Abstract

The oversupply of nutrients (phosphorous and nitrogen) in fresh and marine water bodies presents a serious ecosystem threat due to impacts on water quality through eutrophication. With agriculture characterized as a primary driver of eutrophication, the role of food consumption and trade has been the focus of recent phosphorus and nitrogen impact studies. However, the environmental impacts associated with non-food commodities are significant and yet to be characterized. Here, we link a spatially explicit treatment of phosphorous and nitrogen eutrophication potentials to a multi-regional input–output approach to characterize the importance of overall consumption for marine and freshwater eutrophication across 44 countries and 5 rest-of-world regions over the period 2000–2011. We find that clothing, goods for shelter, services and other manufactured products account for 35% of global marine eutrophication and 38% of the global freshwater eutrophication footprints in 2011, up from 31 and 33%, respectively, in 2000. Relative to food consumption, non-food consumption is also significantly more income elastic and shaped by trade. As economies develop, this points to the need for trade agreements and policies to consider the displacement of ecosystem impacts.

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References

  1. 1.

    Tilman, D., Cassman, K. G., Matson, P. A., Naylor, R. L. & Polasky, S. Agricultural sustainability and intensive production practices. Nature 418, 671–677 (2002).

  2. 2.

    Smith, V. H., Tilman, G. D. & Nekola, J. C. Eutrophication: impacts of excess nutrient inputs on freshwater, marine, and terrestrial ecosystems. Environ. Pollut. 100, 179–196 (1999).

  3. 3.

    Potter, P., Ramankutty, N., Bennett, E. M. & Donner, S. D. Characterizing the spatial patterns of global fertilizer application and manure production. Earth Interact. https://doi.org/10.1175/2009EI288.1 (2010).

  4. 4.

    Diaz, R. J. & Rosenberg, R. Spreading dead zones and consequences for marine ecosystems. Science 321, 926–929 (2008).

  5. 5.

    Steffen, W. et al. Planetary boundaries: guiding human development on a changing planet. Science 347, 1259855 (2015).

  6. 6.

    Leip, A. et al. Impacts of European livestock production: nitrogen, sulphur, phosphorus and greenhouse gas emissions, land-use, water eutrophication and biodiversity. Environ. Res. Lett. 10, 115004 (2015).

  7. 7.

    Lassaletta, L. et al. Food and feed trade as a driver in the global nitrogen cycle: 50-year trends. Biogeochemistry 118, 225–241 (2014).

  8. 8.

    Schipanski, M. E. & Bennett, E. M. The influence of agricultural trade and livestock production on the global phosphorus cycle. Ecosystems 15, 256–268 (2012).

  9. 9.

    Schmitz, C. et al. Trading more food: implications for land use, greenhouse gas emissions, and the food system. Global Environ. Change 22, 189–209 (2012).

  10. 10.

    Xue, X. & Landis, A. E. Eutrophication potential of food consumption patterns. Environ. Sci. Technol. 44, 6450–6456 (2010).

  11. 11.

    Mekonnen, M. M., Lutter, S. & Martinez, A. Anthropogenic nitrogen and phosphorus emissions and related grey water footprints caused by EU-27’s crop production and consumption. Water 8, 1–14 (2016).

  12. 12.

    Oita, A. et al. Substantial nitrogen pollution embedded in international trade. Nat. Geosci. 9, 111–115 (2016).

  13. 13.

    MacDonald, G. K. et al. Rethinking agricultural trade relationships in an era of globalization. Bioscience 65, 275–289 (2015).

  14. 14.

    Hertwich, E. G. The life cycle environmental impacts of consumption. Econ. Syst. Res. 23, 27–47 (2011).

  15. 15.

    He, Q. et al. Economic development and coastal ecosystem change in China. Sci. Rep. 4, 1–9 (2014).

  16. 16.

    Wood, R. et al. Growth in environmental footprints and environmental impacts embodies in trade: resource efficiency indicators from EXIOBASE3. J. Indust. Ecol. https://doi.org/10.1111/jiec.12735 (2018).

  17. 17.

    Huijbregts, M. A. J. et al. ReCiPe2016: a harmonized life cycle impact assessment method at midpoint and endpoint level. Int. J. Life Cycle Assess. 22, 138–147 (2017).

  18. 18.

    Mekonnen, M. M. & Hoekstra, A. Y. Global gray water footprint and water pollution levels related to anthropogenic nitrogen loads to fresh water. Environ. Sci. Technol. 49, 12860–12868 (2015).

  19. 19.

    Giljum, S. et al. Identifying priority areas for European resource policies: a MRIO-based material footprint assessment. J. Econ. Struct. 5, 17 (2016).

  20. 20.

    Ivanova, D. et al. Environmental impact assessment of household consumption. J. Ind. Ecol. 20, 526–536 (2016).

  21. 21.

    Steen-Olsen, K., Wood, R. & Hertwich, E. G. The carbon footprint of Norwegian household consumption 1999-2012. J. Ind. Ecol. 20, 582–592 (2016).

  22. 22.

    Selman, M. & Greenhalgh, S. Eutrophication: Policies, Actions, and Strategies to Address Nutrient Pollution (World Resources Institute, 2009)..

  23. 23.

    European Commission Water Frameworks Directive (The EU Nitrates Directive 1–4, 2010); http://ec.europa.eu/environment/water/water-nitrates/index_en.html

  24. 24.

    Shortle, J. S. & Abler, D. G. Environmental Policies for Agricultural Pollution Control (Centre for Agriculture and Bioscience International, 2001).

  25. 25.

    European Commission DG Environment Joining Forces for Europe’s Shared Waters: Coordination in International River Basin Districts (The EU Water Framework Directive, 2008); http://ec.europa.eu/environment/water/water-framework/index_en.html

  26. 26.

    Sutton, M. A., Howard, C. M., Bleeker, A. & Datta, A. The global nutrient challenge: from science to public engagement. Environ. Dev. 6, 80–85 (2013).

  27. 27.

    Le, C. et al. Eutrophication of lake waters in China: cost, causes, and control. Environ. Manag. 45, 662–668 (2010).

  28. 28.

    Lenzen, M., Moran, D., Kanemoto, K. & Geschke, A. Building Eora: a global multi-region input–output database at high country and sector resolution. Econ. Syst. Res. 25, 20–49 (2013).

  29. 29.

    Weinzettel, J., Steen-Olsen, K., Hertwich, E. G., Borucke, M. & Galli, A. Ecological footprint of nations: comparison of process analysis, and standard and hybrid multiregional input–output analysis. Ecol. Econ. 101, 115–126 (2014).

  30. 30.

    Weinzettel, J. & Wood, R. Environmental footprints of agriculture embodied in international trade: sensitivity of harvested area footprint of Chinese exports. Ecol. Econ. 145, 323–330 (2018).

  31. 31.

    Moran, D. & Wood, R. Convergence between the EORA, WIOD, EXIOBASE, and OPENEU’S consumption-based carbon accounts. Econ. Syst. Res. 26, 1469–5758 (2014).

  32. 32.

    Tukker, A. Towards robust, authoritative assessments of environmental impacts embodied in trade: current state and recommendations. J. Indust. Ecol. https://doi.org/10.1111/jiec.12716 (2018).

  33. 33.

    Elser, J. J. et al. Global analysis of nitrogen and phosphorus limitation of primary producers in freshwater, marine and terrestrial ecosystems. Ecol. Lett. 10, 1135–1142 (2007).

  34. 34.

    Howarth, R. W. & Marino, R. Nitrogen as the limiting nutrient for eutrophication in coastal marine ecosystems: evolving views over three decades. Limnol. Oceanogr. 51, 364–376 (2006).

  35. 35.

    Sterner, R. W. On the phosphorus limitation paradigm for lakes. Int. Rev. Hydrobiol. 93, 433–445 (2008).

  36. 36.

    Azevedo, L. B. et al. Assessing the importance of spatial variability versus model choices in life cycle impact assessment: the case of freshwater eutrophication in Europe. Environ. Sci. Technol. 47, 13565–13570 (2013).

  37. 37.

    Helmes, R. J. K., Huijbregts, Ma. J., Henderson, A. D. & Jolliet, O. Spatially explicit fate factors of phosphorous emissions to freshwater at the global scale. Int. J. Life Cycle Assess. 17, 646–654 (2012).

  38. 38.

    Cosme, N., Jones, M. C., Cheung, W. W. L. & Larsen, H. F. Spatial differentiation of marine eutrophication damage indicators based on species density. Ecol. Indic. 73, 676–685 (2017).

  39. 39.

    Wood, R. et al. Global sustainability accounting-developing EXIOBASE for multi-regional footprint analysis. Sustain 7, 138–163 (2015).

  40. 40.

    Hertwich, E. & Peters, G. Carbon footprint of nations: a global, trade-linked analysis. Environ. Sci. Technol. 43, 6414–6420 (2009).

  41. 41.

    Zhang, C. & Anadon, L. D. A multi-regional input-output analysis of domestic virtual water trade and provincial water footprint in China. Ecol. Econ. 100, 159–172 (2014).

  42. 42.

    Simas, M., Wood, R. & Hertwich, E. Labor embodied in trade. J. Ind. Ecol. 19, 343–356 (2015).

  43. 43.

    Turner, K., Lenzen, M., Wiedmann, T. & Barrett, J. Examining the global environmental impact of regional consumption activities — part 1: a technical note on combining input-output and ecological footprint analysis. Ecol. Econ. 62, 37–44 (2007).

  44. 44.

    Miller, R. A. & Blair, P. D. Input-Output Analysis Foundations and Extensions (Cambridge Univ. Press, Cambridge, 2009).

  45. 45.

    Murray, J. & Wood, R. (eds) The Sustainability Practitioner’s Guide to Input-Output Analysis (Common Ground Research Networks, Champaign, IL, 2010).

  46. 46.

    Stadler, K. et al. EXIOBASE 3 Developing a time series of detailed Environmentally Extended Multi-Regional Input-Output tables. J. Ind. Ecol. https://doi.org/10.1111/jiec.12715 (2018).

  47. 47.

    Aguiar, A., Narayanan, B., & McDougall, R. An overview of the GTAP 9 data base. J. Glob. Econ. 1, 181–208 (2016).

  48. 48.

    Owen, A., Steen-Olsen, K., Barrett, J., Wiedmann, T. & Lenzen, M. A structural decomposition approach to comparing MRIO databases. Econ. Syst. Res. 26, 262–283 (2014).

  49. 49.

    Stadler, K., Steen-olsen, K. & Wood, R. The ‘rest of the world’—estimating the economic structure of missing regions in global multi-regional input-output tables. Econ. Syst. Res. 26, 303–326 (2014).

  50. 50.

    Steen-Olsen, K., Owen, A., Hertwich, E. G. & Lenzen, M. Effects of sector aggregation on CO2 multipliers in multiregional input-output analysis. Econ. Syst. Res. 284–302 (2014).

  51. 51.

    Bouwmeester, M. & Oosterhaven, J. Specification and aggregation errors in environmentally extended input–output models. Environ. Resour. Econ. 56, 307–335 (2013).

  52. 52.

    Dietzenbacher, E. & Lahr, M. L. Expanding extractions. Econ. Syst. Res. 25, 341–360 (2013).

  53. 53.

    FAOSTAT (FAO, accessed 25 February 2016); http://faostat.fao.org/site/567/DesktopDefault.aspx#ancor

  54. 54.

    Fertilizer Use by Crop Fertilizer and Plant Nutrition Bulletin 17 (FAO, 2006).

  55. 55.

    De Klein, C. et al. in 2006 IPCC Guidelines for National Greenhouse Gas Inventories Vol. 4 (eds Eggleston, H. S., Buendia, L., Miwa, K., Ngara, T. & Tanabe, K.) Ch. 11 (IGES, 2006).

  56. 56.

    Bouwman, A. F., Beusen, A. H. W. & Billen, G. Human alteration of the global nitrogen and phosphorus soil balances for the period 1970-2050. Global Biogeochem. Cycles 23, (2009).

  57. 57.

    Bennett, E. M., Carpenter, S. R. & Caraco, N. F. Human impact on erodable phosphorus and eutrophication: a global perspective. Bioscience 51, 227 (2001).

  58. 58.

    Cosme, N., Koski, M. & Hauschild, M. Z. Exposure factors for marine eutrophication impacts assessment based on a mechanistic biological model. Ecol. Modell. 317, 50–63 (2015).

  59. 59.

    Cosme, N., Mayorga, E. & Hauschild, M. Z. Spatially explicit fate factors of waterborne nitrogen emissions at the global scale. Int. J. Life Cycle Assess. https://doi.org/10.1007/s11367-017-1349-0 (2017).

  60. 60.

    Roy, P. O., Huijbregts, M., Deschênes, L. & Margni, M. Spatially-differentiated atmospheric source-receptor relationships for nitrogen oxides, sulfur oxides and ammonia emissions at the global scale for life cycle impact assessment. Atmos. Environ. 62, 74–81 (2012).

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Acknowledgements

We would like to thank K. Bjørset (Norkart), K. Steen-Olsen (Norwegian University of Science and Technology (NTNU)) and M. Simas (NTNU) for their technical support, M. Huijbrets (Radboud University) for his valuable comments and feedback, and G. Majeau-Bettez, C. Bulle (CIRAIG) and F. Verones (NTNU) for help with characterization factors. We would also like to thank R. Lonka (NTNU) for his assistance with the visualization tools.

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Affiliations

  1. Norwegian University of Science and Technology, Trondheim, Norway

    • Helen A. Hamilton
    • , Diana Ivanova
    • , Konstantin Stadler
    • , Daniel Moran
    •  & Richard Wood
  2. Aalborg University, Aalborg, Denmark

    • Stefano Merciai
    •  & Jannick Schmidt
  3. Radboud University, Nijmegen, the Netherlands

    • Rosalie van Zelm

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Contributions

H.A.H. and R.W. designed the study. R.W. prepared the IO model and basic results. S.M. and J.S. developed the phosphorus and nitrogen accounts. R.v.Z. prepared the impact assessment method. H.A.H. and D.I. conducted the analysis. D.M. conducted the sensitivity analysis. H.A.H. made the figures. H.A.H., R.W., K.S. and D.I. contributed to the data interpretation. H.A.H., D.I. and R.W. wrote the paper. H.A.H., R.W., D.I., R.v.Z., K.S., S.M., D.M. and J.S. contributed to manuscript editing.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Richard Wood.

Supplementary information

  1. Supplementary Information

    Supplementary Information, Supplementary Figures 1-4, Supplementary Tables 1-13, Supplementary References 1–81

  2. Supplementary Information Data File

    Supplementary data and results, including all footprint data (aggregates and by producing sectors) and economic data

  3. Statistical Code

    Statistical code for regressions

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DOI

https://doi.org/10.1038/s41893-018-0079-z

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