Skip to main content

Sustainable Farming Behaviours: An Agent Based Modelling and LCA Perspective

  • Chapter
  • First Online:
Agent-Based Modeling of Sustainable Behaviors


The paper is focused on the application of ABM (Agent Based Models) to simulate the evolution of the agricultural system of the Grand Duchy of Luxembourg, which aims at the evaluation of the potential environmental impacts arising from policy implementation, following the methodology known as Consequential Life Cycle Assessment (CLCA). The novelty of our approach is on the multi-modeling consideration of the problem of how to evaluate potential environmental impact of farmer’s behaviours. We consider the coupling of a computational model (ABM) and a matrix-based LCA model. The paper only presents preliminary results, exploring the influence of farmers’ environmental awareness on the environmental impacts linked to farming activities. This is possible thanks to the attribution to the agents’ profiles of one specific feature which simulates their “green consciousness level”.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
USD 69.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 89.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 119.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others


  1. 1.

    Now known as Luxembourg Institute of Socio-economic research

  2. 2.

    The details of the data are available in [19].

  3. 3.

    A flik is the smallest geo-referenced land element registered at the cadaster in Luxembourg.

  4. 4.

    This specific OTE is defined as 2∕3 of activity is field crops.


  1. Berger, T.: Agent-based spatial models applied to agriculture: a simulation tool for technology diffusion, resource use changes and policy analysis. Agric. Econ. 25, 245–260 (2001)

    Article  Google Scholar 

  2. Bert, F.E., Rovere, S.L., Macal, C.M., North, M.J., Podestá, G.P.: Lessons from a comprehensive validation of an agent based-model: the experience of the pampas model of argentinean agricultural systems. Ecol. Model. 273, 284–298 (2014)

    Article  Google Scholar 

  3. Bert, F., North, M., Rovere, S., Tatara, E., Macal, C., Podestá, G.: Simulating agricultural land rental markets by combining agent-based models with traditional economics concepts: the case of the argentine pampas. Environ. Model. Softw. 71, 97–110 (2015).

  4. Berta, F.E., Podestá, G.P., Rovere, S.L., Menéndez, A.N., North, M., Tatarad, E., Laciana, C.E., Weber, E., Toranzo, F.R.: An agent based model to simulate structural and land use changes in agricultural systems of the argentine pampas. Ecol. Model. 222, 3486–3499 (2011)

    Article  Google Scholar 

  5. Bonabeau, E.: Agent-based modeling: methods and techniques for simulating human systems. Proc. Natl. Acad. Sci. 99 (Suppl. 3), 7280–7287 (2002)

    Article  Google Scholar 

  6. Cooper, J.S., Fava, J.A.: Life-cycle assessment practitioner survey: summary of results. J. Ind. Ecol. 10 (4), 12–14 (2006)

    Article  Google Scholar 

  7. European Commission: Commision Regulation (EC) No 1242/2008 of 8 December 2008 establishing a Community typology for agricultural holdings. Official Journal of the European Union (2008)

    Google Scholar 

  8. Filatova, T., Parker, D., Van der Veen, A.: Agent-based urban land markets: agent’s pricing behavior, land prices and urban land use change. J. Artif. Soc. Soc. Simul. 12 (1), 3 (2009)

    Google Scholar 

  9. Goedkoop, M., Heijungs, R., Huijbregts, M., De Schryver, A., Struijs, J., van Zelm, R.: Recipe 2008. A life cycle impact assessment method which comprises harmonised category indicators at the midpoint and the endpoint level. Report I: Characterisation, 1 (2009)

    Google Scholar 

  10. Happe, K., Kellermann, K., Balmann, A.: Agent-based analysis of agricultural policies: an illustration of the agricultural policy simulator AgriPoliS, its adaptation, and behavior. Ecol. Soc. 11 (1), 329–342 (2006).

    Article  Google Scholar 

  11. Howitt, R.: Positive mathematical programming. Am. J Agr. Econ. 77, 329–342 (1995)

    Article  Google Scholar 

  12. ISO: Environmental management—Life cycle assessment—Principles and framework. ISO 14040:2006, International Organization for Standardization, Geneva (2010)

    Google Scholar 

  13. KTBL: Faustzahlen für die Landwirtschaft (in German). ISO, Kuratorium für Technik und Bauwesen in der Landwirtschaft, Darmstadt (2006)

    Google Scholar 

  14. Le, Q.B., Park, S.J., Vlek, P.L., Cremers, A.B.: Land-use dynamic simulator (LUDAS): a multi-agent system model for simulating spatio-temporal dynamics of coupled human–landscape system. I. Structure and theoretical specification. Ecol. Inform. 3 (2), 135–153 (2008)

    Google Scholar 

  15. Marvuglia, A., Benetto, E., Rege, S., Jury, C.: Modelling approaches for consequential life-cycle assessment (c-lca) of bioenergy: critical review and proposed framework for biogas production. Renew. Sust. Energ. Rev. 25, 768–781 (2013)

    Article  Google Scholar 

  16. Murray-Rust, D., Robinson, D.T., Guillem, E., Karali, E., Rounsevell, M.: An open framework for agent based modelling of agricultural land use change. Environ. Model. Softw. 61, 19–38 (2014).

  17. OMG: OMG system modeling language. (2012)

  18. Parker, D.C., Hessl, A., Davis, S.C.: Complexity, land-use modeling, and the human dimension: Fundamental challenges for mapping unknown outcome spaces. Geoforum 39 (2), 789–804 (2008)

    Article  Google Scholar 

  19. Rege, S., Arenz, M., Marvuglia, A., Vázquez-Rowe, I., Benetto, E., Igos, E., Koster, D.: Quantification of agricultural land use changes in consequential Life Cycle Assessment using mathematical programming models following a partial equilibrium approach. J. Environ. Inform. 26 (2), 12–139 (2015)

    Google Scholar 

  20. Schreinemachers, P., Berger, T.: An agent-based simulation model of human-environment interactions in agricultural systems. Environ. Model. Softw. 26 (7), 845–859 (2011).

  21. SER: (2016)

  22. STATEC: (2016)

  23. Vázquez-Rowe, I., Rege, S., Marvuglia, A., Thénie, J., Haurie, A., Benetto, E.: Application of three independent consequential LCA approaches to the agricultural sector in luxembourg. Int. J. Life Cycle Assess. 18 (8), 1593–1604 (2013)

    Article  Google Scholar 

  24. Vázquez-Rowe, I., Marvuglia, A., Rege, S., Benetto, E.: Applying consequential LCA to support energy policy: land use change effects of bioenergy production. Sci. Total Environ. 472, 78–89 (2014)

    Article  Google Scholar 

  25. Weidema, B., Bauer, C., Hischier, R., Mutel, C., Nemecek, T., Reinhard, J., Vadenbo, C., Wernet, G.: The ecoinvent database: overview and methodology, data quality guideline for the ecoinvent database version 3 (2013).

    Google Scholar 

Download references


Luxembourg’s National Research Fund (FNR) is acknowledged for the financial support of project MUSA with id: C12/SR/4011535.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Tomás Navarrete Gutiérrez .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Navarrete Gutiérrez, T., Rege, S., Marvuglia, A., Benetto, E. (2017). Sustainable Farming Behaviours: An Agent Based Modelling and LCA Perspective. In: Alonso-Betanzos, A., et al. Agent-Based Modeling of Sustainable Behaviors. Understanding Complex Systems. Springer, Cham.

Download citation

Publish with us

Policies and ethics