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Even passing 1.5C of global warming temporarily would trigger a “significant” risk of Amazon forest “dieback”, says a new study.

Dieback would see large numbers of trees die, shifting the lush rainforest into a dry savannah.

The research, published in Nature Climate Change, assesses the impact of “overshooting” the aspirational goal of the Paris Agreement on the Amazon and Siberian forests.

Overshoot would see warming surpass 1.5C above pre-industrial levels in the coming decades, before being brought back down before 2100 through large-scale carbon dioxide removal.

Using hundreds of climate-model simulations, the authors assess the influence of the “sensitivity” of the climate – a measure of the planet’s temperature response to a given increase in atmospheric CO2.

Across all simulations where global warming in 2100 surpasses 1.5C, 37% show “some amount of dieback”, the study says.

However, the risk increases further in the long term, with “55% of simulations exhibiting dieback by 2300”.

One author tells Carbon Brief that the study highlights that overshooting 1.5C leaves forest ecosystems “exposed to more risk than [they] need to be”.

The findings show that “we can’t afford complacency”, he warns.

Warming pathways

As the planet warms, there is an increasing risk that parts of the Earth system will cross “tipping points” – critical thresholds that, if exceeded, could push a system into an entirely new state.

For example, a seminal 2022 study warned that five tipping elements – including the collapse of the West Antarctic ice sheet and abrupt permafrost thaw – are already within reach, while others are becoming increasingly more likely as temperatures rise.

One way to limit warming to 1.5C by the end of the century involves initially overshooting the threshold. However, research published last year warns that the longer the 1.5C threshold is breached – and the higher the peak temperature – the greater the risk of crossing tipping points.

The new study uses modelling to investigate the risks of overshoot for the Amazon and Siberian forests.

The paper considers three illustrative mitigation pathways taken from the Intergovernmental Panel on Climate Change’s (IPCC) mitigation report from its sixth assessment cycle, which was published in 2022.

Gregory Munday is an applied scientist at the UK Met Office Hadley Centre and lead author on the study. He tells Carbon brief that the authors selected “optimistic” pathways that “each have different relationships to the Paris Agreement goals”.

For each scenario, the authors assess a range of different climate sensitivities – a measure of the planet’s temperature response to a given increase in atmospheric CO2. The average outcome of each pathway is:

  • The “renewables” scenario shows a future with reduced emissions and a heavy reliance on renewable energy, which keeps warming below 1.5C by 2100.
  • The “negative emissions” pathway shows a world in which warming initially overshoots the 1.5C threshold, but extensive use of carbon removal sees warming drop back below 1.5C before 2100.
  • The “gradual strengthening” pathway illustrates a strengthening of climate policies implemented in 2020, with rapid reductions mid-century and a reliance on net-negative emissions by the end of this century. This pathway sees global average temperatures reach 1.8C by 2100. 

The authors run the emissions pathways through a simple climate “emulatormodel, which calculates the global temperatures associated with each emission pathway.

The charts below show cumulative CO2 emissions (left), atmospheric CO2 concentration (middle) and changes in global average surface temperature compared to the pre-industrial level (right), for the renewables (green), negative emissions (purple) and gradual strengthening (yellow) pathways until the year 2300.

The panels show cumulative CO2 emissions (left), atmospheric CO2 concentration (middle) and changes in global average surface temperature compared to the pre-industrial level (right), for the C1:IMP-Ren renewables scenario (green), C2:IMP-Neg negative emissions (purple) and C3:IMP-GS gradual strengthening (yellow) pathways until the year 2300. Source: Munday et al. (2025)
The panels show cumulative CO2 emissions (left), atmospheric CO2 concentration (middle) and changes in global average surface temperature compared to the pre-industrial level (right), for the C1:IMP-Ren renewables scenario (green), C2:IMP-Neg negative emissions (purple) and C3:IMP-GS gradual strengthening (yellow) pathways until the year 2300. Source: Munday et al. (2025)

The authors then use a different modelling framework to project the impacts of each emissions scenario.

Study author Dr Chris Jones leads the UK Met Office Hadley Centre’s research into vegetation and carbon cycle modelling and their interactions with climate. He tells Carbon Brief that the new study is the first application of this modelling framework, which he describes as a “rapid response tool”.

He says the tool was developed to “rapidly look at a range of climate outcomes, both global and local, for new scenarios”, adding that it provides a “pretty good approximation” of what traditional global climate models would do.

Munday adds that the framework is able to produce results within days or weeks, rather than taking “months and months”.

Finally, the authors use land surface model JULES to assess forest health under the different scenarios. Overall, the authors produce 918 simulations each of Amazon and Siberian forest health.

Forest health

The authors assess forest health using two metrics. The first is the forest growth metric “net primary productivity”, a measure of the rate that energy is stored as biomass by plants, which can indicate forest productivity. The second metric, forest cover, is a way of measuring the forest’s long-term response.

The models show that rising CO2 levels causes net primary productivity to increase, due to the CO2 fertilisation effect, driving more rapid forest growth. Conversely, many of the impacts of climate change, such as increased heat and changes to rainfall patterns, can be detrimental to forests, damaging or killing trees.

To identify the impacts of overshooting 1.5C on the Amazon and Siberian forests, the authors compare the “renewables” and “negative emissions” pathways. Both of these scenarios reach a similar global average temperature by the year 2100, but the former does so without overshoot, while the latter overshoots 1.5C before temperatures come back down.

The maps below show the difference in net primary productivity in the Amazon (left) and Siberian forests (right) between the two scenarios in the year 2100. Brown shading indicates that net primary productivity was higher in the non-overshoot scenario, while blue indicates that it was higher in the overshoot scenario.

The difference in net primary productivity in the Amazon (left) and Siberian forests (right) between the two scenarios. Brown indicates that net primary productivity was higher in the renewables (non-overshoot) scenario, while blue indicates that it was higher in the negative emissions (overshoot) scenario. Source: Munday et al. (2025)
The difference in net primary productivity in the Amazon (left) and Siberian forests (right) between the two scenarios. Brown indicates that net primary productivity was higher in the renewables (non-overshoot) scenario, while blue indicates that it was higher in the negative emissions (overshoot) scenario. Source: Munday et al. (2025)

The maps show that “large areas of both Amazonian and Siberian forest show reduced net primary productivity” by 2100 due to overshoot, compared to a scenario with no overshoot, the paper says.

‘High-risk zones’

From the three pathways, the authors generate 918 simulations of future climate and corresponding Amazon forest health.

The authors use these results to identify which future temperature and rainfall conditions result in net forest “dieback”. This is when large numbers of trees die, shifting the rainforest into a dry savannah.

The plots below show which simulations result in Amazon dieback by the year 2100 (left) and 2300 (right), for different amounts of rainfall and temperature levels in the year 2100. Each graph is divided into four sections – hot and wet (top right), hot and dry (bottom right), cold and wet (top right) and cold and dry (bottom right). These sections are based on average regional temperature and rainfall in the year 2100.

Coloured dots indicate scenarios that see forest dieback. These are coloured by pathway, for renewables (green), negative emissions (purple) and gradual strengthening (yellow). Grey dots indicate scenarios without Amazon dieback. The red lines indicate “high-risk climatic zones”, above which there is “a significant risk of dieback”.

Amazon dieback in the year 2100 (left) and 2300 (right), for different amounts of rainfall and temperature levels in the year 2100. Coloured dots indicate scenarios that see forest dieback. These are coloured by pathway, for renewables (green), negative emissions (purple) and gradual strengthening (yellow). Grey dots indicate scenarios without Amazon dieback. Source: Munday et al. (2025)
Amazon dieback in the year 2100 (left) and 2300 (right), for different amounts of rainfall and temperature levels in the year 2100. Coloured dots indicate scenarios that see forest dieback. These are coloured by pathway, for renewables (green), negative emissions (purple) and gradual strengthening (yellow). Grey dots indicate scenarios without Amazon dieback. Source: Munday et al. (2025)

The study finds that most Amazon dieback scenarios happen in hot, dry conditions, the authors note.

Across all simulations where warming in 2100 is above 1.5C, 37% show “some amount of dieback” the study says. However, in these model runs, the risk increases further in the long term, the study notes, with “55% of simulations exhibiting dieback by 2300”.

Prof Nico Wunderling is a professor of computational Earth system science at the Potsdam Institute for Climate Impact Research and was not involved in the new research. He tells Carbon Brief it is significant that, according to this study, the Amazon will face impacts from climate change below the tipping point threshold of 2-6C, as assessed in the landmark 2022 tipping points paper.

The authors also carry out this analysis for Siberian forests. Instead of a drop in tree cover, they find a change in the composition of trees. Munday tells Carbon Brief that the vegetation shifts “from grassy surface types to lots more trees and shrubs” in a process called “woody encroachment”.

Woody encroachment can have significant negative impacts on terrestrial carbon sequestration, the hydrological cycle and local biodiversity.

“The Siberian forest is probably committed to a long-term, and possibly substantial, expansion of tree cover,” the authors write.

High-risk scenarios

The greatest uncertainty in this study comes from the spread of climate sensitivities, Munday tells Carbon Brief.

He elaborates:

“This means that although we simulate the impacts from extremely optimistic mitigation scenarios, there is a chance that the Earth’s climate sensitivity is much higher than we expect, and so, small but significant risks of short- and long-term forest ecosystem impacts exist in spite of the choice of these strong-mitigation scenarios.”

In other words, if climate sensitivity is higher than expected, forests could face harmful impacts even under low emissions scenarios.

Dr David McKay – a lecturer in geography, climate change and society at the University of Sussex – is the lead author of the 2022 study. He tells Carbon Brief that the new paper “shows the value in focusing not just on model averages, but also exploring a wide range of possible futures to capture potential ‘low probability, high impact’ outcomes”. He adds:

“[The study shows] how negative emissions to reduce warming might help restabilise these forests in future if we do overshoot 1.5C, but as such large-scale CO2 removal remains hypothetical, we shouldn’t assume we can rely on this in practice.”

However, McKay also notes some uncertainties in the models used. Mckay tells Carbon Brief that the vegetation model used in this study doesn’t include fire and “has some limitations around soil moisture stress and vegetation in the tundra”. These are “likely important for resolving potential tipping points in these biomes”.

Therefore, he adds, the study “doesn’t show how regional tipping points could potentially further amplify and lock-in these future forest shifts, even with negative emissions”.

Dr David Lapola is researcher at the University of Campinas in Brazil and was not involved in the study. He also warns that vegetation models provide a “poor representation of how CO2 may affect these forests directly”. Lapola argues that scientists must “collect field data to make any new advancement with models”.

Nevertheless, Lapola tells Carbon Brief that studies such as this will be “extremely useful” for the IPCC’s upcoming seventh assessment cycle, which will include a dedicated chapter on tipping points and other “low-likelihood high impact events” for the first time.

Study author Jones tells Carbon Brief that overshooting 1.5C leaves forest ecosystems “exposed to more risk than [they] need to be”. The findings show that “we can’t afford complacency”, he warns.

The post ‘Significant’ risk of Amazon forest dieback if global warming overshoots 1.5C appeared first on Carbon Brief.

‘Significant’ risk of Amazon forest dieback if global warming overshoots 1.5C

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Climate Change

Q&A: Does the world need ‘carbon capture and storage’ to reach net-zero?

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When carbon dioxide (CO2) is released from a factory or power plant, the gas can be captured and permanently stored underground, preventing it from driving climate change.

This is the idea underpinning carbon capture and storage (CCS), a technology that is at the heart of many nations’ net-zero plans.

Influential organisations, including the Intergovernmental Panel on Climate Change (IPCC), describe CCS as “critical” for cutting emissions from key sectors – and for helping to avoid dangerous global warming.

In particular, capturing CO2 is seen as one of the only viable options for decarbonising some of the world’s highest-emitting industries, such as cement production.

The UK, for example, has committed to investing as much as £21.7bn over the coming decades in its nascent CCS industry, as part of the nation’s net-zero strategy.

Yet, in the UK and elsewhere, there has been a backlash against plans for CCS.

Citing high costs, ties to the fossil-fuel industry and a “history of poor performance”, critics describe CCS as a “dangerous distraction” or a “false climate solution”.

Time and again, the outlook for the roll-out of CCS has been scaled back, as the technology has failed to deliver as quickly as expected – and as policy support has wavered.

Furthermore, critics state that the technology remains “unproven” on the scale required to make a meaningful impact on global emissions.

In this Q&A, Carbon Brief explores the role CCS is expected to play in achieving net-zero, its record to date and the reasons it has been criticised, using the UK as an example.

Article Contents

What is CCS?

CCS involves capturing CO2 emissions released from a large source, such as a gas power plant or a cement factory.

The CO2 is separated from the facility’s exhaust stream, generally using a chemical solvent, before being compressed into a liquid and transported via pipeline or vehicle. The CO2 is then stored by injecting it into underground reservoirs, such as depleted oil fields or saline aquifers.

The term “CCUS” is sometimes also used, referring to the “utilisation” of CO2 to make products, including fertilisers, fuels or building materials. Such uses do not necessarily lead to permanent emissions cuts, as the CO2 can end up later being released back into the atmosphere.

(“CCS” is used in this Q&A, unless quoting another organisation that specifically refers to “CCUS”.)

The infographic below shows the stages of capturing CO2 and transporting it to be either stored or used in other applications.

Infographic showing the stages of capturing, transporting and then storing or using CO2.
Infographic adapted by Carbon Brief from the IEA.

Carbon capture technology was originally rolled out at US and Canadian oil wells in the early 1970s as a way to achieve “enhanced oil recovery”. This involves injecting captured CO2 into depleted wells – a process that stores CO2, but also helps to extract more oil.

This remains, by far, the most significant end use for captured CO2 worldwide, with around three-quarters of it used for this purpose.

Moreover, most of the CO2 currently captured is a by-product of gas purification – the process by which fossil fuels such as methane are separated from other, unwanted substances. Selling this CO2 can make such gas projects more economically viable.

Therefore, as shown in the chart below, which is based on International Energy Agency (IEA) data, the majority of CO2 that is both captured and used today helps the fossil-fuel industry to extract and sell more oil and gas.

CO2 captured, million tonnes per year, by sector and end use as of February 2026. Most CO2 is currently captured by the fossil-fuel industry – and then used to extract more fossil fuels. Fossil fuel processing produces ~49 of 62 Mt total, while enhanced oil recovery uses ~45 Mt. Source: IEA CCUS Projects database.

CCS was first proposed as a way to deal with CO2 emissions in a 1976 academic article, which imagined injecting the captured gas into the ocean.

It is only since the early 2000s that CCS has gained traction as a proposed climate solution, with a 2005 “special report” by the IPCC exploring the topic. At that time, the authors note there were just three small-scale projects trying to capture and permanently store CO2.

Installing CCS at factories or power plants and permanently storing the CO2 would mean that, in theory, such facilities could continue using fossil fuels without contributing to climate change.

Such applications are often mentioned alongside two related technologies, both of which could be used to “suck” CO2 out of the atmosphere and, thus, deliver “negative emissions”.

One is bioenergy with carbon capture and storage (BECCS). Crops absorb CO2 as they grow and BECCS involves a power plant burning these crops, then storing the resulting CO2.

The other technology is direct air carbon capture and storage (DACCS).

These technologies are classed as “CO2 removal”, as they involve absorbing CO2 from the atmosphere using plants or machines and then storing it permanently.

By contrast, CCS installed at a factory is considered a way to avoid CO2 emitted by that specific facility from entering the atmosphere. This Q&A focuses on such applications, which account for the vast majority of existing and planned CCS.

Extract from study by Marchetti, C. (1977), saying: The problem of CO2 control in the atmosphere is tackled by proposing a kind of ‘fuel cycle’ for fossil fuels where CO2 is partially or totally collected at certain transformation points and properly disposed of. CO2 is disposed of by injection into suitable sinking thermohaline currents that carry and spread it into the deep ocean that has a very large equilibrium capacity. The Mediterranean undercurrent entering the Atlantic at Gibraltar has been identified as one such current; it would have sufficient capacity to deal with all CO2 produced in Europe even in the year 2100.
First mention in the academic literature of capturing and storing CO2 for climate change mitigation. Source: Marchetti, C. (1977).

How much CCS capacity has been built so far?

As of February 2026, there were a total of 75 operational CCS projects around the world. As noted above, almost all of them are at fossil-fuel extraction and processing sites, according to the IEA’s database.

Together, these projects capture 62.5m tonnes of CO2 (MtCO2) each year. This is equivalent to the annual greenhouse gas emissions of Ecuador.

(This compares with the