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An LCA impact assessment model linking land occupation and malnutrition-related DALYs

  • Bradley RidouttEmail author
  • Masaharu Motoshita
  • Stephan Pfister
LAND USE IN LCA

Abstract

Purpose

So far, land occupation impact assessment models in life-cycle assessment have predominantly considered biodiversity, ecosystem quality and ecosystem services. However, in a manner similar to water consumption, land occupation has the potential to impact food production and thereby human health. In this study, the impact pathway linking land occupation and protein-energy malnutrition was modelled, establishing a new set of regionalised characterisation factors which were applied in a case study of cotton cultivation.

Methods

The impact assessment model has three main components: a food production model, a food trade model and an effect factor that relates potential food deficits to malnutrition expressed in disability-adjusted life years (DALYs). The food production model uses an NPP-based index to account for variation in the productive capability of land, as well as data on irrigation water supply and national agricultural yields to account for variation in prevailing agricultural technologies. Food production losses have the potential to impact national and global food supplies according to trade status and economic adaptation capacity assessed using the Inequality-adjusted Human Development Index. Health damage data from the Global Burden of Disease report and depth of national food deficit data from the FAO are the basis of the effect factor.

Results and discussion

The model reports potential human health impacts related to land occupation (DALY/m2 year) at 5-arc-minute spatial resolution. The model is relevant to all kinds of land occupation, including food production, as no assumptions are made about the ways food products are utilised, which can be many. The model delivers results sensibly in proportion to potential human health impacts of freshwater consumption, i.e. greater in tropical areas and lesser in arid areas. The case study showed that land occupation impacts on human health might cause one DALY/t seed cotton in extreme cases and less than one DALY per thousand tonnes in others. In the case of India, ~ 9% of national malnutrition-related DALYs were attributable to cotton cultivation which occupies ~ 8% of arable land.

Conclusions

This new model will enable more complete assessment of land occupation impacts in LCA and is especially relevant to the assessment of food, fibre, and bioenergy products. In addition, the model enhances the ability to assess trade-offs which frequently occur, such as between land and water use and GHG emissions. The cotton case study showed that human health impacts can be grossly underestimated in LCA studies when land occupation impacts are not included.

Keywords

Cotton Human health Land occupation Land use footprint Life-cycle impact assessment Virtual flow of land Virtual land use 

Notes

Funding information

This study was jointly funded by ETH Zurich, National Institute of Advanced Industrial Science and Technology, Japan and CSIRO, Australia.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest.

Supplementary material

11367_2019_1590_MOESM1_ESM.docx (175 kb)
ESM 1 (DOCX 175 kb)
11367_2019_1590_MOESM2_ESM.xlsx (39 kb)
ESM 2 (XLSX 39 kb)

References

  1. Alcantara C, Kuemmerle T, Baumann M, Bragina EV, Griffiths P, Hostert P, Knorn J, Müller D, Prishchepov AV, Schierhorn F, Sieber A, Radeloff VC (2013) Mapping the extent of abandoned farmland in Central and Eastern Europe using MODIS time series satellite data. Environ Res Lett 8:035035CrossRefGoogle Scholar
  2. Angelsen A (2010) Policies for reduced deforestation and their impact on agricultural production. Proc Natl Acad Sci U S A 107:19639–19644CrossRefGoogle Scholar
  3. Arbault D, Rivière M, Rugani B, Benetto E, Tiruta-Barna L (2014) Integrated earth system dynamic modelling for life cycle impact assessment of ecosystem services. Sci Total Environ 472:262–272CrossRefGoogle Scholar
  4. Beck T, Bos U, Wittstock B, Baitz M, Fischer M, Sedlbauer K (2010) LANCA®—land use indicator value calculation in life cycle assessment. Fraunhofer Institute for Building Physics, Stuttgart ISBN: 978-3-8396-0170-9Google Scholar
  5. Bhardwaj AK, Zenone T, Jasrotia P, Robertson GP, Chen J, Hamilton SK (2011) Water and energy footprints of bioenergy crop production on marginal lands. Glob Change Biol Bioenergy 3(3):208–222CrossRefGoogle Scholar
  6. Bottrill M, Cheng S, Garside R, Wongbusarakum S, Roe D, Holland MB, Edmond J, Turner WR (2014) What are the impacts of nature conservation interventions on human well-being: a systematic map protocol. Environ Evidence 3:16CrossRefGoogle Scholar
  7. Boulay AM, Motoshita M, Pfister S, Bulle C, Muñoz I, Franceschini H, Margni M (2015) Analysis of water use impact assessment methods (part a): evaluation of modelling choices based on a quantitative comparison of scarcity and human health indicators. Int J Life Cycle Assess 20:139–160CrossRefGoogle Scholar
  8. Brandão M, Milà i Canals L, Clift R (2011) Soil organic carbon changes in the cultivation of energy crops: implications for GHG balances and soil quality for use in LCA. Biomass Bioenergy 35:2323–2336CrossRefGoogle Scholar
  9. Bren d’Amour C, Reitsma F, Baiocchi G, Barthel S, Güneralp B, Erb KH, Haberl H, Creutzig F, Seto KC (2017) Future urban land expansion and implications for global croplands. Proc Natl Acad Sci U S A 114:8939–8944CrossRefGoogle Scholar
  10. Cao V, Margni M, Favis BD, Deschénes L (2015) Aggregated indicator to assess land use impacts in life cycle assessment (LCA) based on the economic value of ecosystem services. J Clean Prod 94:56–66CrossRefGoogle Scholar
  11. Chaudhary A, Verones F, de Baan L, Hellweg S (2015) Quantifying land use impacts on biodiversity: combining species-area models and vulnerability indicators. Environ Sci Technol 49:9987–9985CrossRefGoogle Scholar
  12. Curran MP, de Souza DM, Antón A, Teixeira RFM, Michelsen O, Vidal-Legaz B, Sala S, Milà i Canals L (2016) How well does LCA model land use impacts on biodiversity?—a comparison with approaches from ecology and conservation. Environ Sci Technol 50(6):2782–2795CrossRefGoogle Scholar
  13. de Baan L, Mutel CL, Curran M, Hellweg S, Koellner T (2013) Land use in life cycle assessment: global characterization factors based on regional and global potential species extinction. Environ Sci Technol 47:9281–9290CrossRefGoogle Scholar
  14. de Baan L, Curran M, Rondinini C, Visconti P, Hellweg S, Koellner T (2015) High-resolution assessment of land use impacts on biodiversity in life cycle assessment using species habitat suitability models. Environ Sci Technol 49:2237–2244CrossRefGoogle Scholar
  15. Dick M, da Silva MA, Dewes H (2015) Mitigation of environmental impacts of beef cattle production in southern Brazil – evaluation using farm-based life cycle assessment. J Clean Prod 87:58–67CrossRefGoogle Scholar
  16. Ecoinvent Centre (2008) ecoinvent data (i.e.2.01) http://www.ecoinvent.org
  17. Erb KH, Lauk C, Kastner T, Mayer A, Theurl MC, Haberl H (2016) Exploring the biophysical option space for feeding the world without deforestation. Nat Commun 7:11382CrossRefGoogle Scholar
  18. Estel S, Kuemmerle T, Alcántara C, Levers C, Prishchepov A, Hostert P (2015) Mapping farmland abandonment and recultivation across Europe using MODIS NDVI time series. Remote Sens Environ 163:312–325CrossRefGoogle Scholar
  19. Fader M, Gerten D, Krause M, Lucht W, Cramer W (2013) Spatial decoupling of agricultural production and consumption: quantifying dependences of countries on food imports due to domestic land and water constraints. Environ Res Lett 8:014046CrossRefGoogle Scholar
  20. FAO (2014) FAOSTAT. Food and Agriculture Organization of United Nations web. http://faostat.fao.org/. Accessed 6 Apr 2014
  21. FAO (2015) Food security indicators. Food and Agriculture Organization of United Nations web. http://www.fao.org/economic/ess/ess-fs/ess-fadata/en/#.V5XMG47M2Q8. Accessed 27 Jan 2016
  22. FAO (2017) FAOSTAT. Food and Agriculture Organization of United Nations web. http://faostat.fao.org/. Accessed 6 Sep 2017
  23. Fischer G, van Velthuizen H, Nachtergaele F, Medow S (2000) Global Agro-Ecological Zones 2000. FAO & IIASA, Rome http://webarchive.iiasa.ac.at/Research/LUC/GAEZ/ Google Scholar
  24. Fischer J, Abson DJ, Butsic V, Chappell MJ, Ekroos J, Hanspach J, Kuemmerle T, Smith HG, von Wehrden H (2014) Land sparing versus land sharing: moving forward. Conserv Lett 7(3):149–157CrossRefGoogle Scholar
  25. Foley JA, Ramankutty N, Brauman KA, Cassidy ES, Gerber JS, Johnston M, Mueller ND, O’Connell C, Ray DK, West PC, Balzer C, Bennett EM, Carpenter SR, Hill J, Monfreda C, Polasky S, Rockström J, Sheehan J, Siebert S, Tilman D, Zaks DPM (2011) Solutions for a cultivated planet. Nature 478(7369):337–342CrossRefGoogle Scholar
  26. Frischknecht R, Fantke P, Tschümperlin L, Niero M, Antón A, Bare J, Boulay AM, Cherubini F, Hauschild MZ, Henderson A, Levasseur A, McKone TE, Michelsen O, Milà i Canals M, Pfister S, Ridoutt B, Rosenbaum RK, Verones F, Vigon B, Jolliet O (2016) Global guidance on environmental life cycle impact assessment indicators: progress and case study. Int J Life Cycle Assess 21(3):429–442CrossRefGoogle Scholar
  27. Garnett T, Appleby MC, Balmford A, Bateman IJ, Benton TG, Bloomer P, Burlingane B, Dawkins M, Do-lan L, Fraser D, Herrero M, Hoffmann I, Smith P, Thornton PK, Toulmin C, Vermeulen SJ, Godfray HCJ (2013) Sustainable intensification in agriculture: premises and policies. Science 341:33–34CrossRefGoogle Scholar
  28. Garrigues E, Corson MS, Angers DA, van der Werf HMG, Walter C (2012) Soil quality in life cycle assessment: towards development of an indicator. Ecol Indic 18:434–442CrossRefGoogle Scholar
  29. Garrigues E, Corson MS, Angers DA, van der Werf HMG, Walter C (2013) Development of a soil compaction indicator in life cycle assessment. Int J Life Cycle Assess 18:1316–1324CrossRefGoogle Scholar
  30. GBD 2013 (2015) Global Burden of Disease Study 2013, Institute for Health Metrics and Evaluation, http://ghdx.healthdata.org/global-burden-disease-study-2013-gbd-2013-data-downloads. Accessed 23 July 2016Google Scholar
  31. Goedkoop M, Spriensma R (2001) The eco-indicator 99: a damage oriented method for life cycle impact assessment: methodology report. Ministerie van Volkshiusvesting, Ruimtelijke Ordening en Milieubeheer, Den HaagGoogle Scholar
  32. Heller MC, Keoleian GA, Willett WC (2013) Toward a life cycle-based, diet-level framework for food environmental impact and nutritional quality assessment: a critical review. Environ Sci Technol 47:12632–12647CrossRefGoogle Scholar
  33. Hennecke AM, Mueller-Lindenlauf M, Garcia CA, Fuentes A, Riegelhaupt E, Hellweg S (2016) Optimizing the water, carbon, and land-use footprint of bioenergy production in Mexico – six case studies and the nationwide implications. Biofuels Bioprod Biorefin 10(3):222–239CrossRefGoogle Scholar
  34. Henriksson M, Cederberg C, Swensson C (2014) Carbon footprint and land requirement for dairy herd rations: impacts of feed production practices and regional climate variations. Animal 8(8):1329–1338CrossRefGoogle Scholar
  35. Huerta AR, Güereca LP, Lozano MDR (2016) Environmental impact of beef production in Mexico through life cycle assessment. Resour Conserv Recycl 109:44–53CrossRefGoogle Scholar
  36. ISO 14040 (2006) Environmental management – life cycle assessment – principles and framework. International Organization for Standardization, GenevaGoogle Scholar
  37. ISO 14044 (2006) Environmental management – Life cycle assessment – requirements and guidelines. International Organization for Standardization, GenevaGoogle Scholar
  38. Jolliet O, Müller-Wenk R, Bare J, Brent A, Goedkoop M, Heijungs R, Itsubo N, Peña C, Pennington D, Potting J, Rebitzer G, Stewart M, Udo de Haes H, Weidema B (2004) The LCIA midpoint-damage framework of the UNEP/SETAC life cycle initiative. Int J Life Cycle Assess 9(6):394–404CrossRefGoogle Scholar
  39. Jolliet O, Frischknecht R, Bare J, Boulay AM, Bulle C, Fantke P, Gheewala S, Hauschild M, Itsubo N, Margni M, McKone TE, Mila i Canals L, Postuma L, Prado-Lopez V, Ridoutt B, Sonnemann G, Rosen-baum RK, Seager T, Struijs J, van Zelm R, Vigon B, Weisbrod A (2014) Global guidance on environ-mental life cycle impact assessment indicators: findings of the scoping phase. Int J Life Cycle Assess 19:962–967CrossRefGoogle Scholar
  40. Kauffman NS, Hayes DJ (2011) The trade-off between bioenergy and emissions when land is scarce. Working paper 11-WP 519, Center for Agricultural and Rural Development, Iowa State University, Ames, IowaGoogle Scholar
  41. Knudsen MT, Hermansen JE, Cederberg C, Herzog F, Vale J, Jeanneret P, Sarthou JP, Friedel JK, Balazs K, Fjellstad W, Kainz M, Wolfrum S, Dennis P (2017) Characterization factors for land use impacts on biodiversity in life cycle assessment based on direct measures of plant species richness in European farmland in the ‘temperate broadleaf and mixed Forest’ biome. Sci Total Environ 580:358–366CrossRefGoogle Scholar
  42. Koellner T, de Baan L, Beck T, Brandao M, Civit B, Margni M, Milà i Canals L, Saad R, de Souza DM, Muller-Wenk R (2013) UNEP-SETAC guideline on global land use impact assessment on biodiversity and ecosystem services in LCA. Int J Life Cycle Assess 18:1188–1202CrossRefGoogle Scholar
  43. Kooistra K, Termorshuizen A (2006) The sustainability of cotton: consequences for man and environment. Report 223, Wageningen University, Wageningen, NetherlandsGoogle Scholar
  44. Koponen K, Soimakallio S (2015) Foregone carbon sequestration due to land occupation – the case of agro-bioenergy in Finland. Int J Life Cycle Assess 20:1544–1556CrossRefGoogle Scholar
  45. Kuemmerle T, Olofsson P, Chaskovskyy O, Baumann M, Ostapowicz K, Woodcock CE, Houghton RA, Hostert P, Keeton WS, Radeloff VC (2011) Post-Soviet farmland abandonment, forest recovery, and carbon sequestration in western Ukraine. Glob Chang Biol 17:1335–1349CrossRefGoogle Scholar
  46. Lambin EF, Meyfroidt P (2011) Global land use change, economic globalization, and the looming land scarcity. Proc Natl Acad Sci U S A 108:3465–3472CrossRefGoogle Scholar
  47. Lambin EF, Gibbs HK, Ferreira L, Grau R, Mayaux P, Meyfroidt P, Morton DC, Rudel TK, Gasparri I, Munger J (2013) Estimating the world’s potentially available cropland using a bottom-up approach. Glob Environ Chang 23:892–901CrossRefGoogle Scholar
  48. Leisher C, Samberg LH, van Beukering P, Sanjayan M (2013) Focal areas for measuring the human well-being impacts of a conservation initiative. Sustainability 5:997–1010CrossRefGoogle Scholar
  49. Marselis SM, Feng K, Liu Y, Teodoro JD, Hubacek K (2017) Agricultural land displacement and undernourishment. J Clean Prod 161:619–628CrossRefGoogle Scholar
  50. Mattila T, Helin T, Antikainen R (2012) Land use indicators in life cycle assessment: a case study on beer production. Int J Life Cycle Assess 17:277–286CrossRefGoogle Scholar
  51. Meyfroidt P, Rudel TK, Lambin EF (2010) Forest transitions, trade, and the global displacements of land use. Proc Natl Acad Sci U S A 107:20917–20922CrossRefGoogle Scholar
  52. Milà i Canals L, Antón A, Bauer C, de Camillis C, Freiermuth R, Grant T, Michelsen O, Stevenson M (2016) Land use related impacts on biodiversity. In: Frischknecht R, Jolliet O (eds) Global guidance for life cycle impact assessment indicators. Volume 1. United Nations Environment Programme, Paris, pp 126–143Google Scholar
  53. Monfreda C, Ramankutty N, Foley JA (2008) Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000. Global Biogeochem Cycles 22(1):GB1022.  https://doi.org/10.1029/2007gb002947 CrossRefGoogle Scholar
  54. Morais TG, Domingos T, Teixeira RFM (2016) A spatially explicit life cycle assessment midpoint indicator for soil quality in the European Union using soil organic carbon. Int J Life Cycle Assess 21(8):1076–1091CrossRefGoogle Scholar
  55. Motoshita M, Itsubo N, Inaba A (2010) Damage assessment of water scarcity for agricultural use. Proc 9th Int Conf Ecobalance, Institute of Life Cycle Assessment, Tokyo, JapanGoogle Scholar
  56. Motoshita M, Ono Y, Pfister S, Boulay AM, Berger M, Nansai K, Tahara K, Itsubo N, Inaba A (2014) Consistent characterization factors at midpoint and endpoint relevant to agricultural water scarcity arising from freshwater consumption. Int J Life Cycle Assess 23:2276–2287.  https://doi.org/10.1007/s11367-014-0811-5 CrossRefGoogle Scholar
  57. Motoshita M, Boulay AM, Pfister S, Benini L, de Figueiredo MCB, Gheewala SH, Harding K, Schenker U (2016a) Water use related impacts: water scarcity and human health effects. Part 2: human health effects. In: Frischknecht R, Jolliet O (eds) Global guidance for life cycle impact assessment indicators. Volume 1. United Nations Environment Programme, Paris, pp 116–124Google Scholar
  58. Motoshita M, Ono Y, Finkbeiner M, Inaba A (2016b) The effect of land use on availability of Japanese freshwater resources and its significance for water footprinting. Sustainability 8(1):86–2287.  https://doi.org/10.1007/s11367-014-0811-5 CrossRefGoogle Scholar
  59. Nordborg M, Sasu-Boakye Y, Cederberg C, Berndes G (2017) Challenges in developing regionalized characterization factors in land use impact assessment: impacts on ecosystem services in case studies of animal protein production in Sweden. Int J Life Cycle Assess 22:328–345.  https://doi.org/10.1007/s11367-016-1158-x CrossRefGoogle Scholar
  60. Núñez Pineda M (2011) Modelling Location-dependent Environmental Impacts in Life Cycle Assessment: Water Use, Desertification and Soil Erosion. PhD thesis. Institut de Ciència I Tecnologia Ambientals, Universitat Autònoma de BarcelonaGoogle Scholar
  61. Othoniel B, Rugani B, Heijungs R, Benetto E, Withagen C (2016) Assessment of life cycle impacts on ecosystem services: promise, problems, and prospects. Environ Sci Technol 50(3):1077–1092CrossRefGoogle Scholar
  62. Payen S, Basset-Mens C, Núñez M, Follain S, Grünberger O, Marlet S, Perret S, Roux P (2016) Salinisation impacts in life cycle assessment: a review of challenges and options towards their consistent integration. Int J Life Cycle Assess 21:577–594CrossRefGoogle Scholar
  63. Pfister S, Bayer P (2013) Monthly water stress: spatially and temporally explicit consumptive water footprint of global crop production. J Clean Prod 73:52–62CrossRefGoogle Scholar
  64. Pfister S, Koehler A, Hellweg S (2009) Assessing the environmental impacts of freshwater consumption in LCA. Environ Sci Technol 43:4098–4104CrossRefGoogle Scholar
  65. Pfister S, Bayer P, Koehler A, Hellweg S (2011) Environmental impacts of water use in global crop production: hotspots and trade-offs with land use. Environ Sci Technol 45:5761–5768CrossRefGoogle Scholar
  66. Pfister S, Motoshita M, Ridoutt BG (2014) Progress toward an LCA impact assessment model linking land use and malnutrition-related DALYs. In: Schenck R, Huizenga D (eds) Proceedings of the 9th International Conference on Life Cycle Assessment in the Agri-Food Sector (LCA Food 2014). ACLCA, Vashon, pp 1007–1015Google Scholar
  67. Phalan B, Onial M, Balmford A, Green RE (2011) Reconciling food production and biodiversity conservation: land sharing and land sparing compared. Science 333:1298–1291CrossRefGoogle Scholar
  68. Qiang W, Liu A, Cheng S, Kastner T, Xie G (2013) Agricultural trade and virtual land use: the case of China’s crop trade. Land Use Policy 33:141–150CrossRefGoogle Scholar
  69. Quinteiro P, Dias AC, Ridoutt BG, Arroja L (2014) A framework for modelling the transport and deposition of eroded particles towards water systems in a life cycle inventory. Int J Life Cycle Assess 19:1200–1213CrossRefGoogle Scholar
  70. Ridoutt BG, Page G, Opie K, Huang J, Bellotti W (2014) Carbon, water and land use footprints of beef cattle production systems in southern Australia. J Clean Prod 73:24–30CrossRefGoogle Scholar
  71. Ridoutt BG, Hendrie GA, Noakes M (2017) Dietary strategies to reduce environmental impact: a critical review of the evidence base. Adv Nutr 8:933–946CrossRefGoogle Scholar
  72. Rockström J, Steffen W, Noone K, Persson Å, Chapin FS, Lambin EF, Lenton TM, Scheffer M, Folke C, Schellnhuber HJ, Nykvist B, de Wit CA, Hughes T, van der Leeuw S, Rodhe H, Sörlin S, Snyder PK, Costanza R, Svedin U, Falkenmark M, Karlberg L, Corell RW, Fabry VJ, Hansen J, Walker B, Liverman D, Richardson K, Cruzen P, Foley JA (2009) A safe operating space for humanity. Nature 461:472–475CrossRefGoogle Scholar
  73. Rockstrom J, Williams J, Daily G, Noble A, Matthews N, Gordon L, Wetterstrand H, DeClerck F, Shah M, Steduto P, de Fraiture C, Hatibu N, Unver O, Bird J, Sibanda L, Smith J (2017) Sustainable intensification of agriculture for human prosperity and global sustainability. Ambio 46(1):4–17CrossRefGoogle Scholar
  74. Roos E, Patel M, Spangberg J (2016) Producing oat drink or cow’s milk on a Swedish farm - environmental impacts considering the service of grazing, the opportunity cost of land and the demand for beef and protein. Agric Syst 142:23–32CrossRefGoogle Scholar
  75. Sabaté J, Harwatt H, Soret S (2016) Environmental nutrition: a new frontier for public health. Am J Public Health 105(5):815–821CrossRefGoogle Scholar
  76. Searchinger T, Heimlich R, Houghton RA, Dong F, Elobeid A, Fabiosa J, Tokgoz S, Hayes D, Yu TH (2008) Use of US croplands for biofuels increases greenhouse gases through emissions from land-use change. Science 319:1238–1240CrossRefGoogle Scholar
  77. Staples MD, Olcay H, Malina R, Trivedi P, Pearlson MN, Strzepek K, Paltsev SV, Wollersheim C, Barrett RH (2013) Water consumption footprint and land requirements of large-scale alternative diesel and jet fuel production. Environ Sci Technol 47(21):12557–12565CrossRefGoogle Scholar
  78. Stoessel F, Juraske R, Pfister S, Hellweg S (2012) Life cycle inventory and carbon and water foodprint of fruits and vegetables: application to a Swiss retailer. Environ Sci Technol 46:3253–3262CrossRefGoogle Scholar
  79. Stylianou KS, Heller MC, Fulgoni VL III, Ernstoff AS, Keoleian GA, Jolliet O (2016) A life cycle assessment framework combining nutritional and environmnetal health impacts of diet: a case study on milk. Int J Life Cycle Assess 21:734–746CrossRefGoogle Scholar
  80. Teixeira RFM, de Souza DM, Curran M, Antón A, Michelsen O, Milà i Canals L (2016) Towards consensus on land use impacts on biodiversity in LCA: UNEP/SETAC life cycle initiative preliminary recommendations based on expert contributions. J Clean Prod 112(5):4283–4287CrossRefGoogle Scholar
  81. Tilman D, Balzer C, Hill J, Befort BL (2011) Global food demand and the sustainable intensification of agriculture. Proc Natl Acad Sci U S A 108(50):20260–20264CrossRefGoogle Scholar
  82. Van Kernebeek HRJ, Oosting SJ, Van Ittersum MK, Bikker P, De Boer IJM (2016) Saving land to feed a growing population: consequences for consumption of crop and livestock products. Int J Life Cycle Assess 21(5):677–687CrossRefGoogle Scholar
  83. van Zanten HHE, Mollenhorst H, Klootwijk CW, van Middelaar CE, de Boer IJM (2016) Global food supply: land use efficiency of livestock systems. Int J Life Cycle Assess 21(5):747–758CrossRefGoogle Scholar
  84. Verhoeve A, Dewaelheyns V, Kerselaers E, Rogge E, Gulinck H (2015) Virtual farmland: grasping the occupation of agricultural land by non-agricultural land uses. Land Use Policy 42:547–556CrossRefGoogle Scholar
  85. Vidal Legaz B, Maia De Souza D, Teixeira RFM, Antón A, Putman B, Sala S (2017) Soil quality, properties, and functions in life cycle assessment: an evaluation of models. J Clean Prod 140:502–515CrossRefGoogle Scholar
  86. Weinzettel J, Hertwich EG, Peters GP, Steen-Olsen K, Galli A (2013) Affluence drives the global dis-placement of land use. Glob Environ Chang 23:433–438CrossRefGoogle Scholar
  87. Wirsenius S, Azar C, Berndes G (2010) How much land is needed for global food production under sce-narios of dietary changes and livestock productivity increases in 2030? Agric Syst 103:621–638CrossRefGoogle Scholar
  88. Xie H, Wang P, Yao G (2014) Exploring the dynamic mechanisms of farmland abandonment based on a spatially explicit economic model for environmental sustainability: a case study in Jiangxi Province, China. Sustainability 6:1260–1282CrossRefGoogle Scholar
  89. Yu Y, Feng K, Hubacek K (2013) Tele-connecting local consumption to global land use. Glob Environ Chang 23:1178–1186CrossRefGoogle Scholar
  90. Zhang J, Zhao N, Liu X, Liu Y (2016) Global virtual-land flow and saving through international cereal trade. J Geogr Sci 26(5):619–639CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Bradley Ridoutt
    • 1
    • 2
    Email author
  • Masaharu Motoshita
    • 3
  • Stephan Pfister
    • 4
  1. 1.Agriculture and FoodCommonwealth Scientific and Industrial Research Organisation (CSIRO)Clayton SouthAustralia
  2. 2.Department of Agricultural EconomicsUniversity of the Free StateBloemfonteinSouth Africa
  3. 3.National Institute of Advanced Industrial Science and Technology, Research Institute of Science for Safety and SustainabilityTsukubaJapan
  4. 4.ETH Zurich, Institute of Environmental EngineeringZurichSwitzerland

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