Citation Information

  • Title : Bioenergy crop productivity and potential climate change mitigation from marginal lands in the United States: An ecosystem modeling perspective
  • Source : Original Research
  • Publisher : Wiley Online
  • Volume : 7
  • Issue : 6
  • Year : 2015
  • DOI : 10.1111/gcbb.12212
  • ISBN : 1757-1693
  • Document Type : Journal Article
  • Language : English
  • Authors:
    • Cai, X.
    • Zhuang, Q.
    • Qin, Z.
  • Climates: Humid subtropical (Cwa, Cfa).
  • Cropping Systems:
  • Countries: USA.

Summary

Growing biomass feedstocks from marginal lands is becoming an increasingly attractive choice for producing biofuel as an alternative energy to fossil fuels. Here, we used a biogeochemical model at ecosystem scale to estimate crop productivity and greenhouse gas (GHG) emissions from bioenergy crops grown on marginal lands in the United States. Two broadly tested cellulosic crops, switchgrass, and Miscanthus, were assumed to be grown on the abandoned land and mixed crop-vegetation land with marginal productivity. Production of biomass and biofuel as well as net carbon exchange and nitrous oxide emissions were estimated in a spatially explicit manner. We found that, cellulosic crops, especially Miscanthus could produce a considerable amount of biomass, and the effective ethanol yield is high on these marginal lands. For every hectare of marginal land, switchgrass and Miscanthus could produce 1.0-2.3kl and 2.9-6.9kl ethanol, respectively, depending on nitrogen fertilization rate and biofuel conversion efficiency. Nationally, both crop systems act as net GHG sources. Switchgrass has high global warming intensity (100-390g CO(2)eql(-1) ethanol), in terms of GHG emissions per unit ethanol produced. Miscanthus, however, emits only 21-36g CO(2)eq to produce every liter of ethanol. To reach the mandated cellulosic ethanol target in the United States, growing Miscanthus on the marginal lands could potentially save land and reduce GHG emissions in comparison to growing switchgrass. However, the ecosystem modeling is still limited by data availability and model deficiencies, further efforts should be made to classify crop-specific marginal land availability, improve model structure, and better integrate ecosystem modeling into life cycle assessment.

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