Articles | Volume 7, issue 10
https://doi.org/10.5194/amt-7-3285-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-7-3285-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
02 Oct 2014
Research article |
| 02 Oct 2014
Constraining regional greenhouse gas emissions using geostationary concentration measurements: a theoretical study
P. J. Rayner
School of Earth Sciences, University of Melbourne, Melbourne, Australia
S. R. Utembe
School of Earth Sciences, University of Melbourne, Melbourne, Australia
S. Crowell
College of Atmospheric and Geographic Sciences, University of Oklahoma, Norman, USA
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- TCCON Philippines: First Measurement Results, Satellite Data and Model Comparisons in Southeast Asia V. Velazco et al. 10.3390/rs9121228
- Assessing the capability of different satellite observing configurations to resolve the distribution of methane emissions at kilometer scales A. Turner et al. 10.5194/acp-18-8265-2018
- Simulated retrievals for the remote sensing of CO2, CH4, CO, and H2O from geostationary orbit X. Xi et al. 10.5194/amt-8-4817-2015
- Quantifying CO2 Emissions From Individual Power Plants From Space R. Nassar et al. 10.1002/2017GL074702
- Potential of a geostationary geoCARB mission to estimate surface emissions of CO2, CH4 and CO in a polluted urban environment: case study Shanghai D. O'Brien et al. 10.5194/amt-9-4633-2016
- The potential of satellite spectro-imagery for monitoring CO2 emissions from large cities G. Broquet et al. 10.5194/amt-11-681-2018
- High‐Resolution Lagrangian Inverse Modeling of CO2 Emissions Over the Paris Region During the First 2020 Lockdown Period K. Nalini et al. 10.1029/2021JD036032
- Reviews and syntheses: guiding the evolution of the observing system for the carbon cycle through quantitative network design T. Kaminski & P. Rayner 10.5194/bg-14-4755-2017
- Constraints on methane emissions in North America from future geostationary remote-sensing measurements N. Bousserez et al. 10.5194/acp-16-6175-2016
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- Detection of fossil fuel emission trends in the presence of natural carbon cycle variability Y. Yin et al. 10.1088/1748-9326/ab2dd7
- Diagnostic methods for atmospheric inversions of long-lived greenhouse gases A. Michalak et al. 10.5194/acp-17-7405-2017
- S2MetNet: A novel dataset and deep learning benchmark for methane point source quantification using Sentinel-2 satellite imagery A. Radman et al. 10.1016/j.rse.2023.113708
- A multi-model approach to monitor emissions of CO2 and CO from an urban–industrial complex I. Super et al. 10.5194/acp-17-13297-2017
- Satellite observations of atmospheric methane and their value for quantifying methane emissions D. Jacob et al. 10.5194/acp-16-14371-2016
- Towards accurate methane point-source quantification from high-resolution 2-D plume imagery S. Jongaramrungruang et al. 10.5194/amt-12-6667-2019
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- The Potential of the Geostationary Carbon Cycle Observatory (GeoCarb) to Provide Multi-scale Constraints on the Carbon Cycle in the Americas B. Moore III et al. 10.3389/fenvs.2018.00109
- Quantitative imaging of carbon dioxide plumes using a ground-based shortwave infrared spectral camera M. Knapp et al. 10.5194/amt-17-2257-2024
- Source‐receptor relationships of column‐average CO2 and implications for the impact of observations on flux inversions J. Liu et al. 10.1002/2014JD022914
- Exploring the utility of quantitative network design in evaluating Arctic sea ice thickness sampling strategies T. Kaminski et al. 10.5194/tc-9-1721-2015
- Four years of global carbon cycle observed from the Orbiting Carbon Observatory 2 (OCO-2) version 9 and in situ data and comparison to OCO-2 version 7 H. Peiro et al. 10.5194/acp-22-1097-2022
- Assimilation of atmospheric CO2 observations from space can support national CO2 emission inventories T. Kaminski et al. 10.1088/1748-9326/ac3cea
- Detecting high-emitting methane sources in oil/gas fields using satellite observations D. Cusworth et al. 10.5194/acp-18-16885-2018
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