Adam Brandt
Professor of Energy Science Engineering
Energy Science & Engineering
Bio
Research:
I am interested in reducing the environmental impacts of energy systems. More specifically, I focus on understanding, measuring, and reducing greenhouse gas (GHG) emissions from fossil energy sources. Reducing GHG emissions from fossil fuels is important because fossil energy sources will continue to be key components of our energy system for decades to come.
My research in this area uses the tools of life cycle assessment (LCA) and process optimization to measure and estimate impacts from technologies at broad scales (LCA) and to help reduce these impacts (optimization). Applications include reducing GHG emissions from transportation energy supply and from power systems through CCS.
Teaching:
Through my teaching, I aim to help train the next generation of energy professionals to: optimize energy systems so as to improve their efficiency; rigorously account for the environmental impacts of energy sources; and think critically about systems-scale phenomena in energy production and consumption
Academic Appointments
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Professor, Energy Science & Engineering
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Affiliate, Precourt Institute for Energy
Administrative Appointments
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Associate Professor, Department of Energy Science & Engineering, Stanford University (2019 - 2024)
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Assistant Professor, Department of Energy Resources Engineering, Stanford University (2012 - 2018)
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Acting Assistant Professor, Department of Energy Resources Engineering, Stanford University (2009 - 2012)
Honors & Awards
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Student paper award, United States Association for Energy Economics (2006)
Boards, Advisory Committees, Professional Organizations
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Science Advisory Panel, Methane Reconciliation Project, National Renewable Energy Laboratory (2015 - Present)
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Technical steering committee, Independent Review of Well Stimulation, California Council on Science and Technology. (2013 - Present)
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Organizing committee, Connecting the Dots: The Energy, Water, Food, Climate Nexus (2013 - 2014)
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Selection committee, Stanford Interdisciplinary Graduate Fellowship (2012 - 2014)
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Team leader, Technical review of natural gas leakage, NOVIM (2012 - 2013)
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Invited speaker:, CERA Week 2012, Houston TX, March 6th, 2012 (2012 - 2012)
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Invited speaker: EES seminar. November 28th, 2012, University of Calgary, Institute for sustainable energy, environment and economy (ISEEE) (2012 - 2012)
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Technical advisor, California Environmental Protection Agency, Air Resources Board (CARB) - Low Carbon Fuel Standard regulatory proceedings (2011 - Present)
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Expert testimony, European Commission, Directorate General - Climate. May 27, 2011. (2011 - 2011)
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Invited speaker, Workshop on Low Carbon Fuel Standards, Victoria, BC, October 12th-13th 2011 (2011 - 2011)
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Invited speaker, CRC Workshop on life cycle analysis of biofuels. Argonne National Laboratory, October 17th, 2011 (2011 - 2011)
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Invited speaker, Center for European Policy Studies, Brussels, Belgium. March 21st, 2011 (2011 - 2011)
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Technical advisor, European Union, DG Climate - Fuel Quality Directive regulatory proceedings (2010 - 2011)
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Invited Speaker, SLAC National Accelerator Laboratory, February 1st, 2010 (2010 - 2010)
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Search committee, GCEP post-doctoral scholars (2010 - 2010)
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Invited Speaker, Energy, Environment and Society Speaker Series, Humboldt State University, CA, April 2009 (2009 - 2009)
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Invited Speaker, Stanford University, Stanford Energy Seminar, September 23rd, 2009 (2009 - 2009)
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Invited Speaker, Department of Energy Resources Engineering, Stanford University, CA, December 2007 (2007 - 2007)
Professional Education
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Ph.D., University of California, Berkeley, Energy and Resources (2008)
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M.S., University of California, Berkeley, Energy and Resources (2005)
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B.S., University of California, Santa Barbara, Environmental Studies, emphasis Physics (2003)
Current Research and Scholarly Interests
Research:
I am interested in reducing the environmental impacts of energy systems. More specifically, I focus on understanding, measuring, and reducing greenhouse gas (GHG) emissions from fossil energy sources. Reducing GHG emissions from fossil fuels is important because fossil energy sources will continue to be key components of our energy system for decades to come.
My research in this area uses the tools of life cycle assessment (LCA) and process optimization to measure and estimate impacts from technologies at broad scales (LCA) and to help reduce these impacts (optimization). Applications include reducing GHG emissions from transportation energy supply and from power systems through CCS.
Teaching:
Through my teaching, I aim to help train the next generation of energy professionals to: optimize energy systems so as to improve their efficiency; rigorously account for the environmental impacts of energy sources; and think critically about systems-scale phenomena in energy production and consumption
2024-25 Courses
- ESE Master's Graduate Seminar
ENERGY 351 (Aut) - ESE PhD Graduate Seminar
ENERGY 352 (Aut) - Energy Systems Fundamentals
ENERGY 201A (Aut) - Fundamentals of Energy Processes
EE 293B, ENERGY 201B (Win) - Optimization of Energy Systems
ENERGY 191, ENERGY 291 (Spr) -
Independent Studies (11)
- Advanced Research Work in Energy Science and Engineering
ENERGY 360 (Aut, Win, Spr, Sum) - Directed Reading in Environment and Resources
ENVRES 398 (Aut, Win, Spr, Sum) - Directed Research in Environment and Resources
ENVRES 399 (Aut, Win, Spr, Sum) - Doctoral Degree Research in Energy Science and Engineering
ENERGY 363 (Aut, Win, Spr, Sum) - Doctoral Degree Teaching Requirement
ENERGY 358 (Aut, Win, Spr) - Graduate Directed Reading
ENERGY 300 (Aut, Win, Spr, Sum) - Master's Degree Research in Energy Science and Engineering
ENERGY 361 (Aut, Win, Spr, Sum) - Special Topics in Energy Science and Engineering
ENERGY 273 (Aut, Win, Spr, Sum) - Undergraduate Report on Energy Industry Training
ENERGY 155 (Aut, Win, Spr, Sum) - Undergraduate Research Problems
ENERGY 193 (Aut, Win, Spr, Sum) - Undergraduate Teaching Experience
ENERGY 192 (Aut, Win, Spr, Sum)
- Advanced Research Work in Energy Science and Engineering
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Prior Year Courses
2023-24 Courses
- Energy Systems Fundamentals
ENERGY 201A (Aut) - Fundamentals of Energy Processes
EE 293B, ENERGY 201B (Win) - Optimization of Energy Systems
ENERGY 191, ENERGY 291 (Spr)
2022-23 Courses
- Fundamentals of Energy Processes
EE 293B, ENERGY 293B (Win) - Optimization of Energy Systems
ENERGY 191, ENERGY 291 (Spr)
2021-22 Courses
- Fundamentals of Energy Processes
EE 293B, ENERGY 293B (Win) - Optimization of Energy Systems
ENERGY 191, ENERGY 291 (Spr)
- Energy Systems Fundamentals
Stanford Advisees
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Doctoral Dissertation Reader (AC)
Mohammad Aljubran, Kelsey Foster -
Master's Program Advisor
Audrey McManemin -
Doctoral (Program)
Philippine Burdeau, Richard Chen, Yaqi Fan, Mathis Heyer, Josh Romo, Dimitri Saad, Spencer Zhang
All Publications
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US oil and gas system emissions from nearly one million aerial site measurements.
Nature
2024; 627 (8003): 328-334
Abstract
As airborne methane surveys of oil and gas systems continue to discover large emissions that are missing from official estimates1-4, the true scope of methane emissions from energy production has yet to be quantified. We integrate approximately one million aerial site measurements into regional emissions inventories for six regions in the USA, comprising 52% of onshore oil and 29% of gas production over 15aerial campaigns. We construct complete emissions distributions for each, employing empirically grounded simulations to estimate small emissions. Total estimated emissions range from 0.75% (95% confidence interval (CI)0.65%, 0.84%) of covered natural gas production in a high-productivity, gas-rich region to 9.63% (95% CI 9.04%, 10.39%) in a rapidly expanding, oil-focused region. The six-region weighted average is 2.95% (95% CI 2.79%, 3.14%), or roughly three times the national government inventory estimate5. Only 0.05-1.66% of well sites contribute the majority (50-79%) of well site emissions in 11 outof 15surveys. Ancillary midstream facilities, including pipelines, contribute 18-57% of estimated regional emissions, similarly concentrated in a small number of point sources. Together, the emissions quantified here represent an annual loss of roughly US$1billion in commercial gas value and a US$9.3billion annual social cost6. Repeated, comprehensive, regional remote-sensing surveys offer a path to detect these low-frequency, high-consequence emissions for rapid mitigation, incorporation into official emissions inventories and a clear-eyed assessment of the most effective emission-finding technologies for a given region.
View details for DOI 10.1038/s41586-024-07117-5
View details for PubMedID 38480966
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Large-Scale Controlled Experiment Demonstrates Effectiveness of Methane Leak Detection and Repair Programs at Oil and Gas Facilities.
Environmental science & technology
2024
Abstract
Most jurisdictions around the globe use leak detection and repair (LDAR) programs to find and fix methane leaks from oil and gas operations. In this work, we empirically evaluate the efficacy of LDAR programs using a large-scale, bottom-up, randomized controlled field experiment across ∼200 oil and gas sites in Red Deer, Canada. We find that tanks are the single largest source of emissions, contributing to nearly 60% of the total emissions. The average number of leaks at treatment sites that underwent repair reduced by ∼50% compared to the control sites. Although control sites did not see a reduction in the number of leaks, emissions reduced by approximately 36%, suggesting potential impact of routine maintenance activities to find and fix large leaks. By tracking tags on leaking equipment over time, we find a high degree of persistence; leaks that are repaired remain fixed in follow-up surveys, while non-repaired leaks remain emitting at a similar rate, suggesting that any increase in observed leak emissions following LDAR surveys are likely from new leaks. Our results show that a focus on equipment and sites that are prone to high emissions, such as tanks and oil sites, is key to cost-effective mitigation.
View details for DOI 10.1021/acs.est.3c09147
View details for PubMedID 38314689
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Climate impacts of digital use supply chains
Environmental Research: Climate
2024; 3 (1)
View details for DOI 10.1088/2752-5295/ad22eb
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Measuring Carbon Dioxide Emissions From Liquefied Natural Gas (LNG) Terminals With Imaging Spectroscopy
GEOPHYSICAL RESEARCH LETTERS
2023; 50 (23)
View details for DOI 10.1029/2023GL105755
View details for Web of Science ID 001110949000001
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Methane point source quantification using MethaneAIR: a new airborne imaging spectrometer
ATMOSPHERIC MEASUREMENT TECHNIQUES
2023; 16 (23): 5771-5785
View details for DOI 10.5194/amt-16-5771-2023
View details for Web of Science ID 001168782100001
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A cost comparison of various hourly-reliable and net-zero hydrogen production pathways in the United States.
Nature communications
2023; 14 (1): 7391
Abstract
Hydrogen (H2) as an energy carrier may play a role in various hard-to-abate subsectors, but to maximize emission reductions, supplied hydrogen must be reliable, low-emission, and low-cost. Here, we build a model that enables direct comparison of the cost of producing net-zero, hourly-reliable hydrogen from various pathways. To reach net-zero targets, we assume upstream and residual facility emissions are mitigated using negative emission technologies. For the United States (California, Texas, and New York), model results indicate next-decade hybrid electricity-based solutions are lower cost ($2.02-$2.88/kg) than fossil-based pathways with natural gas leakage greater than 4% ($2.73-$5.94/kg). These results also apply to regions outside of the U.S. with a similar climate and electric grid. However, when omitting the net-zero emission constraint and considering the U.S. regulatory environment, electricity-based production only achieves cost-competitiveness with fossil-based pathways if embodied emissions of electricity inputs are not counted under U.S. Tax Code Section 45V guidance.
View details for DOI 10.1038/s41467-023-43137-x
View details for PubMedID 37968304
View details for PubMedCentralID PMC10651927
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Open-source sky image datasets for solar forecasting with deep learning: A comprehensive survey
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
2024; 189
View details for DOI 10.1016/j.rser.2023.113977
View details for Web of Science ID 001110252500001
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Greenhouse gas intensity of natural hydrogen produced from subsurface geologic accumulations
JOULE
2023; 7 (8): 1818-1831
View details for DOI 10.1016/j.joule.2023.07.001
View details for Web of Science ID 001062967500001
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Excess methane emissions from shallow water platforms elevate the carbon intensity of US Gulf of Mexico oil and gas production.
Proceedings of the National Academy of Sciences of the United States of America
2023; 120 (15): e2215275120
Abstract
The Gulf of Mexico is the largest offshore fossil fuel production basin in the United States. Decisions on expanding production in the region legally depend on assessments of the climate impact of new growth. Here, we collect airborne observations and combine them with previous surveys and inventories to estimate the climate impact of current field operations. We evaluate all major on-site greenhouse gas emissions, carbon dioxide (CO2) from combustion, and methane from losses and venting. Using these findings, we estimate the climate impact per unit of energy of produced oil and gas (the carbon intensity). We find high methane emissions (0.60 Tg/y [0.41 to 0.81, 95% confidence interval]) exceeding inventories. This elevates the average CI of the basin to 5.3 g CO2e/MJ [4.1 to 6.7] (100-y horizon) over twice the inventories. The CI across the Gulf varies, with deep water production exhibiting a low CI dominated by combustion emissions (1.1 g CO2e/MJ), while shallow federal and state waters exhibit an extraordinarily high CI (16 and 43 g CO2e/MJ) primarily driven by methane emissions from central hub facilities (intermediaries for gathering and processing). This shows that production in shallow waters, as currently operated, has outsized climate impact. To mitigate these climate impacts, methane emissions in shallow waters must be addressed through efficient flaring instead of venting and repair, refurbishment, or abandonment of poorly maintained infrastructure. We demonstrate an approach to evaluate the CI of fossil fuel production using observations, considering all direct production emissions while allocating to all fossil products.
View details for DOI 10.1073/pnas.2215275120
View details for PubMedID 37011214
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SKIPP'D: A SKy Images and Photovoltaic Power Generation Dataset for short-term solar forecasting
SOLAR ENERGY
2023; 255: 171-179
View details for DOI 10.1016/j.solener.2023.03.043
View details for Web of Science ID 000971081800001
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Single-blind validation of space-based point-source detection and quantification of onshore methane emissions.
Scientific reports
2023; 13 (1): 3836
Abstract
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
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Understanding variability in petroleum jet fuel life cycle greenhouse gas emissions to inform aviation decarbonization.
Nature communications
2022; 13 (1): 7853
Abstract
A pressing challenge facing the aviation industry is to aggressively reduce greenhouse gas emissions in the face of increasing demand for aviation fuels. Climate goals such as carbon-neutral growth from 2020 onwards require continuous improvements in technology, operations, infrastructure, and most importantly, reductions in aviation fuel life cycle emissions. The Carbon Offsetting Scheme for International Aviation of the International Civil Aviation Organization provides a global market-based measure to group all possible emissions reduction measures into a joint program. Using a bottom-up, engineering-based modeling approach, this study provides the first estimates of life cycle greenhouse gas emissions from petroleum jet fuel on regional and global scales. Here we show that not all petroleum jet fuels are the same as the country-level life cycle emissions of petroleum jet fuels range from 81.1 to 94.8 gCO2e MJ-1, with a global volume-weighted average of 88.7 gCO2e MJ-1. These findings provide a high-resolution baseline against which sustainable aviation fuel and other emissions reduction opportunities can be prioritized to achieve greater emissions reductions faster.
View details for DOI 10.1038/s41467-022-35392-1
View details for PubMedID 36543764
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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; 7 (48): 43973-43980
Abstract
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
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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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Single-blind determination of methane detection limits and quantification accuracy using aircraft-based LiDAR
ELEMENTA-SCIENCE OF THE ANTHROPOCENE
2022; 10 (1)
View details for DOI 10.1525/elementa.2022.00080
View details for Web of Science ID 000921804200001
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Methane Emissions from Natural Gas Gathering Pipelines in the Permian Basin.
Environmental science & technology letters
2022; 9 (11): 969-974
Abstract
The rapid reduction of methane emissions, especially from oil and gas (O&G) operations, is a critical part of slowing global warming. However, few studies have attempted to specifically characterize emissions from natural gas gathering pipelines, which tend to be more difficult to monitor on the ground than other forms of O&G infrastructure. In this study, we use methane emission measurements collected from four recent aerial campaigns in the Permian Basin, the most prolific O&G basin in the United States, to estimate a methane emission factor for gathering lines. From each campaign, we calculate an emission factor between 2.7 (+1.9/-1.8, 95% confidence interval) and 10.0 (+6.4/-6.2) Mg of CH4 year-1 km-1, 14-52 times higher than the U.S. Environmental Protection Agency's national estimate for gathering lines and 4-13 times higher than the highest estimate derived from a published ground-based survey of gathering lines. Using Monte Carlo techniques, we demonstrate that aerial data collection allows for a greater sample size than ground-based data collection and therefore more comprehensive identification of emission sources that comprise the heavy tail of methane emissions distributions. Our results suggest that pipeline emissions are underestimated in current inventories and highlight the importance of a large sample size when calculating basinwide pipeline emission factors.
View details for DOI 10.1021/acs.estlett.2c00380
View details for PubMedID 36398313
View details for PubMedCentralID PMC9648336
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Methane Emissions from Natural Gas Gathering Pipelines in the Permian Basin
ENVIRONMENTAL SCIENCE & TECHNOLOGY LETTERS
2022
View details for DOI 10.1021/acs.estlett.2c00380
View details for Web of Science ID 000867543300001
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Wind data introduce error in time-series reduction for capacity expansion modelling
ENERGY
2022; 256
View details for DOI 10.1016/j.energy.2022.124467
View details for Web of Science ID 000834159800008
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Inefficient and unlit natural gas flares both emit large quantities of methane.
Science (New York, N.Y.)
2022; 377 (6614): 1566-1571
Abstract
Flaring is widely used by the fossil fuel industry to dispose of natural gas. Industry and governments generally assume that flares remain lit and destroy methane, the predominant component of natural gas, with 98% efficiency. Neither assumption, however, is based on real-world observations. We calculate flare efficiency using airborne sampling across three basins responsible for >80% of US flaring and combine these observations with unlit flare prevalence surveys. We find that both unlit flares and inefficient combustion contribute comparably to ineffective methane destruction, with flares effectively destroying only 91.1% (90.2, 91.8; 95% confidence interval) of methane. This represents a fivefold increase in methane emissions above present assumptions and constitutes 4 to 10% of total US oil and gas methane emissions, highlighting a previously underappreciated methane source and mitigation opportunity.
View details for DOI 10.1126/science.abq0385
View details for PubMedID 36173866
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Time-series aggregation for the optimization of energy systems: Goals, challenges, approaches, and opportunities
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
2022; 157
View details for DOI 10.1016/j.rser.2021.111984
View details for Web of Science ID 000784449300002
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Functionality-based life cycle assessment framework: An information and communication technologies (ICT) product case study
JOURNAL OF INDUSTRIAL ECOLOGY
2022
View details for DOI 10.1111/jiec.13240
View details for Web of Science ID 000755456800001
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VideoGasNet: Deep learning for natural gas methane leak classification using an infrared camera
ENERGY
2022; 238
View details for DOI 10.1016/j.energy.2021.121516
View details for Web of Science ID 000709410700002
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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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Designing reliable future energy systems by iteratively including extreme periods in time-series aggregation
APPLIED ENERGY
2021; 304
View details for DOI 10.1016/j.apenergy.2021.117696
View details for Web of Science ID 000701874500001
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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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Carbon implications of marginal oils from market-derived demand shocks.
Nature
2021; 599 (7883): 80-84
Abstract
Expanded use of novel oil extraction technologies has increased the variability of petroleum resources and diversified the carbon footprint of theglobal oil supply1. Past life-cycle assessment (LCA) studies overlooked upstream emission heterogeneity by assuming that a decline in oil demand will displace average crude oil2. We explore the life-cycle greenhouse gas emissions impacts of marginal crude sources, identifying the upstream carbon intensity (CI) of the producers most sensitive to an oil demand decline (for example, due to a shift to alternative vehicles). We link econometric models of production profitability of 1,933 oilfields (~90% of the 2015 world supply) with their production CI. Then, we examine their response to a decline in demand under three oil market structures. According to our estimates, small demand shocks have different upstream CI implications than large shocks. Irrespective of the market structure, small shocks (-2.5% demand) displace mostly heavy crudes with ~25-54% higher CI than that of theglobal average. However, this imbalance diminishes as the shocks become bigger and if producers with market power coordinate their response to a demand decline. The carbon emissions benefits of reduction in oil demand are systematically dependent on the magnitude of demand drop and the global oil market structure.
View details for DOI 10.1038/s41586-021-03932-2
View details for PubMedID 34732864
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Computational optimization of solar thermal generation with energy storage
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
2021; 47
View details for DOI 10.1016/j.seta.2021.101342
View details for Web of Science ID 000729901900005
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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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Greenhouse Gas Emissions of Western Canadian Natural Gas: Proposed Emissions Tracking for Life Cycle Modeling.
Environmental science & technology
2021
Abstract
Natural gas (NG) produced in Western Canada is a major and growing source of Canada's energy and greenhouse gas (GHG) emissions portfolio. Despite recent progress, there is still only limited understanding of the sources and drivers of Western Canadian greenhouse gas (GHG) emissions. We conduct a case study of a production facility based on Seven Generation Energy Ltd.'s Western Canadian operations and an upstream NG emissions intensity model. The case study upstream emissions intensity is estimated to be 3.1-4.0 gCO2e/MJ NG compared to current best estimates of British Columbia (BC) emissions intensities of 6.2-12 gCO2e/MJ NG and a US average estimate of 15 gCO2e/MJ. The analysis reveals that compared to US studies, public GHG emissions data for Western Canada is insufficient as current public data satisfies only 50% of typical LCA model inputs. Company provided data closes most of these gaps (80% of the model inputs). We recommend more detailed data collection and presentation of government reported data such as a breakdown of vented and fugitive methane emissions by source. We propose a data collection template to facilitate improved GHG emissions intensity estimates and insight about potential mitigation strategies.
View details for DOI 10.1021/acs.est.0c06353
View details for PubMedID 34254796
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Blow wind blow: Capital deployment in variable energy systems
ENERGY
2021; 224
View details for DOI 10.1016/j.energy.2021.120198
View details for Web of Science ID 000640929800015
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Concurrent variation in oil and gas methane emissions and oil price during the COVID-19 pandemic
ATMOSPHERIC CHEMISTRY AND PHYSICS
2021; 21 (9): 6605–26
View details for DOI 10.5194/acp-21-6605-2021
View details for Web of Science ID 000647352500002
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Orphaned oil and gas well stimulus-Maximizing economic and environmental benefits
ELEMENTA-SCIENCE OF THE ANTHROPOCENE
2021; 9 (1)
View details for DOI 10.1525/elementa.2020.20.00161
View details for Web of Science ID 000667015100001
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Improving robustness of LCA results through stakeholder engagement: A case study of emerging oil sands technologies
JOURNAL OF CLEANER PRODUCTION
2021; 281
View details for DOI 10.1016/j.jclepro.2020.125277
View details for Web of Science ID 000609019300014
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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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Resampling and data augmentation for short-term PV output prediction based on an imbalanced sky images dataset using convolutional neural networks
Solar Energy
2021; 224
View details for DOI 10.1016/j.solener.2021.05.095
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Optimal design of an electricity-intensive industrial facility subject to electricity price uncertainty: Stochastic optimization and scenario reduction
CHEMICAL ENGINEERING RESEARCH & DESIGN
2020; 163: 204–16
View details for DOI 10.1016/j.cherd.2020.08.022
View details for Web of Science ID 000582383400019
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Extreme events in time series aggregation: A case study for optimal residential energy supply systems
APPLIED ENERGY
2020; 275
View details for DOI 10.1016/j.apenergy.2020.115223
View details for Web of Science ID 000565604700001
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Optimization-based technoeconomic analysis of molten-media methane pyrolysis for reducing industrial sector CO(2)emissions
SUSTAINABLE ENERGY & FUELS
2020; 4 (9): 4598–4613
View details for DOI 10.1039/d0se00427h
View details for Web of Science ID 000563991800021
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Sensor Placement Optimization Software Applied to Site-Scale Methane-Emissions Monitoring
JOURNAL OF ENVIRONMENTAL ENGINEERING
2020; 146 (7)
View details for DOI 10.1061/(ASCE)EE.1943-7870.0001737
View details for Web of Science ID 000536128900003
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PV power output prediction from sky images using convolutional neural network: The comparison of sky-condition-specific sub-models and an end-to-end model
JOURNAL OF RENEWABLE AND SUSTAINABLE ENERGY
2020; 12 (4)
View details for DOI 10.1063/5.0014016
View details for Web of Science ID 000562468800001
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Greenhouse-gas emissions of Canadian liquefied natural gas for use in China: Comparison and synthesis of three independent life cycle assessments
JOURNAL OF CLEANER PRODUCTION
2020; 258
View details for DOI 10.1016/j.jclepro.2020.120701
View details for Web of Science ID 000525323600086
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Carbon intensity of global crude oil refining and mitigation potential
NATURE CLIMATE CHANGE
2020
View details for DOI 10.1038/s41558-020-0775-3
View details for Web of Science ID 000537360700002
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Accuracy of satellite-derived estimates of flaring volume for offshore oil and gas operations in nine countries
ENVIRONMENTAL RESEARCH COMMUNICATIONS
2020; 2 (5)
View details for DOI 10.1088/2515-7620/ab8e17
View details for Web of Science ID 000579510300006
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Repeated leak detection and repair surveys reduce methane emissions over scale of years
ENVIRONMENTAL RESEARCH LETTERS
2020; 15 (3)
View details for DOI 10.1088/1748-9326/ab6ae1
View details for Web of Science ID 000526748500001
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Statistical proxy modeling for life cycle assessment and energetic analysis
ENERGY
2020; 194
View details for DOI 10.1016/j.energy.2019.116882
View details for Web of Science ID 000519654200043
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Life cycle assessment of emerging technologies: Evaluation techniques at different stages of market and technical maturity
JOURNAL OF INDUSTRIAL ECOLOGY
2020; 24 (1)
View details for DOI 10.1111/jiec.12954
View details for Web of Science ID 000512553700005
- Optimal Design of the Power Generation Network in California: Moving towards 100% Renewable Electricity by 2045 World Academy of Science 2020: 27-37
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Machine vision for natural gas methane emissions detection using an infrared camera
APPLIED ENERGY
2020; 257
View details for DOI 10.1016/j.apenergy.2019.113998
View details for Web of Science ID 000506574700033
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Short-term solar PV forecasting using computer vision: The search for optimal CNN architectures for incorporating sky images and PV generation history
JOURNAL OF RENEWABLE AND SUSTAINABLE ENERGY
2019; 11 (6)
View details for DOI 10.1063/1.5122796
View details for Web of Science ID 000505573900006
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Macro-Energy Systems: Toward a New Discipline
JOULE
2019; 3 (10): 2282–86
View details for DOI 10.1016/j.joule.2019.07.017
View details for Web of Science ID 000490703300002
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Single-blind inter-comparison of methane detection technologies - results from the Stanford/EDF Mobile Monitoring Challenge
ELEMENTA-SCIENCE OF THE ANTHROPOCENE
2019; 7
View details for DOI 10.1525/elementa.373
View details for Web of Science ID 000485873300001
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Short-term solar power forecast with deep learning: Exploring optimal input and output configuration
SOLAR ENERGY
2019; 188: 730–41
View details for DOI 10.1016/j.solener.2019.06.041
View details for Web of Science ID 000482532700070
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Clustering methods to find representative periods for the optimization of energy systems: An initial framework and comparison
APPLIED ENERGY
2019; 239: 1283–93
View details for DOI 10.1016/j.apenergy.2019.02.012
View details for Web of Science ID 000462690100097
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Biomethane addition to California transmission pipelines: Regional simulation of the impact of regulations
Applied Energy
2019: 292-301
View details for DOI 10.1016/j.apenergy.2019.05.031
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Design and operations optimization of membrane-based flexible carbon capture
International Journal of Greenhouse Gas Control
2019; 84: 154-163
View details for DOI 10.1016/j.ijggc.2019.03.018
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Three considerations for modeling natural gas system methane emissions in life cycle assessment
Journal of Cleaner Production
2019; 222: 760-767
View details for DOI 10.1016/j.jclepro.2019.03.096
- Short-term solar power forecast with deep learning: Exploring optimal input and output configuration Short-term solar power forecast with deep learning: Exploring optimal input and output configuration 2019; 188: 730-741
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Optimal design and operation of integrated solar combined cycles under emissions intensity constraints
APPLIED ENERGY
2018; 226: 979–90
View details for DOI 10.1016/j.apenergy.2018.06.052
View details for Web of Science ID 000441688100080
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Global carbon intensity of crude oil production.
Science (New York, N.Y.)
2018; 361 (6405): 851–53
View details for DOI 10.1126/science.aar6859
View details for PubMedID 30166477
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Assessment of methane emissions from the U.S. oil and gas supply chain.
Science (New York, N.Y.)
2018; 361 (6398): 186-188
Abstract
Methane emissions from the U.S. oil and natural gas supply chain were estimated by using ground-based, facility-scale measurements and validated with aircraft observations in areas accounting for ~30% of U.S. gas production. When scaled up nationally, our facility-based estimate of 2015 supply chain emissions is 13 ± 2 teragrams per year, equivalent to 2.3% of gross U.S. gas production. This value is ~60% higher than the U.S. Environmental Protection Agency inventory estimate, likely because existing inventory methods miss emissions released during abnormal operating conditions. Methane emissions of this magnitude, per unit of natural gas consumed, produce radiative forcing over a 20-year time horizon comparable to the CO2 from natural gas combustion. Substantial emission reductions are feasible through rapid detection of the root causes of high emissions and deployment of less failure-prone systems.
View details for DOI 10.1126/science.aar7204
View details for PubMedID 29930092
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Climate-wise choices in a world of oil abundance
ENVIRONMENTAL RESEARCH LETTERS
2018; 13 (4)
View details for DOI 10.1088/1748-9326/aaae76
View details for Web of Science ID 000429367300002
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Analysis of the energy return on investment (EROI) of existing fields
AMER CHEMICAL SOC. 2018
View details for Web of Science ID 000435539900426
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Well-to-refinery emissions and net-energy analysis of China's crude-oil supply
NATURE ENERGY
2018; 3 (3): 220–26
View details for DOI 10.1038/s41560-018-0090-7
View details for Web of Science ID 000427602200015
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"Good versus Good Enough?" Empirical Tests of Methane Leak Detection Sensitivity of a Commercial Infrared Camera
ENVIRONMENTAL SCIENCE & TECHNOLOGY
2018; 52 (4): 2368–74
Abstract
Methane, a key component of natural gas, is a potent greenhouse gas. A key feature of recent methane mitigation policies is the use of periodic leak detection surveys, typically done with optical gas imaging (OGI) technologies. The most common OGI technology is an infrared camera. In this work, we experimentally develop detection probability curves for OGI-based methane leak detection under different environmental and imaging conditions. Controlled single blind leak detection tests show that the median detection limit (50% detection likelihood) for FLIR-camera based OGI technology is about 20 g CH4/h at an imaging distance of 6 m, an order of magnitude higher than previously reported estimates of 1.4 g CH4/h. Furthermore, we show that median and 90% detection likelihood limit follows a power-law relationship with imaging distance. Finally, we demonstrate that real-world marginal effectiveness of methane mitigation through periodic surveys approaches zero as leak detection sensitivity improves. For example, a median detection limit of 100 g CH4/h is sufficient to detect the maximum amount of leakage that is possible through periodic surveys. Policy makers should take note of these limits while designing equivalence metrics for next-generation leak detection technologies that can trade sensitivity for cost without affecting mitigation priorities.
View details for PubMedID 29351718
- Solar PV output prediction from video streams using convolutional neural networks Energy & Environmental Science 2018: 8
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Aerial Interyear Comparison and Quantification of Methane Emissions Persistence in the Bakken Formation of North Dakota, USA
Environmental Science and Technology
2018; 52: 8947–8953
View details for DOI 10.1021/acs.est.8b01665
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Convolutional Neural Network for Short-term Solar Panel Output Prediction
IEEE. 2018: 2357–61
View details for Web of Science ID 000469200402088
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Aerial inter-year comparison and quantification of methane emissions persistence in the Bakken formation of North Dakota, USA.
Environmental science & technology
2018
Abstract
We performed an infrared optical gas imaging (OGI) survey by helicopter of hydrocarbon emissions in the Bakken formation of North Dakota. One year after an earlier survey of 682 well pads in September of 2014, the same helicopter crew re-surveyed 353 well pads in 2015 to examine the persistence of emissions. Twenty-one newly producing well pads were added in the same sampling blocks. An instrumented aircraft was also used to quantify emissions from 33 plumes identified by aerial OGI. Wellpads emitting methane and ethane in 2014 were far more likely to be emitting in 2015 than would expected by chance; Monte Carlo simulations suggest >5σ deviation (P<0.0001) from random assignment of detectable emissions between survey years. Scaled-up using basin-wide leakage estimates, the emissions quantified by aircraft are sufficient to explain previously observed basin-wide emissions of methane and ethane.
View details for PubMedID 29989804
- Optimal design and operation of integrated solar combined cycles under emissions intensity constraints Applied Energy 2018; 226 (0306-2619): 979-990
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Assessment of methane emissions from the U.S. oil and gas supply chain
Science
2018: 186–88
Abstract
Methane emissions from the U.S. oil and natural gas supply chain were estimated by using ground-based, facility-scale measurements and validated with aircraft observations in areas accounting for ~30% of U.S. gas production. When scaled up nationally, our facility-based estimate of 2015 supply chain emissions is 13 ± 2 teragrams per year, equivalent to 2.3% of gross U.S. gas production. This value is ~60% higher than the U.S. Environmental Protection Agency inventory estimate, likely because existing inventory methods miss emissions released during abnormal operating conditions. Methane emissions of this magnitude, per unit of natural gas consumed, produce radiative forcing over a 20-year time horizon comparable to the CO2 from natural gas combustion. Substantial emission reductions are feasible through rapid detection of the root causes of high emissions and deployment of less failure-prone systems.
View details for DOI 10.1126/science.aar7204
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Improved characterization of methane emissions from the U.S. oil and gas supply chain
Science
2018; 361 (6398): 186-188
View details for DOI 10.1126/science.aar7204
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Operational optimization of an integrated solar combined cycle under practical time-dependent constraints
ENERGY
2017; 141: 1569–84
View details for DOI 10.1016/j.energy.2017.11.059
View details for Web of Science ID 000423249200019
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Evaluation of a proposal for reliable low-cost grid power with 100% wind, water, and solar
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2017; 114 (26): 6722–27
Abstract
A number of analyses, meta-analyses, and assessments, including those performed by the Intergovernmental Panel on Climate Change, the National Oceanic and Atmospheric Administration, the National Renewable Energy Laboratory, and the International Energy Agency, have concluded that deployment of a diverse portfolio of clean energy technologies makes a transition to a low-carbon-emission energy system both more feasible and less costly than other pathways. In contrast, Jacobson et al. [Jacobson MZ, Delucchi MA, Cameron MA, Frew BA (2015) Proc Natl Acad Sci USA 112(49):15060-15065] argue that it is feasible to provide "low-cost solutions to the grid reliability problem with 100% penetration of WWS [wind, water and solar power] across all energy sectors in the continental United States between 2050 and 2055", with only electricity and hydrogen as energy carriers. In this paper, we evaluate that study and find significant shortcomings in the analysis. In particular, we point out that this work used invalid modeling tools, contained modeling errors, and made implausible and inadequately supported assumptions. Policy makers should treat with caution any visions of a rapid, reliable, and low-cost transition to entire energy systems that relies almost exclusively on wind, solar, and hydroelectric power.
View details for PubMedID 28630353
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Methane, Black Carbon, and Ethane Emissions from Natural Gas Flares in the Bakken Shale, North Dakota
ENVIRONMENTAL SCIENCE & TECHNOLOGY
2017; 51 (9): 5317-5325
Abstract
Incomplete combustion during flaring can lead to production of black carbon (BC) and loss of methane and other pollutants to the atmosphere, impacting climate and air quality. However, few studies have measured flare efficiency in a real-world setting. We use airborne data of plume samples from 37 unique flares in the Bakken region of North Dakota in May 2014 to calculate emission factors for BC, methane, ethane, and combustion efficiency for methane and ethane. We find no clear relationship between emission factors and aircraft-level wind speed or between methane and BC emission factors. Observed median combustion efficiencies for methane and ethane are close to expected values for typical flares according to the US EPA (98%). However, we find that the efficiency distribution is skewed, exhibiting log-normal behavior. This suggests incomplete combustion from flares contributes almost 1/5 of the total field emissions of methane and ethane measured in the Bakken shale, more than double the expected value if 98% efficiency was representative. BC emission factors also have a skewed distribution, but we find lower emission values than previous studies. The direct observation for the first time of a heavy-tail emissions distribution from flares suggests the need to consider skewed distributions when assessing flare impacts globally.
View details for DOI 10.1021/acs.est.6b05183
View details for Web of Science ID 000400723200063
View details for PubMedID 28401762
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When Comparing Alternative Fuel-Vehicle Systems, Life Cycle Assessment Studies Should Consider Trends in Oil Production
JOURNAL OF INDUSTRIAL ECOLOGY
2017; 21 (2): 244-248
View details for DOI 10.1111/jiec.12418
View details for Web of Science ID 000399664800002
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Designing better methane mitigation policies: the challenge of distributed small sources in the natural gas sector
ENVIRONMENTAL RESEARCH LETTERS
2017; 12 (4)
View details for DOI 10.1088/1748-9326/aa6791
View details for Web of Science ID 000399748000001
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Energy Intensity and Greenhouse Gas Emissions from Oil Production in the Eagle Ford Shale
ENERGY & FUELS
2017; 31 (2): 1440-1449
View details for DOI 10.1021/acs.energyfuels.6b02916
View details for Web of Science ID 000394560900041
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Updating the US Life Cycle GHG Petroleum Baseline to 2014 with Projections to 2040 Using Open-Source Engineering-Based Models
ENVIRONMENTAL SCIENCE & TECHNOLOGY
2017; 51 (2): 977-987
Abstract
The National Energy Technology Laboratory produced a well-to-wheels (WTW) life cycle greenhouse gas analysis of petroleum-based fuels consumed in the U.S. in 2005, known as the NETL 2005 Petroleum Baseline. This study uses a set of engineering-based, open-source models combined with publicly available data to calculate baseline results for 2014. An increase between the 2005 baseline and the 2014 results presented here (e.g., 92.4 vs 96.2 g CO2e/MJ gasoline, + 4.1%) are due to changes both in modeling platform and in the U.S. petroleum sector. An updated result for 2005 was calculated to minimize the effect of the change in modeling platform, and emissions for gasoline in 2014 were about 2% lower than in 2005 (98.1 vs 96.2 g CO2e/MJ gasoline). The same methods were utilized to forecast emissions from fuels out to 2040, indicating maximum changes from the 2014 gasoline result between +2.1% and -1.4%. The changing baseline values lead to potential compliance challenges with frameworks such as the Energy Independence and Security Act (EISA) Section 526, which states that Federal agencies should not purchase alternative fuels unless their life cycle GHG emissions are less than those of conventionally produced, petroleum-derived fuels.
View details for DOI 10.1021/acs.est.6b02819
View details for Web of Science ID 000392457700029
View details for PubMedID 28092937
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Are Optical Gas Imaging Technologies Effective For Methane Leak Detection?
ENVIRONMENTAL SCIENCE & TECHNOLOGY
2017; 51 (1): 718-724
Abstract
Concerns over mitigating methane leakage from the natural gas system have become ever more prominent in recent years. Recently, the U.S. Environmental Protection Agency proposed regulations requiring use of optical gas imaging (OGI) technologies to identify and repair leaks. In this work, we develop an open-source predictive model to accurately simulate the most common OGI technology, passive infrared (IR) imaging. The model accurately reproduces IR images of controlled methane release field experiments as well as reported minimum detection limits. We show that imaging distance is the most important parameter affecting IR detection effectiveness. In a simulated well-site, over 80% of emissions can be detected from an imaging distance of 10 m. Also, the presence of "superemitters" greatly enhance the effectiveness of IR leak detection. The minimum detectable limits of this technology can be used to selectively target "superemitters", thereby providing a method for approximate leak-rate quantification. In addition, model results show that imaging backdrop controls IR imaging effectiveness: land-based detection against sky or low-emissivity backgrounds have higher detection efficiency compared to aerial measurements. Finally, we show that minimum IR detection thresholds can be significantly lower for gas compositions that include a significant fraction nonmethane hydrocarbons.
View details for DOI 10.1021/acs.est.6b03906
View details for Web of Science ID 000391346900079
View details for PubMedID 27936621
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Estimating decades-long trends in petroleum field energy return on investment (EROI) with an engineering-based model.
PloS one
2017; 12 (2)
Abstract
This paper estimates changes in the energy return on investment (EROI) for five large petroleum fields over time using the Oil Production Greenhouse Gas Emissions Estimator (OPGEE). The modeled fields include Cantarell (Mexico), Forties (U.K.), Midway-Sunset (U.S.), Prudhoe Bay (U.S.), and Wilmington (U.S.). Data on field properties and production/processing parameters were obtained from a combination of government and technical literature sources. Key areas of uncertainty include details of the oil and gas surface processing schemes. We aim to explore how long-term trends in depletion at major petroleum fields change the effective energetic productivity of petroleum extraction. Four EROI ratios are estimated for each field as follows: The net energy ratio (NER) and external energy ratio (EER) are calculated, each using two measures of energy outputs, (1) oil-only and (2) all energy outputs. In all cases, engineering estimates of inputs are used rather than expenditure-based estimates (including off-site indirect energy use and embodied energy). All fields display significant declines in NER over the modeling period driven by a combination of (1) reduced petroleum production and (2) increased energy expenditures on recovery methods such as the injection of water, steam, or gas. The fields studied had NER reductions ranging from 46% to 88% over the modeling periods (accounting for all energy outputs). The reasons for declines in EROI differ by field. Midway-Sunset experienced a 5-fold increase in steam injected per barrel of oil produced. In contrast, Prudhoe Bay has experienced nearly a 30-fold increase in amount of gas processed and reinjected per unit of oil produced. In contrast, EER estimates are subject to greater variability and uncertainty due to the relatively small magnitude of external energy investments in most cases.
View details for DOI 10.1371/journal.pone.0171083
View details for PubMedID 28178318
View details for PubMedCentralID PMC5298284
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Energetic productivity dynamics of global super-giant oilfields
Energy & Environmental Science
2017; 10 (6): 1493-1504
View details for DOI 10.1039/C7EE01031A
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Potential solar energy use in the global petroleum sector
ENERGY
2017; 118: 884-892
View details for DOI 10.1016/j.energy.2016.10.107
View details for Web of Science ID 000395048900076
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Methane Leaks from Natural Gas Systems Follow Extreme Distributions
ENVIRONMENTAL SCIENCE & TECHNOLOGY
2016; 50 (22): 12512-12520
Abstract
Future energy systems may rely on natural gas as a low-cost fuel to support variable renewable power. However, leaking natural gas causes climate damage because methane (CH4) has a high global warming potential. In this study, we use extreme-value theory to explore the distribution of natural gas leak sizes. By analyzing ∼15 000 measurements from 18 prior studies, we show that all available natural gas leakage data sets are statistically heavy-tailed, and that gas leaks are more extremely distributed than other natural and social phenomena. A unifying result is that the largest 5% of leaks typically contribute over 50% of the total leakage volume. While prior studies used log-normal model distributions, we show that log-normal functions poorly represent tail behavior. Our results suggest that published uncertainty ranges of CH4 emissions are too narrow, and that larger sample sizes are required in future studies to achieve targeted confidence intervals. Additionally, we find that cross-study aggregation of data sets to increase sample size is not recommended due to apparent deviation between sampled populations. Understanding the nature of leak distributions can improve emission estimates, better illustrate their uncertainty, allow prioritization of source categories, and improve sampling design. Also, these data can be used for more effective design of leak detection technologies.
View details for DOI 10.1021/acs.est.6b04303
View details for Web of Science ID 000388155000051
View details for PubMedID 27740745
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Energy Intensity and Greenhouse Gas Emissions from Tight Oil Production in the Bakken Formation
ENERGY & FUELS
2016; 30 (11): 9613-9621
View details for DOI 10.1021/acs.energyfuels.6b01907
View details for Web of Science ID 000388428800088
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Assessment of advanced solvent-based post-combustion CO2 capture processes using a bi-objective optimization technique
APPLIED ENERGY
2016; 179: 1209-1219
View details for DOI 10.1016/j.apenergy.2016.07.062
View details for Web of Science ID 000383291800098
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Improved exergetic life cycle assessment through matrix reduction technique
INTERNATIONAL JOURNAL OF LIFE CYCLE ASSESSMENT
2016; 21 (10): 1379-1390
View details for DOI 10.1007/s11367-016-1118-5
View details for Web of Science ID 000383502300001
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GHGfrack: An Open-Source Model for Estimating Greenhouse Gas Emissions from Combustion of Fuel during Drilling and Hydraulic Fracturing.
Environmental science & technology
2016; 50 (14): 7913-7920
Abstract
This paper introduces GHGfrack, an open-source engineering-based model that estimates energy consumption and associated GHG emissions from drilling and hydraulic fracturing operations. We describe verification and calibration of GHGfrack against field data for energy and fuel consumption. We run GHGfrack using data from 6927 wells in Eagle Ford and 4431 wells in Bakken oil fields. The average estimated energy consumption in Eagle Ford wells using lateral hole diameters of 8 (3)/4 and 6 (1)/8 in. are 2.25 and 2.73 TJ/well, respectively. The average estimated energy consumption in Bakken wells using hole diameters of 6 in. for horizontal section is 2.16 TJ/well. We estimate average greenhouse gas (GHG) emissions of 419 and 510 tonne of equivalent CO2 per well (tonne of CO2 eq/well) for the two aforementioned assumed geometries in Eagle Ford, respectively, and 417 tonne of CO2 eq/well for the case of Bakken. These estimates are limited only to GHG emissions from combustion of diesel fuel to supply energy only for rotation of drill string, drilling mud circulation, and fracturing pumps. Sensitivity analysis of the model shows that the top three key variables in driving energy intensity in drilling are the lateral hole diameter, drill pipe internal diameter, and mud flow rate. In hydraulic fracturing, the top three are lateral casing diameter, fracturing fluid volume, and length of the lateral.
View details for DOI 10.1021/acs.est.6b01940
View details for PubMedID 27341087
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Quantifying atmospheric methane emissions from oil and natural gas production in the Bakken shale region of North Dakota
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
2016; 121 (10): 6101-6111
View details for DOI 10.1002/2015JD024631
View details for Web of Science ID 000381629900057
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Fugitive emissions from the Bakken shale illustrate role of shale production in global ethane shift
GEOPHYSICAL RESEARCH LETTERS
2016; 43 (9): 4617-4623
View details for DOI 10.1002/2016GL068703
View details for Web of Science ID 000378339200065
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Aerial Surveys of Elevated Hydrocarbon Emissions from Oil and Gas Production Sites
ENVIRONMENTAL SCIENCE & TECHNOLOGY
2016; 50 (9): 4877-4886
Abstract
Oil and gas (O&G) well pads with high hydrocarbon emission rates may disproportionally contribute to total methane and volatile organic compound (VOC) emissions from the production sector. In turn, these emissions may be missing from most bottom-up emission inventories. We performed helicopter-based infrared camera surveys of more than 8000 O&G well pads in seven U.S. basins to assess the prevalence and distribution of high-emitting hydrocarbon sources (detection threshold ∼ 1-3 g s(-1)). The proportion of sites with such high-emitting sources was 4% nationally but ranged from 1% in the Powder River (Wyoming) to 14% in the Bakken (North Dakota). Emissions were observed three times more frequently at sites in the oil-producing Bakken and oil-producing regions of mixed basins (p < 0.0001, χ(2) test). However, statistical models using basin and well pad characteristics explained 14% or less of the variance in observed emission patterns, indicating that stochastic processes dominate the occurrence of high emissions at individual sites. Over 90% of almost 500 detected sources were from tank vents and hatches. Although tank emissions may be partially attributable to flash gas, observed frequencies in most basins exceed those expected if emissions were effectively captured and controlled, demonstrating that tank emission control systems commonly underperform. Tanks represent a key mitigation opportunity for reducing methane and VOC emissions.
View details for DOI 10.1021/acs.est.6b00705
View details for PubMedID 27045743
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A new carbon capture proxy model for optimizing the design and time-varying operation of a coal-natural gas power station
INTERNATIONAL JOURNAL OF GREENHOUSE GAS CONTROL
2016; 48: 234-252
View details for DOI 10.1016/j.ijggc.2015.11.023
View details for Web of Science ID 000376458500005
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Comparing Natural Gas Leakage Detection Technologies Using an Open-Source "Virtual Gas Field" Simulator
ENVIRONMENTAL SCIENCE & TECHNOLOGY
2016; 50 (8): 4546-4553
Abstract
We present a tool for modeling the performance of methane leak detection and repair programs that can be used to evaluate the effectiveness of detection technologies and proposed mitigation policies. The tool uses a two-state Markov model to simulate the evolution of methane leakage from an artificial natural gas field. Leaks are created stochastically, drawing from the current understanding of the frequency and size distributions at production facilities. Various leak detection and repair programs can be simulated to determine the rate at which each would identify and repair leaks. Integrating the methane leakage over time enables a meaningful comparison between technologies, using both economic and environmental metrics. We simulate four existing or proposed detection technologies: flame ionization detection, manual infrared camera, automated infrared drone, and distributed detectors. Comparing these four technologies, we found that over 80% of simulated leakage could be mitigated with a positive net present value, although the maximum benefit is realized by selectively targeting larger leaks. Our results show that low-cost leak detection programs can rely on high-cost technology, as long as it is applied in a way that allows for rapid detection of large leaks. Any strategy to reduce leakage should require a careful consideration of the differences between low-cost technologies and low-cost programs.
View details for DOI 10.1021/acs.est.5b06068
View details for Web of Science ID 000374707100045
View details for PubMedID 27007771
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Water Use and Management in the Bakken Shale Oil Play in North Dakota
ENVIRONMENTAL SCIENCE & TECHNOLOGY
2016; 50 (6): 3275-3282
View details for DOI 10.1021/acs.est.5b04079
View details for Web of Science ID 000372392100058
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GHGfrack: An open-source model for estimating greenhouse gas emissions from combustion of fuel in drilling and hydraulic fracturing
Environ. Sci. Technol.
2016: 7913–20
Abstract
This paper introduces GHGfrack, an open-source engineering-based model that estimates energy consumption and associated GHG emissions from drilling and hydraulic fracturing operations. We describe verification and calibration of GHGfrack against field data for energy and fuel consumption. We run GHGfrack using data from 6927 wells in Eagle Ford and 4431 wells in Bakken oil fields. The average estimated energy consumption in Eagle Ford wells using lateral hole diameters of 8 (3)/4 and 6 (1)/8 in. are 2.25 and 2.73 TJ/well, respectively. The average estimated energy consumption in Bakken wells using hole diameters of 6 in. for horizontal section is 2.16 TJ/well. We estimate average greenhouse gas (GHG) emissions of 419 and 510 tonne of equivalent CO2 per well (tonne of CO2 eq/well) for the two aforementioned assumed geometries in Eagle Ford, respectively, and 417 tonne of CO2 eq/well for the case of Bakken. These estimates are limited only to GHG emissions from combustion of diesel fuel to supply energy only for rotation of drill string, drilling mud circulation, and fracturing pumps. Sensitivity analysis of the model shows that the top three key variables in driving energy intensity in drilling are the lateral hole diameter, drill pipe internal diameter, and mud flow rate. In hydraulic fracturing, the top three are lateral casing diameter, fracturing fluid volume, and length of the lateral.
View details for DOI 10.1021/acs.est.6b01940
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Energy Return on Investment (EROI) for Forty Global Oilfields Using a Detailed Engineering-Based Model of Oil Production
PLOS ONE
2015; 10 (12)
Abstract
Studies of the energy return on investment (EROI) for oil production generally rely on aggregated statistics for large regions or countries. In order to better understand the drivers of the energy productivity of oil production, we use a novel approach that applies a detailed field-level engineering model of oil and gas production to estimate energy requirements of drilling, producing, processing, and transporting crude oil. We examine 40 global oilfields, utilizing detailed data for each field from hundreds of technical and scientific data sources. Resulting net energy return (NER) ratios for studied oil fields range from ≈2 to ≈100 MJ crude oil produced per MJ of total fuels consumed. External energy return (EER) ratios, which compare energy produced to energy consumed from external sources, exceed 1000:1 for fields that are largely self-sufficient. The lowest energy returns are found to come from thermally-enhanced oil recovery technologies. Results are generally insensitive to reasonable ranges of assumptions explored in sensitivity analysis. Fields with very large associated gas production are sensitive to assumptions about surface fluids processing due to the shifts in energy consumed under different gas treatment configurations. This model does not currently include energy invested in building oilfield capital equipment (e.g., drilling rigs), nor does it include other indirect energy uses such as labor or services.
View details for DOI 10.1371/journal.pone.0144141
View details for Web of Science ID 000367092500002
View details for PubMedID 26695068
View details for PubMedCentralID PMC4687841
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Net energy analysis of Bakken crude oil production using a well-level engineering-based model
ENERGY
2015; 93: 2191-2198
View details for DOI 10.1016/j.energy.2015.10.113
View details for Web of Science ID 000367409500088
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Embodied Energy and GHG Emissions from Material Use in Conventional and Unconventional Oil and Gas Operations
ENVIRONMENTAL SCIENCE & TECHNOLOGY
2015; 49 (21): 13059-13066
Abstract
Environmental impacts embodied in oilfield capital equipment have not been thoroughly studied. In this paper, we present the first open-source model which computes the embodied energy and greenhouse gas (GHG) emissions associated with materials consumed in constructing oil and gas wells and associated infrastructure. The model includes well casing, wellbore cement, drilling mud, processing equipment, gas compression, and transport infrastructure. Default case results show that consumption of materials in constructing oilfield equipment consumes ∼0.014 MJ of primary energy per MJ of oil produced, and results in ∼1.3 gCO2-eq GHG emissions per MJ (lower heating value) of crude oil produced, an increase of 15% relative to upstream emissions assessed in earlier OPGEE model versions, and an increase of 1-1.5% of full life cycle emissions. A case study of a hydraulically fractured well in the Bakken formation of North Dakota suggests lower energy intensity (0.011 MJ/MJ) and emissions intensity (1.03 gCO2-eq/MJ) due to the high productivity of hydraulically fractured wells. Results are sensitive to per-well productivity, the complexity of wellbore casing design, and the energy and emissions intensity per kg of material consumed.
View details for DOI 10.1021/acs.est.5b03540
View details for Web of Science ID 000364355300052
View details for PubMedID 26421352
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The productivity and potential future recovery of the Bakken formation of North Dakota
JOURNAL OF UNCONVENTIONAL OIL AND GAS RESOURCES
2015; 11: 11–18
View details for DOI 10.1016/j.juogr.2015.04.002
View details for Web of Science ID 000218675000002
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Oil Sands Energy Intensity Assessment Using Facility-Level Data
ENERGY & FUELS
2015; 29 (8): 5204-5212
View details for DOI 10.1021/acs.energyfuels.5b00175
View details for Web of Science ID 000360026700059
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Well-to-Wheels Greenhouse Gas Emissions of Canadian Oil Sands Products: Implications for US Petroleum Fuels
ENVIRONMENTAL SCIENCE & TECHNOLOGY
2015; 49 (13): 8219-8227
Abstract
Greenhouse gas (GHG) regulations affecting U.S. transportation fuels require holistic examination of the life-cycle emissions of U.S. petroleum feedstocks. With an expanded system boundary that included land disturbance-induced GHG emissions, we estimated well-to-wheels (WTW) GHG emissions of U.S. production of gasoline and diesel sourced from Canadian oil sands. Our analysis was based on detailed characterization of the energy intensities of 27 oil sands projects, representing industrial practices and technological advances since 2008. Four major oil sands production pathways were examined, including bitumen and synthetic crude oil (SCO) from both surface mining and in situ projects. Pathway-average GHG emissions from oil sands extraction, separation, and upgrading ranged from ∼6.1 to ∼27.3 g CO2 equivalents per megajoule (in lower heating value, CO2e/MJ). This range can be compared to ∼4.4 g CO2e/MJ for U.S. conventional crude oil recovery. Depending on the extraction technology and product type output of oil sands projects, the WTW GHG emissions for gasoline and diesel produced from bitumen and SCO in U.S. refineries were in the range of 100-115 and 99-117 g CO2e/MJ, respectively, representing, on average, about 18% and 21% higher emissions than those derived from U.S. conventional crudes. WTW GHG emissions of gasoline and diesel derived from diluted bitumen ranged from 97 to 103 and 96 to 104 g CO2e/MJ, respectively, showing the effect of diluent use on fuel emissions.
View details for DOI 10.1021/acs.est.5b01255
View details for Web of Science ID 000357840300086
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Well-to-Wheels Greenhouse Gas Emissions of Canadian Oil Sands Products: Implications for U.S. Petroleum Fuels.
Environmental science & technology
2015; 49 (13): 8219-27
Abstract
Greenhouse gas (GHG) regulations affecting U.S. transportation fuels require holistic examination of the life-cycle emissions of U.S. petroleum feedstocks. With an expanded system boundary that included land disturbance-induced GHG emissions, we estimated well-to-wheels (WTW) GHG emissions of U.S. production of gasoline and diesel sourced from Canadian oil sands. Our analysis was based on detailed characterization of the energy intensities of 27 oil sands projects, representing industrial practices and technological advances since 2008. Four major oil sands production pathways were examined, including bitumen and synthetic crude oil (SCO) from both surface mining and in situ projects. Pathway-average GHG emissions from oil sands extraction, separation, and upgrading ranged from ∼6.1 to ∼27.3 g CO2 equivalents per megajoule (in lower heating value, CO2e/MJ). This range can be compared to ∼4.4 g CO2e/MJ for U.S. conventional crude oil recovery. Depending on the extraction technology and product type output of oil sands projects, the WTW GHG emissions for gasoline and diesel produced from bitumen and SCO in U.S. refineries were in the range of 100-115 and 99-117 g CO2e/MJ, respectively, representing, on average, about 18% and 21% higher emissions than those derived from U.S. conventional crudes. WTW GHG emissions of gasoline and diesel derived from diluted bitumen ranged from 97 to 103 and 96 to 104 g CO2e/MJ, respectively, showing the effect of diluent use on fuel emissions.
View details for DOI 10.1021/acs.est.5b01255
View details for PubMedID 26054375
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Uncertainty in Regional-Average Petroleum GHG Intensities: Countering Information Gaps with Targeted Data Gathering.
Environmental science & technology
2015; 49 (1): 679-686
Abstract
Recent efforts to model crude oil production GHG emissions are challenged by a lack of data. Missing data can affect the accuracy of oil field carbon intensity (CI) estimates as well as the production-weighted CI of groups ("baskets") of crude oils. Here we use the OPGEE model to study the effect of incomplete information on the CI of crude baskets. We create two different 20 oil field baskets, one of which has typical emissions and one of which has elevated emissions. Dispersion of CI estimates is greatly reduced in baskets compared to single crudes (coefficient of variation = 0.2 for a typical basket when 50% of data is learned at random), and field-level inaccuracy (bias) is removed through compensating errors (bias of ∼5% in above case). If a basket has underlying characteristics significantly different than OPGEE defaults, systematic bias is introduced through use of defaults in place of missing data. Optimal data gathering strategies were found to focus on the largest 50% of fields, and on certain important parameters for each field. Users can avoid bias (reduced to <1 gCO2/MJ in our elevated emissions basket) through strategies that only require gathering ∼10-20% of input data.
View details for DOI 10.1021/es505376t
View details for PubMedID 25517046
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Optimization of carbon-capture-enabled coal-gas-solar power generation
ENERGY
2015; 79: 149-162
View details for DOI 10.1016/j.energy.2014.11.003
View details for Web of Science ID 000348959000014
- Know your oil Carnegie Endowment for International Peace. 2015
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Optimization of carbon-capture-enabled coal-gas-solar power generation
Energy
2015; 79: 149-162
View details for DOI 10.1016/j.energy.2014.11.003
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Optimizing heat integration in a flexible coal-natural gas power station with CO2 capture
INTERNATIONAL JOURNAL OF GREENHOUSE GAS CONTROL
2014; 31: 138-152
View details for DOI 10.1016/j.ijggc.2014.09.019
View details for Web of Science ID 000346595300015
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Reproducibility of LCA Models of Crude Oil Production
ENVIRONMENTAL SCIENCE & TECHNOLOGY
2014; 48 (21): 12978-12985
Abstract
Scientific models are ideally reproducible, with results that converge despite varying methods. In practice, divergence between models often remains due to varied assumptions, incompleteness, or simply because of avoidable flaws. We examine LCA greenhouse gas (GHG) emissions models to test the reproducibility of their estimates for well-to-refinery inlet gate (WTR) GHG emissions. We use the Oil Production Greenhouse gas Emissions Estimator (OPGEE), an open source engineering-based life cycle assessment (LCA) model, as the reference model for this analysis. We study seven previous studies based on six models. We examine the reproducibility of prior results by successive experiments that align model assumptions and boundaries. The root-mean-square error (RMSE) between results varies between ∼1 and 8 g CO2 eq/MJ LHV when model inputs are not aligned. After model alignment, RMSE generally decreases only slightly. The proprietary nature of some of the models hinders explanations for divergence between the results. Because verification of the results of LCA GHG emissions is often not possible by direct measurement, we recommend the development of open source models for use in energy policy. Such practice will lead to iterative scientific review, improvement of models, and more reliable understanding of emissions.
View details for DOI 10.1021/es501847p
View details for Web of Science ID 000344449100060
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Reproducibility of LCA models of crude oil production.
Environmental science & technology
2014; 48 (21): 12978-12985
Abstract
Scientific models are ideally reproducible, with results that converge despite varying methods. In practice, divergence between models often remains due to varied assumptions, incompleteness, or simply because of avoidable flaws. We examine LCA greenhouse gas (GHG) emissions models to test the reproducibility of their estimates for well-to-refinery inlet gate (WTR) GHG emissions. We use the Oil Production Greenhouse gas Emissions Estimator (OPGEE), an open source engineering-based life cycle assessment (LCA) model, as the reference model for this analysis. We study seven previous studies based on six models. We examine the reproducibility of prior results by successive experiments that align model assumptions and boundaries. The root-mean-square error (RMSE) between results varies between ∼1 and 8 g CO2 eq/MJ LHV when model inputs are not aligned. After model alignment, RMSE generally decreases only slightly. The proprietary nature of some of the models hinders explanations for divergence between the results. Because verification of the results of LCA GHG emissions is often not possible by direct measurement, we recommend the development of open source models for use in energy policy. Such practice will lead to iterative scientific review, improvement of models, and more reliable understanding of emissions.
View details for DOI 10.1021/es501847p
View details for PubMedID 25279438
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Uncertainty of Oil Field GHG Emissions Resulting from Information Gaps: A Monte Carlo Approach.
Environmental science & technology
2014; 48 (17): 10511-10518
Abstract
Regulations on greenhouse gas (GHG) emissions from liquid fuel production generally work with incomplete data about oil production operations. We study the effect of incomplete information on estimates of GHG emissions from oil production operations. Data from California oil fields are used to generate probability distributions for eight oil field parameters previously found to affect GHG emissions. We use Monte Carlo (MC) analysis on three example oil fields to assess the change in uncertainty associated with learning of information. Single factor uncertainties are most sensitive to ignorance about water-oil ratio (WOR) and steam-oil ratio (SOR), resulting in distributions with coefficients of variation (CV) of 0.1-0.9 and 0.5, respectively. Using a combinatorial uncertainty analysis, we find that only a small number of variables need to be learned to greatly improve on the accuracy of MC mean. At most, three pieces of data are required to reduce bias in MC mean to less than 5% (absolute). However, the parameters of key importance in reducing uncertainty depend on oil field characteristics and on the metric of uncertainty applied. Bias in MC mean can remain after multiple pieces of information are learned, if key pieces of information are left unknown.
View details for DOI 10.1021/es502107s
View details for PubMedID 25110115
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Energy and environment. Methane leaks from North American natural gas systems.
Science
2014; 343 (6172): 733-735
View details for DOI 10.1126/science.1247045
View details for PubMedID 24531957
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A better currency for investing in a sustainable future
Nature Climate Change
2014; 4 (7): 524-527
View details for DOI 10.1038/nclimate2285
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Uncertainty in Regional-Average Petroleum GHG Intensities: Countering Information Gaps with Targeted Data Gathering
Environ. Sci. Technol.
2014: 679–86
Abstract
Recent efforts to model crude oil production GHG emissions are challenged by a lack of data. Missing data can affect the accuracy of oil field carbon intensity (CI) estimates as well as the production-weighted CI of groups ("baskets") of crude oils. Here we use the OPGEE model to study the effect of incomplete information on the CI of crude baskets. We create two different 20 oil field baskets, one of which has typical emissions and one of which has elevated emissions. Dispersion of CI estimates is greatly reduced in baskets compared to single crudes (coefficient of variation = 0.2 for a typical basket when 50% of data is learned at random), and field-level inaccuracy (bias) is removed through compensating errors (bias of ∼5% in above case). If a basket has underlying characteristics significantly different than OPGEE defaults, systematic bias is introduced through use of defaults in place of missing data. Optimal data gathering strategies were found to focus on the largest 50% of fields, and on certain important parameters for each field. Users can avoid bias (reduced to <1 gCO2/MJ in our elevated emissions basket) through strategies that only require gathering ∼10-20% of input data.
View details for DOI 10.1021/es505376t
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Ensuring benefits from North American shale gas development: Towards a research agenda
Journal of Unconventional Oil and Gas Resources
2014; 7: 71–74
View details for DOI 10.1016/j.juogr.2014.01.003
- Oil Sands Energy Intensity Analysis for GREET Model Update Technical Report, Argonne National Laboratory 2014
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Calculating systems-scale energy efficiency and net energy returns: A bottom-up matrix-based approach
ENERGY
2013; 62: 235-247
View details for DOI 10.1016/j.energy.2013.09.054
View details for Web of Science ID 000328522800024
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The energetic implications of curtailing versus storing solar- and wind-generated electricity
ENERGY & ENVIRONMENTAL SCIENCE
2013; 6 (10): 2804-2810
View details for DOI 10.1039/c3ee41973h
View details for Web of Science ID 000325765100002
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Historical trends in greenhouse gas emissions of the Alberta oil sands (1970-2010)
ENVIRONMENTAL RESEARCH LETTERS
2013; 8 (4)
View details for DOI 10.1088/1748-9326/8/4/044036
View details for Web of Science ID 000329604900043
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Peak oil demand: the role of fuel efficiency and alternative fuels in a global oil production decline.
Environmental science & technology
2013; 47 (14): 8031-8041
Abstract
Some argue that peak conventional oil production is imminent due to physical resource scarcity. We examine the alternative possibility of reduced oil use due to improved efficiency and oil substitution. Our model uses historical relationships to project future demand for (a) transport services, (b) all liquid fuels, and (c) substitution with alternative energy carriers, including electricity. Results show great increases in passenger and freight transport activity, but less reliance on oil. Demand for liquids inputs to refineries declines significantly after 2070. By 2100 transport energy demand rises >1000% in Asia, while flattening in North America (+23%) and Europe (-20%). Conventional oil demand declines after 2035, and cumulative oil production is 1900 Gbbl from 2010 to 2100 (close to the U.S. Geological Survey median estimate of remaining oil, which only includes projected discoveries through 2025). These results suggest that effort is better spent to determine and influence the trajectory of oil substitution and efficiency improvement rather than to focus on oil resource scarcity. The results also imply that policy makers should not rely on liquid fossil fuel scarcity to constrain damage from climate change. However, there is an unpredictable range of emissions impacts depending on which mix of substitutes for conventional oil gains dominance-oil sands, electricity, coal-to-liquids, or others.
View details for DOI 10.1021/es401419t
View details for PubMedID 23697883
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CO2 Mitigation Potential of Mineral Carbonation with Industrial Alkalinity Sources in the United States.
Environmental science & technology
2013; 47 (13): 7548-7554
Abstract
The availability of industrial alkalinity sources is investigated to determine their potential for the simultaneous capture and sequestration of CO2 from point-source emissions in the United States. Industrial alkalinity sources investigated include fly ash, cement kiln dust, and iron and steel slag. Their feasibility for mineral carbonation is determined by their relative abundance for CO2 reactivity and their proximity to point-source CO2 emissions. In addition, the available aggregate markets are investigated as possible sinks for mineral carbonation products. We show that in the U.S., industrial alkaline byproducts have the potential to mitigate approximately 7.6 Mt CO2/yr, of which 7.0 Mt CO2/yr are CO2 captured through mineral carbonation and 0.6 Mt CO2/yr are CO2 emissions avoided through reuse as synthetic aggregate (replacing sand and gravel). The emission reductions represent a small share (i.e., 0.1%) of total U.S. CO2 emissions; however, industrial byproducts may represent comparatively low-cost methods for the advancement of mineral carbonation technologies, which may be extended to more abundant yet expensive natural alkalinity sources.
View details for DOI 10.1021/es4003982
View details for PubMedID 23738892
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The energy efficiency of oil sands extraction: Energy return ratios from 1970 to 2010
ENERGY
2013; 55: 693-702
View details for DOI 10.1016/j.energy.2013.03.080
View details for Web of Science ID 000321228400069
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Open-Source LCA Tool for Estimating Greenhouse Gas Emissions from Crude Oil Production Using Field Characteristics.
Environmental science & technology
2013; 47 (11): 5998-6006
Abstract
Existing transportation fuel cycle emissions models are either general and calculate nonspecific values of greenhouse gas (GHG) emissions from crude oil production, or are not available for public review and auditing. We have developed the Oil Production Greenhouse Gas Emissions Estimator (OPGEE) to provide open-source, transparent, rigorous GHG assessments for use in scientific assessment, regulatory processes, and analysis of GHG mitigation options by producers. OPGEE uses petroleum engineering fundamentals to model emissions from oil and gas production operations. We introduce OPGEE and explain the methods and assumptions used in its construction. We run OPGEE on a small set of fictional oil fields and explore model sensitivity to selected input parameters. Results show that upstream emissions from petroleum production operations can vary from 3 gCO2/MJ to over 30 gCO2/MJ using realistic ranges of input parameters. Significant drivers of emissions variation are steam injection rates, water handling requirements, and rates of flaring of associated gas.
View details for DOI 10.1021/es304570m
View details for PubMedID 23634761
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Using Infrastructure Optimization to Reduce Greenhouse Gas Emissions from Oil Sands Extraction and Processing
ENVIRONMENTAL SCIENCE & TECHNOLOGY
2013; 47 (3): 1735-1744
Abstract
The Alberta oil sands are a significant source of oil production and greenhouse gas emissions, and their importance will grow as the region is poised for decades of growth. We present an integrated framework that simultaneously considers economic and engineering decisions for the capture, transport, and storage of oil sands CO(2) emissions. The model optimizes CO(2) management infrastructure at a variety of carbon prices for the oil sands industry. Our study reveals several key findings. We find that the oil sands industry lends itself well to development of CO(2) trunk lines due to geographic coincidence of sources and sinks. This reduces the relative importance of transport costs compared to nonintegrated transport systems. Also, the amount of managed oil sands CO(2) emissions, and therefore the CCS infrastructure, is very sensitive to the carbon price; significant capture and storage occurs only above 110$/tonne CO(2) in our simulations. Deployment of infrastructure is also sensitive to CO(2) capture decisions and technology, particularly the fraction of capturable CO(2) from oil sands upgrading and steam generation facilities. The framework will help stakeholders and policy makers understand how CCS infrastructure, including an extensive pipeline system, can be safely and cost-effectively deployed.
View details for DOI 10.1021/es3035895
View details for Web of Science ID 000314675500071
View details for PubMedID 23276202
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Historical trends in life-cycle greenhouse gas emissions of Alberta oil sands extraction from 1970 to 2010: Causes and implications for future emissions
Environmental Research Letters
2013; 8 (4): 44036
View details for DOI 10.1088/1748-9326/8/4/044036
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Assessing the Potential of Mineral Carbonation with Industrial Alkalinity Sources in the US
International Conference on Greenhouse Gas Technologies (GHGT)
ELSEVIER SCIENCE BV. 2013: 5858–5869
View details for DOI 10.1016/j.egypro.2013.06.510
View details for Web of Science ID 000345500506012
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Estimating greenhouse gas (GHG) emissions from oil production operations using detailed field characteristics
Environmental Science & Technology
2013: 5998–6006
Abstract
Existing transportation fuel cycle emissions models are either general and calculate nonspecific values of greenhouse gas (GHG) emissions from crude oil production, or are not available for public review and auditing. We have developed the Oil Production Greenhouse Gas Emissions Estimator (OPGEE) to provide open-source, transparent, rigorous GHG assessments for use in scientific assessment, regulatory processes, and analysis of GHG mitigation options by producers. OPGEE uses petroleum engineering fundamentals to model emissions from oil and gas production operations. We introduce OPGEE and explain the methods and assumptions used in its construction. We run OPGEE on a small set of fictional oil fields and explore model sensitivity to selected input parameters. Results show that upstream emissions from petroleum production operations can vary from 3 gCO2/MJ to over 30 gCO2/MJ using realistic ranges of input parameters. Significant drivers of emissions variation are steam injection rates, water handling requirements, and rates of flaring of associated gas.
View details for DOI 10.1021/es304570m
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Impact of alkalinity sources on the life-cycle energy efficiency of mineral carbonation technologies
ENERGY & ENVIRONMENTAL SCIENCE
2012; 5 (9): 8631-8641
View details for DOI 10.1039/c2ee22180b
View details for Web of Science ID 000307595000022
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Variability and Uncertainty in Life Cycle Assessment Models for Greenhouse Gas Emissions from Canadian Oil Sands Production
ENVIRONMENTAL SCIENCE & TECHNOLOGY
2012; 46 (2): 1253-1261
Abstract
Because of interest in greenhouse gas (GHG) emissions from transportation fuels production, a number of recent life cycle assessment (LCA) studies have calculated GHG emissions from oil sands extraction, upgrading, and refining pathways. The results from these studies vary considerably. This paper reviews factors affecting energy consumption and GHG emissions from oil sands extraction. It then uses publicly available data to analyze the assumptions made in the LCA models to better understand the causes of variability in emissions estimates. It is found that the variation in oil sands GHG estimates is due to a variety of causes. In approximate order of importance, these are scope of modeling and choice of projects analyzed (e.g., specific projects vs industry averages); differences in assumed energy intensities of extraction and upgrading; differences in the fuel mix assumptions; treatment of secondary noncombustion emissions sources, such as venting, flaring, and fugitive emissions; and treatment of ecological emissions sources, such as land-use change-associated emissions. The GHGenius model is recommended as the LCA model that is most congruent with reported industry average data. GHGenius also has the most comprehensive system boundaries. Last, remaining uncertainties and future research needs are discussed.
View details for DOI 10.1021/es202312p
View details for Web of Science ID 000299136200087
View details for PubMedID 22191713
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Willingness to Pay for a Climate Backstop: Liquid Fuel Producers and Direct CO2 Air Capture
ENERGY JOURNAL
2012; 33 (1): 53-81
View details for DOI 10.5547/ISSN0195-6574-EJ-Vol33-No1-3
View details for Web of Science ID 000298868300003
- Exploring the variation of GHG emissions from conventional oil production using an engineering-based LCA model American Center for Life Cycle Assessment (ACLCA) LCA XII Conference 2012
- Optimal heat integration in a coal-natural gas energy park with CO2 capture GHGT-11, the 11th International Conference on Greenhouse Gas Control Technologies 2012
- Impact of CO2 Emissions Policy and System Configuration on Optimal Operation of an Integrated Fossil-Renewable Energy Park Carbon Management Technologies Conference 2012
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Optimal operation of an integrated energy system including fossil fuel power generation, CO2 capture and wind
ENERGY
2011; 36 (12): 6806-6820
View details for DOI 10.1016/j.energy.2011.10.015
View details for Web of Science ID 000298894000011
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Oil Depletion and the Energy Efficiency of Oil Production: The Case of California
SUSTAINABILITY
2011; 3 (10): 1833-1854
View details for DOI 10.3390/su3101833
View details for Web of Science ID 000208763700011
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A General Mathematical Framework for Calculating Systems-Scale Efficiency of Energy Extraction and Conversion: Energy Return on Investment (EROI) and Other Energy Return Ratios
ENERGIES
2011; 4 (8): 1211-1245
View details for DOI 10.3390/en4081211
View details for Web of Science ID 000294246300008
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Oil Shale as an Energy Resource in a CO2 Constrained World: The Concept of Electricity Production with in Situ Carbon Capture
ENERGY & FUELS
2011; 25 (4): 1633-1641
View details for DOI 10.1021/ef101714x
View details for Web of Science ID 000289697700034
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CO2 Interim Storage: Technical Characteristics and Potential Role in CO2 Market Development
10th International Conference on Greenhouse Gas Control Technologies
ELSEVIER SCIENCE BV. 2011: 2628–2636
View details for DOI 10.1016/j.egypro.2011.02.162
View details for Web of Science ID 000298299702115
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Land Use Greenhouse Gas Emissions from Conventional Oil Production and Oil Sands
ENVIRONMENTAL SCIENCE & TECHNOLOGY
2010; 44 (22): 8766-8772
Abstract
Debates surrounding the greenhouse gas (GHG) emissions from land use of biofuels production have created a need to quantify the relative land use GHG intensity of fossil fuels. When contrasting land use GHG intensity of fossil fuel and biofuel production, it is the energy yield that greatly distinguishes the two. Although emissions released from land disturbed by fossil fuels can be comparable or higher than biofuels, the energy yield of oil production is typically 2-3 orders of magnitude higher, (0.33-2.6, 0.61-1.2, and 2.2 5.1 PJ/ha) for conventional oil production, oil sands surface mining, and in situ production, respectively). We found that land use contributes small portions of GHGs to life cycle emissions of California crude and in situ oil sands production ( <0.4% or < 0.4 gCO₂e/MJ crude refinery feedstock) and small to modest portions for Alberta conventional oil (0.1-4% or 0.1-3.4 gCO₂e/MJ) and surface mining of oil sands (0.9-11% or 0.8-10.2 gCO₂e/MJ).Our estimates are based on assumptions aggregated over large spatial and temporal scales and assuming 100% reclamation. Values on finer spatial and temporal scales that are relevant to policy targets need to account for site-specific information, the baseline natural and anthropogenic disturbance.
View details for DOI 10.1021/es1013278
View details for Web of Science ID 000284248300064
View details for PubMedID 20949948
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The Climate Impacts of Bioenergy Systems Depend on Market and Regulatory Policy Contexts
ENVIRONMENTAL SCIENCE & TECHNOLOGY
2010; 44 (19): 7347-7350
Abstract
Biomass can help reduce greenhouse gas (GHG) emissions by displacing petroleum in the transportation sector, by displacing fossil-based electricity, and by sequestering atmospheric carbon. Which use mitigates the most emissions depends on market and regulatory contexts outside the scope of attributional life cycle assessments. We show that bioelectricity's advantage over liquid biofuels depends on the GHG intensity of the electricity displaced. Bioelectricity that displaces coal-fired electricity could reduce GHG emissions, but bioelectricity that displaces wind electricity could increase GHG emissions. The electricity displaced depends upon existing infrastructure and policies affecting the electric grid. These findings demonstrate how model assumptions about whether the vehicle fleet and bioenergy use are fixed or free parameters constrain the policy questions an analysis can inform. Our bioenergy life cycle assessment can inform questions about a bioenergy mandate's optimal allocation between liquid fuels and electricity generation, but questions about the optimal level of bioenergy use require analyses with different assumptions about fixed and free parameters.
View details for DOI 10.1021/es100418p
View details for Web of Science ID 000282209700029
View details for PubMedID 20873876
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Global oil depletion: A review of the evidence
ENERGY POLICY
2010; 38 (9): 5290-5295
View details for DOI 10.1016/j.enpol.2010.04.046
View details for Web of Science ID 000279743500052
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Review of mathematical models of future oil supply: Historical overview and synthesizing critique
ENERGY
2010; 35 (9): 3958-3974
View details for DOI 10.1016/j.energy.2010.04.045
View details for Web of Science ID 000281178000051
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Energy Intensity and Greenhouse Gas Emissions from Thermal Enhanced Oil Recovery
ENERGY & FUELS
2010; 24: 4581-4589
View details for DOI 10.1021/ef100410f
View details for Web of Science ID 000281029700059
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Dynamics of the oil transition: Modeling capacity, depletion, and emissions
ENERGY
2010; 35 (7): 2852-2860
View details for DOI 10.1016/j.energy.2010.03.014
View details for Web of Science ID 000279410500013
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Converting Oil Shale to Liquid Fuels with the Alberta Taciuk Processor: Energy Inputs and Greenhouse Gas Emissions
ENERGY & FUELS
2009; 23: 6253-6258
View details for DOI 10.1021/ef900678d
View details for Web of Science ID 000272700300063
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Carbon Dioxide Emissions from Oil Shale Derived Liquid Fuels
236th National Meeting of the American-Chemical-Society
AMER CHEMICAL SOC. 2009: 219–248
View details for Web of Science ID 000292522500011
- An assessment of the evidence for a near-term peak in global oil production UK Energy Research Centre 2009
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Converting oil shale to liquid fuels: Energy inputs and greenhouse gas emissions of the Shell in situ conversion process
ENVIRONMENTAL SCIENCE & TECHNOLOGY
2008; 42 (19): 7489-7495
Abstract
Oil shale is a sedimentary rock that contains kerogen, a fossil organic material. Kerogen can be heated to produce oil and gas (retorted). This has traditionally been a CO2-intensive process. In this paper, the Shell in situ conversion process (ICP), which is a novel method of retorting oil shale in place, is analyzed. The ICP utilizes electricity to heat the underground shale over a period of 2 years. Hydrocarbons are produced using conventional oil production techniques, leaving shale oil coke within the formation. The energy inputs and outputs from the ICP, as applied to oil shales of the Green River formation, are modeled. Using these energy inputs, the greenhouse gas (GHG) emissions from the ICP are calculated and are compared to emissions from conventional petroleum. Energy outputs (as refined liquid fuel) are 1.2-1.6 times greater than the total primary energy inputs to the process. In the absence of capturing CO2 generated from electricity produced to fuel the process, well-to-pump GHG emissions are in the range of 30.6-37.1 grams of carbon equivalent per megajoule of liquid fuel produced. These full-fuel-cycle emissions are 21%-47% larger than those from conventionally produced petroleum-based fuels.
View details for DOI 10.1021/es800531f
View details for Web of Science ID 000259603700074
View details for PubMedID 18939591
- Converting oil shale to liquid fuels: Energy inputs and greenhouse gas emissions of the Shell in situ conversion process Environmental Science & Technology 2008; 42: 7489-7495
- Dynamics of the oil transition: Modeling capacity, costs, and emissions University of California Energy Institute, Energy Policy and Economics Working Paper 021 2008
- The Race for 21 Century Auto Fuels AIP Conference Proceedings edited by Hafemeister, D. 2008: 235–50
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Scraping the bottom of the barrel: greenhouse gas emission consequences of a transition to low-quality and synthetic petroleum resources
CLIMATIC CHANGE
2007; 84 (3-4): 241-263
View details for DOI 10.1007/s10584-007-9275-y
View details for Web of Science ID 000248911200001
-
Testing Hubbert
ENERGY POLICY
2007; 35 (5): 3074-3088
View details for DOI 10.1016/j.enpol.2006.11.004
View details for Web of Science ID 000246346000038
- A low carbon fuel standard for California, part 1: Technical analysis California Energy Commission 2007
- Testing Hubbert Energy Policy 2007; 35: 3074-3088
- Scraping the bottom of the barrel: CO2 emissions consequences of a transition to low-quality and synthetic petroleum resources Climatic Change 2007; 84: 241-263
- A low carbon fuel standard for California, part 2: Policy analysis California Energy Commission 2007
-
Risks of the oil transition
ENVIRONMENTAL RESEARCH LETTERS
2006; 1 (1)
View details for DOI 10.1088/1748-9326/1/1/014004
View details for Web of Science ID 000202975700007
- Risks of the oil transition Environmental Research Letters 2006; 1 (1)
- Research roadmap for greenhouse gas inventory methods California Energy Commission Report 2005; CEC-500-2005-097