Abstract

This paper develops a dynamic linear optimization framework to examine the optimal land allocation for two perennial crops, switchgrass and miscanthus, that can be co-fired with coal for electricity generation. Detailed spatial data at county level is used to determine the heterogeneous costs of producing and delivering biomass to power plants in Illinois over a 15-year period. A transportation module is incorporated in the model to link power plants to perennial crop growing areas such that power plants obtain their biomass input from the cheapest sources. A supply curve for bioenergy is thereby generated and the implications of various levels of production for farm income, subsidy payments and for the environment are analyzed. The environmental benefit in the form of reduced carbon-dioxide emissions from co-firing biomass with coal are determined by conducting a lifecycle analysis of carbon-dioxide emissions from electricity generated by co-firing bioenergy crops as compared to that generated from coal only. The lifecycle analysis includes the soil carbon sequestered by perennial grasses and the carbon emissions displaced by these grasses due to both conversion of land from row crops and co-firing the grasses with coal. Spatial variability in land use and in soil carbon sequestration potential of land use choices, and their policy implications are discussed.

Original languageEnglish (US)
Title of host publicationDynamics, Games and Science II
Subtitle of host publicationDYNA 2008, in Honor of Maurício Peixoto and David Rand, University of Minho, Braga, Portugal, September 8-12, 2008
EditorsMauricio Matos Peixoto, Alberto Adrego Pinto, David A Rand
PublisherSpringer
Pages471-501
Number of pages31
ISBN (Electronic)9783642147883
ISBN (Print)9783642147876, 9783662520024
DOIs
StatePublished - 2011

Publication series

NameSpringer Proceedings in Mathematics
Volume2
ISSN (Print)2190-5614
ISSN (Electronic)2190-5622

ASJC Scopus subject areas

  • General Mathematics
  • Statistics, Probability and Uncertainty

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