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Identifying the socio-economic drivers behind greenhouse gas emissions is crucial to design mitigation policies. Existing studies predominantly analyze short-term CO2 emissions from fossil fuels, neglecting long-term trends and other GHGs. We examine the drivers of all greenhouse gas emissions between 1820–2050 globally and regionally. The Industrial Revolution triggered sustained emission growth worldwide—initially through fossil fuel use in industrialized economies but also as a result of agricultural expansion and deforestation. Globally, technological innovation and energy mix changes prevented 31 (17–42) Gt CO2e emissions over two centuries. Yet these gains were dwarfed by 81 (64–97) Gt CO2e resulting from economic expansion, with regional drivers diverging sharply: population growth dominated in Latin America and Sub-Saharan Africa, while rising affluence was the main driver of emissions elsewhere. Meeting climate targets now requires the carbon intensity of GDP to decline 3 times faster than the global

We investigate the probabilities of triggering climate tipping points under five Shared Socioeconomic Pathways (SSPs) and how they are altered by including the additional carbon emissions that could arise from tipping points within the Earth's carbon cycle. The crossing of a climate tipping point at a threshold level of global mean surface temperature (threshold temperature) would commit the affected subsystem of the Earth to abrupt and largely irreversible changes with negative impacts on human well-being. However, it remains unclear which tipping points would be triggered under the different SSPs due to uncertainties in the climate sensitivity to anthropogenic greenhouse gas emissions, the threshold temperatures and timescales of climate tipping points, and the response of tipping points within the Earth's carbon cycle to global warming. We include those uncertainties in our analysis to derive probabilities of triggering for 16 previously identified climate tipping points within the Earth system.

The ocean ecosystem is a vital component of the global carbon cycle, storing enough carbon to keep atmospheric CO2 considerably lower than it would otherwise be. However, this conception is based on simple models, neglecting the coupled land-ocean feedback. Using an interactive Earth system model, we show that the role ocean biology plays in controlling atmospheric CO2 is more complex than previously thought. Atmospheric CO2 in a new equilibrium state after the biological pump is shut down increases by more than 50% (163 ppm), lower than expected as approximately half the carbon lost from the ocean is adsorbed by the land. The abiotic ocean is less capable of taking up anthropogenic carbon due to the warmer climate, an absent biological surface pCO2 deficit and a higher Revelle factor. Prioritizing research on and preserving marine ecosystem functioning would be crucial to mitigate climate change and the risks associated with it.

Evidence shows a continuing increase in the frequency and severity of global heatwaves1,2, raising concerns about the future impacts of climate change and the associated socioeconomic costs3,4. Here we develop a disaster footprint analytical framework by integrating climate, epidemiological and hybrid input–output and computable general equilibrium global trade models to estimate the midcentury socioeconomic impacts of heat stress. We consider health costs related to heat exposure, the value of heat-induced labour productivity loss and indirect losses due to economic disruptions cascading through supply chains. Here we show that the global annual incremental gross domestic product loss increases exponentially from 0.03 ± 0.01 (SSP 245)–0.05 ± 0.03 (SSP 585) percentage points during 2030–2040 to 0.05 ± 0.01–0.15 ± 0.04 percentage points during 2050–2060. By 2060, the expected global economic losses reach a total of 0.6–4.6% with losses attributed to health loss (37–45%), labour productivity loss (18–37%) and i

An extensive new multi-proxy database of paleo-temperature time series (Temperature 12k) enables a more robust analysis of global mean surface temperature (GMST) and associated uncertainties than was previously available. We applied five different statistical methods to reconstruct the GMST of the past 12,000 years (Holocene). Each method used different approaches to averaging the globally distributed time series and to characterizing various sources of uncertainty, including proxy temperature, chronology and methodological choices. The results were aggregated to generate a multi-method ensemble of plausible GMST and latitudinal-zone temperature reconstructions with a realistic range of uncertainties. The warmest 200-year-long interval took place around 6500 years ago when GMST was 0.7 °C (0.3, 1.8) warmer than the 19th Century (median, 5th, 95th percentiles). Following the Holocene global thermal maximum, GMST cooled at an average rate −0.08 °C per 1000 years (−0.24, −0.05). The multi-method ensembles and th

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