Environment, Development and Sustainability

, Volume 18, Issue 5, pp 1323–1337 | Cite as

Using stated preference methods to assess environmental impacts of forest biomass power plants in Portugal

  • Anabela Botelho
  • Lina Lourenço-Gomes
  • Lígia Pinto
  • Sara Sousa
  • Marieta Valente


As a renewable energy source, the use of forest biomass for electricity generation is advantageous in comparison with fossil fuels; however, the activity of forest biomass power plants causes adverse impacts, affecting particularly neighbouring communities. The main objective of this study is to estimate the effects of the activity of forest biomass power plants on the welfare of two groups of stakeholders, namely local residents and the general population. To this end, we apply two stated preference methods: contingent valuation and discrete choice experiments, respectively. The former method was applied to estimate the minimum compensation residents of neighbouring communities of two forest biomass power plants in Portugal would be willing to accept. The latter method was applied among the general population to estimate their willingness to pay to avoid specific environmental impacts. The results show that the presence of the selected facilities affects individuals’ well-being. On the other hand, in the discrete choice experiments conducted among the general population all impacts considered were valued, in particular odour and fauna and flora impacts. The results of this study stress the importance of performing an equity analysis of the welfare effects on different groups of stakeholders from the installation of forest biomass power plants, as their effects on welfare are location and impact specific. Policy makers should take into account the views of all stakeholders either directly or indirectly involved when deciding crucial issues regarding the sitting of new forest biomass power plants, in order to achieve an efficient and equitable outcome.


Forest biomass Stated preference methods Contingent valuation Discrete choice experiments Environmental impacts Public attitudes 


  1. Adamowicz, W., Louviere, J., & Williams, M. (1994). Combining revealed and stated preference methods for valuing environmental amenities. Journal of Environmental Economics and Management, 26, 271–292.CrossRefGoogle Scholar
  2. Armolaitis, K., Varnagiryte-Kabasinskiene, I., Stupak, I., Kukkola, M., Miksys, V., & Wojcik, J. (2013). Carbon and nutrients of Scots pine stands on sandy soils in Lithuania in relation to bioenergy sustainability. Biomass and Bioenergy, 54, 250–259.CrossRefGoogle Scholar
  3. Arrow, K., Solow, R., Portney, P., Leamer, E., Radner, R., & Schuman, H. (1993). Report of the NOAA Panel on Contingent Valuation. Federal Register, 58(10), 4601–4614.Google Scholar
  4. Atkinson, G., & Mourato, S. (2008). Environmental cost-benefit analysis. Annual Review of Environment and Resources, 33, 317–344.CrossRefGoogle Scholar
  5. Bateman, I., Carson, R., Day, B., Hanemann, M., Hanley, N., Hett, T., et al. (2002). Economic valuation with stated preference techniques: A manual. Edwar Elgar: Cheltenham.CrossRefGoogle Scholar
  6. Botelho, A., Lourenço-Gomes, L., Pinto, L.M.C., & Sousa, S. (2014), How to design reliable discrete choice surveys: The use of qualitative research methods. In 2nd international conference on project evaluationICOPEV 2014, organized by CGIT—Research Centre for Industrial and Technology Management, School of Engineering of University of Minho, 26–27 June 2014, Guimarães.Google Scholar
  7. Botelho, A., Pinto, L. M. C., & Sousa, P. (2013). Valuing wind farms’ environmental impacts by geographical distance: A contingent valuation study in Portugal. Working Paper NIMA 52, Braga, Universidade do Minho, 2013.Google Scholar
  8. CAM—Comissão de Agricultura e Mar (2013). Relatório: Grupo de Trabalho da Biomassa, Junho de 2013. Edição: Assembleia da República.Google Scholar
  9. Cameron, A. C., & Trivedi, P. K. (2005). Microeconometrics: Methods and applications. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  10. Cameron, A. C., & Trivedi, P. K. (2009). Microeconometrics using Stata. College Station, TX: Stata Press.Google Scholar
  11. Carneiro, P., & Ferreira, P. (2012). The economic, environmental and strategic value of biomass. Renewable Energy, 44, 17–22.CrossRefGoogle Scholar
  12. DGEG—Direcção Geral de Energia e Geologia (2007). Energias Renováveis em Portugal. Renewable Energy in Portugal.Google Scholar
  13. Dockerty, T., Appleton, K., & Lovett, A. (2012). Public opinion on energy crops in the landscape: Considerations for the expansion of renewable energy from biomass. Journal of Environmental Planning and Management, 55(9), 1134–1158.CrossRefGoogle Scholar
  14. Enersilva (2007). EnersilvaPromoção do uso da Biomassa Florestal para fins energéticos no sudoeste da Europa, 20042007. Projecto Enersilva.Google Scholar
  15. Evans, A., Strezov, V., & Evans, T. J. (2010). Sustainability considerations for electricity generation from biomass. Renewable and Sustainable Energy Reviews, 14(5), 1419–1427.CrossRefGoogle Scholar
  16. Ferreira, S., Moreira, N. A., & Monteiro, E. (2009). Bioenergy overview for Portugal. Biomass and Bioenergy, 33(11), 1567–1576.CrossRefGoogle Scholar
  17. Greene, W. (2012). NLOGIT, version 5.0. Reference guide. Plainview, NY: Econometric Software, Inc.Google Scholar
  18. Haab, T. C., Interis, M. G., Petrolia, D. R., & Whitehead, J. C. (2013). From hopeless to curious? Thoughts on Hausman’s “Dubious to Hopeless” critique of contingent valuation. Applied Economic Perspectives and Policy, 35(4), 593–612.CrossRefGoogle Scholar
  19. Hanley, N., Wright, R. E., & Adamowicz, V. (1998). Using choice experiments to value the environment: Design issues, current experience and future prospects. Environmental & Resource Economics, 11(3–4), 413–428.CrossRefGoogle Scholar
  20. Hanley, N., Wright, R. E., & Mourato, S. (2001). Choice modelling approaches: A superior alternative for environmental valuation. Journal of Economic Surveys, 15(3), 435–462.CrossRefGoogle Scholar
  21. Hensher, D. A., & Greene, W. H. (2003). The mixed logit model: The state of practice. Transportation, 30(2), 133–176.CrossRefGoogle Scholar
  22. ICNF—Instituto da Conservação da Natureza e das Florestas (2013). Inventário Florestal Nacional: Áreas dos usos do solo e das espécies florestais de Portugal continental (resultados provisórios).Google Scholar
  23. Jonsell, M. (2007). Effects on biodiversity of forest fuel extraction, governed by processes working on a large scale. Biomass and Bioenergy, 31, 726–732.CrossRefGoogle Scholar
  24. Lamers, P., Thiffault, E., Paré, D., & Junginger, M. (2013). Feedstock specific environmental risk levels related to biomass extraction for energy boreal and temperate forests. Biomass and Bioenergy, 55, 212–226.CrossRefGoogle Scholar
  25. Lancaster, K. (1966). A new approach to consumer theory. Journal of Political Economy, 84, 132–157.CrossRefGoogle Scholar
  26. Mabee, W. E., & Saddler, J. N. (2007). Forests and energy in OECD countries, Food and Agriculture Organization of the United NationsForests and Energy working paper 1.Google Scholar
  27. McFadden, D., & Train, K. (2000). Mixed MNL models for discrete response. Journal of Applied Econometrics, 15, 447–470.CrossRefGoogle Scholar
  28. Mendesohn, R., & Olmstead, S. (2009). The economic valuation of environmental amenities and disamenities: Methods and applications. Annual Review of Environment and Resources, 34, 325–347.CrossRefGoogle Scholar
  29. Miranda, M., & Hale, B. (2001). Protecting the forest from the trees: The social costs of energy production in Sweden. Energy, 26, 869–889.CrossRefGoogle Scholar
  30. Mitchell, R. C., & Carson, R. T. (1989). Using surveys to value public goods: The contingent valuation method. Resources for the Future: Washington DC.Google Scholar
  31. OECD/IEA (1998). Benign energy? The environmental implications of renewables. Organisation for Economic Co-operation and Development and International Energy Agency.Google Scholar
  32. Owens, S. (2004). Siting, sustainable development and social priorities. Journal of Risk Research, 7(2), 101–114.CrossRefGoogle Scholar
  33. Patrão, G. (2011). The Portuguese energy strategy and the role of biomass. In Workshop BIOGAIR: Biomass on the Portuguese energy sector. University of Aveiro, Aveiro, 13th of May, 2011.Google Scholar
  34. Pearce, D., Atkinson, G., & Mourato, S. (2006). Cost-benefit analysis and the environment: Recent developments. Paris: OECD.Google Scholar
  35. Pearce, D., Mourato, S., & Wright, R. (2001). Environmental cost-benefit analysis: Recent developments. Paris: OECD.Google Scholar
  36. Revelt, D., & Train, K. (1998). Mixed logit with repeated choices: Households’ choices of appliance efficiency level. Review of Economics and Statistics, 80(4), 647–657.CrossRefGoogle Scholar
  37. Schlamadinger, B., & Marland, G. (2001). The role of bioenergy and related land use in global net CO2 emissions. In Woody biomass as an energy sourcechallenges in Europe, EFI Proceedings no 39, pp. 21–27.Google Scholar
  38. Siitonen, J. (2001). Forest management, Coarse Woody Debris and Saproxylic Organisms: Fennoscandian Boreal forests as an example. Ecological Bulletins, 49, 11–41.Google Scholar
  39. UN (2007). Sustainable bioenergy: A framework for decision makers. United Nations—Energy.Google Scholar
  40. Upreti, B., & Horst, D. (2004). National renewable energy policy and local opposition in the UK: The failed development of a biomass electricity plant. Biomass and Bioenergy, 26, 61–69.CrossRefGoogle Scholar
  41. Whitehead, J. C. (2006). A Practitioner’s Primer on the Contingent Valuation Method. In A. Alberini & J. R. Kahn (Eds.), Handbook on contingent valuation (pp. 66–91). Cheltenham: Edward Elgar.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Anabela Botelho
    • 1
  • Lina Lourenço-Gomes
    • 2
  • Lígia Pinto
    • 3
  • Sara Sousa
    • 4
  • Marieta Valente
    • 3
  1. 1.DEGEI and GOVCOPPUniversity of AveiroAveiroPortugal
  2. 2.CETRAD and DESGUniversity of Trás-os-Montes and Alto DouroVila RealPortugal
  3. 3.EEG and NIMAUniversity of MinhoBragaPortugal
  4. 4.ISCACPolytechnic Institute of CoimbraCoimbraPortugal

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