Quantifying city fossil-fuel CO2 emission: the limit and potential of OCO-2
Ruixue Lei, The Pennsylvania State University, rxl5385@psu.edu (Presenter)
Sha Feng, Pacific Northwest National Laboratory, sfeng@pnnl.gov
Alexandre Danjou, Laboratoire des Sciences du Climat et de l'Environnement, alexandre.danjou@lsce.ipsl.fr
Grégoire Broquet, Laboratoire des Sciences du Climat et de l'Environnement, gregoire.broquet@lsce.ipsl.fr
Dien Wu, California Institute of Technology, dienwu@caltech.edu
John C. Lin, University of Utah, john.lin@utah.edu
Christopher O'Dell, Colorado State University, odell@atmos.colostate.edu
Thomas Lauvaux, Laboratoire des Sciences du Climat et de l'Environnement, thomas.lauvaux@lsce.ipsl.fr
Housing more than 50% of the world’s population and contributing more than 70% of the world's anthropogenic CO2 emission, cities need more accurate quantification and proper management of its fossil-fuel (FF) CO2 emission in order to achieve the 1.5 or 2.0 degree temperature reduction goals in the Paris Climate Agreement. Current satellites, such as Orbiting Carbon Observatory 2 (OCO-2), have shown some potentials in the CO2 monitoring at the global scale but still are not very satisfying at city FF CO2 detections limited by accuracy, scanning track width, re-visited period, etc. Snapshot Area Mapping (SAM) observations from upon available Orbiting Carbon Observatory 3 (OCO-3) was designed to provide a tremendous new opportunity to study CO2 emissions from targeted cities.
Lahore, the second-largest city in Pakistan, has fast-growing economy, and populational booming in recent two decades. Its flat topography and increasing FFCO2 emission make it an ideal testbed for demonstrating the capability of the trend detection of FFCO2 from space. Here we tested the FFCO2 trend detection over Lahore based on about 20 OCO-2 tracks over Lahore in 2014-2019 with the Weather Research and Forecasting (WRF)-Chem model with the consideration of atmospheric transport errors generated by the Monte-Carlo method. WRF-Chem was run at 3-km spatial resolution and the FFCO2 emissions were downscaled from the 1-km Open-source Data Inventory for Anthropogenic CO2 (ODIAC) emissions. The simulations of 25 tracks over Lahore, Pakistan show that the OCO-2 quality flags are also helpful for city studies although they were originally designed for global studies. Bayesian inversion shows an annual 6.7% increasing trend of fossil fuel CO2 emissions over Lahore. But the trend is driven by the prior, not the optimized emissions based on OCO-2 satellite data because of the limited number of high-quality tracks.
Recording: Video_Talk_Lei_16_21.mp4
Presentation Type: Talk
Session: Next-Gen Data Management, Syntheses, and Products + From Manipulative Experiments to Models (and back)
Session Date: Friday (3/12) 1:25 PM
Quantifying city fossil-fuel CO2 emission: the limit and potential of OCO-2
Ruixue Lei, The Pennsylvania State University, rxl5385@psu.edu (Presenter)
Sha Feng, Pacific Northwest National Laboratory, sfeng@pnnl.gov
Alexandre Danjou, Laboratoire des Sciences du Climat et de l'Environnement, alexandre.danjou@lsce.ipsl.fr
Grégoire Broquet, Laboratoire des Sciences du Climat et de l'Environnement, gregoire.broquet@lsce.ipsl.fr
Dien Wu, California Institute of Technology, dienwu@caltech.edu
John C. Lin, University of Utah, john.lin@utah.edu
Christopher O'Dell, Colorado State University, odell@atmos.colostate.edu
Thomas Lauvaux, Laboratoire des Sciences du Climat et de l'Environnement, thomas.lauvaux@lsce.ipsl.fr
Housing more than 50% of the world’s population and contributing more than 70% of the world's anthropogenic CO2 emission, cities need more accurate quantification and proper management of its fossil-fuel (FF) CO2 emission in order to achieve the 1.5 or 2.0 degree temperature reduction goals in the Paris Climate Agreement. Current satellites, such as Orbiting Carbon Observatory 2 (OCO-2), have shown some potentials in the CO2 monitoring at the global scale but still are not very satisfying at city FF CO2 detections limited by accuracy, scanning track width, re-visited period, etc. Snapshot Area Mapping (SAM) observations from upon available Orbiting Carbon Observatory 3 (OCO-3) was designed to provide a tremendous new opportunity to study CO2 emissions from targeted cities.
Lahore, the second-largest city in Pakistan, has fast-growing economy, and populational booming in recent two decades. Its flat topography and increasing FFCO2 emission make it an ideal testbed for demonstrating the capability of the trend detection of FFCO2 from space. Here we tested the FFCO2 trend detection over Lahore based on about 20 OCO-2 tracks over Lahore in 2014-2019 with the Weather Research and Forecasting (WRF)-Chem model with the consideration of atmospheric transport errors generated by the Monte-Carlo method. WRF-Chem was run at 3-km spatial resolution and the FFCO2 emissions were downscaled from the 1-km Open-source Data Inventory for Anthropogenic CO2 (ODIAC) emissions. The simulations of 25 tracks over Lahore, Pakistan show that the OCO-2 quality flags are also helpful for city studies although they were originally designed for global studies. Bayesian inversion shows an annual 6.7% increasing trend of fossil fuel CO2 emissions over Lahore. But the trend is driven by the prior, not the optimized emissions based on OCO-2 satellite data because of the limited number of high-quality tracks.
Recording: Video_Talk_Lei_16_21.mp4
Presentation Type: Talk
Session: Next-Gen Data Management, Syntheses, and Products + From Manipulative Experiments to Models (and back)
Session Date: Friday (3/12) 1:25 PM