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Switchgrass-Based Bioethanol Productivity and Potential Environmental Impact from Marginal Lands in China

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  • Xun Zhang

    (Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer and Information Engineering, Beijing Technology and Business University, No. 11 Fucheng Road, Haidian District, Beijing 100048, China
    Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China)

  • Jingying Fu

    (Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China
    College of Resource and Environment, University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, China)

  • Gang Lin

    (Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China)

  • Dong Jiang

    (Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China
    College of Resource and Environment, University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, China)

  • Xiaoxi Yan

    (Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China
    College of Resource and Environment, University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, China)

Abstract

Switchgrass displays an excellent potential to serve as a non-food bioenergy feedstock for bioethanol production in China due to its high potential yield on marginal lands. However, few studies have been conducted on the spatial distribution of switchgrass-based bioethanol production potential in China. This study created a land surface process model (Environmental Policy Integrated Climate GIS (Geographic Information System)-based (GEPIC) model) coupled with a life cycle analysis (LCA) to explore the spatial distribution of potential bioethanol production and present a comprehensive analysis of energy efficiency and environmental impacts throughout its whole life cycle. It provides a new approach to study the bioethanol productivity and potential environmental impact from marginal lands based on the high spatial resolution GIS data, and this applies not only to China, but also to other regions and to other types of energy plant. The results indicate that approximately 59 million ha of marginal land in China are suitable for planting switchgrass, and 22 million tons of ethanol can be produced from this land. Additionally, a potential net energy gain (NEG) of 1.75 x 106 million MJ will be achieved if all of the marginal land can be used in China, and Yunnan Province offers the most significant one that accounts for 35% of the total. Finally, this study obtained that the total environmental effect index of switchgrass-based bioethanol is the equivalent of a population of approximately 20,300, and a reduction in the global warming potential (GWP) is the most significant environmental impact.

Suggested Citation

  • Xun Zhang & Jingying Fu & Gang Lin & Dong Jiang & Xiaoxi Yan, 2017. "Switchgrass-Based Bioethanol Productivity and Potential Environmental Impact from Marginal Lands in China," Energies, MDPI, vol. 10(2), pages 1-15, February.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:2:p:260-:d:91051
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    References listed on IDEAS

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    Cited by:

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    2. Mengmeng Hao & Jingying Fu & Dong Jiang & Xiaoxi Yan & Shuai Chen & Fangyu Ding, 2018. "Sustainable Development of Sweet Sorghum-Based Fuel Ethanol from the Perspective of Water Resources in China," Sustainability, MDPI, vol. 10(10), pages 1-15, September.
    3. Francis Rathinam & Sayak Khatua & Zeba Siddiqui & Manya Malik & Pallavi Duggal & Samantha Watson & Xavier Vollenweider, 2021. "Using big data for evaluating development outcomes: A systematic map," Campbell Systematic Reviews, John Wiley & Sons, vol. 17(3), September.
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    5. Francesco Latterini & Walter Stefanoni & Alessandro Suardi & Vincenzo Alfano & Simone Bergonzoli & Nadia Palmieri & Luigi Pari, 2020. "A GIS Approach to Locate a Small Size Biomass Plant Powered by Olive Pruning and to Estimate Supply Chain Costs," Energies, MDPI, vol. 13(13), pages 1-17, July.
    6. Manju Dhakad Tanwar & Felipe Andrade Torres & Ali Mubarak Alqahtani & Pankaj Kumar Tanwar & Yashas Bhand & Omid Doustdar, 2023. "Promising Bioalcohols for Low-Emission Vehicles," Energies, MDPI, vol. 16(2), pages 1-22, January.
    7. Yakubu Abdul-Salam & Melf-Hinrich Ehlers & Jelte Harnmeijer, 2017. "Anaerobic Digestion of Feedstock Grown on Marginal Land: Break-Even Electricity Prices," Energies, MDPI, vol. 10(9), pages 1-21, September.

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