FoodPrints of households

  • Dominik Saner
  • Claudio Beretta
  • Boris Jäggi
  • Ronnie Juraske
  • Franziska Stoessel
  • Stefanie Hellweg
LCA OF NUTRITION AND FOOD CONSUMPTION

Abstract

Purpose

Food consumption is one of the main drivers of environmental impacts. To develop meaningful strategies for the reduction of impacts, food consumption patterns need to be understood on the household level, as purchasing decisions are taken on this level. The goals of this study were to develop a model that estimates food demand and environmental impact as a function of household characteristics, to assess variability between households, and to provide a basis for the development of consumer-targeted political interventions. We titled the study “FoodPrints of households,” as we assessed food consumption in terms of carbon footprint (in analogy to (Stoessel et al. Environ Sci Technol 46(6):3253–3262 2012)).

Methods

We used data from the Swiss household budget survey and applied multiple linear regressions based on generalized linear models to quantify food and beverage demand of individual households. Seven household characteristics, such as size, income, and educational level, served as input variables for the regressions. In a case study, food and beverage demand of 3238 individual households of a Swiss municipality was environmentally assessed with life cycle assessment, and scenarios for different reduction strategies were evaluated.

Results and discussion

We found that the carbon footprints of in-home food consumption per household member and year vary from 0.08 t CO2 eq. to 5 t CO2 eq. with a median value of 1 t CO2 eq. This variability is significantly smaller than the carbon footprint variability for the consumption areas of housing and mobility, where 25 % of the people are responsible for 50 % of the environmental impacts. Differences between high- and low-impact households can be primarily explained by differences in meat and dairy consumption.

Conclusions

This paper presents a model for quantifying food demand and impacts on a household level in Switzerland and represents a basis for developing targeted political measures to mitigate food consumption impacts. Household budget data is also available for many other countries, and the methods presented in this paper could therefore also be applied to other geographical regions.

Keywords

Food consumption Generalized linear models Household food impacts Multiple linear regression 

Supplementary material

11367_2015_924_MOESM1_ESM.pdf (2 mb)
ESM 1(PDF 2027 kb)

References

  1. Baroni L, Cenci L, Tettamanti M, Berati M (2007) Evaluating the environmental impact of various dietary patterns combined with different food production systems. Eur J Clin Nutr 61(2):279–286CrossRefGoogle Scholar
  2. Beretta C, Stoessel F, Baier U, Hellweg S (2013) Quantifying food losses and the potential for reduction in Switzerland. Waste Manag 33(3):764–773CrossRefGoogle Scholar
  3. Biesiot WK, Noorman J (1999) Energy requirements of household consumption: a case study of The Netherlands. Ecol Econ 28(3):367–383CrossRefGoogle Scholar
  4. Carlsson-Kanyama A, Ekström MP, Shanahan H (2003) Food and life cycle energy inputs: consequences of diet and ways to increase efficiency. Ecol Econ 44:293–307CrossRefGoogle Scholar
  5. Colomb V, Ait Amar S, Basset Mens C, Gac A, Gaillard G et al. (2014) AGRIBALYSE®, the French LCI Database for agricultural products: high quality data for producers and environmental labelling. In: Proceedings of the 9th International Conference LCA of Food, 8–10 October 2014, San FranciscoGoogle Scholar
  6. Dalgaard R, Halberg N, Rasmussen MD (2007) How to prepare a less pollutant family meal? Proceedings from the 5th International Conference ‘LCA in foods’, Gothenburg, SwedenGoogle Scholar
  7. Durlinger B, Tyszler M, Scholten J, BroekemaR, Blonk H (2014) Agri-Footprint; a Life Cycle Inventory database covering food and feed production and processing. In: Proceedings of the 9th International Conference LCA of Food, 8–10 October 2014, San FranciscoGoogle Scholar
  8. ecoinvent Centre. (2012) “ecoinvent data v2.2.” Retrieved 16 July, 2012, from http://www.ecoinvent.org/database/
  9. ecoinvent Centre. (2014) “ecoinvent v3.” 2014, from http://www.ecoinvent.org/ecoinvent-v3/
  10. ESU-services Ltd. (2012) “ESU life cycle inventory database on demand.” Retrieved 16 July, 2012, from http://www.esu-services.ch/data/data-on-demand/
  11. European Commission (2003) Household Budget Surveys in the EU. Office for Official Publications of the European Communities, Brussels (LX)Google Scholar
  12. Gill J (2001) Generalized linear models—a unified approach. Sage Publications Inc., Thousand Oaks (CA)Google Scholar
  13. Girod B, De Haan P (2009) GHG reduction potential of changes in consumption patterns and higher quality levels: evidence from Swiss household consumption survey. Energy Policy 37:5650–5661CrossRefGoogle Scholar
  14. Humbert S, Loerincik Y, Rossi V, Margni M, Jolliet O (2009) Life cycle assessment of spray dried soluble coffee and comparison with alternatives (drip filter and capsule espresso). J Clean Prod 17:1351–1358CrossRefGoogle Scholar
  15. IPCC (2007) Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. IPCC Fourth Assessment Report (AR4). S. Solomon, D. Qin, M. Manninget al. New York, NY, IPCCGoogle Scholar
  16. Jungbluth N, Stucki M, Leuenberger M (2011) “Environmental impacts of Swiss consumption and production.” from http://www.bafu.admin.ch/publikationen/publikation/01611/index.html?lang=en
  17. Meier T, Christen O (2012) Gender as a factor in an environmental assessment of the consumption of animal and plant-based foods in Germany. Int J Life Cycle Assess 17:550–564CrossRefGoogle Scholar
  18. Mohr P, Wilson C, Dunn K, Brindal E, Wittert G (2007) Personal and lifestyle characteristics predictive of the consumption of fast foods in Australia. Public Health Nutr 10(12):1456–1463CrossRefGoogle Scholar
  19. Moll HC, Noorman KJ, Kok R, Engstrom R, Throne-Holst H et al (2005) Pursuing more sustainable consumption by analyzing household metabolism in European countries and cities. J Ind Ecol 9(1–2):259–275Google Scholar
  20. Muñoz I, Milà i Canals L, Fernández-Alba AR (2010) Life cycle assessment of the average Spanish diet including human excretion. Int J Life Cycle Assess 15:794–805CrossRefGoogle Scholar
  21. Nielsen PH, Nielsen AM, Weidema BP, Dalgaard R, Halberg N (2012) “LCA food data base.” Retrieved 16 July, 2012, from www.lcafood.dk
  22. Öko-Institut e.V. (2012) “GEMIS.” Retrieved 16 July, 2012, from http://www.gemis.de
  23. Peano L, Bengoa X, Humbert S, Loerincik Y, Lansche Y et al. (2014) The World Food LCA Database project: towards more accurate food datasets. In: Proceedings of the 9th International Conference LCA of Food, 8–10 October 2014, San Francisco, USAGoogle Scholar
  24. Proviande (2011) “Fleischkonsum 2011.” Retrieved 8 October, 2012, from http://www.schweizerfleisch.ch/fileadmin/dokumente/downloads/proviande/statistik/konsum/Tabelle_Konsum_2011_d.pdf
  25. Rodríguez C, Ciroth A, Srocka M (2014) The importance of regionalized LCIA in agricultural LCA—new software implementation and case study. In: Proceedings of the 9th International Conference LCA of Food, 8–10 October 2014, San Francisco, USAGoogle Scholar
  26. Ruini L, Marino M, Pratesi C, Redavid E, Principato L et al. (2014) LCA applied to sustainable diets: Double Pyramid and Tool Chef to promote healthy and environmentally sustainable consumption. In: Proceedings of the 9th International Conference LCA of Food, 8–10 October 2014, San Francisco, USAGoogle Scholar
  27. Saner D, Blumer YB, Lang DJ, Koehler A (2011) Scenarios for the implementation of EU waste legislation at national level and their consequences for emissions from municipal waste incineration. Resour Conserv Recycl 57:67–77CrossRefGoogle Scholar
  28. Saner D, Jäggi B, Waraich RA, Heeren N, Hellweg S (2013) Household housing and mobility demands and their life cycle assessment. Environ Sci Technol 47(11):5988–5997CrossRefGoogle Scholar
  29. Scholz R, Tietje WO (2002) Embedded case study methods. Sage Publications Inc., Thousand Oaks (CA)Google Scholar
  30. Schweizer Milchproduzenten (2012) “Marktakteure und Strukturen.” Retrieved 8 October, 2012, from http://www.swissmilk.ch/de/produzenten/milchmarkt/marktakteure-strukturen/konsumenten.html
  31. Stoessel F, Juraske R, Pfister S, Hellweg S (2012) Life cycle inventory and carbon and water food print of fruits and vegetables: application to a Swiss retailer. Environ Sci Technol 46(6):3253–3262CrossRefGoogle Scholar
  32. Swiss Federal Customs Administration (2012) “Swiss foreign trade statistics.” Retrieved 1 July, 2012, from https://www.swiss-impex.admin.ch/
  33. Swiss Federal Statistical Office (SFSO) (2012) “Census.” Retrieved 1 July, 2012, from http://www.bfs.admin.ch/bfs/portal/de/index/infothek/erhebungen__quellen/blank/blank/vz/uebersicht.html
  34. Swiss Federal Statistical Office (SFSO) (2012) “Household budget survey.” Retrieved 1 July, 2012, from http://www.bfs.admin.ch/bfs/portal/en/index/infothek/erhebungen__quellen/blank/blank/habe/01.html
  35. Thrane M (2006) LCA of Danish fish products. New methods and insights. Int J Life Cycle Assess 11:66–74CrossRefGoogle Scholar
  36. Tukker A, Huppes G, Suh S, Heijungs R, Guinée JB et al (2006) Environmental impacts of products. J Ind Ecol 10:159–182CrossRefGoogle Scholar
  37. Tyszler M, Kramer G, Blonk H (2014) Just eating healthier is not enough: studying the environmental impact of different diet scenarios for the Netherlands by linear programming. In: Proceedings of the 9th International Conference LCA of Food, 8–10 October 2014, San Francisco, USAGoogle Scholar
  38. United Nations Statistics Division (2012) “COICOP (Classification of Individual Consumption According to Purpose).” Retrieved 8 May, 2012, from http://unstats.un.org/unsd/cr/registry/regcst.asp?Cl=5
  39. van der Horst K, Brunner TA, Siegrist M (2011) Fast food and take-away food consumption are associated with different lifestyle characteristics. J Hum Nutr Diet 24(6):596–602CrossRefGoogle Scholar
  40. van Dooren C, Aiking H (2014) Defining a nutritionally healthy, environmentally friendly, and culturally acceptable low lands diet. In: Proceedings of the 9th International Conference LCA of Food, 8–10 October 2014, San Francisco, USAGoogle Scholar
  41. Vimentis (2012) “National poverty line.” Retrieved 17 October, 2012, from http://www.vimentis.ch/d/lexikon/108/Armutsgrenze.html
  42. Vringer K, Blok K (1996) The direct and indirect energy requirement of households in the Netherlands (vol 23, pg 895, 1995). Energ Policy 24(2):203–203CrossRefGoogle Scholar
  43. Xue XA, Landis E (2010) Eutrophication potential of food consumption patterns. Environ Sci Technol 44:6450–6456CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Dominik Saner
    • 1
  • Claudio Beretta
    • 1
  • Boris Jäggi
    • 2
  • Ronnie Juraske
    • 1
  • Franziska Stoessel
    • 1
  • Stefanie Hellweg
    • 1
  1. 1.ETH Zurich, Group for Ecological Systems DesignInstitute of Environmental EngineeringZurichSwitzerland
  2. 2.ETH Zurich, Transport and Spatial PlanningInstitute for Transport Planning and SystemsZurichSwitzerland

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