Publications
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- Brandt, A. (2015). Embodied Energy and GHG Emissions from Material Use in Conventional and Unconventional Oil and Gas Operations. Environmental Science & Technology, 49(21), 13059–13066. https://doi.org/10.1021/acs.est.5b03540
- Ghandi, A., Yeh, S., Brandt, A., Vafi, K., Cai, H., Wang, M., Scanion, B., & Reedy, R. (2015). Energy Intensity and Greenhouse Gas Emissions from Crude Oil Production in the Eagle Ford Region: Input Data and Analysis Methods. https://www.researchgate.net/project/Sustainability-of-Future-Energy.
- McNally, M., & Brandt, A. (2015). The productivity and potential future recovery of the Bakken formation of North Dakota. Journal of Unconventional Oil and Gas Resources, 11, 11-18. https://doi.org/10.1016/j.juogr.2015.04.002
- Heath, G., Steinberg, D., Warner, E., & Brandt, A. (2015). Estimating U.S. Methane Emissions from the Natural Gas Supply Chain: Approaches, Uncertainties, Current Estimates, and Future Studies.
- An Independent Scientific Assessment of Well Stimulation in California Volume II - Potential Environmental Impacts of Hydraulic Fracturing and Acid Stimulations. (2015). An Independent Scientific Assessment of Well Stimulation in California Volume II: Potential Environmental Impacts of Hydraulic Fracturing and Acid Stimulations. https://doi.org/10.2172/1236176
- Englander, J., Brandt, A., Elgowainy, A., Cai, H., Han, J., Yeh, S., & Wang, M. (2015). Oil Sands Energy Intensity Assessment Using Facility-Level Data. Energy & Fuels, 29(8), 5204–5212. https://doi.org/10.1021/acs.energyfuels.5b00175
- Cai, H., Brandt, A., Yeh, S., Englander, J., Han, J., Elgowainy, A., & Wang, M. (2015). Well-to-Wheels Greenhouse Gas Emissions of Canadian Oil Sands Products: Implications for U.S. Petroleum Fuels. Environmental Science & Technology, 49(13), 8219–8227. https://doi.org/10.1021/acs.est.5b01255
- Brodrick, P., Kang, C., Brandt, A., & Durlofsky, L. (2015). Optimization of carbon-capture-enabled coal-gas-solar power generation. Energy, 79, 149-162. https://doi.org/10.1016/j.energy.2014.11.003
- Yeh, S., Zhao, A., Hogan, S., Brandt, A., Englander, J., Bellman, D., & Wang, M. (2015). Past and Future Land Use Impacts of Canadian Oil Sands and Greenhouse Gas Emissions. Project: Sustainability of Future Energy, Report number: UCD-ITS. https://doi.org/10.13140/RG.2.1.2632.2642
- Brandt, A., Sun, Y., & Vafi, K. (2014). Uncertainty in Regional-Average Petroleum GHG Intensities: Countering Information Gaps with Targeted Data Gathering. Environmental Science & Technology, 49(1), 679–686. https://doi.org/10.1021/es505376t
- Kang, C., Brandt, A., & Durlofsky, L. (2014). Optimizing heat integration in a flexible coal-natural gas power station with CO2 capture. International Journal of Greenhouse Gas Control, 31, 138-152. https://doi.org/10.1016/j.ijggc.2014.09.019
- Kang, C., Brandt, A., & Durlofsky, L. (2014). Optimizing heat integration in a flexible coal–natural gas power station with CO2 capture. International Journal of Greenhouse Gas Control, 31, 138-152. https://doi.org/10.1016/j.ijggc.2014.09.019
- Vafi, K., & Brandt, A. (2014). Reproducibility of LCA Models of Crude Oil Production. Environmental Science & Technology, 48(21), 12978–12985. https://doi.org/10.1021/es501847p
- Brazilian, M., Brandt, A., Billman, L., Heath, G., Logan, J., Mann, M., Melaina, M., Statwick, P., Arent, D., & Benson, S. (2014). Ensuring benefits from North American shale gas development: Towards a research agenda. Journal of Unconventional Oil and Gas Resources, 7, 71-74. https://doi.org/10.1016/j.juogr.2014.01.003
- Vafi, K., & Brandt, A. (2014). Uncertainty of Oil Field GHG Emissions Resulting from Information Gaps: A Monte Carlo Approach. Environmental Science & Technology, 48(17), https://doi.org/10.1021/es502107s. https://doi.org/10.1021/es502107s
- Carbajales-Dale, M., Barnhart, C., Brandt, A., & Benson, S. (2014). A better currency for investing in a sustainable future. Nature Climate Change, 4, pages524–527. https://doi.org/10.1038/nclimate2285
- Brandt, A., Heath, G., & Kourt, E. (2014). Methane Leaks from North American Natural Gas Systems. Science, 343(6172), 733-735. https://doi.org/10.1126/science.1247045
- Brandt, A., Dale, M., & Barnhart, C. (2013). Calculating systems-scale energy efficiency and net energy returns: A bottom-up matrix-based approach. Energy, 62, 235-247. https://doi.org/10.1016/j.energy.2013.09.054
- Englander, J., Bharadwaj, S., & Brandt, A. (2013). Historical trends in greenhouse gas emissions of the Alberta oil sands (1970–2010). Environmental Research Letters, 8(4), 044036. https://doi.org/10.1088/1748-9326/8/4/044036
- Barnhart, C., Dale, M., Brandt, A., & Benson, S. (2013). The energetic implications of curtailing versus storing solar- and wind-generated electricity. Energy & Environmental Science, 6(10), 2804-2810. https://doi.org/http://dx.doi.org/10.1039/c3ee41973h
2020
Nie, Y., Sun, Y., Chen, Y., Orsini, R., & Brandt, A. (2020). 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, 12(4), 046101. https://doi.org/10.1063/5.0014016
2019
Ravikumar, A.P., Sreedhara, S., Wang, J., Englander, J., Roda-Stuart, D., Bell, C., Zimmerle, D., Lyon, D., Mogstad, I., Ratner, B. and Brandt, A.R., 2019. Single-blind inter-comparison of methane detection technologies – results from the Stanford/EDF Mobile Monitoring Challenge. Elem Sci Anth, 7(1), p.37. DOI: http://doi.org/10.1525/elementa.373
Sun, Y., Venugopal, V., & Brandt, A. R. (2019). Short-term solar power forecast with deep learning: Exploring optimal input and output configuration. Solar Energy, 188, 730–741. https://doi.org/10.1016/j.solener.2019.06.041
Venugopal, V., Sun, Y., & Brandt, A. R. (2019). 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, 11(6), 066102. https://doi.org/10.1063/1.5122796
Wang, J., Tchapmi, L. P., Ravikumar, A. P., McGuire, M., Bell, C. S., Zimmerle, D., Savarese, S., Brandt, A. R. (2020). Machine vision for natural gas methane emissions detection using an infrared camera. Applied Energy, 257, 113998. DOI: https://doi.org/10.1016/j.apenergy.2019.113998
2018
R.A. Alvarez, D. Zavala-Araiza, D.R. Lyon, D.T. Allen, Z.R. Barkley, A.R. Brandt, K.J. Davis, S.C. Herndon, D.J. Jacob, A. Karion, E.A. Kort, B.K. Lamb, T. Lauvaux, J.D. Maasakkers, A.J. Marchese, M. Omara, S.W. Pacala, J. Peischl, A.L. Robinson, P.B. Shepson, C. Sweeney, A. Townsend-Small, S.C. Wofsy, S.P. Hamburg. Assessment of methane emissions from the U.S. oil and gas supply chain. Science. DOI: 10.1126/science.aar7204
*Brandt, A.R., M.S. Masnadi, J.G. Englander, J.G. Koomey, D. Gordon. Climate-wise oil choices in a world of oil abundance. Environmental Research Letters DOI: 10.1088/1748- 9326/aaae76
*P.G. Brodrick, A.R. Brandt., L.J. Durlofsky. Optimal design and operation of integrated solar combined cycles under emissions intensity constraints. Applied Energy
DOI: 10.1016/j.apenergy.2018.06.052
Englander, J.G.; Brandt, A.R.; Conley, S.; Lyon, D.; Jackson, R.B. (2018). Aerial inter-year comparison and quantification of methane emissions persistence in the Bakken formation of North Dakota, USA. Environmental Science & Technology. DOI: 10.1021/acs.est.8b01665
*Masnadi, M.S., D. Schunack, Y. Li, S.O. Roberts, A.R. Brandt, H.M. El-Houjeiri, S. Przesmitzki, M.Q. Wang. Well-to-refinery emissions and net-energy analysis of China?s crude-oil supply. Nature Energy. DOI: 10.1038/s41560-018-0090-7