Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Global human-made mass exceeds all living biomass


Humanity has become a dominant force in shaping the face of Earth1,2,3,4,5,6,7,8,9. An emerging question is how the overall material output of human activities compares to the overall natural biomass. Here we quantify the human-made mass, referred to as ‘anthropogenic mass’, and compare it to the overall living biomass on Earth, which currently equals approximately 1.1 teratonnes10,11. We find that Earth is exactly at the crossover point; in the year 2020 (± 6), the anthropogenic mass, which has recently doubled roughly every 20 years, will surpass all global living biomass. On average, for each person on the globe, anthropogenic mass equal to more than his or her bodyweight is produced every week. This quantification of the human enterprise gives a mass-based quantitative and symbolic characterization of the human-induced epoch of the Anthropocene.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Biomass and anthropogenic mass estimates since the beginning of the twentieth century on a dry-mass basis.
Fig. 2: Biomass (dry and wet), anthropogenic mass and anthropogenic mass waste estimates since the beginning of the twentieth century.
Fig. 3: Contrasting key components of global biomass and anthropogenic mass in the year 2020 (dry-weight basis).

Similar content being viewed by others

Data availability

All data used in this study are available on GitHub, at Anthropogenic mass data are available from ref. 22 and at TRENDY Dynamic Global Vegetation Models outputs are available at Leaves dry matter content measurements were obtained via TryDB, at Other datasets used in this study are available from the published literature, as detailed in the Methods and Supplementary Information.

Code availability

All code used in this study is available on GitHub, at


  1. Ramankutty, N. & Foley, J. A. Estimating historical changes in global land cover: croplands from 1700 to 1992. Glob. Biogeochem. Cycles 13, 997–1027 (1999).

    ADS  CAS  Google Scholar 

  2. Krausmann, F. et al. Growth in global materials use, GDP and population during the 20th century. Ecol. Econ. 68, 2696–2705 (2009).

    Google Scholar 

  3. Matthews, E. The Weight of Nations: Material Outflows from Industrial Economies (World Resources Inst., 2000).

  4. Smil, V. Harvesting the Biosphere: What We Have Taken from Nature (MIT Press, 2013).

  5. Smil, V. Making the Modern World: Materials and Dematerialization (John Wiley & Sons, 2013).

  6. Haff, P. K. Technology as a geological phenomenon: implications for human well-being. Geol. Soc. Lond. Spec. Publ. 395, 301–309 (2014).

    ADS  Google Scholar 

  7. Zalasiewicz, J. et al. Scale and diversity of the physical technosphere: a geological perspective. Anthropocene Rev. 4, 9–22 (2017).

    Google Scholar 

  8. Zalasiewicz, J., Waters, C. N., Williams, M. & Summerhayes, C. The Anthropocene as a Geological Time Unit: A Guide to the Scientific Evidence and Current Debate (Cambridge Univ. Press, 2018).

  9. Stephens, L. et al. Archaeological assessment reveals Earth’s early transformation through land use. Science 365, 897–902 (2019).

    ADS  CAS  PubMed  Google Scholar 

  10. Erb, K.-H. et al. Unexpectedly large impact of forest management and grazing on global vegetation biomass. Nature 553, 73–76 (2018).

    ADS  CAS  PubMed  Google Scholar 

  11. Bar-On, Y. M., Phillips, R. & Milo, R. The biomass distribution on Earth. Proc. Natl Acad. Sci. USA 115, 6506–6511 (2018).

    CAS  PubMed  Google Scholar 

  12. Pan, Y. et al. A large and persistent carbon sink in the world’s forests. Science 333, 988–993 (2011).

    ADS  CAS  PubMed  Google Scholar 

  13. Reddington, C. L. et al. Air quality and human health improvements from reductions in deforestation-related fire in Brazil. Nat. Geosci. 8, 768–771 (2015).

    ADS  CAS  Google Scholar 

  14. Ceballos, G. & Ehrlich, P. R. Mammal population losses and the extinction crisis. Science 296, 904–907 (2002).

    ADS  CAS  PubMed  Google Scholar 

  15. WWF. Living Planet Report–2018: Aiming Higher (WWF, 2018).

  16. Bar-On, Y. M. & Milo, R. Towards a quantitative view of the global ubiquity of biofilms. Nat. Rev. Microbiol. 17, 199–200 (2019).

    CAS  PubMed  Google Scholar 

  17. Pauliuk, S. & Hertwich, E. G. Socioeconomic metabolism as paradigm for studying the biophysical basis of human societies. Ecol. Econ. 119, 83–93 (2015).

    Google Scholar 

  18. Haberl, H. et al. Contributions of sociometabolic research to sustainability science. Nat. Sustainability 2, 173–184 (2019).

    Google Scholar 

  19. Fischer-Kowalski, M. et al. Methodology and indicators of economy-wide material flow accounting. J. Ind. Ecol. 15, 855–876 (2011).

    Google Scholar 

  20. Krausmann, F., Schandl, H., Eisenmenger, N., Giljum, S. & Jackson, T. Material flow accounting: measuring global material use for sustainable development. Annu. Rev. Environ. Resour. 42, 647–675 (2017).

    Google Scholar 

  21. Krausmann, F. et al. Global socioeconomic material stocks rise 23-fold over the 20th century and require half of annual resource use. Proc. Natl Acad. Sci. USA 114, 1880–1885 (2017).

    CAS  PubMed  Google Scholar 

  22. Krausmann, F., Lauk, C., Haas, W. & Wiedenhofer, D. From resource extraction to outflows of wastes and emissions: the socioeconomic metabolism of the global economy, 1900–2015. Glob. Environ. Change 52, 131–140 (2018).

    PubMed  PubMed Central  Google Scholar 

  23. Steffen, W., Broadgate, W., Deutsch, L., Gaffney, O. & Ludwig, C. The trajectory of the Anthropocene: the great acceleration. Anthropocene Rev. 2, 81–98 (2015).

    Google Scholar 

  24. Vitousek, P. M., Ehrlich, P. R., Ehrlich, A. H. & Matson, P. A. Human appropriation of the products of photosynthesis. Bioscience 36, 368–373 (1986).

    Google Scholar 

  25. Haberl, H. et al. Quantifying and mapping the human appropriation of net primary production in Earth’s terrestrial ecosystems. Proc. Natl Acad. Sci. USA 104, 12942–12947 (2007).

    ADS  CAS  PubMed  Google Scholar 

  26. Haberl, H., Erb, K.-H. & Krausmann, F. Human appropriation of net primary production: patterns, trends, and planetary boundaries. Annu. Rev. Environ. Resour. 39, 363–391 (2014).

    Google Scholar 

  27. Vitousek, P. M. Human domination of Earth’s ecosystems. Science 277, 494–499 (1997).

    CAS  Google Scholar 

  28. Dirzo, R. et al. Defaunation in the Anthropocene. Science 345, 401–406 (2014).

    ADS  CAS  PubMed  Google Scholar 

  29. Crutzen, P. J. in Earth System Science in the Anthropocene (eds. Ehlers, E. & Kraft, T.) 13–18 (Springer, 2006).

  30. Steffen, W., Crutzen, J. & McNeill, J. R. The Anthropocene: are humans now overwhelming the great forces of Nature? Ambio 36, 614–621 (2007).

    CAS  PubMed  Google Scholar 

  31. Lewis, S. L. & Maslin, M. A. Defining the Anthropocene. Nature 519, 171–180 (2015).

    ADS  CAS  PubMed  Google Scholar 

  32. Waters, C. N. et al. The Anthropocene is functionally and stratigraphically distinct from the Holocene. Science 351, aad2622 (2016).

    PubMed  Google Scholar 

  33. Krausmann, F. et al. Economy-wide Material Flow Accounting. Introduction and Guide Version 1, Social Ecology Working Paper 151 (Alpen-Adria Univ., 2015).

  34. Miatto, A., Schandl, H., Fishman, T. & Tanikawa, H. Global patterns and trends for non-metallic minerals used for construction. J. Ind. Ecol. 21, 924–937 (2017).

    Google Scholar 

  35. Cooper, A. H., Brown, T. J., Price, S. J., Ford, J. R. & Waters, C. N. Humans are the most significant global geomorphological driving force of the 21st century. Anthropocene Rev. 5, 222–229 (2018).

    Google Scholar 

  36. Food and Agriculture Organization of the United Nations. Global Forest Resources Assessment 2010: Main Report (FAO, 2010).

  37. Liu, Y. Y. et al. Recent reversal in loss of global terrestrial biomass. Nat. Clim. Chang. 5, 470–474 (2015).

    ADS  Google Scholar 

  38. Sitch, S. et al. Recent trends and drivers of regional sources and sinks of carbon dioxide. Biogeosciences 12, 653–679 (2015).

    ADS  Google Scholar 

  39. Friedlingstein, P. et al. Global carbon budget 2019. Earth Syst. Sci. Data 11, 1783–1838 (2019).

    ADS  Google Scholar 

  40. Food and Agriculture Organization of the United Nations FAOSTAT

  41. Magnabosco, C. et al. The biomass and biodiversity of the continental subsurface. Nat. Geosci. 11, 707–717 (2018).

    ADS  CAS  Google Scholar 

  42. Haverd, V. et al. A new version of the CABLE land surface model (Subversion revision r4601) incorporating land use and land cover change, woody vegetation demography, and a novel optimisation-based approach to plant coordination of photosynthesis. Geosci. Model Dev. 11, 2995–3026 (2018).

    ADS  CAS  Google Scholar 

  43. Melton, J. R. & Arora, V. K. Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0. Geosci. Model Dev. 9, 323–361 (2016).

    ADS  CAS  Google Scholar 

  44. Lawrence, D. M. et al. The community land model version 5: description of new features, benchmarking, and impact of forcing uncertainty. J. Adv. Model. Earth Syst. 11, 4245–4287 (2019).

    ADS  Google Scholar 

  45. Tian, H. et al. North American terrestrial CO2 uptake largely offset by CH4 and N2O emissions: toward a full accounting of the greenhouse gas budget. Clim. Change 129, 413–426 (2015).

    ADS  CAS  PubMed  Google Scholar 

  46. Meiyappan, P., Jain, A. K. & House, J. I. Increased influence of nitrogen limitation on CO2 emissions from future land use and land use change. Glob. Biogeochem. Cycles 29, 1524–1548 (2015).

    ADS  CAS  Google Scholar 

  47. Mauritsen, T. et al. Developments in the MPI-M Earth System Model version1.2 (MPI-ESM1.2) and its response to increasing CO2. J. Adv. Model. Earth Syst. 11, 998–1038 (2019).

    ADS  PubMed  PubMed Central  Google Scholar 

  48. Clark, D. B. et al. The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation dynamics. Geosci. Model Dev. 4, 701–722 (2011).

    ADS  Google Scholar 

  49. Poulter, B., Frank, D. C., Hodson, E. L. & Zimmermann, N. E. Impacts of land cover and climate data selection on understanding terrestrial carbon dynamics and the CO2 airborne fraction. Biogeosciences 8, 2027–2036 (2011).

    ADS  CAS  Google Scholar 

  50. Smith, B. et al. Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model. Biogeosciences 11, 2027–2054 (2014).

    ADS  Google Scholar 

  51. Lienert, S. & Joos, F. A Bayesian ensemble data assimilation to constrain model parameters and land-use carbon emissions. Biogeosciences 15, 2909–2930 (2018).

    ADS  CAS  Google Scholar 

  52. Zaehle, S. & Friend, A. D. Carbon and nitrogen cycle dynamics in the O-CN land surface model: 1. Model description, site-scale evaluation, and sensitivity to parameter estimates. Glob. Biogeochem. Cycles 24, GB1005 (2010).

    ADS  Google Scholar 

  53. Krinner, G. et al. A dynamic global vegetation model for studies of the coupled atmosphere–biosphere system. Glob. Biogeochem. Cycles 19, GB1015 (2005).

    ADS  Google Scholar 

  54. Goll, D. S. et al. Carbon–nitrogen interactions in idealized simulations with JSBACH (version 3.10). Geosci. Model Dev. 10, 2009–2030 (2017).

    ADS  CAS  Google Scholar 

  55. Walker, A. P. et al. The impact of alternative trait-scaling hypotheses for the maximum photosynthetic carboxylation rate (Vcmax) on global gross primary production. New Phytol. 215, 1370–1386 (2017).

    CAS  PubMed  Google Scholar 

  56. Kato, E., Kinoshita, T., Ito, A., Kawamiya, M. & Yamagata, Y. Evaluation of spatially explicit emission scenario of land-use change and biomass burning using a process-based biogeochemical model. J. Land Use Sci. 8, 104–122 (2013).

    Google Scholar 

  57. Tang, Z. et al. Patterns of plant carbon, nitrogen, and phosphorus concentration in relation to productivity in China’s terrestrial ecosystems. Proc. Natl Acad. Sci. USA 115, 4033–4038 (2018).

    PubMed  Google Scholar 

  58. Poorter, H. et al. Biomass allocation to leaves, stems and roots: meta-analyses of interspecific variation and environmental control. New Phytol. 193, 30–50 (2012).

    CAS  PubMed  Google Scholar 

  59. Heldal, M., Norland, S. & Tumyr, O. X-ray microanalytic method for measurement of dry matter and elemental content of individual bacteria. Appl. Environ. Microbiol. 50, 1251–1257 (1985).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. von Stockar, U. & Liu, J. Does microbial life always feed on negative entropy? Thermodynamic analysis of microbial growth. Biochim. Biophys. Acta 1412, 191–211 (1999).

    Google Scholar 

  61. Guo, L., Lin, H., Fan, B., Cui, X. & Chen, J. Impact of root water content on root biomass estimation using ground penetrating radar: evidence from forward simulations and field controlled experiments. Plant Soil 371, 503–520 (2013).

    CAS  Google Scholar 

  62. Glass, S. V. & Zelinka, S. L. in Wood Handbook: Wood as an Engineering Material Vol. 190, 4.1–4.19 (US Department of Agriculture, 2010).

  63. Loveys, B. R. et al. Thermal acclimation of leaf and root respiration: an investigation comparing inherently fast- and slow-growing plant species. Glob. Change Biol. 9, 895–910 (2003).

    ADS  Google Scholar 

  64. Sheremetev, S. N. Herbs on the Soil Moisture Gradient (Water Relations and the Structural-Functional Organization) (KMK, 2005).

  65. Michaletz, S. T. & Johnson, E. A. A heat transfer model of crown scorch in forest fires. Can. J. For. Res. 36, 2839–2851 (2006).

    Google Scholar 

  66. Messier, J., McGill, B. J. & Lechowicz, M. J. How do traits vary across ecological scales? A case for trait-based ecology. Ecol. Lett. 13, 838–848 (2010).

    PubMed  Google Scholar 

  67. Boucher, F. C., Thuiller, W., Arnoldi, C., Albert, C. H. & Lavergne, S. Unravelling the architecture of functional variability in wild populations of Polygonum viviparum L. Funct. Ecol. 27, 382–391 (2013).

    PubMed  PubMed Central  Google Scholar 

  68. Dahlin, K. M., Asner, G. P. & Field, C. B. Environmental and community controls on plant canopy chemistry in a Mediterranean-type ecosystem. Proc. Natl Acad. Sci. USA 110, 6895–6900 (2013).

    ADS  CAS  PubMed  Google Scholar 

  69. Kattge, J. et al. TRY–a global database of plant traits. Glob. Change Biol. 17, 2905–2935 (2011).

    ADS  Google Scholar 

  70. Lebigot, E. O. Uncertainties: a Python package for calculations with uncertainties. (2010).

  71. Wiedenhofer, D., Fishman, T., Lauk, C., Haas, W. & Krausmann, F. Integrating material stock dynamics into economy-wide material flow accounting: concepts, modelling, and global application for 1900–2050. Ecol. Econ. 156, 121–133 (2019).

    Google Scholar 

Download references


We thank U. Alon, S. Dan, G. Eshel, T. Fishman, E. Gelbrieth, T. Kaufmann, T. Klein, A. Knoll, E. Noor, N. Page, R. Phillips, J. Pongratz, M. Shamir, M. Shtein, B. Smith, C. Waters, T. Wiesel, M. Williams and members of our laboratory for help and discussions, and S. Sitch and the TRENDY DGVM community for access to their simulation outputs. This research was supported by the European Research Council (Project NOVCARBFIX 646827); Beck-Canadian Center for Alternative Energy Research; Dana and Yossie Hollander; Ullmann Family Foundation; Helmsley Charitable Foundation; Larson Charitable Foundation; Wolfson Family Charitable Trust; Charles Rothschild; and Selmo Nussenbaum. R.M. is the Charles and Louise Gartner professional chair. Y.M.B.-O is an Azrieli Fellow.

Author information

Authors and Affiliations



E.E., L.B.-U. and R.M. wrote the manuscript. E.E. performed the bulk of the research and data analysis. L.B.-U. contributed to the anthropogenic mass analysis and biomass estimation. Y.M.B.-O. contributed to the biomass estimation and carbon content calculation. J.G. contributed to the water content calculation. E.E., J.G. and Y.M.B.-O. performed the uncertainty analysis. E.E., L.B.-U. and R.M. conceived the study. R.M. supervised the study. All authors discussed the results, and commented on the manuscript.

Corresponding author

Correspondence to Ron Milo.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature thanks Fridolin Krausmann, Dominik Wiedenhofer and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Sensitivity analysis of the anthropogenic mass definition.

af, The effect of adding the following to the anthropogenic mass (dark purple): a, mass of the human population, b, mass of livestock, c, mass of crops and agroforestry, d, mass of earthworks, dredging and waste/overburden from mineral and metal production, and f, mass of anthropogenic atmospheric CO2 stocks, as well as e, the exclusion of the mass of industrial roundwood. The total biomass weight is depicted by the green line. Black dot indicates the year of intersection based on the alternative anthropogenic mass definition. Violet area and light green-dashed line indicate extrapolated anthropogenic mass and biomass estimates, respectively. Full description of the sensitivity analysis is provided in Supplementary Information section 1.

Extended Data Fig. 2 Anthropogenic mass composition since the year 1900, divided into material groups.

Dataset is based on ref. 22.

Extended Data Fig. 3 Anthropogenic mass relative annual change, with highlights of notable global events.

Relative annual change is calculated as the difference between two consecutive years divided by the earlier year anthropogenic mass value.

Extended Data Fig. 4 Anthropogenic mass metal estimates since the beginning of the twentieth century, divided into material sub-groups.

Data are taken from the comprehensive work of the Institute of Social Ecology, Vienna. We used a recent study71, which has some minor updates compared to the study used to achieve the main results22.

Extended Data Fig. 5 Anthropogenic mass estimates for (industrial round) wood, glass and plastic since the beginning of the twentieth century, divided into material sub-groups.

Data are taken from the comprehensive work of the Institute of Social Ecology, Vienna. We used a recent study71, which has some minor updates compared to the study used to achieve the main results22.

Extended Data Fig. 6 Calculation steps in plant biomass estimation for 1990–2017.

As further detailed in the Methods section ‘Biomass change over the years 1900–2017’.

Extended Data Table 1 The different anthropogenic mass groups and their mass estimates in selected years

Supplementary information

Supplementary Information

Supplementary Discussions: This file contains Supplementary Section 1 & 2. It includes the sensitivity analysis of the anthropogenic mass definition, as well as an additional discussion on the biomass trend in recent years.

Reporting Summary

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Elhacham, E., Ben-Uri, L., Grozovski, J. et al. Global human-made mass exceeds all living biomass. Nature 588, 442–444 (2020).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.


Quick links

Nature Briefing Anthropocene

Sign up for the Nature Briefing: Anthropocene newsletter — what matters in anthropocene research, free to your inbox weekly.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing: Anthropocene