
Evan Sherwin
Postdoctoral Scholar, Energy Resources Engineering
Bio
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
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Graduate Research Fellow, National Science Foundation (2014-2018)
Boards, Advisory Committees, Professional Organizations
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Founder and Chair, Methane Emissions Technology Alliance (2019 - Present)
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Programs Chair, Climate Change AI (2020 - Present)
Professional Education
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Ph.D., Carnegie Mellon University, Engineering and Public Policy (2019)
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M.S., Carnegie Mellon University, Machine Learning (2018)
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Bachelor of Arts, University of California Berkeley (2011)
All Publications
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Quantifying Regional Methane Emissions in the New Mexico Permian Basin with a Comprehensive Aerial Survey.
Environmental science & technology
2022
Abstract
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
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Tackling Climate Change with Machine Learning
ACM COMPUTING SURVEYS
2023; 55 (2)
View details for DOI 10.1145/3485128
View details for Web of Science ID 000778458900019
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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
2022; 15 (23): 7155-7169
View details for DOI 10.5194/amt-15-7155-2022
View details for Web of Science ID 000897864900001
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Low-Cost Representative Sampling for a Natural Gas Distribution System in Transition
ACS OMEGA
2022
View details for DOI 10.1021/acsomega.2c05314
View details for Web of Science ID 000890922100001
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Estimating global oilfield-specific flaring with uncertainty using a detailed geographic database of oil and gas fields
ENVIRONMENTAL RESEARCH LETTERS
2021; 16 (12)
View details for DOI 10.1088/1748-9326/ac3956
View details for Web of Science ID 000723862900001
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Displacing fishmeal with protein derived from stranded methane
NATURE SUSTAINABILITY
2021
View details for DOI 10.1038/s41893-021-00796-2
View details for Web of Science ID 000721454400003
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Closing the methane gap in US oil and natural gas production emissions inventories.
Nature communications
2021; 12 (1): 4715
Abstract
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
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Electrofuel Synthesis from Variable Renewable Electricity: An Optimization-Based Techno-Economic Analysis.
Environmental science & technology
2021
Abstract
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
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Single-blind test of airplane-based hyperspectral methane detection via controlled releases
ELEMENTA-SCIENCE OF THE ANTHROPOCENE
2021; 9 (1)
View details for DOI 10.1525/elementa.2021.00063
View details for Web of Science ID 000632683000003
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Characterizing the association between low-income electric subsidies and the intra-day timing of electricity consumption
ENVIRONMENTAL RESEARCH LETTERS
2020; 15 (9)
View details for DOI 10.1088/1748-9326/aba030
View details for Web of Science ID 000570724400001
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Estimation of the year-on-year volatility and the unpredictability of the United States energy system
NATURE ENERGY
2018; 3 (4): 341–46
View details for DOI 10.1038/s41560-018-0121-4
View details for Web of Science ID 000430252700020