The second-largest reservoir in the US reached a record-low water height on Saturday – just days after the country’s largest reservoir broke its own record. 

Both Lake Mead and Lake Powell are located on the Colorado River.

They provide water for populations across seven US states in the south-western US, with around 40 million people getting some or all of their municipal water from the Colorado River.

The river also provides water for around 5.5m acres (22,258 square kilometres) of farmland across Colorado, Arizona, California and the other states in the river basin.

Experts tell Carbon Brief that climate change, population growth and over-consumption are all contributing to the current record-low levels of the reservoirs.

Record lows

At full capacity, Lakes Mead and Powell can hold a combined 68 cubic kilometres of water – enough to supply all household consumption in the contiguous US for nearly 1.5 years. However, the water level in both reservoirs has been declining for decades.

The chart below shows the water level of Lake Mead, in metres above mean sea level. The reservoir, which began to fill in 1935 following the construction of the Hoover Dam, has a “full pool” maximum capacity of 347.60 metres. The water level in Lake Mead reached a record low of 317.11 metres on 7 August.

The following chart shows the water level of Lake Powell, in metres above mean sea level. Lake Powell’s full-pool level is 1,127.76 metres.

While the reservoir reached its maximum capacity several times in the 1980s, it has not done so since. On 15 August, the water level in Lake Powell was recorded at a new record-low of 1,072.87 metres.

Both reservoirs have continued to decline in the days since breaking their respective records. The downward trend will largely continue in both lakes until next spring, when the snowpack in the mountains of the Upper Colorado River Basin begins to melt, says Dr Jack Schmidt, a senior research scientist at Utah State University’s Center for Colorado River Studies. He tells Carbon Brief:

“The big dilemma of the moment is that we’re only in the middle of August, and we have no assurance of what the coming winter will be. The only thing we can be sure of is that we will be depleting overall total basin reservoir storage from now until, roughly, early April.”

Compounding factors

The record lows across the two reservoirs are the result of several compounding factors, experts tell Carbon Brief.

Since the turn of the 20th century, the amount of water flowing along the Upper Colorado River has declined by about 20%. Research suggests that half of this decline can be attributed to human-induced climate change.

Most of the river’s streamflow comes from the snowpack of the Upper Colorado River Basin, which stretches across five western US states but is primarily located in Colorado and Utah.

This region has been gripped by a historic “megadrought” for more than a quarter of a century. Nearly half of the megadrought’s intensity over 2000-18 is attributable to climate change, according to a 2020 study.

At the same time, the increasing population in the US south-west has put added pressure on the Colorado River’s water supply. The number of people obtaining some or all of their water from the Colorado system has grown by 15 million (around 60%) since 1992.

Schmidt tells Carbon Brief:

“There’s an ultimate cause of the present water crisis, and there’s a proximate cause. The ultimate cause is a warming climate, a warming planet and a pretty clear correlation between warming conditions and decreased runoff in the Colorado River Basin.

“The proximate cause is that in this messy democratic republic of ours, big policy decisions that match the variability of the climate occur painfully slowly – with intense political negotiations – and only incrementally.”

On 31 July, the US Bureau of Reclamation, which manages water resources in the western US, released an environmental impact statement on its proposed post-2026 strategy for managing Lakes Powell and Mead. The strategy itself has not been released yet.

Schmidt notes that the statement does appear to give the Bureau flexibility to “respond to crisis” by reducing the delivery of water to several states. However, he adds:

“They acknowledge it won’t work if we just stay critically dry, and of course every climate model for the 21st century, especially with a continually warming planet, says that that’s exactly what’s going to happen.”

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The post Analysis: The two largest reservoirs in the US have hit record-low levels appeared first on Carbon Brief.

Analysis: The two largest reservoirs in the US have hit record-low levels

As tech giants race to build out AI and the sprawling infrastructure it depends on, climate concerns have tended to focus on one thing: power-hungry data centres.

Their electricity use is growing so fast that by 2030, it’s projected to be nearly three times more than the combined annual consumption of Pakistan, Bangladesh and Nigeria. With the explosion in the construction of data centres driving new investment in fossil fuels, especially in the US, greenhouse gas emissions generated by data centres – now standing at less than 1% of the global total – are set to soar.

But this narrow focus on electricity has let AI’s supporters and the International Energy Agency (IEA) make a convenient case: that rising emissions can be more than offset by the technology’s green applications, like optimising renewables or boosting efficiency. That story conceals how AI’s real climate danger lies elsewhere: in the oil fields, where it’s helping fossil fuel companies extract planet-heating oil and gas faster and more cheaply.

As a senior manager at Microsoft, Holly Alpine was shocked by this blind spot. In 2024, she and her husband Will – also a Microsoft manager – quit their jobs and launched a campaign to hold Big Tech accountable for the emissions its technology enables.

Over the past two years, they have teamed up with two researchers to quantify just how deep the fossil fuel industry’s embrace of AI tools runs.

Their peer-reviewed study, published last week, found that when AI is adopted at similar rates across the fossil fuel and renewable energy sectors, the net effect is a rise in emissions of 0.47–1.8 gigatonnes of CO2 annually. That’s equivalent to Mexico’s annual emissions at the low end, and to Russia’s – the world’s fourth-largest emitter – at the high end. It is also 3.3 to 13.3 times higher than the emissions currently generated by powering AI data centres.

We spoke with Alpine about the risks of overlooking this side of the AI climate story and what can be done to shift the focus.

Q: Why has the climate conversation focused so heavily on data-centre power use when your modelling suggests that’s the smaller part of the AI emissions story?

A: It’s been quite unfortunate that it has been framed that way and that it has stuck so much because that framing is wholly incomplete, very misleading and is leading to very dangerous consequences.

It’s in the fossil fuel industry and the technology companies’ favour to frame the equation in this way because it leaves out any responsibility and accountability of the tech’s use by fossil fuel companies, which is a large part of their business. They’re some of their largest customers and they have teams of engineers and sales folks who are dedicated to the fossil fuel industry.

Simply comparing the power needed to run the technology and its [clean energy] applications is also kind of apples to oranges. On the one hand, you have real-world actual emissions and, on the other, hypothetical future avoidance of emissions as a result of potential future use cases for renewables.

What we are saying is that we need to look at both sides of the ledger for AI applications, renewables versus fossil fuels, and then also add the emissions generated by running data centers on top of it.

Q: How do AI applications help fossil fuel companies in a way that drives up emissions?

A: It’s everything from finding more oil and gas underground by processing hundreds of terabytes of seismic and well data that would otherwise have to be done manually. These AI models can process this data extremely quickly and create high-resolution images of what is underground. It helps companies pinpoint the oil and gas reserves that are most likely to be commercially recoverable.

Fossil fuel companies can identify and develop fossil fuel deposits with a lot more certainty, allowing them to move forward with projects that would otherwise have been too risky or too slow to pursue. AI makes them viable.

We’ve seen that rig counts [number of active drilling rigs] have dropped dramatically, so they need fewer resources to get out even more fossil fuels. Their costs are decreasing, while their production is increasing.

Q: How deep do these relationships run between Big Tech and fossil fuel companies? How do they compare with equivalent relationships with renewable energy companies?

A: I have to caveat that I have not worked for Microsoft for about two years. But what we saw at the time was that the fossil fuel-dedicated teams were much larger in terms of the number of employees, the size of the contracts, and the long-standing relationships.

This is not new. Microsoft has worked with the fossil fuel industry for many years and has deep partnerships, starting with the humble machine-learning going back many years. AI is just the latest wave of technology being applied in this way.

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There are also relationships between the tech companies and renewables companies [and] battery storage developers. There are definitely sustainability-related applications of the technology.

One of the recommendations that we had given the company [Microsoft] was to shift the ratio of engineering resources from fossil to low and no-carbon energy sectors within the company. When they came out with their principles for engagement with the fossil fuel industry in 2023, they committed to shifting engineering resources. But then we did not see any actual change in business practices.

Q: Tech companies are now quietly scaling back some of their climate commitments, but there was a point, not long ago, when they wanted to be seen as climate leaders. Was there ever a genuine commitment to do that, or was it just an image they were projecting?

A: It depends on how you evaluate a company for its climate impact. If all we are looking is its own operational emissions, then in that case, Microsoft was and, still is to some extent, a climate leader.

But if we evaluate a company based on what it is producing, then I would say it’s a very different story. Back in 2019, ExxonMobil said it was able to produce an extra 50,000 barrels [of oil] per day purely thanks to Microsoft technology. There was also another public and quantified deal with Chevron.

We calculated that those emissions alone from just two deals among dozens were 300% of Microsoft’s entire operational emissions, including data centres. So, how do you want to evaluate your company?

If you look at other sectors and, say, evaluate a weapons manufacturer on its violence footprint, you don’t just look at their supply chain and the violence within it to create the weapons. You look at the real-world impact of the weapons they’re manufacturing. Yet we completely left technology companies off the hook.

Q: You make some recommendations as well in the paper. They include the idea of putting some supply-side constraints on this AI-enabled productivity for fossil fuel companies. What would that look like in practice?

A: Ultimately, our goal would be to have disclosure and governance measures that limit AI’s role in increasing fossil fuel productivity. The first thing would be a recognition of “enabled emissions” even as a measurable category because, at the moment, they are not included in any emissions disclosure or accountability frameworks.

Then we should require transparency around these fossil fuel contracts and constrain some of these specific mechanisms that the research identifies.

We are not trying to have a blanket ban on AI or even a blanket ban on AI use in the fossil fuel industry. There are some great applications, like methane leak detection, for example. But we just want to align applications with climate science and ensure that any contracts that move forward have been evaluated against a 1.5C future.

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The easy thing would be for companies to voluntarily put guardrails on how their tech can be used, which is not new. There just currently are none for climate. But we do think that… policy is what needs to be implemented.

We also think that if we can change the market structure and incentives, then this kind of restriction will follow. If we look at ESG investing and how sustainable investing is defined, if we include what these companies are doing into that evaluation, then that can move capital flows.

Q: What do you think are the most promising avenues where you can shift the AI narrative and drive the change you are seeking to achieve?

A: We are now building off the study and there are various governance frameworks that we are attempting to incorporate this sort of evaluation into like the Greenhouse Gas Protocol or the Science Based Targets initiative (SBTi)

Luckily, we have seen some very promising drafts for the future of those frameworks that do include evaluations and disclosures of this work, which is really exciting.

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We also need to look at companies for impacts in order to evaluate their sustainability metrics, and there could be potential greenwashing concerns that we could address on the legal side of things.

And then [there are] different policy workstreams. In the EU, we were quite hopeful about the AI Act,and the various use cases that were classified as high risk and would go through additional scrutiny. Unfortunately, with the Omnibus passing [in July], that opportunity is a little restrained.

But now with the Cloud and AI Development Act (CADA) coming out with various European frameworks around evaluating tech’s impacts, we hope to inform those discussions with this research.

The post “Dangerous consequences” – how AI’s climate framing lets Big Tech off the hook appeared first on Climate Home News.

“Dangerous consequences” – how AI’s climate framing lets Big Tech off the hook

Emissions from land-use change – including deforestation, loss of peatland and forest degradation – have been falling over the course of the 21st century.

The latest Global Carbon Budget report, formally published in May in the journal Earth System Science Data, notes a “statistically significant decrease” in land-use change emissions since the late 1990s.

The 21st-century decline in land-use emissions has accelerated in recent years, with the report highlighting a “steep drop” after 2015.

Writing for Carbon Brief in November 2025, climate scientists Dr Zeke Hausfather and Prof Pierre Friedlingstein noted that land-use emissions in 2025 had decreased by “around 32% compared to their average in the 2000s”.

Via six charts, Carbon Brief explores how – and why – land-use emissions have fallen over the past quarter of a century as fossil-fuel emissions have continued to climb.

How have land-use emissions changed?

Deforestation, forest degradation, loss of peatlands and harvesting trees for wood all release carbon into the atmosphere.

Collectively, these emissions are known as land-use, land-use change and forestry (LULUCF) emissions, referred to here as land-use emissions.

Each year, global land-use emission trends are analysed in the Global Carbon Budget report. The report, produced by dozens of scientists, documents how human-caused greenhouse gas emissions are changing over time.

Key findings from the annual report are released each year in the autumn, before being published formally in an academic journal the following year following a peer-review process.

(For more on the findings of the 2025 report, read Carbon Brief’s summary.)

The latest edition of the Global Carbon Budget report notes that, in the four decades to 1999, net CO2 emissions from land-use change remained “relatively constant”, sitting at around 6.6bn tonnes of carbon dioxide (GtCO2) per year.

However, since the late 1990s, global land-use emissions have been falling.

The 2025 report estimates that land-use emissions over 2015-24 averaged at 5GtCO2 a year. This is around 23% lower than the average over 1995-2004 and 19% lower than 2005-14, it says.

In contrast, global emissions from fossil fuels and cement have increased every decade since 1959, rising from an average of 11GtCO2 in the 1960s to 35.9GtCO2 over 2015-24, it says.

“Preliminary data” included in the report suggests that land-use emissions in 2025 clocked in lower than their 2014-25 average, at 4.1GtCO2, as fossil-fuel and cement emissions reached a new high of 38.1GtCO2.

(For more on how land-use emissions are calculated, see: Why are estimates of land-use emissions uncertain?)

The chart below shows how land-use emissions have been falling in the 21st century and have helped to temper the overall rise of human-caused emissions.

Why have land-use emissions fallen?

The Global Carbon Budget attributes falling land-use emissions since the late 1990s to decreasing emissions from deforestation, in particular “permanent deforestation”.

Permanent deforestation refers to the complete removal of trees for the conversion of forest to another land use, such as agriculture, mining or the construction of towns and cities. This sets it apart from other forms of deforestation, such as logging and rotational farming, where the canopy is removed on a more temporary basis.

The Global Carbon Budget also points to “increasing [CO2] removals” from forest regrowth as a reason for falling land-use emissions since the turn of the century.

(For more on the countries and policies that have driven these changes, see: Which countries are behind falling land-use emissions? and: Which countries are leading on forest regrowth?)

Looking at more recent trends, the report attributes a “steep drop” in land-use emissions in the decade since 2015 to the “combined effect” of a “peak” in peat fire emissions in 2015, as well as a “long-term decline” in deforestation emissions in many countries over 2010-20.

The chart below shows how deforestation and forest growth have been responsible for the bulk of change to land-use emissions over the 21st century.

Over 2015-24, the sequestration of CO2 through reforestation and afforestation efforts offset two-thirds of deforestation emissions, according to the Global Carbon Budget report.

Specifically, it notes that deforestation was responsible for an average of 6.96GtCO2 of emissions each year over 2015-24. Forest growth, on the other hand, removed 4.76GtCO2 a year.

Just under half – 2.2GtCO2 – of carbon removals over 2015-24 was from afforestation and reforestation efforts and the remaining 2.56GtCO2 were driven by forest regrowth from shifting cultivation cycles, it says.

Forest regrowth from shifting cultivation refers to the recovery of a forest after a plot has been farmed for a short period and then abandoned.

This is shown in the chart below below, which shows how carbon removals from forest regrowth have offset emissions from deforestation.

In the near-term, the Global Carbon Budget attributes its projection of a drop in land-use emissions between 2024 and 2025 to the “end of El Niño conditions”.

(The naturally occurring weather phenomenon typically leads to the drying out of peatlands in the tropics and causes more planned deforestation fires to burn out of control.)

Prof Pierre Friedlingstein, director of the Global Carbon Budget office and a professor at the University of Exeter, tells Carbon Brief there is “no indication” of what might happen in the future, but adds that land-use emissions trends over the 21st century are “going in the right direction”. He says:

“If you are optimistic, you hope the trend will not reverse and start increasing again. But we don’t know for sure. The assumption, given current land policies across the world, is that deforestation should continue to decline.”

Which countries are behind falling land-use emissions?

The countries that contributed the most to land-use emissions over 2015-24 were Brazil, the Democratic Republic of the Congo (DRC) and Indonesia, according to the Global Carbon Budget.

It notes that these three countries together contributed more than half – 57% – of global land-use emissions.

Over the first quarter of the 21st century, falling land-use emissions in Brazil and Indonesia have combined with increased afforestation and reforestation in China to drive down overall land-use emissions, according to the Global Carbon Budget.

This is illustrated in the chart below, which shows how China’s land-use emissions have dropped below zero, as Brazil and Indonesia’s emissions have declined.

Friedlingstein says that the decline in land-use emissions since the 2000s has been “primarily driven by a decline in deforestation in Brazil”.

He tells Carbon Brief that tree clearance in the South American country rose in the 1990s then started to fall after a peak in the 2000s:

“There was a bit of up and down – mainly due to politics and who was in charge in Brazil – [whether the president] was [Luiz Inácio] Lula [da Silva] or [Jair] Bolsonaro. But the long-term trend in Brazil is a decline in deforestation due to forest protection policies.”

These policies included a 2004 “action plan” for the prevention and control of deforestation in the Amazon, a 2006 soy moratorium, which banned the purchasing and financing of soya produced in deforested areas of the Amazon, as well as the expansion of protected areas across Brazil during the second half of the 2000s.

Prof Julia Pongratz, a professor of physical geography and land-use systems at the University of Munich and contributor to the Global Carbon Budget, says Brazil is the “single most important contributor to the early-2000s global land-use change emissions peak and subsequent decline”.

She says that the largest contributor to an “acceleration” in the decline of global land-use emissions in the past decade has been Indonesia, which she notes has “rewetted more peatland area since 2017 alone than Europe in its entire history”.

Around the world, peatlands are exploited and damaged by humans for a range of purposes, including converting the land for agriculture and peat extraction for horticulture and fuel. Peatland wetting refers to the process of restoring water levels in drained peatlands in order to return them to their natural, waterlogged conditions, which allows for peat formation and carbon storage.

Another reason for Indonesia’s downward trend in land-use emissions is that there have been fewer spikes in emissions caused by fires related to human land-use activities over the last decade, says Pongratz.

Emissions from ecosystem fires are not always counted towards national and regional land-use emissions budgets, which estimate the sum of human-caused emissions. Deforestation fires and those related to peatland drainage are included, whereas fires caused by droughts and heatwaves are not.

Pongratz says it is “hard to separate natural and land-use drivers completely”, given that deforestation and peatland fires often “get out of control and cause spikes in emissions” during dry El Niño conditions.

(For more on uncertainties in land-use emissions data, see: Why are estimates of land-use emissions uncertain?)

Pongratz notes that international trade regulations that have helped to drive down land-use emissions in Brazil and Indonesia have had a lesser effect in the DRC, where the root drivers of deforestation are different:

“Emissions in the DRC have increased, then stayed high in the last two decades. This is partly related to population growth and expanding smallholder and subsistence farming.

“The picture is different in Brazil and Indonesia, which are much more driven by export; international regulations aiming at curbing deforestation thus have larger effects in these countries.”

Which countries are leading on forest regrowth?

Reforestation and afforestation schemes that draw down carbon from the atmosphere have helped to reduce the overall emissions from land-use change over the course of the 21st century.

As noted above, the 2025 Global Carbon Budget report highlights how the removal of carbon from forests offset two-thirds of deforestation emissions over 2015-24. 

The report says that China, the EU and US account for the highest levels of carbon sequestration from reforestation and afforestation, collectively drawing 1.1GtCO2 per year over the 2015-24 period.

This, it says, is “partly related to expanding forest area as a consequence of the forest transition in the 19th and 20th centuries and subsequent regrowth of forest”.

The chart below, which draws from the latest edition of the “state of carbon dioxide removal” report, shows how carbon uptake by forests has increased over the last 20 years in a number of countries, most notably in China.

In China, a raft of reforestation and improved land management policies were introduced in the 1990s which have led to the rehabilitation of tens of millions of hectares of forests. Research has shown the schemes have significantly increased the country’s uptake of carbon and switched its land from a carbon source to a carbon sink.

The Global Carbon Budget highlights that substantial carbon removal from reforestation and afforestation occurred in other regions, such as Brazil, Russia and Indonesia. However, in these regions, emissions from deforestation and other land-use changes “dominate”, it says.

Why are estimates of land-use emissions uncertain?

Tallying the world’s emission from land-use change is complex.

The Global Carbon Budget estimates an uncertainty range of 2.6GtCO2 per year for its average annual global land-use emissions figure for 2015-24 – more than half the overall figure of 5GtCO2.

To calculate overall land-use emissions for the annual Global Carbon Budget report, researchers create an average from three land-use models: BLUE, OSCAR and LUCE.

These models combine satellite and statistical information on land cover and land-use changes from global and regional datasets.

Pongratz, who is involved in the LUCE model, explains that scientists can measure the exchange of CO2 between land and atmosphere, but are not able to determine whether CO2 is being released or sequestered from a managed area as a result of human activities or other climate or environmental factors. She continues:

“For this, you need to turn to modelling, where you can isolate drivers – and, again, models are uncertain and the land-use input imperfect. This is why we use all available model estimates – three at the moment.”

The Global Carbon Budget highlights that its three different models treat different components of the land-use emissions “budget” differently.

While models agree “relatively well” about emissions from permanent deforestation, they take different approaches in their approach to shifting cultivation patterns, which increases both emissions and removals, as well as wood harvesting, it says.

Moreover, it notes that land-use emissions and removals occur on different timelines. While carbon removals generated by forest growth and soil recovery are “slow”, there is an “instantaneous component” to emissions from deforestation, it says.

(For more on the challenges in analysing changes to the global carbon cycle, see Carbon Brief’s recent in-depth interview with Prof Philippe Ciais, one of the world’s leading experts on land-use emissions.)

The Global Carbon Budget notes that its confidence in its 2025 projection for overall land-use emissions remains “low” given that the figure is based on deforestation, degradation and peat fire emissions, which are “only a proxy” for land-use change.

The report notes that 2023 is the final year in which it calculates land-use emissions directly from land-use statistics across all three bookkeeping models. For more recent years, full statistics are not yet available across the models and scientists instead turn to short-term proxies.

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The post Why land-use emissions have fallen by a third this century – in six charts appeared first on Carbon Brief.

Why land-use emissions have fallen by a third this century – in six charts