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Biomass supply chain management in North Carolina (part 1): predictive model for cropland conversion to biomass feedstocks

Authors :
Kevin R Caffrey
Mari S Chinn
Matthew W Veal
Source :
AIMS Energy, Vol 4, Iss 2, Pp 256-279 (2016)
Publication Year :
2016
Publisher :
AIMS Press, 2016.

Abstract

Increased interest in biomass cultivation requires detailed analysis of spatial production potential of possible biorefinery locations, with emphasis on feedstock production cost minimization. Integrated assessment of publicly available spatial data on current crop production, soil type, and yield potential, coupled with techno-economic production cost estimates, can support a functional method for rapid analysis of potential biorefinery sites. A novel predictive model was developed to determine cropland conversion using a probabilistic profit based equation for multiple biomass crops: giant reed, miscanthus, switchgrass, and sorghum (with either canola or barley as a winter crop). The three primary regions of North Carolina (Mountains, Piedmont, and Coastal Plain) were used as a case study and with a single parameter uncertainty analysis was completed. According to the model, the county chosen to represent the Coastal Plain (Duplin County) had the largest potential acreage that would be converted (15,071 ha, 7.1% total land, 9.3% of cropland) primarily to sorghum with canola as a winter crop. Large portions were also predicted to convert to giant reed and switchgrass, depending on the price and yield parameters used. The Piedmont (Granville County, 7697 ha, 5.5% total land, 6.9% cropland) and Mountain (Henderson County, 2117 ha, 2.2% total land, 2.3% cropland) regions were predicted to convert primarily to switchgrass acreage for biomass production, with much less available biomass overall compared to the Coastal Plain. This model provided meaningful insight into regional cropping systems and feedstock availability, allowing for improved business planning in designated regions. Determination of cropland conversion is imperative to develop realistic biomass logistical operations, which in conjunction can assist with rapid determination of profitable biomass availability. After this rapid analysis method is conducted in-depth on-ground biorefinery feasibility analysis can occur, ensuring resource are used only in locations with a high potential for available low cost biomass feedstocks.

Details

Language :
English
ISSN :
23338334
Volume :
4
Issue :
2
Database :
Directory of Open Access Journals
Journal :
AIMS Energy
Publication Type :
Academic Journal
Accession number :
edsdoj.821134822b94921b7c5fd1b1a428533
Document Type :
article
Full Text :
https://doi.org/10.3934/energy.2016.2.256