Environmental and social footprints of international trade

Abstract

Globalization has led to an increasing geospatial separation of production and consumption, and, as a consequence, to an unprecedented displacement of environmental and social impacts through international trade. A large proportion of total global impacts can be associated with trade, and the trend is rising. Advances in global multi-region input-output models have allowed researchers to draw detailed, international supply-chain connections between harmful production in social and environmental hotspots and affluent consumption in global centres of wealth. The general direction of impact displacement is from developed to developing countries—an increase of health impacts in China from air pollution linked to export production for the United States being one prominent example. The relocation of production across countries counteracts national mitigation policies and may negate ostensible achievements in decoupling impacts from economic growth. A comprehensive implementation of the United Nations Sustainable Development Goals therefore requires the inclusion of footprint indicators to avoid loopholes in national sustainability assessments.

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Fig. 1: Burden shifting.
Fig. 2: Average physical distances of national footprints in kilometres in 2010.
Fig. 3: Semi-quantitative visualization of the identity and frequency of environmental and social indicators used in footprint or trade studies.
Fig. 4: Closeness of commonly used GMRIO matrices measured in unitless cross-entropy distances and depicted on a two-dimensional plane using multidimensional scaling.

References

  1. 1.

    World Trade Statistical Review 2017 (World Trade Organization, 2017); https://www.wto.org/english/res_e/statis_e/wts2017_e/wts17_toc_e.htm

  2. 2.

    Acquaye, A. et al. Measuring the environmental sustainability performance of global supply chains: a multi-regional input-output analysis for carbon, sulphur oxide and water footprints. J. Environ. Manage. 187, 571–585 (2017).

    Article  Google Scholar 

  3. 3.

    Wiedmann, T. in Taking Stock of Industrial Ecology (eds Clift, R. & Druckman A.) 159–180 (Springer International Publishing, New York, 2016).

  4. 4.

    Hoekstra, A. Y. & Wiedmann, T. O. Humanity’s unsustainable environmental footprint. Science 344, 1114–1117 (2014).

    Article  Google Scholar 

  5. 5.

    Galli, A. et al. Integrating ecological, carbon and water footprint into a “footprint family” of indicators: definition and role in tracking human pressure on the planet. Ecol. Indic. 16, 100–112 (2012).

    Article  Google Scholar 

  6. 6.

    Hoekstra, A. Y. & Wiedmann, T. O. Humanity’s unsustainable environmental footprint. Science 344, 1114–1117 (2014).

    Article  Google Scholar 

  7. 7.

    Jiang, X. & Green, C. The impact on global greenhouse gas emissions of geographic shifts in global supply chains. Ecol. Econ. 139, 102–114 (2017).

    Article  Google Scholar 

  8. 8.

    Mi, Z. et al. Chinese CO2 emission flows have reversed since the global financial crisis. Nat. Commun. 8, 1712 (2017).

    Article  Google Scholar 

  9. 9.

    Liu, X. et al. Virtual carbon and water flows embodied in international trade: a review on consumption-based analysis. J. Clean. Prod. 146, 20–28 (2017).

    Article  Google Scholar 

  10. 10.

    de Vries, G. J. & Ferrarini, B. What accounts for the growth of carbon dioxide emissions in advanced and emerging economies? The role of consumption, technology and global supply chain participation. Ecol. Econ. 132, 213–223 (2017).

    Article  Google Scholar 

  11. 11.

    Zhao, Y. et al. Identifying the economic and environmental impacts of China’s trade in intermediates within the Asia-Pacific region. J. Clean. Prod. 149, 164–179 (2017).

    Article  Google Scholar 

  12. 12.

    Zhang, Z., Zhu, K. & Hewings, G. J. D. The effects of border-crossing frequencies associated with carbon footprints on border carbon adjustments. Energy Econ. 65, 105–114 (2017).

    Article  Google Scholar 

  13. 13.

    Moran, D. D., Lenzen, M., Kanemoto, K. & Geschke, A. Does ecologically unequal exchange occur? Ecol Econ. 89, 177–186 (2013).

    Article  Google Scholar 

  14. 14.

    Hoekstra, R., Michel, B. & Suh, S. The emission cost of international sourcing: using structural decomposition analysis to calculate the contribution of international sourcing to CO2-emission growth. Econ. Sys. Res. 28, 151–167 (2016).

    Article  Google Scholar 

  15. 15.

    Plank, B., Eisenmenger, N., Schaffartzik, A. & Wiedenhofer, D. International trade drives global resource use: a structural decomposition analysis of raw material consumption from 1990–2010. Environ. Sci. Technol. 52, 4190–4198 (2018).

    Article  Google Scholar 

  16. 16.

    Alsamawi, A., Murray, J., Lenzen, M. & Reyes, R. C. Trade in occupational safety and health: tracing the embodied human and economic harm in labour along the global supply chain. J. Clean. Prod. 147, 187–196 (2017).

    Article  Google Scholar 

  17. 17.

    Xiao, Y. et al. The corruption footprints of nations. J. Ind. Ecol. 22, 68–78 (2018).

    Article  Google Scholar 

  18. 18.

    Simas, M. et al. Correlation between production and consumption-based environmental indicators: the link to affluence and the effect on ranking environmental performance of countries. Ecol. Indic. 76, 317–323 (2017).

    Article  Google Scholar 

  19. 19.

    Wiedmann, T. O. et al. The material footprint of nations. Proc. Natl Acad. Sci. USA 112, 6271–6276 (2015).

    Article  Google Scholar 

  20. 20.

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

  21. 21.

    O’Neill, D. W., Fanning, A. L., Lamb, W. F. & Steinberger, J. K. A good life for all within planetary boundaries. Nat. Sustain. 1, 88–95 (2018).

    Article  Google Scholar 

  22. 22.

    Tian, X., Geng, Y., Sarkis, J. & Zhong, S. Trends and features of embodied flows associated with international trade based on bibliometric analysis. Resour. Conserv. Recycl. 131, 148–157 (2018).

    Article  Google Scholar 

  23. 23.

    Tukker, A., Giljum, S. & Wood, R. Recent progress in assessment of resource efficiency and environmental impacts embodied in trade: an introduction to this special issue. J. Ind. Ecol. https://doi.org/10.1111/jiec.12736 (2018).

  24. 24.

    Weinzettel, J. et al. Affluence drives the global displacement of land use. Global Environ. Change 23, 433–438 (2013).

    Article  Google Scholar 

  25. 25.

    Peters, G. P., Davis, S. J. & Andrew, R. A synthesis of carbon in international trade. Biogeosciences 9, 3247–3276 (2012).

    Article  Google Scholar 

  26. 26.

    Giljum, S., Bruckner, M. & Martinez, A. Material footprint assessment in a global input-output framework. J. Ind. Ecol. 19, 792–804 (2015).

    Article  Google Scholar 

  27. 27.

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

    Article  Google Scholar 

  28. 28.

    Peters, G. P. & Hertwich, E. G. CO2 embodied in international trade with implications for global climate policy. Environ. Sci. Technol. 42, 1401–1407 (2008).

    Article  Google Scholar 

  29. 29.

    Font Vivanco, D., Wang, R. & Hertwich, E. Nexus strength: a novel metric for assessing the global resource nexus. J. Ind. Ecol. https://doi.org/10.1111/jiec.12704 (2017).

  30. 30.

    Holland, R. A. et al. Global impacts of energy demand on the freshwater resources of nations. Proc. Natl Acad. Sci. USA 112, E6707–E6716 (2015).

    Article  Google Scholar 

  31. 31.

    Chen, B. et al. Global land-water nexus: agricultural land and freshwater use embodied in worldwide supply chains. Sci. Total Environ. 613–614, 931–943 (2018).

    Google Scholar 

  32. 32.

    Steinmann, Z. J. N. et al. Resource footprints are good proxies of environmental damage. Environ. Sci. Technol. 51, 6360–6366 (2017).

    Article  Google Scholar 

  33. 33.

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

    Article  Google Scholar 

  34. 34.

    Zhang, Q. et al. Transboundary health impacts of transported global air pollution and international trade. Nature 543, 705–709 (2017).

    Article  Google Scholar 

  35. 35.

    Lin, J. et al. China’s international trade and air pollution in the United States. Proc. Natl Acad. Sci. USA 111, 1736–1741 (2014).

    Article  Google Scholar 

  36. 36.

    Faturay, F., Lenzen, M. & Nugraha, K. A new sub-national multi-region input–output database for Indonesia. Econ. Sys. Res. 29, 234–251 (2017).

    Article  Google Scholar 

  37. 37.

    Lenzen, M. et al. New multi-regional input–output databases for Australia – enabling timely and flexible regional analysis. Econ. Sys. Res. 29, 275–295 (2017).

    Article  Google Scholar 

  38. 38.

    Bachmann, C., Roorda, M. J. & Kennedy, C. Developing a multi-scale multi-region input-output model. Econ. Sys. Res. 27, 172–193 (2015).

    Article  Google Scholar 

  39. 39.

    Wang, Y., Geschke, A. & Lenzen, M. Constructing a time series of nested multiregion input–output tables. Int. Reg. Sci. Rev. 40, 476–499 (2017).

    Article  Google Scholar 

  40. 40.

    Wenz, L. et al. Regional and sectoral disaggregation of multi-regional input-output tables - a flexible algorithm. Econ. Sys. Res. 27, 194–212 (2015).

    Article  Google Scholar 

  41. 41.

    Geschke, A. & Hadjikakou, M. Virtual laboratories and MRIO analysis – an introduction. Econ. Sys. Res. 29, 143–157 (2017).

    Article  Google Scholar 

  42. 42.

    Lenzen, M. et al. Compiling and using input–output frameworks through collaborative virtual laboratories. Sci. Total Environ. 485–486, 241–251 (2014).

    Article  Google Scholar 

  43. 43.

    Lenzen, M. et al. The global MRIO Lab – charting the world economy. Econ. Sys. Res. 29, 158–186 (2017).

    Article  Google Scholar 

  44. 44.

    Kanemoto, K., Moran, D., Lenzen, M. & Geschke, A. International trade undermines national emission reduction targets: new evidence from air pollution. Global Environ. Change 24, 52–59 (2014).

    Article  Google Scholar 

  45. 45.

    Moran, D. & Kanemoto, K. Tracing global supply chains to air pollution hotspots. Environ. Res. Lett. 11, 094017 (2016).

    Article  Google Scholar 

  46. 46.

    Kanemoto, K., Moran, D. & Hertwich, E. G. Mapping the carbon footprint of nations. Environ. Sci. Technol. 50, 10512–10517 (2016).

    Article  Google Scholar 

  47. 47.

    Meng, J. et al. Globalization and pollution: tele-connecting local primary PM2.5 emissions to global consumption. Proc. R. Soc. A 472, 2195 (2016).

    Article  Google Scholar 

  48. 48.

    Liang, S. et al. Consumption-based human health impacts of primary PM2.5: the hidden burden of international trade. J. Clean. Prod. 167, 133–139 (2017).

    Article  Google Scholar 

  49. 49.

    Xiao, Y., Murray, J. & Lenzen, M. International trade linked with disease burden from airborne particulate pollution. Resour. Conserv. Recycl. 129, 1–11 (2018).

    Article  Google Scholar 

  50. 50.

    Takahashi, K. et al. Production-based emissions, consumption-based emissions and consumption-based health impacts of PM2.5 carbonaceous aerosols in Asia. Atmos. Environ. 97, 406–415 (2014).

    Article  Google Scholar 

  51. 51.

    Jiang, X. et al. Revealing the hidden health costs embodied in Chinese exports. Environ. Sci. Technol. 49, 4381–4388 (2015).

    Article  Google Scholar 

  52. 52.

    Lin, J. et al. Global climate forcing of aerosols embodied in international trade. Nat. Geosci. 9, 790–794 (2016).

    Article  Google Scholar 

  53. 53.

    Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES, 2017); https://www.cites.org/eng/disc/text.php

  54. 54.

    Lenzen, M. et al. International trade drives biodiversity threats in developing nations. Nature 486, 109–112 (2012).

    Article  Google Scholar 

  55. 55.

    Chaudhary, A. & Brooks, T. M. National consumption and global trade impacts on biodiversity. World Dev. https://doi.org/10.1016/j.worlddev.2017.10.012 (2017).

  56. 56.

    Wilting, H. C. et al. Quantifying biodiversity losses due to human consumption: a global-scale footprint analysis. Environ. Sci. Technol. 51, 3298–3306 (2017).

    Article  Google Scholar 

  57. 57.

    Marques, A. et al. How to quantify biodiversity footprints of consumption? A review of multi-regional input–output analysis and life cycle assessment. Curr. Opin. Environ. Sust. 29, 75–81 (2017).

    Article  Google Scholar 

  58. 58.

    Verones, F. et al. Resource footprints and their ecosystem consequences. Sci. Rep. 7, 40743 (2017).

    Article  Google Scholar 

  59. 59.

    Moran, D. & Kanemoto, K. Identifying species threat hotspots from global supply chains. Nat. Ecol. Evol. 1, 0023 (2017).

    Article  Google Scholar 

  60. 60.

    Ewing, B. R. et al. Integrating ecological and water footprint accounting in a multi-regional input–output framework. Ecol. Indic. 23, 1–8 (2012).

    Article  Google Scholar 

  61. 61.

    Yu, Y., Feng, K. & Hubacek, K. Tele-connecting local consumption to global land use. Global Environ. Change 23, 1178–1186 (2013).

    Article  Google Scholar 

  62. 62.

    Font Vivanco, D., Sprecher, B. & Hertwich, E. Scarcity-weighted global land and metal footprints. Ecol. Indic. 83, 323–327 (2017).

    Article  Google Scholar 

  63. 63.

    Wang, R., Hertwich, E. & Zimmerman, J. B. Virtual water flows uphill toward money. Environ. Sci. Technol. 50, 12320–12330 (2016).

    Article  Google Scholar 

  64. 64.

    Chen, Z.-M. & Chen, G. Q. Virtual water accounting for the globalized world economy: national water footprint and international virtual water trade. Ecol. Indic. 28, 142–149 (2013).

    Article  Google Scholar 

  65. 65.

    Arto, I., Andreoni, V. & Rueda-Cantuche, J. M. Global use of water resources: a multiregional analysis of water use, water footprint and water trade balance. Water Resour. Econom. 15, 1–14 (2016).

    Article  Google Scholar 

  66. 66.

    Dalin, C. et al. Evolution of the global virtual water trade network. Proc. Natl Acad. Sci. USA 109, 5989–5994 (2012).

    Article  Google Scholar 

  67. 67.

    Chenoweth, J., Hadjikakou, M. & Zoumides, C. Quantifying the human impact on water resources: a critical review of the water footprint concept. Hydrol. Earth Syst. Sci. 18, 2325–2342 (2014).

    Article  Google Scholar 

  68. 68.

    Wichelns, D. Virtual water and water footprints do not provide helpful insight regarding international trade or water scarcity. Ecol. Indic. 52, 277–283 (2015).

    Article  Google Scholar 

  69. 69.

    Lenzen, M. et al. International trade of scarce water. Ecol. Econ. 94, 78–85 (2013).

    Article  Google Scholar 

  70. 70.

    Lutter, S. et al. Spatially explicit assessment of water embodied in European trade: a product-level multi-regional input-output analysis. Global Environ. Change 38, 171–182 (2016).

    Article  Google Scholar 

  71. 71.

    Wan, L., Cai, W., Jiang, Y. & Wang, C. Impacts on quality-induced water scarcity: drivers of nitrogen-related water pollution transfer under globalization from 1995 to 2009. Environ. Res. Lett. 11, 074017 (2016).

    Article  Google Scholar 

  72. 72.

    Dalin, C., Wada, Y., Kastner, T. & Puma, M. J. Groundwater depletion embedded in international food trade. Nature 543, 700–704 (2017).

    Article  Google Scholar 

  73. 73.

    Chen, B. et al. Global energy flows embodied in international trade: a combination of environmentally extended input–output analysis and complex network analysis. Appl. Energ. 210, 98–107 (2018).

    Article  Google Scholar 

  74. 74.

    Wu, X. F. & Chen, G. Q. Global primary energy use associated with production, consumption and international trade. Energy Policy 111, 85–94 (2017).

    Article  Google Scholar 

  75. 75.

    Zheng, X. et al. High sensitivity of metal footprint to national GDP in part explained by capital formation. Nat. Geosci. 11, 269–273 (2018).

    Article  Google Scholar 

  76. 76.

    Fang, K. & Heijungs, R. Investigating the inventory and characterization aspects of footprinting methods: lessons for the classification and integration of footprints. J. Clean. Prod. 108, 1028–1036 (2015).

    Article  Google Scholar 

  77. 77.

    Simas, M., Wood, R. & Hertwich, E. Labor embodied in trade - the role of labor and energy productivity and implications for greenhouse gas emissions. J. Ind. Ecol. 19, 343–356 (2015).

    Article  Google Scholar 

  78. 78.

    Simas, M. et al. The “bad labor” footprint: quantifying the social impacts of globalization. Sustainability 6, 7514–7540 (2014).

    Article  Google Scholar 

  79. 79.

    Alsamawi, A., Murray, J. & Lenzen, M. The employment footprints of nations: uncovering master-servant relationships. J. Ind. Ecol. 18, 59–70 (2014).

    Article  Google Scholar 

  80. 80.

    Alsamawi, A. et al. The inequality footprints of nations: a novel approach to quantitative accounting of income inequality. PLoS ONE 9, e110881 (2014).

    Article  Google Scholar 

  81. 81.

    Gómez-Paredes, J., Yamasue, E., Okumura, H. & Ishihara, K. N. The labour footprint: a framework to assess labour in a complex economy. Econ. Sys. Res. 27, 415–439 (2015).

    Article  Google Scholar 

  82. 82.

    Gómez-Paredes, J. et al. Consuming childhoods: an assessment of child labor’s role in indian production and global consumption. J. Ind. Ecol. 20, 611–622 (2016).

    Article  Google Scholar 

  83. 83.

    Xiao, Y. et al. How social footprints of nations can assist in achieving the sustainable development goals. Ecol. Econ. 135, 55–65 (2017).

    Article  Google Scholar 

  84. 84.

    Andrew, R. M., Davis, S. J. & Peters, G. P. Climate policy and dependence on traded carbon. Environ. Res. Lett. 8, 034011 (2013).

    Article  Google Scholar 

  85. 85.

    Bringezu, S. et al. Multi-scale governance of sustainable natural resource use—challenges and opportunities for monitoring and institutional development at the national and global level. Sustainability 8, 778 (2016).

    Article  Google Scholar 

  86. 86.

    IPCC Climate Change 2014: Mitigation of Climate Change (eds Edenhofer, O. et al.) (Cambridge Univ. Press, 2014).

  87. 87.

    Afionis, S. et al. Consumption-based carbon accounting: does it have a future? Wiley Interdiscip. Rev. Clim. Change 8, e438 (2017).

    Article  Google Scholar 

  88. 88.

    Barrett, J. et al. Consumption-based GHG emission accounting: a UK case study. Climate Policy 13, 451–470 (2013).

    Article  Google Scholar 

  89. 89.

    Grasso, M. The political feasibility of consumption-based carbon accounting. New Political Econ. 21, 401–413 (2016).

    Article  Google Scholar 

  90. 90.

    Jakob, M. & Marschinski, R. Interpreting trade-related CO2 emission transfers. Nat. Clim. Change 3, 19–23 (2013).

    Article  Google Scholar 

  91. 91.

    Foran, B., Lenzen, M., Dey, C. & Bilek, M. Integrating sustainable chain management with triple bottom line reporting. Ecol. Econ. 52, 143–157 (2005).

    Article  Google Scholar 

  92. 92.

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

    Article  Google Scholar 

  93. 93.

    Wiebe, K. S. & Yamano, N. Estimating CO 2 Emissions Embodied in Final Demand and Trade Using the OECD ICIO 2015 (OECD, 2016).

  94. 94.

    Gilijum, S. et al. Empirical Assessment of the OECD Inter-Country Input-Output Database to Calculate Demand-Based Material Flows (OECD, Working Party on Environmental Information, 2017).

  95. 95.

    Natural Resources: Resource Efficiency Indicators (UNEP, Environment Live, accessed 1 January 2018); http://www.uneplive.org/material

  96. 96.

    SDG Indicators: Global Indicator Framework for the Sustainable Development Goals and Targets of the 2030 Agenda for Sustainable Development (UNSD, 2018); https://unstats.un.org/sdgs/indicators/indicators-list/

  97. 97.

    Wiedmann, T. & Barrett, J. Policy-relevant applications of environmentally extended MRIO databases - experiences from the UK. Econ. Sys. Res. 25, 143–156 (2013).

    Article  Google Scholar 

  98. 98.

    Gros, D. & Egenhofer, C. The case for taxing carbon at the border. Climate Policy 11, 1262–1268 (2011).

    Article  Google Scholar 

  99. 99.

    Sakai, M. & Barrett, J. Border carbon adjustments: addressing emissions embodied in trade. Energy Policy 92, 102–110 (2016).

    Article  Google Scholar 

  100. 100.

    Steininger, K. et al. Justice and cost effectiveness of consumption-based versus production-based approaches in the case of unilateral climate policies. Global Environ. Change 24, 75–87 (2014).

    Article  Google Scholar 

  101. 101.

    Barrett, J. & Scott, K. Link between climate change mitigation and resource efficiency: a UK case study. Global Environ. Change 22, 299–307 (2012).

    Article  Google Scholar 

  102. 102.

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

    Article  Google Scholar 

  103. 103.

    Raworth, K. Doughnut Economics: Seven Ways to Think Like a 21st Century Economist (Chelsea Green Publishing, Vermont, 2017).

  104. 104.

    Allen, C., Metternicht, G. & Wiedmann, T. National pathways to the Sustainable Development Goals (SDGs): a comparative review of scenario modelling tools. Environ. Sci. Policy 66, 199–207 (2016).

    Article  Google Scholar 

  105. 105.

    International Trade in Resources: A Biophysical Assessment (UNEP, 2015).

  106. 106.

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

  107. 107.

    Dalin, C. & Rodríguez-Iturbe, I. Environmental impacts of food trade via resource use and greenhouse gas emissions. Environ. Res. Lett. 11, 035012 (2016).

    Article  Google Scholar 

  108. 108.

    Wiedmann, T. et al. Quo Vadis MRIO? Methodological, data and institutional requirements for multi-region input-output analysis. Ecol. Econ. 70, 1937–1945 (2011).

    Article  Google Scholar 

  109. 109.

    Södersten, C.-J., Wood, R. & Hertwich, E. G. Environmental impacts of capital formation. J. Ind. Ecol. 22, 55–67 (2018).

    Article  Google Scholar 

  110. 110.

    Pauliuk, S., Arvesen, A., Stadler, K. & Hertwich, E. G. Industrial ecology in integrated assessment models. Nat. Clim. Change 7, 13–20 (2017).

    Article  Google Scholar 

  111. 111.

    Liu, J. et al. Systems integration for global sustainability. Science 347, 1258832 (2015).

    Article  Google Scholar 

  112. 112.

    Cherniwchan, J., Copeland, B. R. & Taylor, M. S. Trade and the environment: new methods, measurements, and results. Annu. Rev. Econ. 9, 59–85 (2017).

    Article  Google Scholar 

  113. 113.

    Pfister, S., Hadjkakou, M. & Wiedmann, T. How Distant are Consumers from their Environmental Footprints and Economic benefits? (9th Biennial Conference of the International Society for Industrial Ecology: Science in Support of Sustainable and Resilient Communities, 2017).

  114. 114.

    Abd Rahman, M. D. et al. A flexible adaptation of the WIOD database in a virtual laboratory. Econ. Sys Res. 29, 187–208 (2017).

    Article  Google Scholar 

  115. 115.

    Leontief, W. Quantitative input and output relations in the economic system of the United States. Rev. Econ. Stat. 18, 105–125 (1936).

    Article  Google Scholar 

  116. 116.

    Toward the UN Handbook on Supply and Use Tables and Input–Output Tables (UNSD, 2017); https://unstats.un.org/unsd/envaccounting/londongroup/meeting21/3_unsd.pdf

  117. 117.

    Tukker, A. & Dietzenbacher, E. Global multiregional input–output frameworks: an introduction and outlook. Econ. Sys. Res. 25, 1–19 (2013).

    Article  Google Scholar 

  118. 118.

    Inomata, S. & Owen, A. Comparative evaluation of MRIO databases. Econ. Sys. Res. 26, 239–244 (2014).

    Article  Google Scholar 

  119. 119.

    Moran, D. & Wood, R. Convergence between the Eora, WIOD, EXIOBASE and Open-EU’s consumption-based carbon accounts. Econ. Sys. Res. 26, 245–261 (2014).

    Article  Google Scholar 

  120. 120.

    Owen, A. et al. A structural decomposition approach to comparing MRIO databases. Econ. Sys. Res. 26, 262–283 (2014).

    Article  Google Scholar 

  121. 121.

    Lenzen, M., Wood, R. & Wiedmann, T. Uncertainty analysis for multi-region input–output models – a case study of the UK’s carbon footprint. Econ. Sys. Res. 22, 43–63 (2010).

    Article  Google Scholar 

  122. 122.

    Leontief, W. & Duchin, F. The Future Impact of Automation on Workers (Oxford Univ. Press, New York, 1986).

  123. 123.

    Leontief, W. Environmental repercussions and the economic structure: an input–output approach. Rev. Econ. Stat. 52, 262–271 (1970).

    Article  Google Scholar 

  124. 124.

    Leontief, W. Structure of the world economy: outline of a simple input–output formulation. Am. Econ. Rev. 64, 823–834 (1974).

    Google Scholar 

  125. 125.

    Leontief, W. (ed.) in Input Output Economics 418–428 (Oxford Univ. Press, New York, 1986).

  126. 126.

    Bullard, C. W. & Herendeen, R. A. The energy cost of goods and services. Energy Policy 3, 268–278 (1975).

    Article  Google Scholar 

  127. 127.

    Costanza, R. Embodied energy and economic valuation. Science 210, 1219–1224 (1980).

    Article  Google Scholar 

  128. 128.

    Proops, J. L. R., Faber, M. & Wagenhals, G. Reducing CO 2 Emissions: A Comparative Input-Output-Study for Germany and the UK (Springer-Verlag, Berlin, 1993).

  129. 129.

    Heijungs, R. & Suh, S. The Computational Structure of Life Cycle Assessment (Kluwer Academic Publishers, Dordrecht, 2002).

  130. 130.

    System of Environmental-Economic Accounting 2012 — Central Framework (UN, EY, FAO, IMF, OECD, World Bank, 2014); http://unstats.un.org/unsd/envaccounting/seeaRev/SEEA_CF_Final_en.pdf

  131. 131.

    Rose, A. & Miernyk, W. Input–output analysis: the first fifty years. Econ. Sys. Res. 1, 229–272 (1989).

    Article  Google Scholar 

  132. 132.

    Dietzenbacher, E. et al. Input-output analysis: the next 25 years. Econ. Sys. Res. 25, 369–389 (2013).

    Article  Google Scholar 

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Acknowledgements

We thank J. Barrett, University of Leeds, for advice on the policy relevance of consumption-based accounting. Data, help and advice from S. Pfister, ETH Zurich, Switzerland, for preparing the footprint distances maps is greatly acknowledged.

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T.W. and M.L. wrote the paper. T.W. analysed data to create Figs. 13.

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Correspondence to Thomas Wiedmann.

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Supplementary Table, Supplementary References.

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Wiedmann, T., Lenzen, M. Environmental and social footprints of international trade. Nature Geosci 11, 314–321 (2018). https://doi.org/10.1038/s41561-018-0113-9

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