Articles | Volume 20, issue 1
https://doi.org/10.5194/acp-20-99-2020
© 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-20-99-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Jan 2020
Research article |
| 03 Jan 2020
| 03 Jan 2020
A methodology to constrain carbon dioxide emissions from coal-fired power plants using satellite observations of co-emitted nitrogen dioxide
Universities Space Research Association (USRA), Goddard Earth Sciences Technology and Research (GESTAR), Columbia, MD, USA
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Bryan N. Duncan
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Nickolay A. Krotkov
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Lok N. Lamsal
Universities Space Research Association (USRA), Goddard Earth Sciences Technology and Research (GESTAR), Columbia, MD, USA
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Steffen Beirle
Max-Planck-Institut für Chemie, Mainz, Germany
Debora Griffin
Air Quality Research Division, Environment and Climate Change Canada, Toronto, ON, Canada
Chris A. McLinden
Air Quality Research Division, Environment and Climate Change Canada, Toronto, ON, Canada
Daniel L. Goldberg
Energy Systems Division, Argonne National Laboratory, Lemont, IL, USA
Zifeng Lu
Energy Systems Division, Argonne National Laboratory, Lemont, IL, USA
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43 citations as recorded by crossref.
- Physics-Guided Multitask Learning for Estimating Power Generation and CO2 Emissions From Satellite Imagery J. Hanna et al. 10.1109/TGRS.2023.3286444
- China’s Fossil Fuel CO2 Emissions Estimated Using Surface Observations of Coemitted NO2 S. Feng et al. 10.1021/acs.est.3c07756
- NH3 Emissions and Lifetime Estimated by Satellite Observations with Differential Evolution Algorithm Y. Xie et al. 10.3390/atmos15030251
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- Climate mitigation policies for cities must consider air quality impacts R. Commane & L. Schiferl 10.1016/j.chempr.2022.02.006
- NiO-based sensor for in situ CO monitoring above 1000 °C: behavior and mechanism Y. Wang et al. 10.1007/s42114-022-00480-9
- Analyzing nitrogen oxides to carbon dioxide emission ratios from space: A case study of Matimba Power Station in South Africa J. Hakkarainen et al. 10.1016/j.aeaoa.2021.100110
- Catalog of NOx emissions from point sources as derived from the divergence of the NO2 flux for TROPOMI S. Beirle et al. 10.5194/essd-13-2995-2021
- Identification of NOx hotspots from oversampled TROPOMI NO2 column based on image segmentation method K. Wang et al. 10.1016/j.scitotenv.2021.150007
- A lightweight NO2-to-NOx conversion model for quantifying NOx emissions of point sources from NO2 satellite observations S. Meier et al. 10.5194/acp-24-7667-2024
- Estimating Carbon Dioxide Emissions from Power Plant Water Vapor Plumes Using Satellite Imagery and Machine Learning H. Couture et al. 10.3390/rs16071290
- Impact of COVID-19 force confinement for CO2 emission, NO2 concentration, and daily traffic congestion throughout EU nations and the United Kingdom (UK) M. Sahraei & B. Ziaei 10.1007/s13762-023-05391-w
- Characterization of Aerosol and CO2 Co-Emissions around Power Plants through Satellite-Based Synergistic Observations L. Sun et al. 10.3390/rs16091609
- Using Space‐Based CO2 and NO2 Observations to Estimate Urban CO2 Emissions E. Yang et al. 10.1029/2022JD037736
- Refining Spatial and Temporal XCO2 Characteristics Observed by Orbiting Carbon Observatory-2 and Orbiting Carbon Observatory-3 Using Sentinel-5P Tropospheric Monitoring Instrument NO2 Observations in China K. Guo et al. 10.3390/rs16132456
- Improved spatial representation of a highly resolved emission inventory in China: evidence from TROPOMI measurements N. Wu et al. 10.1088/1748-9326/ac175f
- Total organic carbon measurements reveal major gaps in petrochemical emissions reporting M. He et al. 10.1126/science.adj6233
- Daily Emission Patterns of Coal-Fired Power Plants in China Based on Multisource Data Fusion N. Wu et al. 10.1021/acsenvironau.2c00014
- A new method for inferring city emissions and lifetimes of nitrogen oxides from high-resolution nitrogen dioxide observations: a model study F. Liu et al. 10.5194/acp-22-1333-2022
- Toward monitoring daily anthropogenic CO2 emissions with air pollution sensors from space H. Li & B. Zheng 10.1016/j.oneear.2024.08.019
- Analyzing Local Carbon Dioxide and Nitrogen Oxide Emissions From Space Using the Divergence Method: An Application to the Synthetic SMARTCARB Dataset J. Hakkarainen et al. 10.3389/frsen.2022.878731
- Retrieving CH4-emission rates from coal mine ventilation shafts using UAV-based AirCore observations and the genetic algorithm–interior point penalty function (GA-IPPF) model T. Shi et al. 10.5194/acp-22-13881-2022
- An assessment of China's industrial emission characteristics using satellite observations of XCO2, SO2, and NO2 Y. Fu et al. 10.1016/j.apr.2022.101486
- Quantifying factory-scale CO2/CH4 emission based on mobile measurements and EMISSION-PARTITION model: cases in China T. Shi et al. 10.1088/1748-9326/acbce7
- A high-temperature mixed potential CO gas sensor for in situ combustion control Y. Wang et al. 10.1039/D0TA06320G
- Automated detection of atmospheric NO<sub>2</sub> plumes from satellite data: a tool to help infer anthropogenic combustion emissions D. Finch et al. 10.5194/amt-15-721-2022
- Investigating the impact of control strategies on the sulfur dioxide emissions of South Korean industrial facilities using an aircraft mass balance approach G. Wong et al. 10.1016/j.atmosenv.2024.120496
- Satellite-based estimates of decline and rebound in China’s CO 2 emissions during COVID-19 pandemic B. Zheng et al. 10.1126/sciadv.abd4998
- Vertical Evolution of Ozone Formation Sensitivity Based on Synchronous Vertical Observations of Ozone and Proxies for Its Precursors: Implications for Ozone Pollution Prevention Strategies Q. Hu et al. 10.1021/acs.est.4c00637
- High-precision methodology for quantifying gas point source emission T. Shi et al. 10.1016/j.jclepro.2021.128672
- Urban NO x emissions around the world declined faster than anticipated between 2005 and 2019 D. Goldberg et al. 10.1088/1748-9326/ac2c34
- How effective are emission taxes in reducing air pollution? T. Erbertseder et al. 10.2139/ssrn.4353315
- Estimating global 0.1° scale gridded anthropogenic CO2 emissions using TROPOMI NO2 and a data-driven method Y. Zhang et al. 10.1016/j.scitotenv.2024.175177
- Satellite Data Applications for Sustainable Energy Transitions M. Edwards et al. 10.3389/frsus.2022.910924
- 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
- Ozone Monitoring Instrument (OMI) Aura nitrogen dioxide standard product version 4.0 with improved surface and cloud treatments L. Lamsal et al. 10.5194/amt-14-455-2021
- A Data-Driven Method to Monitor Carbon Dioxide Emissions of Coal-Fired Power Plants S. Zhou et al. 10.3390/en16041646
- Quantifying daily NOx and CO2 emissions from Wuhan using satellite observations from TROPOMI and OCO-2 Q. Zhang et al. 10.5194/acp-23-551-2023
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- A real-time carbon emission estimation framework for industrial parks with non-intrusive load monitoring J. Liu et al. 10.1016/j.seta.2023.103482
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- Aircraft and satellite observations reveal historical gap between top–down and bottom–up CO2 emissions from Canadian oil sands S. Wren et al. 10.1093/pnasnexus/pgad140
Latest update: 20 Nov 2024
Short summary
We present a novel method to infer CO2 emissions from individual power plants, based on satellite observations of co-emitted NO2. We find that the CO2 emissions estimated by our satellite-based method during 2005–2017 are in reasonable agreement with the CEMS measurements for US power plants. The broader implication of our methodology is that it has the potential to provide an additional constraint on CO2 emissions from power plants in regions of the world without reliable emissions accounting.
We present a novel method to infer CO2 emissions from individual power plants, based on...
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