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Session Proposal: Showcasing methodologies and datasets for tracking greenhouse gas emissions: a dialogue between fields (AGU25)

GC096
Showcasing methodologies and datasets for tracking greenhouse gas emissions: a dialogue between fields

Session ID#: 250607

Session Description:
Growth rates of carbon dioxide, methane, and nitrous oxide are at or near record highs. Measurement techniques, datasets, and modeling approaches for quantifying greenhouse gas emissions are rapidly proliferating. This session seeks to bring together researchers from the atmospheric sciences and fields specific to emissions sectors (e.g. ecology, biogeochemistry, oceanography, hydrology, energy resources, atmosphere/surface remote sensing, global change, machine learning) to find synergy in methodology and bring together disparate datasets. The primary goal will be to connect a community of practitioners to measurements, models, or inventories that complement their own work. A secondary goal will be to brainstorm ways to facilitate integrative science, for example, validating models when measurements are at vastly different spatial scales, or making use of tools developed for a different discipline. Presentations will showcase outstanding tools and products in their field for which they see interdisciplinary potential.
Index Terms:

0368 Troposphere: constituent transport and chemistry [ATMOSPHERIC COMPOSITION AND STRUCTURE]
0428 Carbon cycling [BIOGEOSCIENCES]
1615 Biogeochemical cycles, processes, and modeling [GLOBAL CHANGE]
4806 Carbon cycling [OCEANOGRAPHY: BIOLOGICAL AND CHEMICAL]
Primary Convener:  Ethan D. Kyzivat, Harvard University, Earth and Planetary Sciences, Cambridge, United States
Convener:  Wu Sun, Carnegie Institution for Science Stanford, Department of Global Ecology, Stanford, CA, United States
 
Connecting observations to emissions: emulating atmospheric transport to enable near-real-time greenhouse gas flux inversions (Invited) (1845887)
Alexander J Turner, University of Washington, Department of Atmospheric and Climate Science, Seattle, United States and Nikhil Dadheech, University of Washington, Seattle, United States
 
Production chain complexity drives emissions disparities across global chemical industry and products. (1853032)
Weichen Zhao, University College London, London, United Kingdom
 
Identifying global dairy and beef cattle operations by combining disparate datasets with AI and remote sensing to improve GHG emissions estimates and monitoring. (1880241)
Dr. Aaron Davitt1,2, Edward Boyda3, Paul Tulloch4, Derek Tesser5, Ashutosh Pawar5, Joey Jilek5, Andrew Tulloch6, Vasit Sagan7, Lekha Sridhar1 and Lauren Betz8, (1)WattTime, Oakland, United States, (2)Climate TRACE, Denver, United States, (3)The Earth Genome, Los Altos, United States, (4)Stanford University, Stanford, United States, (5)Saint Louis University, Remote Sensing Laboratory, Department of Earth, Environmental and Geospatial Science, St. Louis, United States, (6)Carleton University Ottawa, Ottawa, Canada, (7)Saint Louis University, Saint Louis, United States, (8)Climate TRACE, Salt Lake City, United States
 
Global fine-resolution analytical inversion of TROPOMI methane observations enabled by the stretched-grid high-performance GEOS-Chem model (1898801)
Dandan Zhang, Daniel J. Varon, Melissa Payer Sulprizio, Elizabeth W. Lundgren, Nicholas Balasus, Lucas Estrada and Daniel J. Jacob, Harvard University, School of Engineering and Applied Sciences, Cambridge, United States
 
PyKGML: A Python Library for Efficient Development and Benchmark of Knowledge-Guided Machine Learning for Greenhouse Gas Modeling (1903759)
Yufeng Yang1, An Min1, Gavin McNicol2, Chongwei Chen3, Zhenong Jin1,4, Vipin Kumar3 and Licheng LIU1, (1)University of Minnesota Twin Cities, Department of Bioproducts and Biosystems Engineering, Saint Paul, United States, (2)University of Illinois Chicago, Department of Earth and Environmental Sciences, Chicago, United States, (3)University of Minnesota Twin Cities, Department of Computer Science & Engineering, Minneapolis, United States, (4)Peking University, The Institute of Ecology, College of Urban and Environmental Science, Beijing, China
 
Application of Combined Vermicompost and Rapeseed Cake with Inorganic Fertilization and Assessment of Nutrients Cycling, NH3 and GHGs Emissions during Wheat-maize Rotation (1907465)
Syed Turab Raza, Yunnan University, Kunming, China
 
Improving source attribution within national to regional methane budgets using facility-level data and hyperspectral imaging spectrometers (1923486)
Tia Scarpelli1, Daniel Cusworth1, Riley Duren1, Gabriel Maxemin1, Daniel Bon1, Jinsol Kim1 and Rose Wang2, (1)Carbon Mapper, Pasadena, United States, (2)RMI, New York, United States
 
Integrating remote sensing physics with geospatial foundational models for global manure pond detection (1925847)
Ashutosh Pawar1, Vasit Sagan1, Derek Tesser1, Omar Al Akkad1, Joey Jilek1, Alessandro Farbo2 and Dr. Aaron Davitt3,4, (1)Saint Louis University, Remote Sensing Laboratory, Department of Earth, Environmental and Geospatial Science, St. Louis, United States, (2)University of Torino, Department of Agriculture, Forestry and Food Sciences, Torino, Italy, (3)WattTime, Oakland, United States, (4)Climate TRACE, Denver, United States
 
Contemporary Arctic-boreal Zone Carbon Dioxide and Methane Flux Budgets and their Radiative Impact (1929198)
Bethany Sutherland1, Jennifer Watts1, Luke D Schiferl2, Brendan M Rogers1, Abhishek Chatterjee3, Stefano Potter1, Elchin E Jafarov1, Jeralyn M Poe4, Roisin Commane2, Benjamin Gaubert5, Jonathan A Wang6, Christina Schaedel1, Lori Bruhwiler7, Benjamin Poulter8, Youmi Oh9, Scot Miller10, Isabel Wargowsky1, Anna Virkalla1 and David M Lawrence11, (1)Woodwell Climate Research Center, Falmouth, United States, (2)Lamont-Doherty Earth Observatory, Palisades, United States, (3)California Institute of Technology, Jet Propulsion Laboratory, Pasadena, United States, (4)Northern Arizona University, Flagstaff, AZ, United States, (5)National Center for Atmospheric Research (NCAR), Atmospheric Chemistry Observations & Modeling Laboratory (ACOM), Boulder,CO, United States, (6)University of Utah, School of Biological Sciences, Salt Lake City, UT, United States, (7)NOAA, Global Monitoring Laboratory, Boulder, United States, (8)Spark Climate Solutions, San Francisco, United States, (9)NOAA Global Monitoring Laboratory, Boulder, United States, (10)Johns Hopkins University, Environmental Health and Engineering, Baltimore, United States, (11)NSF National Center for Atmospheric Research, Boulder, United States
 
How Well Can High-Resolution Satellite Observations Constrain Emissions? Observing System Simulation Experiments Using the Integrated Methane Inversion (IMI) (1933357)
Xiaolin Wang1, Daniel J. Jacob1, Nicholas Balasus1, James D. East2, Lucas Estrada1, Sarah Hancock1 and Jack Bruno3, (1)Harvard University, School of Engineering and Applied Sciences, Cambridge, United States, (2)Harvard University, School of Engineering and Applied Sciences, Cambridge, MA, United States, (3)Harvard University, Department of Earth and Planetary Sciences, Cambridge, United States
 
Downscaling of OCO-2 Target Mode Observations for Fine-Scale Analysis of CO2 sources in Urban Areas (1967223)
Jonathan F Dooley1, Taylor Jones2, Russell Goebel3, Lucy Hutyra4, Leeza Moldavchuk4 and Luis Carvalho5, (1)Georgetown University, Washington, United States, (2)Georgetown University, Washington, DC, United States, (3)Boston University, Boston, MA, United States, (4)Boston University, Earth & Environment, Boston, MA, United States, (5)Associate Professor, Dept. of Mathematics and Statistics Boston University, Boston, MA, United States
 
Integrating the Global Lakes and Wetlands Database (GLWD v2) in global carbon studies (Invited) (1970579)
Etienne Fluet-Chouinard, Pacific Northwest National Laboratory, Richland, WA, United States, Mira Anand, Confluvio Consulting Inc, Montreal, Canada, Florence Tan, McGill University, Department of Geography, Montreal, Canada and Bernhard Lehner, McGill University, Department of Geography, Montreal, QC, Canada
 
Integrating Remote Sensing and Foundation Models to Improve Global GHG Emission Estimation (1973512)
Vasit Sagan1, Derek Tesser2, Alifu Haireti1, Ashutosh Pawar1, Omar Al Akkad1, Joey Jilek1, Dr. Aaron Davitt3 and Edward Boyda4, (1)Saint Louis University, Remote Sensing Laboratory, Department of Earth, Environmental and Geospatial Science, St. Louis, United States, (2)Saint Louis University, Remote Sensing Laboratory, Department of Earth, Environment and Geospatial Sciences, St. Louis, United States, (3)WattTime, Oakland, United States, (4)The Earth Genome, Los Altos, United States
 
Quantifying Chinese Coal Mine Methane Emissions Across Scales: Merging Underground, Flux Tower, Point Source and Wide-Area Remote Sensing Observations With Atmospheric Emissions Inversion Models (1981642)
Jason Blake Cohen1, Wei Hu1, Yanqiu Liu1, Bo Zheng1, Fan Lu1, Louyao Guan1, Shuo Wang2, Pravash Tiwari1, Lingxiao Lu1, Qin He1, Kai Qin1 and Xun Tang1, (1)China University of Mining and Technology, School of Environment Science and Spatial Informatics, Xuzhou, China, (2)China University of Mining and Technology, Carbon Neutrality Institute, Xuzhou, China
 
A Benchmark Dataset to Constrain Regional Inverse Model Emissions Using Oversampled Methane Observations from MethaneAIR (1988218)
Maryann R Sargent1, Jasna V. Pittman2, Jonathan E Franklin3, Jacob Bushey2, Bruce Daube2, Jacob Hohl4, Liam Downing3, Amin R Nehrir5, Raia Ottenheimer6, Dr. Zhan Zhang, PhD7, Eleanor Walker8, Sébastien Roche9, Christopher Chan Miller10, Joshua Simon Benmergui11, Ethan Manninen12 and Steven C Wofsy2, (1)Harvard University, Harvard John A. Paulson School of Engineering and Applied Sciences, Cambridge, MA, United States, (2)Harvard University, Harvard John A. Paulson School of Engineering and Applied Sciences, Cambridge, United States, (3)Harvard University, Cambridge, United States, (4)Center for Astrophysics | Harvard & Smithsonian, Cambridge, MA, USA, Cambridge, United States, (5)NASA Langley Research Center, Hampton, United States, (6)Harvard University, Toronto, United States, (7)Environmental Defense Fund, New York, United States, (8)Stanford University, Earth Systems Science, Stanford, United States, (9)University of Toronto, Department of Physics, Toronto, ON, Canada, (10)Environmental Defense Fund, Harvard University, Cambridge, United States, (11)MethaneSAT, LLC, Austin, United States, (12)Harvard University, John A. Paulson School of Engineering and Applied Sciences, Cambridge, MA, United States
 
Synergistic carbon and nitrogen emissions from soils treated with different rates of dairy manure indicate nutrient loss through biotic and abiotic controls (1997339)
Anna C Ortiz, USDA-ARS Conservation and Production Laboratory, Livestock and Nutrient Management Research Unit, Bushland, TX, United States, Tera Thompson, USDA-ARS Conservation and Production Laboratory, Livestock and Nutrient Managment, Bushland,TX, United States, William Willis, USDA-ARS Conservation and Production Laboratory, Livestock and Nutrient Mangament, Bushland,TX, United States, Marty Rhoads, West Texas A & M University, Department of Agriculture, Canyon, United States and Jacek Koziel, USDA-ARS Conservation and Production Laboratory, Livestock and Nutrient Managment Research Unit, Bushland, United States
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