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Implications of Expanding Bioenergy Production from Wood in British Columbia: An Application of a Regional Wood Fibre Allocation Model

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  • Stennes, Brad
  • Niquidet, Kurt
  • van Kooten, G. Cornelis
Abstract
Energy has been produced from woody biomass in British Columbia for many decades, but it was used primarily within the pulp and paper sector, using residual streams from timber processing, to create heat and electricity for on-site use. More recently, there has been limited stand-alone electricity production and increasing capacity to produce wood pellets, with both using ‘waste’ from the sawmill sector. Hence, most of the low-cost feedstock sources associated with traditional timber processing is now fully employed. While previous studies model bioenergy production in isolation, we employ a transportation model of the BC forest sector with 24 regions to demonstrate that it is necessary to consider the interaction between utilization of woody feedstock for pellet production and electricity generation and its traditional uses (e.g., production of pulp, oriented strand board, etc). We find that, despite the availability of large areas of mountain pine beetle killed timber, this wood does not enter the energy mix. Further expansion of biofeedstock for energy is met by a combination of woody debris collected at harvesting sites and/or bidding away of fibre from existing users.

Suggested Citation

  • Stennes, Brad & Niquidet, Kurt & van Kooten, G. Cornelis, 2009. "Implications of Expanding Bioenergy Production from Wood in British Columbia: An Application of a Regional Wood Fibre Allocation Model," Working Papers 50782, University of Victoria, Resource Economics and Policy.
    • Handle: RePEc:ags:uvicwp:50782
    DOI: 10.22004/ag.econ.50782
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    References listed on IDEAS

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    1. Anthony Mogus & Brad Stennes & G. Cornelis van Kooten, 2005. "Canada-US Softwood Lumber Trade Revisited: Examining the Role of Substitution Bias in the Context of a Spatial Price Equilibrium Framework," Working Papers 2005-08, University of Victoria, Department of Economics, Resource Economics and Policy Analysis Research Group.
    2. DeCarolis, Joseph F. & Keith, David W., 2005. "The Costs of Wind's Variability: Is There a Threshold?," The Electricity Journal, Elsevier, vol. 18(1), pages 69-77.
    3. John H. Duloy & Roger D. Norton, 1975. "Prices and Incomes in Linear Programming Models," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 57(4), pages 591-600.
    4. G. Cornelis van Kooten & Alison Eagle & James Manley & Tara Smolak, 2004. "How Costly are Carbon Offsets? A Meta-Analysis of Forest Carbon Sinks," Working Papers 2004-01, University of Victoria, Department of Economics, Resource Economics and Policy Analysis Research Group.
    5. van Kooten, G. Cornelis & Eagle, Alison J. & Manley, James G. & Smolak, Tara M., 2004. "How Costly Are Carbon Offsets? A Meta-Analysis Of Carbon Forest Sinks," Working Papers 18166, University of Victoria, Resource Economics and Policy.
    6. Niquidet, Kurt & Stennes, Brad & van Kooten, G. Cornelis, 2008. "Bio-energy from Mountain Pine Beetle Timber and Forest Residuals: The Economics Story," Working Papers 45476, University of Victoria, Resource Economics and Policy.
    7. Stennes, Brad & Wilson, Bill, 2005. "An analysis of lumber trade restrictions in North America: application of a spatial equilibrium model," Forest Policy and Economics, Elsevier, vol. 7(3), pages 297-308, March.
    8. Kumar, Amit & Flynn, Peter & Sokhansanj, Shahab, 2008. "Biopower generation from mountain pine infested wood in Canada: An economical opportunity for greenhouse gas mitigation," Renewable Energy, Elsevier, vol. 33(6), pages 1354-1363.
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    Cited by:

    1. G. Cornelis van Kooten, 2017. "The Policy Challenge of Creating Forest Offset Credits: A Case Study from the Interior of British Columbia," Working Papers 2017-02, University of Victoria, Department of Economics, Resource Economics and Policy Analysis Research Group.
    2. G. Cornelis van Kooten, 2013. "Economic analysis of feed-in tariffs for generating electricity from renewable energy sources," Chapters, in: Roger Fouquet (ed.), Handbook on Energy and Climate Change, chapter 9, pages 224-253, Edward Elgar Publishing.
    3. Emily Hope & Bruno Gagnon & Vanja Avdić, 2020. "Assessment of the Impact of Climate Change Policies on the Market for Forest Industrial Residues," Sustainability, MDPI, vol. 12(5), pages 1-20, February.
    4. van Kooten, G. Cornelis, 2017. "The Economic Challenge of Mitigating Climate Change through Forestry Activities," 2017 International Congress, August 28-September 1, 2017, Parma, Italy 261275, European Association of Agricultural Economists.
    5. G. Cornelis van Kooten, 2011. "Biotechnology in Agriculture and Forestry: Economic Perspectives," Working Papers 2011-05, University of Victoria, Department of Economics, Resource Economics and Policy Analysis Research Group.
    6. Miguel RIVIERE & Sylvain CAURLA, 2018. "Integrating non-timber objectives into bio-economic models of the forest sector: a review of recent innovations and current shortcomings," Working Papers of BETA 2018-26, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    7. Craig M.T. Johnston & G. Cornelis van Kooten, 2014. "Carbon Neutrality of Hardwood and Softwood Biomass: Issues of Temporal Preference," Working Papers 2014-06, University of Victoria, Department of Economics, Resource Economics and Policy Analysis Research Group.
    8. G. Cornelis van Kooten, 2016. "California Dreaming: The Economics of Renewable Energy," Working Papers 2016-05, University of Victoria, Department of Economics, Resource Economics and Policy Analysis Research Group.
    9. Buongiorno, Joseph & Raunikar, Ronald & Zhu, Shushuai, 2011. "Consequences of increasing bioenergy demand on wood and forests: An application of the Global Forest Products Model," Journal of Forest Economics, Elsevier, vol. 17(2), pages 214-229, April.

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    More about this item

    Keywords

    Environmental Economics and Policy; Resource /Energy Economics and Policy;

    JEL classification:

    • Q23 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Forestry
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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