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Uncertainties in Life Cycle Greenhouse Gas Emissions from Advanced Biomass Feedstock Logistics Supply Chains in Kansas

Author

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  • Long Nguyen

    (Civil, Architectural and Environmental Engineering, Drexel University, Philadelphia, PA 19104, USA)

  • Kara G. Cafferty

    (Department of Biofuels and Renewable Energy Technologies, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415, USA)

  • Erin M. Searcy

    (Department of Biofuels and Renewable Energy Technologies, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415, USA)

  • Sabrina Spatari

    (Civil, Architectural and Environmental Engineering, Drexel University, Philadelphia, PA 19104, USA)

Abstract

To meet Energy Independence and Security Act (EISA) cellulosic biofuel mandates, the United States will require an annual domestic supply of about 242 million Mg of biomass by 2022. To improve the feedstock logistics of lignocellulosic biofuels in order to access available biomass resources from areas with varying yields, commodity systems have been proposed and designed to deliver quality-controlled biomass feedstocks at preprocessing “depots”. Preprocessing depots densify and stabilize the biomass prior to long-distance transport and delivery to centralized biorefineries. The logistics of biomass commodity supply chains could introduce spatially variable environmental impacts into the biofuel life cycle due to needing to harvest, move, and preprocess biomass from multiple distances that have variable spatial density. This study examines the uncertainty in greenhouse gas (GHG) emissions of corn stover logistics within a bio-ethanol supply chain in the state of Kansas, where sustainable biomass supply varies spatially. Two scenarios were evaluated each having a different number of depots of varying capacity and location within Kansas relative to a central commodity-receiving biorefinery to test GHG emissions uncertainty. The first scenario sited four preprocessing depots evenly across the state of Kansas but within the vicinity of counties having high biomass supply density. The second scenario located five depots based on the shortest depot-to-biorefinery rail distance and biomass availability. The logistics supply chain consists of corn stover harvest, collection and storage, feedstock transport from field to biomass preprocessing depot, preprocessing depot operations, and commodity transport from the biomass preprocessing depot to the biorefinery. Monte Carlo simulation was used to estimate the spatial uncertainty in the feedstock logistics gate-to-gate sequence. Within the logistics supply chain GHG emissions are most sensitive to the transport of the densified biomass, which introduces the highest variability (0.2–13 g CO 2 e/MJ) to life cycle GHG emissions. Moreover, depending upon the biomass availability and its spatial density and surrounding transportation infrastructure (road and rail), logistics can increase the variability in life cycle environmental impacts for lignocellulosic biofuels. Within Kansas, life cycle GHG emissions could range from 24 g CO 2 e/MJ to 41 g CO 2 e/MJ depending upon the location, size and number of preprocessing depots constructed. However, this range can be minimized through optimizing the siting of preprocessing depots where ample rail infrastructure exists to supply biomass commodity to a regional biorefinery supply system.

Suggested Citation

  • Long Nguyen & Kara G. Cafferty & Erin M. Searcy & Sabrina Spatari, 2014. "Uncertainties in Life Cycle Greenhouse Gas Emissions from Advanced Biomass Feedstock Logistics Supply Chains in Kansas," Energies, MDPI, vol. 7(11), pages 1-22, November.
    • Handle: RePEc:gam:jeners:v:7:y:2014:i:11:p:7125-7146:d:41952
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    References listed on IDEAS

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    1. Uria-Martinez, Rocio & Leiby, Paul, 2012. "Advanced Biofuels System Configuration In The U.S.: Cost And Performance Tradeoffs," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 125005, Agricultural and Applied Economics Association.
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    4. Adam J. Liska & Haishun Yang & Maribeth Milner & Steve Goddard & Humberto Blanco-Canqui & Matthew P. Pelton & Xiao X. Fang & Haitao Zhu & Andrew E. Suyker, 2014. "Biofuels from crop residue can reduce soil carbon and increase CO2 emissions," Nature Climate Change, Nature, vol. 4(5), pages 398-401, May.
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    Cited by:

    1. Yuxi Wang & Jingxin Wang & Xufeng Zhang & Shawn Grushecky, 2020. "Environmental and Economic Assessments and Uncertainties of Multiple Lignocellulosic Biomass Utilization for Bioenergy Products: Case Studies," Energies, MDPI, vol. 13(23), pages 1-20, November.
    2. Fengli Zhang & Dana M. Johnson & Jinjiang Wang, 2015. "Life-Cycle Energy and GHG Emissions of Forest Biomass Harvest and Transport for Biofuel Production in Michigan," Energies, MDPI, vol. 8(4), pages 1-14, April.
    3. Zhao, Yan & Damgaard, Anders & Xu, Yingjie & Liu, Shan & Christensen, Thomas H., 2019. "Bioethanol from corn stover – Global warming footprint of alternative biotechnologies," Applied Energy, Elsevier, vol. 247(C), pages 237-253.
    4. Rui Zhao & Yiyun Liu & Zhenyan Zhang & Sidai Guo & Ming-Lang Tseng & Kuo-Jui Wu, 2018. "Enhancing Eco-Efficiency of Agro-Products’ Closed-Loop Supply Chain under the Belt and Road Initiatives: A System Dynamics Approach," Sustainability, MDPI, vol. 10(3), pages 1-15, March.
    5. Barbosa-Póvoa, Ana Paula & da Silva, Cátia & Carvalho, Ana, 2018. "Opportunities and challenges in sustainable supply chain: An operations research perspective," European Journal of Operational Research, Elsevier, vol. 268(2), pages 399-431.
    6. Espinoza Pérez, Andrea Teresa & Camargo, Mauricio & Narváez Rincón, Paulo César & Alfaro Marchant, Miguel, 2017. "Key challenges and requirements for sustainable and industrialized biorefinery supply chain design and management: A bibliographic analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 350-359.
    7. José Eduardo Galve & Daniel Elduque & Carmelo Pina & Carlos Javierre, 2016. "Sustainable Supply Chain Management: The Influence of Disposal Scenarios on the Environmental Impact of a 2400 L Waste Container," Sustainability, MDPI, vol. 8(6), pages 1-12, June.
    8. Baral, Nawa Raj & Quiroz-Arita, Carlos & Bradley, Thomas H., 2017. "Uncertainties in corn stover feedstock supply logistics cost and life-cycle greenhouse gas emissions for butanol production," Applied Energy, Elsevier, vol. 208(C), pages 1343-1356.
    9. Sabrina Spatari & Alexander Stadel & Paul R. Adler & Saurajyoti Kar & William J. Parton & Kevin B. Hicks & Andrew J. McAloon & Patrick L. Gurian, 2020. "The Role of Biorefinery Co-Products, Market Proximity and Feedstock Environmental Footprint in Meeting Biofuel Policy Goals for Winter Barley-to-Ethanol," Energies, MDPI, vol. 13(9), pages 1-15, May.

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