Is hydrothermal treatment coupled with carbon capture and storage an energy-producing negative emissions technology?

Cheng, Fangwei; Porter, Michael D.; Colosi, Lisa M.

doi:10.1016/j.enconman.2019.112252

Cited by 131Thermochemical Biomass Conversion ProcessesCarbon Dioxide Capture TechnologiesHybrid Renewable Energy Systems

Is hydrothermal treatment coupled with carbon capture and storage an energy-producing negative emissions technology?

Cheng, Fangwei, Porter, Michael D., Colosi, Lisa M.·2020·Energy Conversion and Management

DOI 10.1016/j.enconman.2019.112252

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Cheng, Porter and Colosi evaluated the performance of hydrothermal treatment technologies with CCS as NET for a different type of feedstock and process conditions.
“Interestingly, in a recent publication, Cheng, Porter and Colosi evaluated the performance of hydrothermal treatment technologies (HTT) -namely hydrothermal carbonization, hydrothermal liquefaction and hydrothermal gasification- with CCS as NET for a different type of feedstock an process conditions [13].”
From Integration of hydrothermal liquefaction and carbon capture and storage for the production of advanced liquid biofuels with negative CO2 emissions (2020) · cites this paper as [13]
In Cheng et al.'s study, supercritical conditions were not evaluated and the yields are relatively low, as they are mainly estimated based on reported data in batch operation.
“however, supercritical conditions are not evaluated and the yields are relatively low, as they are mainly estimated based on reported data in batch operation.”
From Integration of hydrothermal liquefaction and carbon capture and storage for the production of advanced liquid biofuels with negative CO2 emissions (2020) · cites this paper as [13]
The economic evaluation was not part of Cheng et al.'s study.
“Furthermore, the economic evaluation was not part of the study, but an interesting comparison between conventional BECCS -direct combustion of biomass- and HTT+CCS is presented.”
From Integration of hydrothermal liquefaction and carbon capture and storage for the production of advanced liquid biofuels with negative CO2 emissions (2020) · cites this paper as [13]
Cheng, Porter and Colosi estimated the EROI in the order of 2 and identified a trade-off between energy yield and carbon sequestration.
“The authors estimated the energy recovery of investment, EROI (EROI=Energy of product/Energy utilized in production process) in the order of 2, and identified a trade-off between energy yield and carbon sequestration.”
From Integration of hydrothermal liquefaction and carbon capture and storage for the production of advanced liquid biofuels with negative CO2 emissions (2020) · cites this paper as [13]
The value of -17.2 kg CO2eq/GJfuel is higher than the -50 kg CO2eq/GJfuel reported by Cheng, Porter and Colosi for HTT+CCS of lignocellulosic biomass.
“The value of -17.2 kg CO2eq/GJfuel is higher than the reported by Cheng, Porter and Colosi [13], who recently estimated the global warming potential of HTT+CCS of lignocellulosic biomass in the order of -50 kg CO2eq/GJfuel.”
From Integration of hydrothermal liquefaction and carbon capture and storage for the production of advanced liquid biofuels with negative CO2 emissions (2020) · cites this paper as [13]

Random Forests
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538 · see citing works
Classification and Regression Trees.
Gordon, A. D., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984) · Biometrics · doi:10.2307/2530946 · Cited by 23,834 · see citing works
Classification And Regression Trees
Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (2017) · doi:10.1201/9781315139470 · Cited by 11,417 · see citing works
Foundations of Machine LearningPreprint
Singh, A. (2021) · Introduction to AI Techniques for Renewable Energy Systems · doi:10.2139/ssrn.3399990 · Cited by 3,655 · see citing works
Recent developments in life cycle assessment
Finnveden, G., Hauschild, M. Z., Ekvall, T., Guinée, J., Heijungs, R., Hellweg, S., Koehler, A., Pennington, D., & Suh, S. (2009) · Journal of Environmental Management · doi:10.1016/j.jenvman.2009.06.018 · Cited by 3,444 · see citing works
Hydrothermal liquefaction of biomass: A review of subcritical water technologies
Toor, S. S., Rosendahl, L., & Rudolf, A. (2011) · Energy · doi:10.1016/j.energy.2011.03.013 · Cited by 1,840 · see citing works
Biophysical and economic limits to negative CO2 emissions
Smith, P., Davis, S. J., Creutzig, F., Fuss, S., Minx, J., Gabrielle, B., Kato, E., Jackson, R. B., Cowie, A., Kriegler, E., et al. (2016) · Nature Climate Change · doi:10.1038/nclimate2870 · Cited by 1,440 · see citing works
Potential yields and properties of oil from the hydrothermal liquefaction of microalgae with different biochemical content
Biller, P., & Ross, A. B. (2011) · Bioresource Technology · doi:10.1016/j.biortech.2010.06.028 · Cited by 1,131 · see citing works
Foundations of Machine Learning
Mohri, M., Rostamizadeh, A., & Talwalkar, A. (2018) · doi:10.7551/mitpress/10290.001.0001 · Cited by 1,122 · see citing works
Science and policy characteristics of the Paris Agreement temperature goal
Schleussner, C., Rogelj, J., Schaeffer, M., Lissner, T., Licker, R., Fischer, E. M., Knutti, R., Levermann, A., Frieler, K., & Hare, B. (2016) · Nature Climate Change · doi:10.1038/nclimate3096 · Cited by 909 · see citing works
Impact of torrefaction on the grindability and fuel characteristics of forest biomass
Phanphanich, M., & Mani, S. (2011) · Bioresource Technology · doi:10.1016/j.biortech.2010.08.028 · Cited by 892 · see citing works
A review of hydrothermal biomass processing
Tekin, K., Karagöz, S., & Bektaş, S. (2014) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2014.07.216 · Cited by 730 · see citing works
Hydrothermal liquefaction (HTL) of microalgae for biofuel production: State of the art review and future prospects
López Barreiro, D., Prins, W., Ronsse, F., & Brilman, W. (2013) · Biomass and Bioenergy · doi:10.1016/j.biombioe.2012.12.029 · Cited by 695 · see citing works
What is the Minimum EROI that a Sustainable Society Must Have?
Hall, C. A. S., Balogh, S., & Murphy, D. J. (2009) · Energies · doi:10.3390/en20100025 · Cited by 614 · see citing works
Life-cycle assessment of potential algal biodiesel production in the United Kingdom: A comparison of raceways and air-lift tubular bioreactors
Stephenson, A. L., Kazamia, E., Dennis, J. S., Howe, C. J., Scott, S. A., & Smith, A. G. (2010) · Energy & Fuels · doi:10.1021/ef1003123 · Cited by 571 · see citing works
Well-to-wheels energy use and greenhouse gas emissions of ethanol from corn, sugarcane and cellulosic biomass for US use
Wang, M., Han, J., Dunn, J. B., Cai, H., & Elgowainy, A. (2012) · Environmental Research Letters · doi:10.1088/1748-9326/7/4/045905 · Cited by 536 · see citing works
Techno-economic and life cycle assessment on lignocellulosic biomass thermochemical conversion technologies: A review
Patel, M., Zhang, X., & Kumar, A. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2015.09.070 · Cited by 535 · see citing works
Hydrothermal carbonization of biomass for energy and crop production
Reza, M. T., Andert, J., Wirth, B., Busch, D., Pielert, J., Lynam, J. G., & Mumme, J. (2014) · Applied Bioenergy · doi:10.2478/apbi-2014-0001 · Cited by 396 · see citing works
Can BECCS deliver sustainable and resource efficient negative emissions?
Fajardy, M., & Mac Dowell, N. (2017) · Energy & Environmental Science · doi:10.1039/c7ee00465f · Cited by 392 · see citing works
An energy evaluation of coupling nutrient removal from wastewater with algal biomass production
Sturm, B., & Lamer, S. L. (2011) · Applied Energy · doi:10.1016/j.apenergy.2010.12.056 · Cited by 301 · see citing works
Pilot-scale data provide enhanced estimates of the life cycle energy and emissions profile of algae biofuels produced via hydrothermal liquefaction
Liu, X., Saydah, B., Eranki, P., Colosi, L. M., Greg Mitchell, B., Rhodes, J., & Clarens, A. F. (2013) · Bioresource Technology · doi:10.1016/j.biortech.2013.08.112 · Cited by 246 · see citing works
Self-citation
Hydrothermal Treatment of Protein, Polysaccharide, and Lipids Alone and in Mixtures
Teri, G., Luo, L., & Savage, P. E. (2014) · Energy & Fuels · doi:10.1021/ef501760d · Cited by 233 · see citing works
Bioenergy with carbon capture and storage (BECCS): Global potential, investment preferences, and deployment barriers
Fridahl, M., & Lehtveer, M. (2018) · Energy Research & Social Science · doi:10.1016/j.erss.2018.03.019 · Cited by 218 · see citing works
Identifying Cost-Effective CO 2 Control Levels for Amine-Based CO 2 Capture Systems
Rao, A. B., & Rubin, E. S. (2005) · Industrial & Engineering Chemistry Research · doi:10.1021/ie050603p · Cited by 214 · see citing works
Prediction of biochar yield from cattle manure pyrolysis via least squares support vector machine intelligent approach
Cao, H., Xin, Y., & Yuan, Q. (2015) · Bioresource Technology · doi:10.1016/j.biortech.2015.12.024 · Cited by 194 · see citing works
Biomass enables the transition to a carbon-negative power system across western North America
Sanchez, D. L., Nelson, J. H., Johnston, J., Mileva, A., & Kammen, D. M. (2015) · Nature Climate Change · doi:10.1038/nclimate2488 · Cited by 181 · see citing works
The role of negative CO2 emissions for reaching 2 °C—insights from integrated assessment modelling
van Vuuren, D. P., Deetman, S., van Vliet, J., van den Berg, M., van Ruijven, B. J., & Koelbl, B. S. (2013) · Climatic Change · doi:10.1007/s10584-012-0680-5 · Cited by 180 · see citing works
Potential for using municipal solid waste as a resource for bioenergy with carbon capture and storage (BECCS)
Pour, N., Webley, P. A., & Cook, P. J. (2017) · International journal of greenhouse gas control · doi:10.1016/j.ijggc.2017.11.007 · Cited by 169 · see citing works
Assessing the environmental impact of energy production from hydrochar generated via hydrothermal carbonization of food wastes
Berge, N. D., Li, L., Flora, J. R. V., & Ro, K. S. (2015) · Waste Management · doi:10.1016/j.wasman.2015.04.029 · Cited by 155 · see citing works
Effect of process parameters on hydrothermal liquefaction of oil palm biomass for bio-oil production and its life cycle assessment
Chan, Y. H., Yusup, S. B., Quitain, A. T., Tan, R. R., Sasaki, M., Lam, H. L., & Uemura, Y. (2015) · Energy Conversion and Management · doi:10.1016/j.enconman.2015.03.075 · Cited by 154 · see citing works
Hydrothermal carbonization of coniferous biomass: Effect of process parameters on mass and energy yields
Sermyagina, E., Saari, J., Kaikko, J., & Vakkilainen, E. K. (2015) · Journal of Analytical and Applied Pyrolysis · doi:10.1016/j.jaap.2015.03.012 · Cited by 149 · see citing works
Bio-oil production from hydrothermal liquefaction of high-protein high-ash microalgae including wild Cyanobacteria sp. and cultivated Bacillariophyta sp.
Huang, Y., Chen, Y., Xie, J., Liu, H., Yin, X., & Wu, C. (2016) · Fuel · doi:10.1016/j.fuel.2016.06.013 · Cited by 138 · see citing works
The impacts of biomass properties on pyrolysis yields, economic and environmental performance of the pyrolysis-bioenergy-biochar platform to carbon negative energy
Li, W., Dang, Q. F., Brown, R. C., Laird, D. A., & Wright, M. M. (2017) · Bioresource Technology · doi:10.1016/j.biortech.2017.06.049 · Cited by 138 · see citing works
The energy return on investment of BECCS: is BECCS a threat to energy security?
Fajardy, M., & Mac Dowell, N. (2018) · Energy & Environmental Science · doi:10.1039/c7ee03610h · Cited by 126 · see citing works
Advanced models for the prediction of product yield in hydrothermal liquefaction via a mixture design of biomass model components coupled with process variables
Yang, J., He, Q. S., Corscadden, K. W., Niu, H., Lin, J., & Astatkie, T. (2018) · Applied Energy · doi:10.1016/j.apenergy.2018.10.035 · Cited by 105 · see citing works
Process Simulation Development of Fast Pyrolysis of Wood Using Aspen Plus
Onarheim, K., Solantausta, Y., & Lehto, J. (2014) · Energy & Fuels · doi:10.1021/ef502023y · Cited by 94 · see citing works
Integrating Algae with Bioenergy Carbon Capture and Storage (ABECCS) Increases Sustainability
Beal, C. M., Archibald, I., Huntley, M. E., Greene, C. H., & Johnson, Z. I. (2018) · Earth s Future · doi:10.1002/2017ef000704 · Cited by 93 · see citing works
Investigation into the applicability of Bond Work Index (BWI) and Hardgrove Grindability Index (HGI) tests for several biomasses compared to Colombian La Loma coal
Williams, O. S. A., Eastwick, C. N., Kingman, S., Giddings, D., Lormor, S., & Lester, E. H. (2015) · Fuel · doi:10.1016/j.fuel.2015.05.027 · Cited by 86 · see citing works
Sequestration of fermentation CO2 from ethanol production
Kheshgi, H. S., & Prince, R. C. (2004) · Energy · doi:10.1016/j.energy.2004.11.004 · Cited by 72 · see citing works
Corn stover availability for biomass conversion: situation analysis
Hess, J. R., Kenney, K., Wright, C. T., Perlack, R. D., & Turhollow, A. (2009) · Cellulose · doi:10.1007/s10570-009-9323-z · Cited by 71 · see citing works
Hydrothermal liquefaction of microalgae to produce biofuels: state of the art and future prospects
Vlaskin, M. S., Chernova, N. I., Киселева, С. В., Попель, О. С., & Зиновьевич, Ж. А. (2017) · Thermal Engineering · doi:10.1134/s0040601517090105 · Cited by 64 · see citing works
Investigating the role of feedstock properties and process conditions on products formed during the hydrothermal carbonization of organics using regression techniques
Li, L., Flora, J. R. V., Caicedo, J. M., & Berge, N. D. (2015) · Bioresource Technology · doi:10.1016/j.biortech.2015.03.054 · Cited by 57 · see citing works
Quantifying the sensitivity of feedstock properties and process conditions on hydrochar yield, carbon content, and energy content
Li, L., Wang, Y., Xu, J., Flora, J. R. V., Hoque, S., & Berge, N. D. (2018) · Bioresource Technology · doi:10.1016/j.biortech.2018.04.066 · Cited by 57 · see citing works
Sludge carbonization and activation: From hazardous waste to functional materials for water treatment
Cheng, F., Luo, H., Hu, L., Yu, B., Luo, Z., & de Cortalezzi, M. M. F. (2016) · Journal of environmental chemical engineering · doi:10.1016/j.jece.2016.11.013 · Cited by 48 · see citing works
Self-citation
Willow supply strategies to energy plants
Gigler, J. K., Meerdink, G., & Hendrix, E. M. T. (1999) · Biomass and Bioenergy · doi:10.1016/s0961-9534(99)00041-0 · Cited by 47 · see citing works
Evaluating the Water Quality Impacts of Hydrothermal Liquefaction Assessment of Carbon, Nitrogen, and Energy Recovery
Bauer, S. K., Reynolds, C. F., Peng, S., & Colosi, L. M. (2018) · Bioresource Technology Reports · doi:10.1016/j.biteb.2018.04.010 · Cited by 23 · see citing works
Self-citation
On the potential for BECCS efficiency improvement through heat recovery from both post-combustion and oxy-combustion facilities
Dowell, N. M., & Fajardy, M. (2016) · Faraday Discussions · doi:10.1039/c6fd00051g · Cited by 22 · see citing works
Evaluating the Impacts of ACP Management on the Energy Performance of Hydrothermal Liquefaction via Nutrient Recovery
Bauer, S. K., Cheng, F., & Colosi, L. M. (2019) · Energies · doi:10.3390/en12040729 · Cited by 13 · see citing works
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Authors: Cheng, F., Porter, M. D., & Colosi, L. M.
Affiliations: University of Virginia (US)
Corresponding author: Colosi, Lisa M.
ORCID: Cheng, Fangwei
Porter, Michael D.
Colosi, Lisa M.
Venue: Energy Conversion and Management
Publisher: Elsevier BV
Published: 2020-01
Volume: 203
Pages: 112252
ISSN: 0196-8904 (ISSN-L)
DOI: 10.1016/j.enconman.2019.112252
OpenAlex: W2990367159
Cited by: 131
References: 48
Citations by year: 2026: 11 · 2025: 30 · 2024: 20 · 2023: 23 · 2022: 20 · 2021: 20 · 2020: 7
FWCI: 4.15
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
Locations: Energy Conversion and Management (publishedVersion)
Funders: G. Unger Vetlesen Foundation
Topics: Physical Sciences › Engineering › Biomedical Engineering › Thermochemical Biomass Conversion Processes
Physical Sciences › Engineering › Mechanical Engineering › Carbon Dioxide Capture Technologies
Physical Sciences › Energy › Energy Engineering and Power Technology › Hybrid Renewable Energy Systems
Keywords: hydrothermal treatment, carbon capture and storage, negative emissions technologies, energy return on investment, global warming potential, biocrude, hydrochar, lignocellulosic biomass, microalgae, random forest, life cycle assessment

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