Planetary Health Check

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The Great Acceleration

Twenty-four indicators of the human enterprise and the Earth system, 1750 to 2024 — the synchronised surge that earth-system scientists call the Great Acceleration. Warm panels track socio-economic trends; cool panels track the planet's response. Across both views the colour reads the same way: how much of each indicator's total rise has accrued by a given year. Hover any panel to read its value; the faint line marks 1950.

Show

About this figure

The Great Acceleration is the steepest, most synchronised burst of change in the human story. Each of the 24 panels is one indicator, drawn from 1750 to 2024 and framed so its rise fills the panel. Two ways to read them:

  • Charts — each panel is a curve over time, its area washed by a horizontal gradient encoding cumulative progress: the share of the indicator's total rise reached by that year. Early centuries stay dark; recent decades glow. The badge gives the overall change (×N, or a +Δ for losses and anomalies).
  • Stripes — the same data as a band of one stripe per year, in the warming-stripes tradition, with the colour carrying the chosen metric.

The Show control sets what each panel measures — in Charts it changes the plotted curve, in Stripes the stripe colour:

  • Value — the indicator itself, in its own units (people, ppm, tonnes…).
  • Rate — how fast it is rising each year. The year-on-year increase peaks sharply after 1950 for almost every panel; this is the acceleration made literal.
  • Cumulative — the running share of all the change since 1750, from 0 to 100 %. The steep climb after mid-century shows how much has happened within a single lifetime.
  • Indexed (Charts only) — each indicator divided by its 1750 level on a logarithmic scale, so growth of any size is comparable across panels; a straight line means steady proportional growth. Indicators measured as anomalies or losses (which start at or below zero) keep their value curve here.

Source

Indicator set and framing after the Great Acceleration synthesis; series compiled and updated to 2024 by GLOBAÏA from the underlying datasets.

  1. The Great Acceleration — Steffen, W., Broadgate, W., Deutsch, L., Gaffney, O., & Ludwig, C. (2015). The trajectory of the Anthropocene: the Great Acceleration. The Anthropocene Review 2(1), 81–98.
  2. Anthropocene context — McNeill, J. R., & Engelke, P. (2016). The Great Acceleration: An Environmental History of the Anthropocene since 1945. Harvard University Press.

Indicator data & sources

Each of the 24 panels is a measured or modelled series running from 1750 to 2024. The data behind every indicator, in the figure's two groups — the human enterprise first, then the Earth-system response.

Socio-economic trends

  1. World population Billion Global population from the History Database of the Global Environment (HYDE) v3.3. Klein Goldewijk (2024). History Database of the Global Environment 3.3. Utrecht University. doi:10.24416/UU01-AEZZIT. Klein Goldewijk et al. (2017). Anthropogenic land use estimates for the Holocene — HYDE 3.2. Earth Syst. Sci. Data 9, 927–953.
  2. Real GDP Trillion 2011 US$ Global real Gross Domestic Product in year-2011 US dollars, from the Maddison Project Database 2023. Bolt & van Zanden (2024). Maddison Project Database 2023. DataverseNL, V1. doi:10.34894/INZBF2. Bolt & van Zanden (2025). Maddison-style estimates of the evolution of the world economy: a new 2023 update. J. Econ. Surv. 39, 631–671.
  3. Foreign direct investment Trillion US$/yr Global foreign direct investment, inflation-adjusted. Pre-1990 after Steffen et al. (2015) from IMF (1948–69) and UNCTAD (1970–89) data; 1990–2023 from UNCTAD. Steffen et al. (2015). The trajectory of the Anthropocene: the Great Acceleration. Anthr. Rev. 2, 81–98. IMF (n.d.). International Monetary Fund eLibrary Data. imf.org. UNCTAD (n.d.). UN Trade and Development Data Hub. unctadstat.unctad.org.
  4. Urban population Billion Global urban population from the HYDE database v3.3. Klein Goldewijk (2024). History Database of the Global Environment 3.3. Utrecht University. doi:10.24416/UU01-AEZZIT. Klein Goldewijk et al. (2017). Anthropogenic land use estimates for the Holocene — HYDE 3.2. Earth Syst. Sci. Data 9, 927–953.
  5. Primary energy use Exajoule/yr World primary energy use, from Our World in Data based on the Energy Institute and Smil (2017). Our World in Data (2024). Global direct primary energy consumption. ourworldindata.org/grapher/global-primary-energy. Energy Institute (2024). Statistical Review of World Energy. Smil (2017). Energy Transitions: Global and National Perspectives (Appendix A). Praeger.
  6. Fertilizer consumption Million tonnes/yr Global nitrogen, phosphate and potassium consumption from IFA data; pre-1961 as reported in Steffen et al. (2015). Steffen et al. (2015). The trajectory of the Anthropocene: the Great Acceleration. Anthr. Rev. 2, 81–98. IFA (2019). IFASTAT Consumption Database. ifastat.org.
  7. Large dams Thousand dams Total number of large dams built since 1900 (≥15 m high, or 5–15 m impounding >3 million m³), from ICOLD via Perera et al. (2021). Perera et al. (2021). Ageing Water Storage Infrastructure: An Emerging Global Risk. United Nations University. ICOLD (2020). World Register of Dams: General Synthesis. icold-cigb.org.
  8. Water use Thousand km³/yr Global water use. 1900–1999 after Steffen et al. (2015) using the WaterGAP model; 2000–2022 from FAO AQUASTAT. Steffen et al. (2015). The trajectory of the Anthropocene: the Great Acceleration. Anthr. Rev. 2, 81–98. Flörke et al. (2013). Domestic and industrial water uses of the past 60 years. Glob. Environ. Change 23, 144–156. aus der Beek et al. (2010). Modelling historical and current irrigation water demand: Europe. Adv. Geosci. 27, 79–85. Alcamo et al. (2003). Development and testing of the WaterGAP 2 global model. Hydrol. Sci. J. 48, 317–337. FAO (n.d.). AQUASTAT. data.apps.fao.org/aquastat.
  9. Paper production Million tonnes/yr Global paper and paperboard production from the FAO. FAO (n.d.). FAOSTAT: Forestry Production and Trade. fao.org/faostat.
  10. Global infrastructure agreements Thousand agreements Number of global infrastructure agreements from Haner (2023), based on the Consolidated, League of Nations and UN treaty series. Haner (2023). Organizing peace: an algorithmic analysis of four centuries of international law and the decline of war (doctoral dissertation, Northeastern University). ProQuest.
  11. Telecommunications Billion subscriptions Global sum of fixed landlines and mobile-phone subscriptions. Landlines after Canning (1998) for 1950–89 and UNSD for 1990–2022; mobile from UNSD, 1990–2022. Canning (1998). A database of world stocks of infrastructure, 1950–1995. World Bank Econ. Rev. 12(3), 529–548. UNSD (2014). UNdata: landline and mobile telephones. data.un.org.
  12. Transistors per microprocessor Billion Transistors per microprocessor from Rupp (2022), processed by Our World in Data, with a value of 1 added in 1947 for the first transistor. Rupp (2022). Microprocessor Trend Data. github.com/karlrupp/microprocessor-trend-data. Processed by Our World in Data.

Earth-system trends

  1. Carbon dioxide ppm Global atmospheric carbon dioxide concentration from the Indicators of Global Climate Change 2024. Smith et al. (2025). Indicators of Global Climate Change 2024. doi:10.5281/ZENODO.7883757.
  2. Nitrous oxide ppb Global atmospheric nitrous oxide concentration from the Indicators of Global Climate Change 2024. Smith et al. (2025). Indicators of Global Climate Change 2024. doi:10.5281/ZENODO.7883757.
  3. Methane ppb Global atmospheric methane concentration from the Indicators of Global Climate Change 2024. Smith et al. (2025). Indicators of Global Climate Change 2024. doi:10.5281/ZENODO.7883757.
  4. Stratospheric ozone % decline Maximum total-column ozone decline (2-year moving average) over Halley, Antarctica during October, against a 305 DU first-decade baseline. Shanklin, British Antarctic Survey (n.d.). Antarctic Ozone. legacy.bas.ac.uk/met/jds/ozone.
  5. Surface temperature °C vs 1961–1990 Global surface temperature anomaly (combined land and ocean) from the HadCRUT5 analysis, relative to 1961–1990. Morice et al. (2021). An updated assessment of near-surface temperature change from 1850: the HadCRUT5 data set. J. Geophys. Res. Atmos. 126, e2019JD032361. Version 5.0.2.0.
  6. Ocean acidification H⁺, nmol/kg Global mean surface-ocean hydrogen-ion concentration from a model–data fusion (14 CMIP6 models), observation-based to 2014 then SSP2-4.5. Jiang et al. (2023). Global surface ocean acidification indicators from 1750 to 2100. J. Adv. Model. Earth Syst. 15.
  7. Marine fish capture Million tonnes/yr Global marine fish capture from the FAO. FAO (n.d.). Fishery and aquaculture statistics: capture production quantity. fao.org/fishery.
  8. Shrimp aquaculture Million tonnes/yr Global aquaculture shrimp production from the FAO. FAO (n.d.). Fishery and aquaculture statistics: aquaculture production quantity. fao.org/fishery.
  9. Nitrogen to coastal zone Million tonnes N/yr Model-calculated human-induced nitrogen flux into the coastal margin (riverine flux, sewage and atmospheric deposition). Mackenzie et al. (2002). Century-scale nitrogen and phosphorus controls of the carbon cycle. Chem. Geol. 190, 13–32.
  10. Tropical forest loss % loss vs 1700 Loss of tropical forests relative to 1700. 1700 and 1750–1992 from Pongratz et al. (2008); 1993–2022 from the Copernicus Climate Change Service. Pongratz et al. (2008). A reconstruction of global agricultural areas and land cover for the last millennium. Glob. Biogeochem. Cycles 22(4), GB3018. Copernicus Climate Change Service (2019). Land cover classification gridded maps from 1992 to present. doi:10.24381/cds.006f2c9a.
  11. Domesticated land % of land area Agricultural land (cropland and pasture) as a share of total land area. 1750–1960 from Pongratz et al. (2008); 1961–2022 from the FAO. Pongratz et al. (2008). A reconstruction of global agricultural areas and land cover for the last millennium. Glob. Biogeochem. Cycles 22(4), GB3018. FAO (n.d.). FAOSTAT: Land Use. fao.org/faostat.
  12. Terrestrial biosphere degradation % MSA decrease Loss of terrestrial mean species abundance relative to undisturbed ecosystems, as an approximation for biosphere degradation. After Steffen et al. (2015), based on Alkemade et al. (2009) and ten Brink et al. (2010). Alkemade et al. (2009). GLOBIO3: a framework to investigate options for reducing global terrestrial biodiversity loss. Ecosystems 12, 374–390. ten Brink et al. (2010). Global MSA baseline scenarios. In Rethinking Global Biodiversity Strategies. PBL Netherlands Environmental Assessment Agency.