IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i6p2506-d335849.html
   My bibliography  Save this article

Greenhouse Gas Emissions in Norwegian Agriculture: The Regional and Structural Dimension

Author

Listed:
  • Klaus Mittenzwei

    (Department of Economics and Society, Norwegian Institute of Bioeconomy Research, Høgskoleveien 7, NO-1433 Ås, Norway)

Abstract

This paper studies the hypothesis that farm structure and the regional distribution of agricultural activity themselves have a significant impact on greenhouse gas (GHG) emissions from agriculture. Applying a dynamic model for the Norwegian agricultural sector covering the entire farm population, the model results support the hypothesis. Even without mitigation options, GHG emissions decline by 1.4 per cent if agriculture becomes regionally concentrated and increase by 1.5 per cent if a policy that favors a small-scale farm structure is put in place. Adding a carbon tax to a policy that leads to regional concentration, may help to reconcile competing policy objectives. A switch from animal production to crop production, and an extensification of animal production keeps a large resource base across the country while cutting GHG emissions.

Suggested Citation

  • Klaus Mittenzwei, 2020. "Greenhouse Gas Emissions in Norwegian Agriculture: The Regional and Structural Dimension," Sustainability, MDPI, vol. 12(6), pages 1-13, March.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:6:p:2506-:d:335849
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/6/2506/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/6/2506/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Arne Stolbjerg Drud, 1994. "CONOPT—A Large-Scale GRG Code," INFORMS Journal on Computing, INFORMS, vol. 6(2), pages 207-216, May.
    2. Mihaly Himics & Thomas Fellmann & Jesus Barreiro‐Hurle, 2020. "Setting Climate Action as the Priority for the Common Agricultural Policy: A Simulation Experiment," Journal of Agricultural Economics, Wiley Blackwell, vol. 71(1), pages 50-69, February.
    3. David S. Bullock & Klaus Mittenzwei & Paal B. Wangsness, 2016. "Balancing public goods in agriculture through safe minimum standards," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 43(4), pages 561-584.
    4. Ferris, Michael C. & Munson, Todd S., 2000. "Complementarity problems in GAMS and the PATH solver," Journal of Economic Dynamics and Control, Elsevier, vol. 24(2), pages 165-188, February.
    5. Klaus Mittenzwei & Wolfgang Britz, 2018. "Analysing Farm‐specific Payments for Norway using the Agrispace Model," Journal of Agricultural Economics, Wiley Blackwell, vol. 69(3), pages 777-793, September.
    6. Britz, Wolfgang, 2014. "A New Graphical User Interface Generator for Economic Models and its Comparison to Existing Approaches," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 63(04), pages 1-15, December.
    7. Britz, Wolfgang, 2014. "A New Graphical User Interface Generator for Economic Models and its Comparison to Existing Approaches," Journal of International Agricultural Trade and Development, Journal of International Agricultural Trade and Development, vol. 63(4).
    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. Hongpeng Guo & Sidong Xie & Chulin Pan, 2021. "The Impact of Planting Industry Structural Changes on Carbon Emissions in the Three Northeast Provinces of China," IJERPH, MDPI, vol. 18(2), pages 1-20, January.

    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. Klaus Mittenzwei & Wolfgang Britz, 2018. "Analysing Farm‐specific Payments for Norway using the Agrispace Model," Journal of Agricultural Economics, Wiley Blackwell, vol. 69(3), pages 777-793, September.
    2. Durand-Lasserve, Olivier & Almutairi, Hossa & Aljarboua, Abdullah & Pierru, Axel & Pradhan, Shreekar & Murphy, Frederic, 2023. "Hard-linking a top-down economic model with a bottom-up energy system for an oil-exporting country with price controls," Energy, Elsevier, vol. 266(C).
    3. Ni, Yuanming & Steinshamn, Stein I. & Kvamsdal, Sturla F., 2022. "Negative shocks in an age-structured bioeconomic model and how to deal with them," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 15-30.
    4. Britz, Wolfgang & Ciaian, Pavel & Gocht, Alexander & Kanellopoulos, Argyris & Kremmydas, Dimitrios & Müller, Marc & Petsakos, Athanasios & Reidsma, Pytrik, 2021. "A design for a generic and modular bio-economic farm model," Agricultural Systems, Elsevier, vol. 191(C).
    5. Huiyi Cao & Kamil A. Khan, 2023. "General convex relaxations of implicit functions and inverse functions," Journal of Global Optimization, Springer, vol. 86(3), pages 545-572, July.
    6. Duarte, Belmiro P.M. & Sagnol, Guillaume & Wong, Weng Kee, 2018. "An algorithm based on semidefinite programming for finding minimax optimal designs," Computational Statistics & Data Analysis, Elsevier, vol. 119(C), pages 99-117.
    7. Artur M. Schweidtmann & Alexander Mitsos, 2019. "Deterministic Global Optimization with Artificial Neural Networks Embedded," Journal of Optimization Theory and Applications, Springer, vol. 180(3), pages 925-948, March.
    8. Conrado Borraz-Sánchez & Russell Bent & Scott Backhaus & Hassan Hijazi & Pascal Van Hentenryck, 2016. "Convex Relaxations for Gas Expansion Planning," INFORMS Journal on Computing, INFORMS, vol. 28(4), pages 645-656, November.
    9. Andreas Lundell & Jan Kronqvist & Tapio Westerlund, 2022. "The supporting hyperplane optimization toolkit for convex MINLP," Journal of Global Optimization, Springer, vol. 84(1), pages 1-41, September.
    10. Tosoni, E. & Salo, A. & Govaerts, J. & Zio, E., 2019. "Comprehensiveness of scenarios in the safety assessment of nuclear waste repositories," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 561-573.
    11. Santos, Lucas F. & Costa, Caliane B.B. & Caballero, José A. & Ravagnani, Mauro A.S.S., 2022. "Framework for embedding black-box simulation into mathematical programming via kriging surrogate model applied to natural gas liquefaction process optimization," Applied Energy, Elsevier, vol. 310(C).
    12. Masaki Kimizuka & Sunyoung Kim & Makoto Yamashita, 2019. "Solving pooling problems with time discretization by LP and SOCP relaxations and rescheduling methods," Journal of Global Optimization, Springer, vol. 75(3), pages 631-654, November.
    13. Michael D. Teter & Johannes O. Royset & Alexandra M. Newman, 2019. "Modeling uncertainty of expert elicitation for use in risk-based optimization," Annals of Operations Research, Springer, vol. 280(1), pages 189-210, September.
    14. Britz, Wolfgang & van der Mensbrugghe, Dominique, 2017. "A flexible, modular and extendable framework for CGE analysis in GAMS," Conference papers 332918, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    15. Rastinejad, Justin & Putnam, Sloane & Stuber, Matthew D., 2023. "Technoeconomic assessment of solar technologies for the hybridization of industrial process heat systems using deterministic global dynamic optimization," Renewable Energy, Elsevier, vol. 216(C).
    16. Ferrari, Emanuele & Roson, Roberto Britz, Wolfgang & Britz, Wolfgang & Dudu, Hasan, 2019. "An extented myGTAP model to address subsistence production and sub-national households as a module in CGEBox," Conference papers 333059, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    17. Emmanuel Ogbe & Xiang Li, 2019. "A joint decomposition method for global optimization of multiscenario nonconvex mixed-integer nonlinear programs," Journal of Global Optimization, Springer, vol. 75(3), pages 595-629, November.
    18. Leon Lasdon & Judith S. Liebman, 1998. "The Teachers' Forum: Teaching Nonlinear Programming Using Cooperative Active Learning," Interfaces, INFORMS, vol. 28(4), pages 119-132, August.
    19. Marian Leimbach & Anselm Schultes & Lavinia Baumstark & Anastasis Giannousakis & Gunnar Luderer, 2017. "Solution algorithms for regional interactions in large-scale integrated assessment models of climate change," Annals of Operations Research, Springer, vol. 255(1), pages 29-45, August.
    20. Ximing Cai & Daene C. McKinney & Leon S. Lasdon & David W. Watkins, 2001. "Solving Large Nonconvex Water Resources Management Models Using Generalized Benders Decomposition," Operations Research, INFORMS, vol. 49(2), pages 235-245, April.

    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:gam:jsusta:v:12:y:2020:i:6:p:2506-:d:335849. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.