Planetary Health Check

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The Great Acceleration

Twenty-four indicators of the human enterprise and the Earth system, 1750 to 2025 — 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 change 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, framed so its rise fills the panel, over a shared 1750–2025 window. 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 change reached by that year. The badge gives the overall change (×N, or a +Δ for losses and anomalies), measured over the years that indicator covers.
  • Stripes — the same data as a band of one stripe per year, in the warming-stripes tradition, with the colour carrying the chosen metric.
  • Where a panel is blank — no indicator here is drawn outside its own record. Most begin well after 1750: paper production is measured from 1961, foreign direct investment from 1948, stratospheric ozone from 1956. Those years carry a plain tint rather than a colour, the years are printed under the badge, and hovering them reports no data instead of a number.

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 steeply it is climbing in each year, as the local trend in units per year. Declines are shown as declines: the curve crosses below zero, and in Stripes the colour turns violet. Marine fish capture and stratospheric ozone both fall back after their peaks.
  • Cumulative — how much of the indicator's total change had already happened by each year, from 0 to 100 %. An indicator that overshoots and then recovers passes above 100 % and comes back down, which is why stratospheric ozone peaks around 120 % in 2006.
  • Indexed (Charts only) — each indicator divided by its earliest measured level on a logarithmic scale, so growth of any size is comparable across panels; a straight line means steady proportional growth. Indicators that start at or below zero, and the few whose first measured year is so small that the ratio says more about early reporting than about growth, keep their value curve here.

Source

Indicator set and framing after the Great Acceleration synthesis; series compiled by GLOBAÏA from the underlying datasets and carried to 2025 wherever the record reaches that far.

  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, drawn across the years it actually covers within the 1750–2025 window. 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 mid-year population, spliced by Our World in Data: 1750–1799 from the History Database of the Global Environment (HYDE) v3.3, 1800–1949 from Gapminder, and 1950–2023 from the United Nations World Population Prospects 2024. The last two years, 2024 and 2025, are the UN's medium-variant projection rather than an estimate. Our World in Data (2026). Population. ourworldindata.org/grapher/population. United Nations, Department of Economic and Social Affairs (2024). World Population Prospects 2024. population.un.org/wpp. Klein Goldewijk (2024). History Database of the Global Environment 3.3. Utrecht University. doi:10.24416/UU01-AEZZIT. Gapminder (2022). Population, v7. gapminder.org/data.
  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; 1990–2024 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; 2000–2023 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). The source runs to 2100 on SSP2-4.5; the panel stops at 2020, the last decadal year the observational record supports. 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). Four points, 1750 to 2000. The source's next value is a 2035 scenario, so the panel ends at 2000 rather than interpolating toward it. 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); 1961–2023 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). Six points at 50-year steps, 1750 to 2000. The source's next value is a 2050 baseline scenario, so the panel ends at 2000 rather than interpolating toward it. 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.