Investigating the future supply distribution of industrial grade wood pellets in the global bioenergy market
Abstract
This study analyzes the potential resource distribution in global competitive feedstock markets for industrial grade wood pellets. Based on historic trade patterns and expected future production and demand structures, a set of potential buyers and sellers of industrial grade wood pellets are simulated for 2022, 2030, and 2040. In contrast to previous trade modeling efforts, this study assumes a fully competitive market, i.e., excluding long-term contract arrangements, to show resource distributions under a potential future commodity market. This is done via a non-cooperative bi-level Stackelberg leader-follower game model. Of particular interest is the potential impact of international feedstock competition on the availability of US feedstock resources. The model results show that the main destinations for US wood pellet exports typically pay 10-20% more per tonne than the domestic market. The results show that domestic wood pellets are available to US industry at prices higher than the expected $88 per tonne delivered.
- Authors:
-
- Idaho National Lab. (INL), Idaho Falls, ID (United States)
- Utrecht Univ., Utrecht (The Netherlands)
- Publication Date:
- Research Org.:
- Idaho National Lab. (INL), Idaho Falls, ID (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Sustainable Transportation Office. Bioenergy Technologies Office
- OSTI Identifier:
- 1473707
- Report Number(s):
- INL/JOU-16-38378-Rev000
Journal ID: ISSN 1759-7269
- Grant/Contract Number:
- AC07-05ID14517
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Biofuels
- Additional Journal Information:
- Journal Name: Biofuels; Journal ID: ISSN 1759-7269
- Publisher:
- Taylor & Francis
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 09 BIOMASS FUELS; Stackelberg game, bi-level programming, international trade, wood pellets
Citation Formats
Roni, Mohammad S., Lamers, Patrick, and Hoefnagels, Ric. Investigating the future supply distribution of industrial grade wood pellets in the global bioenergy market. United States: N. p., 2018.
Web. doi:10.1080/17597269.2018.1432268.
Roni, Mohammad S., Lamers, Patrick, & Hoefnagels, Ric. Investigating the future supply distribution of industrial grade wood pellets in the global bioenergy market. United States. https://doi.org/10.1080/17597269.2018.1432268
Roni, Mohammad S., Lamers, Patrick, and Hoefnagels, Ric. Thu .
"Investigating the future supply distribution of industrial grade wood pellets in the global bioenergy market". United States. https://doi.org/10.1080/17597269.2018.1432268. https://www.osti.gov/servlets/purl/1473707.
@article{osti_1473707,
title = {Investigating the future supply distribution of industrial grade wood pellets in the global bioenergy market},
author = {Roni, Mohammad S. and Lamers, Patrick and Hoefnagels, Ric},
abstractNote = {This study analyzes the potential resource distribution in global competitive feedstock markets for industrial grade wood pellets. Based on historic trade patterns and expected future production and demand structures, a set of potential buyers and sellers of industrial grade wood pellets are simulated for 2022, 2030, and 2040. In contrast to previous trade modeling efforts, this study assumes a fully competitive market, i.e., excluding long-term contract arrangements, to show resource distributions under a potential future commodity market. This is done via a non-cooperative bi-level Stackelberg leader-follower game model. Of particular interest is the potential impact of international feedstock competition on the availability of US feedstock resources. The model results show that the main destinations for US wood pellet exports typically pay 10-20% more per tonne than the domestic market. The results show that domestic wood pellets are available to US industry at prices higher than the expected $88 per tonne delivered.},
doi = {10.1080/17597269.2018.1432268},
journal = {Biofuels},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {2}
}
Figures / Tables:

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