I study the role of hydrocarbon fuels in a rapidly decarbonizing economy. I'm a "pick important problems first and figure out the best methods later" kind of researcher, drawing on my expertise in techno-economic assessment, machine learning and applied statistics, econometrics, optimization, and various engineering subdisciplines along the way. My current focus is assessing and demonstrating the value of diverse methane emission sensing and mitigation technologies across the oil and gas value chain in an increasingly data-rich environment.

Honors & Awards

  • Graduate Research Fellow, National Science Foundation (2014-2018)

Boards, Advisory Committees, Professional Organizations

  • Founder and Chair, Methane Emissions Technology Alliance (2019 - Present)
  • Programs Chair, Climate Change AI (2020 - Present)

Professional Education

  • Ph.D., Carnegie Mellon University, Engineering and Public Policy (2019)
  • M.S., Carnegie Mellon University, Machine Learning (2018)
  • Bachelor of Arts, University of California Berkeley (2011)

Stanford Advisors

All Publications

  • Single-blind validation of space-based point-source detection and quantification of onshore methane emissions. Scientific reports Sherwin, E. D., Rutherford, J. S., Chen, Y., Aminfard, S., Kort, E. A., Jackson, R. B., Brandt, A. R. 2023; 13 (1): 3836


    Satellites are increasingly seen as a tool for identifying large greenhouse gas point sources for mitigation, but independent verification of satellite performance is needed for acceptance and use by policy makers and stakeholders. We conduct to our knowledge the first single-blind controlled methane release testing of satellite-based methane emissions detection and quantification, with five independent teams analyzing data from one to five satellites each for this desert-based test. Teams correctly identified 71% of all emissions, ranging from 0.20 [0.19, 0.21] metric tons per hour (t/h) to 7.2 [6.8, 7.6] t/h. Three-quarters (75%) of quantified estimates fell within±50% of the metered value, comparable to airplane-based remote sensing technologies. The relatively wide-area Sentinel-2 and Landsat 8 satellites detected emissions as low as 1.4 [1.3, 1.5, 95% confidence interval] t/h, while GHGSat's targeted system quantified a 0.20 [0.19, 0.21] t/h emission to within 13%. While the fraction of global methane emissions detectable by satellite remains unknown, we estimate that satellite networks could see 19-89% of total oil and natural gas system emissions detected in a recent survey of a high-emitting region.

    View details for DOI 10.1038/s41598-023-30761-2

    View details for PubMedID 36882586

  • Quantifying Regional Methane Emissions in the New Mexico Permian Basin with a Comprehensive Aerial Survey. Environmental science & technology Chen, Y., Sherwin, E. D., Berman, E. S., Jones, B. B., Gordon, M. P., Wetherley, E. B., Kort, E. A., Brandt, A. R. 2022


    Limiting emissions of climate-warming methane from oil and gas (O&G) is a major opportunity for short-term climate benefits. We deploy a basin-wide airborne survey of O&G extraction and transportation activities in the New Mexico Permian Basin, spanning 35 923 km2, 26 292 active wells, and over 15 000 km of natural gas pipelines using an independently validated hyperspectral methane point source detection and quantification system. The airborne survey repeatedly visited over 90% of the active wells in the survey region throughout October 2018 to January 2020, totaling approximately 98 000 well site visits. We estimate total O&G methane emissions in this area at 194 (+72/-68, 95% CI) metric tonnes per hour (t/h), or 9.4% (+3.5%/-3.3%) of gross gas production. 50% of observed emissions come from large emission sources with persistence-averaged emission rates over 308 kg/h. The fact that a large sample size is required to characterize the heavy tail of the distribution emphasizes the importance of capturing low-probability, high-consequence events through basin-wide surveys when estimating regional O&G methane emissions.

    View details for DOI 10.1021/acs.est.1c06458

    View details for PubMedID 35317555

  • Tackling Climate Change with Machine Learning ACM COMPUTING SURVEYS Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., Luccioni, A., Maharaj, T., Sherwin, E. D., Mukkavilli, S., Kording, K. P., Gomes, C. P., Ng, A. Y., Hassabis, D., Platt, J. C., Creutzig, F., Chayes, J., Bengio, Y. 2023; 55 (2)

    View details for DOI 10.1145/3485128

    View details for Web of Science ID 000778458900019

  • Detecting and quantifying methane emissions from oil and gas production: algorithm development with ground-truth calibration based on Sentinel-2 satellite imagery ATMOSPHERIC MEASUREMENT TECHNIQUES Zhang, Z., Sherwin, E. D., Varon, D. J., Brandt, A. R. 2022; 15 (23): 7155-7169
  • Low-Cost Representative Sampling for a Natural Gas Distribution System in Transition. ACS omega Sherwin, E. D., Lever, E., Brandt, A. R. 2022; 7 (48): 43973-43980


    Natural gas distribution systems within municipalities supply a substantial fraction of energy consumed in the United States. As decarbonization of the natural gas system necessitates new modes of operation outside original design purposes, for example, increased hydrogen or biogas blending, it becomes increasingly important to understand in advance how existing infrastructure will respond to these changes. Such an analysis will require detailed information about the existing asset base, such as local soil composition, plastic type, and other characteristics that are not systematically tracked at present or have substantial missing data. Opportunistic sampling, for example, collecting measurements at assets that are already undergoing maintenance, has the potential to substantially reduce the cost of gathering such data but only if the results are representative of the full asset base. To assess prospects for such an approach, we employ a dataset including the entire service line and leak database from a large natural gas distribution utility (∼66,700 km of service pipelines and over 530,000 leaks over decades of observations). This dataset shows that service lines affected by excavation damage produce an approximately random sample of plastic and steel service lines, with similar distributions of component age, operating pressure, and pipeline diameter, as well as a relatively uniform spatial distribution. This means that opportunistic measurements at these locations will produce a first-order estimate of the relative prevalence of key characteristics across the utility's full asset base of service lines. We employ this approach to estimate the plastic type, which is unknown for roughly 80% of plastic service lines in the database. We also find that while 32% of leaks across all components occur in threaded steel junctions, excavation damage accounts for 75% of hazardous grade 1 leaks in plastic service lines and corrosion accounts for 47% in steel service lines. Insights from this sampling approach can thus help natural gas utilities collect the data they need to ensure a safe and reliable transition to a lower-emission system.

    View details for DOI 10.1021/acsomega.2c05314

    View details for PubMedID 36506195

    View details for PubMedCentralID PMC9730304

  • Low-Cost Representative Sampling for a Natural Gas Distribution System in Transition ACS OMEGA Sherwin, E. D., Lever, E., Brandt, A. R. 2022
  • Single-blind determination of methane detection limits and quantification accuracy using aircraft-based LiDAR ELEMENTA-SCIENCE OF THE ANTHROPOCENE Bell, C., Rutherford, J., Brandt, A., Sherwin, E., Vaughn, T., Zimmerle, D. 2022; 10 (1)
  • Estimating global oilfield-specific flaring with uncertainty using a detailed geographic database of oil and gas fields ENVIRONMENTAL RESEARCH LETTERS Zhang, Z., Sherwin, E. D., Brandt, A. R. 2021; 16 (12)
  • Displacing fishmeal with protein derived from stranded methane NATURE SUSTAINABILITY El Abbadi, S. H., Sherwin, E. D., Brandt, A. R., Luby, S. P., Criddle, C. S. 2021
  • Closing the methane gap in US oil and natural gas production emissions inventories. Nature communications Rutherford, J. S., Sherwin, E. D., Ravikumar, A. P., Heath, G. A., Englander, J., Cooley, D., Lyon, D., Omara, M., Langfitt, Q., Brandt, A. R. 2021; 12 (1): 4715


    Methane (CH4) emissions from oil and natural gas (O&NG) systems are an important contributor to greenhouse gas emissions. In the United States, recent synthesis studies of field measurements of CH4 emissions at different spatial scales are ~1.5-2* greater compared to official greenhouse gas inventory (GHGI) estimates, with the production-segment as the dominant contributor to this divergence. Based on an updated synthesis of measurements from component-level field studies, we develop a new inventory-based model for CH4 emissions, for the production-segment only, that agrees within error with recent syntheses of site-level field studies and allows for isolation of equipment-level contributions. We find that unintentional emissions from liquid storage tanks and other equipment leaks are the largest contributors to divergence with the GHGI. If our proposed method were adopted in the United States and other jurisdictions, inventory estimates could better guide CH4 mitigation policy priorities.

    View details for DOI 10.1038/s41467-021-25017-4

    View details for PubMedID 34354066

  • Electrofuel Synthesis from Variable Renewable Electricity: An Optimization-Based Techno-Economic Analysis. Environmental science & technology Sherwin, E. D. 2021


    Sectors such as aviation may require low-carbon liquid fuels to dramatically reduce emissions. This analysis characterizes the economic viability of electrofuels, synthesized from CO2 from direct air capture (DAC) and hydrogen from electrolysis of water, powered primarily by solar or wind electricity. This optimization-based techno-economic analysis suggests that using today's technology, hydrocarbon electrofuels would cost upward of $4/liter of gasoline equivalent (lge), potentially falling to $1.7-1.8/lge in the next decade and <$1/lge by 2050. Only in the latter case are electrofuels potentially less costly than using petroleum fuels offset with DAC with sequestration. Achieving low-end electrofuel costs is contingent on substantial reductions in the capital cost of DAC, electrolyzers, and renewable electricity generation. However, the system also requires sufficient operational flexibility to efficiently power this capital-intensive equipment on variable electricity. Such forms of flexibility include various types of storage, supplementary natural gas and grid electricity interconnections (penalized with a steep carbon price), curtailment, and the ability to modestly adjust fuel synthesis and DAC operating levels over time scales of several hours to days.

    View details for DOI 10.1021/acs.est.0c07955

    View details for PubMedID 33983018

  • Single-blind test of airplane-based hyperspectral methane detection via controlled releases ELEMENTA-SCIENCE OF THE ANTHROPOCENE Sherwin, E. D., Chen, Y., Ravikumar, A. P., Brandt, A. R. 2021; 9 (1)
  • Characterizing the association between low-income electric subsidies and the intra-day timing of electricity consumption ENVIRONMENTAL RESEARCH LETTERS Sherwin, E. D., Azevedo, I. L. 2020; 15 (9)
  • Estimation of the year-on-year volatility and the unpredictability of the United States energy system NATURE ENERGY Sherwin, E. D., Henrion, M., Azevedo, I. L. 2018; 3 (4): 341–46