IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v69y2018icp456-470.html
   My bibliography  Save this article

Economic and policy factors driving adoption of institutional woody biomass heating systems in the U.S

Author

Listed:
  • Young, Jesse D.
  • Anderson, Nathaniel M.
  • Naughton, Helen T.
  • Mullan, Katrina

Abstract

Abundant stocks of woody biomass that are associated with active forest management can be used as fuel for bioenergy in many applications. Though factors driving large-scale biomass use in industrial settings have been studied extensively, small-scale biomass combustion systems commonly used by institutions for heating have received less attention. A zero inflated negative binomial (ZINB) model is employed to identify economic and policy factors favorable to installation and operation of these systems. This allows us to determine the effectiveness of existing policies and identify locations where conditions offer the greatest potential for additional promotion of biomass use. Adoption is driven by heating needs, fossil fuel prices, and proximity to woody biomass resources, specifically logging residues, National Forests, and fuel treatments under the National Fire Plan.

Suggested Citation

  • Young, Jesse D. & Anderson, Nathaniel M. & Naughton, Helen T. & Mullan, Katrina, 2018. "Economic and policy factors driving adoption of institutional woody biomass heating systems in the U.S," Energy Economics, Elsevier, vol. 69(C), pages 456-470.
  • Handle: RePEc:eee:eneeco:v:69:y:2018:i:c:p:456-470
    DOI: 10.1016/j.eneco.2017.11.020
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988317304127
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2017.11.020?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yoo, James & Ready, Richard C., 2014. "Preference heterogeneity for renewable energy technology," Energy Economics, Elsevier, vol. 42(C), pages 101-114.
    2. Loeffler, Dan & Anderson, Nathaniel, 2014. "Emissions tradeoffs associated with cofiring forest biomass with coal: A case study in Colorado, USA," Applied Energy, Elsevier, vol. 113(C), pages 67-77.
    3. Touš, Michal & Pavlas, Martin & Stehlík, Petr & Popela, Pavel, 2011. "Effective biomass integration into existing combustion plant," Energy, Elsevier, vol. 36(8), pages 4654-4662.
    4. Aguilar, Francisco X. & Goerndt, Michael E. & Song, Nianfu & Shifley, Stephen, 2012. "Internal, external and location factors influencing cofiring of biomass with coal in the U.S. northern region," Energy Economics, Elsevier, vol. 34(6), pages 1790-1798.
    5. Bridgwater, A. V. & Toft, A. J. & Brammer, J. G., 2002. "A techno-economic comparison of power production by biomass fast pyrolysis with gasification and combustion," Renewable and Sustainable Energy Reviews, Elsevier, vol. 6(3), pages 181-246, September.
    6. Jenkins, Timothy L. & Sutherland, John W., 2014. "A cost model for forest-based biofuel production and its application to optimal facility size determination," Forest Policy and Economics, Elsevier, vol. 38(C), pages 32-39.
    7. Garay, Aldo M. & Hashimoto, Elizabeth M. & Ortega, Edwin M.M. & Lachos, Víctor H., 2011. "On estimation and influence diagnostics for zero-inflated negative binomial regression models," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1304-1318, March.
    8. Hitaj, Claudia, 2013. "Wind power development in the United States," Journal of Environmental Economics and Management, Elsevier, vol. 65(3), pages 394-410.
    9. Selden Thomas M. & Song Daqing, 1994. "Environmental Quality and Development: Is There a Kuznets Curve for Air Pollution Emissions?," Journal of Environmental Economics and Management, Elsevier, vol. 27(2), pages 147-162, September.
    10. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    11. Song, Nianfu & Aguilar, Francisco X. & Shifley, Stephen R. & Goerndt, Michael E., 2012. "Factors affecting wood energy consumption by U.S. households," Energy Economics, Elsevier, vol. 34(2), pages 389-397.
    12. Jay Gregg & Steven Smith, 2010. "Global and regional potential for bioenergy from agricultural and forestry residue biomass," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 15(3), pages 241-262, March.
    13. Rummer, Bob, 2008. "Assessing the cost of fuel reduction treatments: A critical review," Forest Policy and Economics, Elsevier, vol. 10(6), pages 355-362, August.
    14. Salomón, Marianne & Savola, Tuula & Martin, Andrew & Fogelholm, Carl-Johan & Fransson, Torsten, 2011. "Small-scale biomass CHP plants in Sweden and Finland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4451-4465.
    15. Pavlas, Martin & Stehlík, Petr & Oral, Jaroslav & Šikula, Jiří, 2006. "Integrating renewable sources of energy into an existing combined heat and power system," Energy, Elsevier, vol. 31(13), pages 2499-2511.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kuznetsov, G.V. & Malyshev, D. Yu & Syrodoy, S.V. & Gutareva, N. Yu & Purin, M.V. & Kostoreva, Zh. A., 2022. "Justification of the use of forest waste in the power industry as one of the components OF BIO-coal-water suspension fuel," Energy, Elsevier, vol. 239(PA).
    2. Golmohamadi, Hessam & Larsen, Kim Guldstrand & Jensen, Peter Gjøl & Hasrat, Imran Riaz, 2022. "Integration of flexibility potentials of district heating systems into electricity markets: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    3. Jesse D. Young & Nathaniel M. Anderson & Helen T. Naughton, 2018. "Influence of Policy, Air Quality, and Local Attitudes toward Renewable Energy on the Adoption of Woody Biomass Heating Systems," Energies, MDPI, vol. 11(11), pages 1-24, October.
    4. Wang, Kui & Zhang, Yuanyuan & Sekelj, Gasper & Hopke, Philip K., 2019. "Economic analysis of a field monitored residential wood pellet boiler heating system in New York State," Renewable Energy, Elsevier, vol. 133(C), pages 500-511.
    5. Flavio Andreoli Bonazzi & Sirio R.S. Cividino & Ilaria Zambon & Enrico Maria Mosconi & Stefano Poponi, 2018. "Building Energy Opportunity with a Supply Chain Based on the Local Fuel-Producing Capacity," Sustainability, MDPI, vol. 10(7), pages 1-15, June.
    6. Hu, Xun & Gholizadeh, Mortaza, 2020. "Progress of the applications of bio-oil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jesse D. Young & Nathaniel M. Anderson & Helen T. Naughton, 2018. "Influence of Policy, Air Quality, and Local Attitudes toward Renewable Energy on the Adoption of Woody Biomass Heating Systems," Energies, MDPI, vol. 11(11), pages 1-24, October.
    2. Derek S. Young & Andrew M. Raim & Nancy R. Johnson, 2017. "Zero-inflated modelling for characterizing coverage errors of extracts from the US Census Bureau's Master Address File," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(1), pages 73-97, January.
    3. González, Arnau & Riba, Jordi-Roger & Puig, Rita & Navarro, Pere, 2015. "Review of micro- and small-scale technologies to produce electricity and heat from Mediterranean forests׳ wood chips," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 143-155.
    4. Fabrice Gilles & Sabina Issehnane & Florent Sari, 2022. "Using short-term jobs as a way to find a regular job. What kind of role for local context?," TEPP Working Paper 2022-07, TEPP.
    5. Michael Greenstone & Rema Hanna, 2014. "Environmental Regulations, Air and Water Pollution, and Infant Mortality in India," American Economic Review, American Economic Association, vol. 104(10), pages 3038-3072, October.
    6. repec:hal:spmain:info:hdl:2441/dambferfb7dfprc9m052g20qh is not listed on IDEAS
    7. Tonini, Davide & Vadenbo, Carl & Astrup, Thomas Fruergaard, 2017. "Priority of domestic biomass resources for energy: Importance of national environmental targets in a climate perspective," Energy, Elsevier, vol. 124(C), pages 295-309.
    8. Nasreen, Samia & Anwar, Sofia & Ozturk, Ilhan, 2017. "Financial stability, energy consumption and environmental quality: Evidence from South Asian economies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 1105-1122.
    9. Khan, Syed Abdul Rehman & Zaman, Khalid & Zhang, Yu, 2016. "The relationship between energy-resource depletion, climate change, health resources and the environmental Kuznets curve: Evidence from the panel of selected developed countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 468-477.
    10. Paulo M. D. C. Parente & Richard J. Smith, 2021. "Quasi‐maximum likelihood and the kernel block bootstrap for nonlinear dynamic models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(4), pages 377-405, July.
    11. Cornelia Lawson, 2013. "Academic Inventions Outside the University: Investigating Patent Ownership in the UK," Industry and Innovation, Taylor & Francis Journals, vol. 20(5), pages 385-398, July.
    12. Opschoor, J. (Hans) B., 1995. "Ecospace and the fall and rise of throughput intensity," Ecological Economics, Elsevier, vol. 15(2), pages 137-140, November.
    13. Song, Tao & Zheng, Tingguo & Tong, Lianjun, 2008. "An empirical test of the environmental Kuznets curve in China: A panel cointegration approach," China Economic Review, Elsevier, vol. 19(3), pages 381-392, September.
    14. Giedrė Lapinskienė & Kęstutis Peleckis & Neringa Slavinskaitė, 2017. "Energy consumption, economic growth and greenhouse gas emissions in the European Union countries," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 18(6), pages 1082-1097, November.
    15. Vipin Arora & Shuping Shi, 2016. "Nonlinearities and tests of asset price bubbles," Empirical Economics, Springer, vol. 50(4), pages 1421-1433, June.
    16. Luiz Paulo Fávero & Joseph F. Hair & Rafael de Freitas Souza & Matheus Albergaria & Talles V. Brugni, 2021. "Zero-Inflated Generalized Linear Mixed Models: A Better Way to Understand Data Relationships," Mathematics, MDPI, vol. 9(10), pages 1-28, May.
    17. Da Fonseca José & Grasselli Martino & Ielpo Florian, 2014. "Estimating the Wishart Affine Stochastic Correlation Model using the empirical characteristic function," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(3), pages 1-37, May.
    18. Hansen, Lars Peter & Heaton, John & Luttmer, Erzo G J, 1995. "Econometric Evaluation of Asset Pricing Models," Review of Financial Studies, Society for Financial Studies, vol. 8(2), pages 237-274.
    19. Das, Marcel & van Soest, Arthur, 1999. "A panel data model for subjective information on household income growth," Journal of Economic Behavior & Organization, Elsevier, vol. 40(4), pages 409-426, December.
    20. Gillespie, Colin S., 2015. "Fitting Heavy Tailed Distributions: The poweRlaw Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 64(i02).
    21. Luis Garicano & Thomas N. Hubbard, 2016. "The Returns to Knowledge Hierarchies," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 32(4), pages 653-684.

    More about this item

    Keywords

    Institutions; Woody biomass; Heating; ZINB; Policy;
    All these keywords.

    JEL classification:

    • L73 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - Forest Products
    • L78 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - Government Policy
    • 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
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R53 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Public Facility Location Analysis; Public Investment and Capital Stock

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:69:y:2018:i:c:p:456-470. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.