1016/j.atmosres.2024.107643
- CO anthropogenic emissions in Europe from 2011 to 2021: insights from Measurement of Pollution in the Troposphere (MOPITT) satellite data A. Fortems-Cheiney et al. 10.5194/acp-24-4635-2024
- Quantifying CO<sub>2</sub> emissions of a city with the Copernicus Anthropogenic CO<sub>2</sub> Monitoring satellite mission G. Kuhlmann et al. 10.5194/amt-13-6733-2020
- Spatially resolved hourly traffic emission over megacity Delhi using advanced traffic flow data A. Biswal et al. 10.5194/essd-15-661-2023
- The CO2 Human Emissions (CHE) Project: First Steps Towards a European Operational Capacity to Monitor Anthropogenic CO2 Emissions G. Balsamo et al. 10.3389/frsen.2021.707247
- Impacts of Horizontal Resolution on Global Data Assimilation of Satellite Measurements for Tropospheric Chemistry Analysis T. Sekiya et al. 10.1029/2020MS002180
- Quantification of methane emissions in Hamburg using a network of FTIR spectrometers and an inverse modeling approach A. Forstmaier et al. 10.5194/acp-23-6897-2023
- An online emission module for atmospheric chemistry transport models: implementation in COSMO-GHG v5.6a and COSMO-ART v5.1-3.1 M. Jähn et al. 10.5194/gmd-13-2379-2020
- Analysis of the Anthropogenic and Biogenic NOx Emissions Over 2008–2017: Assessment of the Trends in the 30 Most Populated Urban Areas in Europe A. Fortems‐Cheiney et al. 10.1029/2020GL092206
- Multiple-Criteria Fuzzy Optimization of the Heat Treatment Processes for Two Steel Rolled Products L. Dymova et al. 10.3390/app11052324
- Improving urban CO2 spatial distribution modelling using multi-source data E. Sun et al. 10.1016/j.uclim.2024.101902
- Optimizing a dynamic fossil fuel CO<sub>2</sub> emission model with CTDAS (CarbonTracker Data Assimilation Shell, v1.0) for an urban area using atmospheric observations of CO<sub>2</sub>, CO, NO<sub><i>x</i></sub>, and SO<sub>2</sub> I. Super et al. 10.5194/gmd-13-2695-2020
- Evaluation of the GRAMM/GRAL model for high-resolution wind fields in Heidelberg, Germany M. May et al. 10.1016/j.atmosres.2023.107207
- Complementing XCO2 imagery with ground-based CO2 and 14CO2 measurements to monitor CO2 emissions from fossil fuels on a regional to local scale E. Potier et al. 10.5194/amt-15-5261-2022
- Assessing the Impact of Atmospheric CO2 and NO2 Measurements From Space on Estimating City-Scale Fossil Fuel CO2 Emissions in a Data Assimilation System T. Kaminski et al. 10.3389/frsen.2022.887456
- Identifying a Country’s Freight Transport-Intensive Economic Sectors and Their Logistics Emissions—Method Development and Exemplary Evaluation with Austria P. Miklautsch et al. 10.3390/su142215050
- Potential of 14C-based vs. ΔCO-based ΔffCO2 observations to estimate urban fossil fuel CO2 (ffCO2) emissions F. Maier et al. 10.5194/acp-24-8183-2024
- European pollen reanalysis, 1980–2022, for alder, birch, and olive M. Sofiev et al. 10.1038/s41597-024-03686-2
- Quantifying uncertainty in carbon emission estimation: Metrics and methodologies K. Lee et al. 10.1016/j.jclepro.2024.142141
- Comparison of OCO-2 target observations to MUCCnet – is it possible to capture urban XCO2 gradients from space? M. Rißmann et al. 10.5194/amt-15-6605-2022
- Quantifying CO2 Emissions of Power Plants With CO2 and NO2 Imaging Satellites G. Kuhlmann et al. 10.3389/frsen.2021.689838
- A local- to national-scale inverse modeling system to assess the potential of spaceborne CO<sub>2</sub> measurements for the monitoring of anthropogenic emissions D. Santaren et al. 10.5194/amt-14-403-2021
- Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO): global and European emission temporal profile maps for atmospheric chemistry modelling M. Guevara et al. 10.5194/essd-13-367-2021
1 citations as recorded by crossref.
Latest update: 13 Dec 2024
Short summary
Emission data contain uncertainties introduced by the methodology and the data used. We quantified uncertainties in gridded emissions using the uncertainty in underlying data, showing that disaggregation in space and time significantly increases the uncertainty. Understanding uncertainties helps to interpret atmospheric measurements and the gap with modelled concentrations. Moreover, our analyses help identify regions with large uncertainties, which require further scrutiny.
Emission data contain uncertainties introduced by the methodology and the data used. We...
Altmetrics
Final-revised paper
Preprint