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Sudhanshu Pandey

Photo of Sudhanshu Pandey

Address:

4800 Oak Grove Drive

Pasadena, CA 91109

Curriculum Vitae:

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Website:

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Member of:

Tropospheric Composition

Scientist

Biography

My research advances our understanding of atmospheric trace gases and the carbon cycle. I employ satellite remote sensing and sophisticated numerical models to quantify emissions, characterize atmospheric transport, and investigate chemical variations in atmospheric concentrations. I have extensive experience developing and applying observational and emission‐quantification techniques.

Education

  • Ph.D., Physics, Utrecht University (2017)
  • BS-MS, Earth Sciences, Indian Institute of Science Education & Research, Kolkata, India (2012)

Professional Experience

  • Scientist - NASA Jet Propulsion Laboratory (2022 - Present)
  • Scientist, SRON Netherlands Institute for Space Research, Leiden, The Netherlands. 2016-2022.

Community Service

  • Reviewer for scientific journals.
  • Reviewer for research proposals.
  • Hosted meetings at conferences.
  • Mentoring students.

Research Interests

  • Remote Sensing: Observing atmospheric gases with satellite-based instruments.
  • Plume Detection: Detecting and quantifying emissions from specific sources using satellite tools.
  • Atmospheric Transport Modeling: Investigating trace-gas transport processes in the atmosphere.
  • Data Assimilation: Integrating observational data into models using Bayesian statistical methods.
  • Machine Learning: Applying convolutional neural networks to identify and quantify key emission sources.
  • Theoretical Research: Advancing the fundamental understanding of trace-gas observations and modeling within the carbon-cycle science.

Selected Publications

  1. Ke, X., et al. (2025). Low-latency global carbon budget reveals a continuous decline of the land carbon sink during the 2023/24 El Niño event. arXiv preprint. https://doi.org/10.48550/arXiv.2504.09189
  2. Pandey, S., et al. (2025). Relating Multi‐Scale Plume Detection and Area Estimates of Methane Emissions: A Theoretical and Empirical Analysis. Environmental Science & Technology, 59(16), 7931–7947. https://doi.org/10.1021/acs.est.4c07415
  3. Albuhaisi, A., et al. (2025). Integrating Satellite Observations and Hydrological Models to Unravel Large TROPOMI Methane Emissions in South Sudan Wetlands. Remote Sensing, 16, 4744. https://doi.org/10.3390/rs16244744
  4. Pandey, S., et al. (2024). Toward low‐latency estimation of atmospheric CO₂ growth rates using satellite observations: Evaluating sampling errors of satellite and in situ observing approaches. AGU Advances, 5, e2023AV001145.
  5. Pandey, S., et al. (2024). Quantitative Evidence of Improved Estimates of Earth’s Carbon Cycle Components. Under review at Nature Communications. https://doi.org/10.22541/essoar.172405915.56306923/v1
  6. Varon, D. J., et al. (2024). Quantifying NOx point sources with Landsat and Sentinel-2 satellite observations of NO2 plumes, Proc. Natl. Acad. Sci., 121, e2317077121, https://doi.org/10.1073/pnas.2317077121
  7. Byrne, B., et al. (2024). Unprecedented Canadian forest carbon emissions during 2023. Accepted in Nature, preprint DOI: 10.21203/rs.3.rs-3684305/v1
  8. Sadavarte, P., et al. (2024). Rebuttal to Correspondence on “Methane Emissions from Superemitting Coal Mines in Australia Quantified Using TROPOMI Satellite Observations.” Environmental Science & Technology, 58, 5629–5630.
  9. Pandey, S., et al. (2023). Daily detection and quantification of methane leaks using Sentinel-3: A tiered satellite observation approach with Sentinel-2 and Sentinel-5P. Remote Sensing of Environment, 296, 113716.
  10. Schuit, B. J., et al. (2023). Automated detection and monitoring of methane super-emitters using satellite data. Atmospheric Chemistry and Physics, 23, 9071–9098.
  11. Worden, J. R., et al. (2023). Verifying methane inventories and trends with atmospheric methane data. AGU Advances, 4.
  12. Naus, S., et al. (2023). Assessing the relative importance of satellite-detected methane superemitters in quantifying total emissions for oil and gas production areas in Algeria. Environmental Science & Technology.
  13. Varon, D. J., et al. (2023). Continuous weekly monitoring of methane emissions from the Permian Basin by inversion of TROPOMI satellite observations. Atmospheric Chemistry and Physics, 23, 7503–7520.
  14. Maasakkers, J. D., et al. (2022). Reconstructing and quantifying methane emissions from the full duration of a 38-day natural gas well blowout using space-based observations. Remote Sensing of Environment, 270, 112755.
  15. Maasakkers, J. D., et al. (2022). Using satellites to uncover large methane emissions from landfills. Science Advances, 8, 1–9.
  16. Sadavarte, P., et al. (2022). A high-resolution gridded inventory of coal mine methane emissions for India and Australia. Elementa, 10, 1–14.
  17. Pandey, S., et al. (2022). Order of magnitude wall time improvement of variational methane inversions by physical parallelization: A demonstration using TM5-4DVAR. Geoscientific Model Development, 15, 4555–4567.
  18. Pandey, S., et al. (2021). Using satellite data to identify the methane emission controls of South Sudan’s wetlands. Biogeosciences, 18, 557–572.
  19. Cusworth, D. H., et al. (2021). Multi‐satellite imaging of a gas well blowout enables quantification of total methane emissions. Geophysical Research Letters, 48(2), 1–9.
  20. Sadavarte, P., et al. (2021). Methane emissions from super‐emitting coal mines in Australia quantified using TROPOMI satellite observations. Environmental Science & Technology, 55(24), 16573–16580.
  21. Mazzini, A., et al. (2021). Relevant methane emission to the atmosphere from a geological gas manifestation. Scientific Reports.
  22. Zavala‐Araiza, D., et al. (2021). A tale of two regions: methane emissions from oil and gas production in offshore/onshore Mexico. Environmental Research Letters.
  23. Ma, S., et al. (2021). Satellite constraints on the latitudinal distribution and temperature sensitivity of wetland methane emissions. AGU Advances, 2(3), 1–12.
  24. Zhang, Y., et al. (2020). Quantifying methane emissions from the largest oil‐producing basin in the United States from space. Science Advances.
  25. Pandey, S., et al. (2019). Satellite observations reveal extreme methane leakage from a natural gas well blowout. Proceedings of the National Academy of Sciences, 116(52), 26376–26381.
  26. Ganesan, A. L., et al. (2019). Advancing scientific understanding of the global methane budget in support of the Paris Agreement. Global Biogeochemical Cycles, 33(12), 1475–1512.
  27. Varon, D. J., et al. (2019). Satellite discovery of anomalously large methane point sources from oil/gas production. Geophysical Research Letters.
  28. Dekker, I. N., et al. (2019). What caused the extreme CO concentrations during the 2017 high pollution episode in India? Atmospheric Chemistry and Physics, 19, 3433–3445.
  29. Borsdorff, T., et al. (2019). Carbon monoxide air‐pollution on sub‐city scales and along arterial roads detected by the Tropospheric Monitoring Instrument. Atmospheric Chemistry and Physics, 19, 3579–3588.
  30. Naus, S., et al. (2019). Constraints and biases in a tropospheric two‐box model of OH. Atmospheric Chemistry and Physics, 19(1), 407–424.
  31. Nechita‐Banda, N., et al. (2018). Monitoring emissions from the 2015 Indonesian fires using CO satellite data. Philosophical Transactions of the Royal Society B: Biological Sciences, 373(1760), 20170307.
  32. Bruhwiler, L. M., et al. (2017). US CH₄ emissions from oil and gas production: Have recent large increases been detected? Journal of Geophysical Research: Atmospheres, 122(7), 4070–4083.
  33. Worden, J. R., et al. (2017). Reduced biomass burning emissions reconcile conflicting estimates of the post‐2006 atmospheric methane budget. Nature Communications, 8, 2227.
  34. Pandey, S., et al. (2017). Enhanced methane emissions from tropical wetlands during the 2011 La Niña. Scientific Reports, 7.
  35. Pandey, S., et al. (2016). Inverse modeling of GOSAT‐retrieved ratios of total column CH₄ and CO₂ for 2009 and 2010. Atmospheric Chemistry and Physics, 16(8), 5043–5062.
  36. Pandey, S., et al. (2015). On the use of satellite‐derived CH₄: CO₂ columns in a joint inversion of CH₄ and CO₂ fluxes. Atmospheric Chemistry and Physics, 15(15), 8615–8629.










Projects

OCO-2 - Orbiting Carbon Observatory
CMS Flux (Carbon Monitoring System Flux)
OCO-3 - Orbiting Carbon Observatory 3