Ecological Overshoot

Ricter · Jul 31, 2023

A devastating Dust Bowl heat wave is now more than twice as likely, study says
By Jeff Berardelli

May 21, 2020 / 8:19 AM / CBS News
The Great Plains Dust Bowl of the 1930s was arguably the most devastating ecological disaster in American history, turning prairies into deserts and whipping up killer dust storms. The catastrophe was partly manmade — driven by decades of land mismanagement — and fueled by brutal heat waves and years of relentless drought.

More than eight decades later, the summer of 1936 remains the hottest summer on record in the U.S. However, new research finds that the heat waves that powered the Dust Bowl are now 2.5 times more likely to happen again in our modern climate due to another type of manmade crisis — climate change.

In this April 15, 1935 photo, a dust cloud approaches a ranch in Boise City, Oklahoma. AP Photo
Even though it seemed like a natural disaster, the groundwork for much of the suffering caused by the Dust Bowl was laid by humans.

Until the late 1800s the Great Plains were covered by endless acres of native grasslands, well attuned to the unique climate of the region. That had all changed by the turn of the 20th century, as a series of federal land acts enticed pioneers to move to the region and set up farms with the promise of free or cheap land.

With cold winters, hot summers and a dry, windy climate, the area was considered marginal farmland. But with demand from a growing wheat and cattle market, farms quickly replaced deep-rooted grasslands, which normally helped to trap soil and moisture even during droughts.

The decimation of native grasslands led to a significant loss of both soil moisture and the ability to keep soil in place. It is estimated that three to four inches of topsoil was blown away during the 1930s. To make matters worse, some relatively inexperienced farmers engaged in deep plowing of virgin topsoils and enabled overgrazing.

This absence of sound land management led to a feedback loop, where the lack of vegetation and moist soils meant the land no longer had the ability to cool itself through evaporation. So when natural climate fluctuations in the Atlantic and Pacific Oceans led to a streak of years with heat and drought in the Plains, the land not only had no buffer, but actually acted to amplify the disaster.

In this March 29, 1937 photo, the desolation of the Dust Bowl is graphically illustrated by these rippling dunes banked against a fence, farm home, barn and windmill in Guymon, Oklahoma. This property was abandoned by its owner when destructive dust clouds forced him to seek his fortune elsewhere. AP Photo
The authors of the study found that even way back then, emissions had already started to influence the climate. "These extremes occurred during a period of multidecadal warming, with early twentieth century global-scale drought likely amplified by greenhouse gases," they write.

The 1936 heat wave was so extreme it is considered a once-in-100-year event, with 25% of all U.S. daily heat records set during that summer and half of such records set during the 1930s. Temperatures routinely topped 110 degrees Fahrenheit.

The images below show the area covered by the 1936 heat wave, and from top to bottom: the number of days with extreme heat, the length of the longest heat wave stretch, and the hottest temperatures recorded.

When the Dust Bowl hit, day turned into night as biblical dust storms buried parts of roads and buildings, especially in parts of Kansas, Oklahoma and Texas. On "Black Sunday" in the Oklahoma Panhandle — April 14, 1935 — Thelmas Bemount Campbell described her terror to author Amy Dee Stephens as a dust storm enveloped her home:

"We could see it rolling toward us at a terrific speed like a prairie fire. The wind was so strong that we heard later it had broken the wind gauges…When it hit, everything became very still and we were enveloped in this terrible blackness. We couldn't see our hand in front of our face. Some people thought they had been struck blind."

As the dust storms became larger and more intense, children developed fatal "dust pneumonia" and business owners, already reeling from the Great Depression, were devastated, some driven to suicide and others forced to flee with their families in a mass exodus. In total, the Dust Bowl killed around 7,000 people and left 2 million homeless.

The heat, drought and dust storms also had a cascade effect on U.S. agriculture. Wheat production fell by 36% and maize production plummeted by 48% during the 1930s.

A cow forages for food in dust-blown pastures on July 8, 1936, in Ford County, Kansas, where a month of rainless days and soaring temperatures, well above 100 degrees in many areas, ruined pasturage and crops. AP Photo
The Dust Bowl is an example of an environmental disaster clearly made worse by the unintended consequences of man. And the study concludes that climate change may soon bring about the next one: "It is likely that the 1930s records will be broken in the near-future even if there is action to mitigate emissions."

To arrive at their conclusion, the researchers ran thousands of computer model simulations of the 1930s heat waves, but with atmospheric greenhouse gas concentrations at today's levels.

The study used a novel climate model developed at the University of Oxford that does not run on supercomputers, but rather on the personal computers of volunteers from around the world. This technique suited their particular 1930s heat wave investigation because thousands of simulations could be conducted for each Dust Bowl year.

The simulations showed that as a result of rapidly increasing heat-trapping greenhouse gases, the 1-in-100-year 1936 heat wave is, at the very least, now more of a 1-in-40-year event for the Great Plains — meaning a heat wave of that magnitude is now more than twice as likely and could occur twice in the average person's lifetime.

Lead author of the study Dr. Tim Cowan, of the University of Southern Queensland in Australia, cautions that even this 40-year return period is likely an underestimate, and in the future extreme heat waves will occur even more often.

But given the rise in greenhouse gases over many decades, CBS News asked Cowan why we haven't already seen a return of Dust Bowl-like conditions in the Great Plains. Cowan explains that the answers lie in the modern-day watering of crops. "Groundwater is used quite extensively across the U.S., and we know, from previous research, that increased irrigation and agricultural intensification has led to cooler summer maximum temperatures," he said.

But Cowan's work suggests that our luck will eventually run out, either when natural conditions and manmade climate change conspire to overwhelm the cooling influence of irrigation or when groundwater is sufficiently depleted.

In the western Great Plains the majority of groundwater comes from one of the world's largest aquifers -- the Ogallala Aquifer, which runs from Nebraska to Texas. But in recent decades, water is being extracted much faster than it is being replenished. Well outputs in the central and southern parts of the aquifer are declining due to excessive pumping, and prolonged droughts have parched the area, bringing back Dust Bowl-style storms.

Map of the Ogallala Aquifer NOAA
According to the federal government's 2018 National Climate Assessment, parts of the Ogallala Aquifer should be considered a nonrenewable resource.

As a result, Cowan warns, "Dwindling water availability in regions of low groundwater recharge may mean that cooler summer conditions may switch to warmer temperatures in decades to come under the influence of rising greenhouse gas emissions."

If these Dust Bowl conditions do return, scientists say we should prepare for a shock to the food system. A recent study predicted that the U.S. would exhaust 94% of its wheat reserves in a four-year Dust Bowl-like event. This would lead to a 31% loss of global wheat stocks.

Besides the impacts on food systems, an April study from the University of Washington finds the expected increase in extreme heat will also be a health shock. The research warns of danger for agricultural pickers in the U.S., with unsafe work days more than doubling by 2050 and heat waves happening five times more often as the planet continues to warm.

The bottom line, Cowan says: "It is likely that there will be more extreme heat wave conditions in the central U.S. in the future, given the rise in greenhouse gases levels, so communities and governments need to be prepared for this eventuality."

https://www.cbsnews.com/news/dust-bowl-heat-wave-climate-change-twice-as-likely-study-says/

gwb-trading · Jul 31, 2023

Ricter said:
A devastating Dust Bowl heat wave is now more than twice as likely, study says
By Jeff Berardelli

May 21, 2020 / 8:19 AM / CBS News
The Great Plains Dust Bowl of the 1930s was arguably the most devastating ecological disaster in American history, turning prairies into deserts and whipping up killer dust storms. The catastrophe was partly manmade — driven by decades of land mismanagement — and fueled by brutal heat waves and years of relentless drought.

More than eight decades later, the summer of 1936 remains the hottest summer on record in the U.S. However, new research finds that the heat waves that powered the Dust Bowl are now 2.5 times more likely to happen again in our modern climate due to another type of manmade crisis — climate change.

In this April 15, 1935 photo, a dust cloud approaches a ranch in Boise City, Oklahoma. AP Photo
Even though it seemed like a natural disaster, the groundwork for much of the suffering caused by the Dust Bowl was laid by humans.

Until the late 1800s the Great Plains were covered by endless acres of native grasslands, well attuned to the unique climate of the region. That had all changed by the turn of the 20th century, as a series of federal land acts enticed pioneers to move to the region and set up farms with the promise of free or cheap land.

With cold winters, hot summers and a dry, windy climate, the area was considered marginal farmland. But with demand from a growing wheat and cattle market, farms quickly replaced deep-rooted grasslands, which normally helped to trap soil and moisture even during droughts.

The decimation of native grasslands led to a significant loss of both soil moisture and the ability to keep soil in place. It is estimated that three to four inches of topsoil was blown away during the 1930s. To make matters worse, some relatively inexperienced farmers engaged in deep plowing of virgin topsoils and enabled overgrazing.

This absence of sound land management led to a feedback loop, where the lack of vegetation and moist soils meant the land no longer had the ability to cool itself through evaporation. So when natural climate fluctuations in the Atlantic and Pacific Oceans led to a streak of years with heat and drought in the Plains, the land not only had no buffer, but actually acted to amplify the disaster.

In this March 29, 1937 photo, the desolation of the Dust Bowl is graphically illustrated by these rippling dunes banked against a fence, farm home, barn and windmill in Guymon, Oklahoma. This property was abandoned by its owner when destructive dust clouds forced him to seek his fortune elsewhere. AP Photo
The authors of the study found that even way back then, emissions had already started to influence the climate. "These extremes occurred during a period of multidecadal warming, with early twentieth century global-scale drought likely amplified by greenhouse gases," they write.

The 1936 heat wave was so extreme it is considered a once-in-100-year event, with 25% of all U.S. daily heat records set during that summer and half of such records set during the 1930s. Temperatures routinely topped 110 degrees Fahrenheit.

The images below show the area covered by the 1936 heat wave, and from top to bottom: the number of days with extreme heat, the length of the longest heat wave stretch, and the hottest temperatures recorded.

When the Dust Bowl hit, day turned into night as biblical dust storms buried parts of roads and buildings, especially in parts of Kansas, Oklahoma and Texas. On "Black Sunday" in the Oklahoma Panhandle — April 14, 1935 — Thelmas Bemount Campbell described her terror to author Amy Dee Stephens as a dust storm enveloped her home:

"We could see it rolling toward us at a terrific speed like a prairie fire. The wind was so strong that we heard later it had broken the wind gauges…When it hit, everything became very still and we were enveloped in this terrible blackness. We couldn't see our hand in front of our face. Some people thought they had been struck blind."

As the dust storms became larger and more intense, children developed fatal "dust pneumonia" and business owners, already reeling from the Great Depression, were devastated, some driven to suicide and others forced to flee with their families in a mass exodus. In total, the Dust Bowl killed around 7,000 people and left 2 million homeless.

The heat, drought and dust storms also had a cascade effect on U.S. agriculture. Wheat production fell by 36% and maize production plummeted by 48% during the 1930s.

A cow forages for food in dust-blown pastures on July 8, 1936, in Ford County, Kansas, where a month of rainless days and soaring temperatures, well above 100 degrees in many areas, ruined pasturage and crops. AP Photo
The Dust Bowl is an example of an environmental disaster clearly made worse by the unintended consequences of man. And the study concludes that climate change may soon bring about the next one: "It is likely that the 1930s records will be broken in the near-future even if there is action to mitigate emissions."

To arrive at their conclusion, the researchers ran thousands of computer model simulations of the 1930s heat waves, but with atmospheric greenhouse gas concentrations at today's levels.

The study used a novel climate model developed at the University of Oxford that does not run on supercomputers, but rather on the personal computers of volunteers from around the world. This technique suited their particular 1930s heat wave investigation because thousands of simulations could be conducted for each Dust Bowl year.

The simulations showed that as a result of rapidly increasing heat-trapping greenhouse gases, the 1-in-100-year 1936 heat wave is, at the very least, now more of a 1-in-40-year event for the Great Plains — meaning a heat wave of that magnitude is now more than twice as likely and could occur twice in the average person's lifetime.

Lead author of the study Dr. Tim Cowan, of the University of Southern Queensland in Australia, cautions that even this 40-year return period is likely an underestimate, and in the future extreme heat waves will occur even more often.

But given the rise in greenhouse gases over many decades, CBS News asked Cowan why we haven't already seen a return of Dust Bowl-like conditions in the Great Plains. Cowan explains that the answers lie in the modern-day watering of crops. "Groundwater is used quite extensively across the U.S., and we know, from previous research, that increased irrigation and agricultural intensification has led to cooler summer maximum temperatures," he said.

But Cowan's work suggests that our luck will eventually run out, either when natural conditions and manmade climate change conspire to overwhelm the cooling influence of irrigation or when groundwater is sufficiently depleted.

In the western Great Plains the majority of groundwater comes from one of the world's largest aquifers -- the Ogallala Aquifer, which runs from Nebraska to Texas. But in recent decades, water is being extracted much faster than it is being replenished. Well outputs in the central and southern parts of the aquifer are declining due to excessive pumping, and prolonged droughts have parched the area, bringing back Dust Bowl-style storms.

Map of the Ogallala Aquifer NOAA
According to the federal government's 2018 National Climate Assessment, parts of the Ogallala Aquifer should be considered a nonrenewable resource.

As a result, Cowan warns, "Dwindling water availability in regions of low groundwater recharge may mean that cooler summer conditions may switch to warmer temperatures in decades to come under the influence of rising greenhouse gas emissions."

If these Dust Bowl conditions do return, scientists say we should prepare for a shock to the food system. A recent study predicted that the U.S. would exhaust 94% of its wheat reserves in a four-year Dust Bowl-like event. This would lead to a 31% loss of global wheat stocks.

Besides the impacts on food systems, an April study from the University of Washington finds the expected increase in extreme heat will also be a health shock. The research warns of danger for agricultural pickers in the U.S., with unsafe work days more than doubling by 2050 and heat waves happening five times more often as the planet continues to warm.

The bottom line, Cowan says: "It is likely that there will be more extreme heat wave conditions in the central U.S. in the future, given the rise in greenhouse gases levels, so communities and governments need to be prepared for this eventuality."

https://www.cbsnews.com/news/dust-bowl-heat-wave-climate-change-twice-as-likely-study-says/
More...

So it is just working up to get as warm as the 1930s.

Ricter · Jul 31, 2023

gwb-trading said:
So it is just working up to get as warm as the 1930s.
More...

Yes, but for reasons not so easily reversed, to put it mildly. Not to mention the scope: global instead of regional.

Ricter · Aug 1, 2023

WE CAN’T HANDLE THE TRUTH ABOUT THE HUMAN PREDICAMENT

August 1, 2023

Posted by:Art Berman

Category:The Petroleum Truth Report

Climate change is as obvious as gravity. The only people who debate gravity have advanced degrees in theoretical physics. Almost everyone in America—regardless of training or experience—has a strong opinion about climate change for some reason.

Cognitive dissonance is part of the problem. This is what happens when two strongly held beliefs conflict.

Most Americans believe in the progress narrative—that human ingenuity, technology and hard work can overcome almost any obstacle. The idea that the effects of progress may be harming the planet, other species and future generations of humans creates psychologic conflict or cognitive dissonance. We cannot hold both beliefs at the same time so we deny the existence of one or the other—in this case, climate change.

For many, the default position is—in the unlikely event that climate change is a problem—that technology, ingenuity and hard work will find a solution. That works just fine as long as we are energy- and systems-ignorant. Once we open our eyes to the bigger picture, it becomes clear that it’s not that simple.

The progress narrative is only partly true. It leaves out the fact that most of civilization’s progress—at least as measured by economic growth or GDP (gross domestic product)—over the last few centuries is because of fossil fuels (Figure 1). The role of technology and innovation was secondary.

Figure 1. The increase in world economic growth correlates with fossil fuel consumption. Source: EIA, BP, IEA, FRED, OWWD, World Bank & Labyrinth Consulting Services, Inc.

Oil is the economy and profits are linked to its consumption. The R-squared (r2) correlation between oil consumption and global GDP is 96% (Figure 2). That correlation is as statistically perfect as it gets in the real world.

Figure 2. World oil consumption vs GDP (gross domestic product). Oil is the Economy and profits are linked to its consumption. Source: EIA, World Bank & Labyrinth Consulting Services, Inc.

For all of our technology and ingenuity, oil, natural gas and coal are responsible for the wealth of nations. Every barrel of oil equivalent (boe) contains about 4.5 human-years of work. That means that our civilization has more than 380 billion fossil-energy slaves working for us all of the time (Table 1).

Table 1. Oil, natural gas and coal account for about 85 billion barrels of oil equivalent consumption every year. That converts to more than 380 billion years of human work. Source: BP 2020 Statistical Review of Energy and Labyrinth Consulting Services, Inc.

We have added an average of 4.7 billion fossil slaves every year for the last decade in addition to the base amount of almost 340 billion 10 years ago (Figure 3).

Figure 3. Average addition of 4.7 billion work-year equivalents from coal, natural gas and oil consumption over the last decade on top of the base level of 340 billion human work-year equivalents 10 years ago. Source: EIA, BP, IEA, FRED, OWWD, World Bank & Labyrinth Consulting Services, Inc.

This broader perspective shows that simply switching from fossil fuels to renewable energy is not a solution, certainly not in the time window of urgency for climate change. Nor has anyone proven that net emissions from renewable energy are substantially less than from fossil fuels once all of the embedded energy consumption in their extraction, transportation, manufacture and distribution are taken into account.

Assuming that renewable emissions are lower, there is simply not time nor resources available to scale from about 7% wind and solar to a large enough percentage of world energy consumption to make a difference. Even the most optimistic net-zero projections do not indicate that wind and solar energy will account for more than one-third of total final energy by 2050.

More importantly, climate change is not the biggest problem facing the world. It is a symptom of the much larger problem of overshoot.

Overshoot means that humans are using natural resources and polluting at rates beyond the planet’s capacity to recover. The main cause of overshoot is the extraordinary growth of human population made possible by fossil energy.

Overshoot is more difficult to dispute than climate change—the destruction of rainforests, the extinction of other species, the pollution of land, river and seas, the acidification of the oceans, and loss of fisheries and coral reefs. These are not part of any natural process and human activity is clearly responsible.

Technology, unfortunately, is no more a solution to climate change, overshoot or the human predicament that it was the primary cause for human prosperity.

Carbon emissions and the overshooting of planetary boundaries are unlikely to decrease as long as energy consumption, world GDP and population continue to increase (Figure 4). The interrelationship of these factors with the degradation of Earth’s ecosystem means that there are no solutions without a structural change in all of these factors as a starting point.

Figure 4. Carbon emissions and overshoot of planetary boundaries are unlikely to decrease as long as energy consumption, world GDP and population continue to increase. Source: OWID, Global Footprint Network , Global Carbon Atlas & Labyrinth Consulting Services, Inc.

This implies that a civilization paradigm shift is required but I think that we are psychologically incapable of acknowledging that. Even if we could notionally concede this possibility, we would immediately start rationalizing that of course technology, efficiency and human ingenuity are central to any path forward. In short order, we’d be back to carbon capture, renewable energy, circular economies and related fantasies.

We just can’t handle the truth about the human predicament.

https://www.artberman.com/2023/08/01/we-cant-handle-the-truth-about-the-human-predicament/

Ricter · Aug 10, 2023

Turns out there’s another problem with AI – its environmental toll
AI uses huge amounts of electricity and water to work, and the problem is only going to get worse – what can be done?

Chris Stokel-Walker
Tue 1 Aug 2023 11.40 BST

Servers to mine crytpo or power AI take an enormous amount of electricity. Photograph: Erik Isakson/Getty Images/Blend Images

Technology never exists in a vacuum, and the rise of cryptocurrency in the last two or three years shows that. While plenty of people were making extraordinary amounts of money from investing in bitcoin and its competitors, there was consternation about the impact those get-rich-quick speculators had on the environment.

Mining cryptocurrency was environmentally taxing. The core principle behind it was that you had to expend effort to get rich. To mint a bitcoin or another cryptocurrency, you had to first “mine” it. Your computer would be tasked with completing complicated equations that, if successfully done, could create a new entry on to the blockchain.

People began working on an industrial scale, snapping up the high-powered computer chips, called GPUs (graphics processing units), that could mine for crypto faster than your off-the-shelf computer components at such pace that Goldman Sachs estimated 169 industries were affected by the 2022 chip shortage. And those computer chips required more electricity to power them; bitcoin mining alone uses more electricity than Norway and Ukraine combined.

The environmental cost of the crypto craze is still being tallied – including by the Guardian this April.

The AI environmental footprint

A booming part of tech – which uses the exact same GPUs as intensely, if not more so, than crypto mining – has got away with comparatively little scrutiny of its environmental impact. We are, of course, talking about the AI revolution.

Generative AI tools are powered by GPUs, which are complex computer chips able to handle the billions of calculations a second required to power the likes of ChatGPT and Google Bard. (Google uses its own similar technology, called tensor processing units, or TPUs.)

There should be more conversation about the environmental impact of AI, says Sasha Luccioni, a researcher in ethical and sustainable AI at Hugging Face, which has become the de facto conscience of the AI industry. (Meta recently released its Llama 2 open-source large language model through Hugging Face.)

“Fundamentally speaking, if you do want to save the planet with AI, you have to consider also the environmental footprint [of AI first],” she says. “It doesn’t make sense to burn a forest and then use AI to track deforestation.”

Counting the carbon cost

Luccioni is one of a number of researchers trying – with difficulty – to quantify AI’s environmental impact. It’s difficult for a number of reasons, among them that the companies behind the most popular tools, as well as the companies selling the chips that power them, aren’t very willing to share details of how much energy their systems use.

There’s also an intangibility to AI that stymies proper accounting of its environmental footprint. “I think AI is not part of these pledges or initiatives, because people think it’s not material, somehow,” she says. “You can think of a computer or something that has a physical form, but AI is so ephemeral. Even for companies trying to make efforts, I don’t typically see AI on the radar.”

That ephemerality also exists for end users. We know that we’re causing harm to the planet when we turn on our cars because we can see or smell the fumes coming out of the exhaust after we turn the key. With AI, you can’t see the cloud-based servers being queried, or the chips rifling through their memory to complete the processing tasks asked of it. For many, the huge volumes of water coursing through pipes inside data centres, deployed to keep the computers powering the AI tools cool, are invisible.

You just type in your query, wait a few seconds, then get a response. Where’s the harm in that?

Putting numbers to the problem

Let’s start with the water use. Training GPT-3 used by 3.5m litres of water through data centre usage, according to one academic study, and that’s provided it used more efficient US data centres. If it was trained on Microsoft’s data centres in Asia, the water usage balloons to closer to 5m litres.

Prior to the integration of GPT-4 into ChatGPT, researchers estimated that the generative AI chatbot would use up 500ml of water – a standard-sized water bottle – every 20 questions and corresponding answers. And ChatGPT was only likely to get thirstier with the release of GPT-4, the researchers forecast.

Estimating energy use, and the resulting carbon footprint, is trickier. One third-party analysis by researchers estimated that training of GPT-3, a predecessor of ChatGPT, consumed 1,287 MWh, and led to emissions of more than 550 tonnes of carbon dioxide equivalent, similar to flying between New York and San Francisco on a return journey 550 times.

Reporting suggests GPT-4 is trained on around 570 times more parameters than GPT-3. That doesn’t mean it uses 570 times more energy, of course – things get more efficient – but it does suggest that things are getting more energy intensive, not less.

For better or for worse

Tech boffins are trying to find ways to maintain AI’s intelligence without the huge energy use. But it’s difficult. One recent study, published earlier this month, suggests that many of the workarounds already tabled end up trading off performance for environmental good.

It leaves the AI sector in an unenviable position. Users are already antsy about what they see as a worsening performance of generative AI tools like ChatGPT (whether that’s just down to their perception or based in reality isn’t yet certain).

Sacrificing performance to reduce ecological impact seems unlikely. But we need to rethink AI’s use – and fast. Technology analysts Gartner believe that by 2025, unless a radical rethink takes place in how we develop AI systems to better account for their environmental impact, the energy consumption of AI tools will be greater than that of the entire human workforce. By 2030, machine learning training and data storage could account for 3.5% of all global electricity consumption. Pre-AI revolution, datacentres used up 1% of all the world’s electricity demand in any given year.

So what should we do? Treating AI more like cryptocurrency – with an increased awareness of its harmful environmental impacts, alongside awe at its seemingly magical powers of deduction – would be a start.

https://www.theguardian.com/technol...rtificial-intelligence?CMP=Share_iOSApp_Other

Tsing Tao · Aug 10, 2023

Ricter said:
Turns out there’s another problem with AI – its environmental toll
AI uses huge amounts of electricity and water to work, and the problem is only going to get worse – what can be done?

Chris Stokel-Walker
Tue 1 Aug 2023 11.40 BST

Servers to mine crytpo or power AI take an enormous amount of electricity. Photograph: Erik Isakson/Getty Images/Blend Images

Technology never exists in a vacuum, and the rise of cryptocurrency in the last two or three years shows that. While plenty of people were making extraordinary amounts of money from investing in bitcoin and its competitors, there was consternation about the impact those get-rich-quick speculators had on the environment.

Mining cryptocurrency was environmentally taxing. The core principle behind it was that you had to expend effort to get rich. To mint a bitcoin or another cryptocurrency, you had to first “mine” it. Your computer would be tasked with completing complicated equations that, if successfully done, could create a new entry on to the blockchain.

People began working on an industrial scale, snapping up the high-powered computer chips, called GPUs (graphics processing units), that could mine for crypto faster than your off-the-shelf computer components at such pace that Goldman Sachs estimated 169 industries were affected by the 2022 chip shortage. And those computer chips required more electricity to power them; bitcoin mining alone uses more electricity than Norway and Ukraine combined.

The environmental cost of the crypto craze is still being tallied – including by the Guardian this April.

The AI environmental footprint

A booming part of tech – which uses the exact same GPUs as intensely, if not more so, than crypto mining – has got away with comparatively little scrutiny of its environmental impact. We are, of course, talking about the AI revolution.

Generative AI tools are powered by GPUs, which are complex computer chips able to handle the billions of calculations a second required to power the likes of ChatGPT and Google Bard. (Google uses its own similar technology, called tensor processing units, or TPUs.)

There should be more conversation about the environmental impact of AI, says Sasha Luccioni, a researcher in ethical and sustainable AI at Hugging Face, which has become the de facto conscience of the AI industry. (Meta recently released its Llama 2 open-source large language model through Hugging Face.)

“Fundamentally speaking, if you do want to save the planet with AI, you have to consider also the environmental footprint [of AI first],” she says. “It doesn’t make sense to burn a forest and then use AI to track deforestation.”

Counting the carbon cost

Luccioni is one of a number of researchers trying – with difficulty – to quantify AI’s environmental impact. It’s difficult for a number of reasons, among them that the companies behind the most popular tools, as well as the companies selling the chips that power them, aren’t very willing to share details of how much energy their systems use.

There’s also an intangibility to AI that stymies proper accounting of its environmental footprint. “I think AI is not part of these pledges or initiatives, because people think it’s not material, somehow,” she says. “You can think of a computer or something that has a physical form, but AI is so ephemeral. Even for companies trying to make efforts, I don’t typically see AI on the radar.”

That ephemerality also exists for end users. We know that we’re causing harm to the planet when we turn on our cars because we can see or smell the fumes coming out of the exhaust after we turn the key. With AI, you can’t see the cloud-based servers being queried, or the chips rifling through their memory to complete the processing tasks asked of it. For many, the huge volumes of water coursing through pipes inside data centres, deployed to keep the computers powering the AI tools cool, are invisible.

You just type in your query, wait a few seconds, then get a response. Where’s the harm in that?

Putting numbers to the problem

Let’s start with the water use. Training GPT-3 used by 3.5m litres of water through data centre usage, according to one academic study, and that’s provided it used more efficient US data centres. If it was trained on Microsoft’s data centres in Asia, the water usage balloons to closer to 5m litres.

Prior to the integration of GPT-4 into ChatGPT, researchers estimated that the generative AI chatbot would use up 500ml of water – a standard-sized water bottle – every 20 questions and corresponding answers. And ChatGPT was only likely to get thirstier with the release of GPT-4, the researchers forecast.

Estimating energy use, and the resulting carbon footprint, is trickier. One third-party analysis by researchers estimated that training of GPT-3, a predecessor of ChatGPT, consumed 1,287 MWh, and led to emissions of more than 550 tonnes of carbon dioxide equivalent, similar to flying between New York and San Francisco on a return journey 550 times.

Reporting suggests GPT-4 is trained on around 570 times more parameters than GPT-3. That doesn’t mean it uses 570 times more energy, of course – things get more efficient – but it does suggest that things are getting more energy intensive, not less.

For better or for worse

Tech boffins are trying to find ways to maintain AI’s intelligence without the huge energy use. But it’s difficult. One recent study, published earlier this month, suggests that many of the workarounds already tabled end up trading off performance for environmental good.

It leaves the AI sector in an unenviable position. Users are already antsy about what they see as a worsening performance of generative AI tools like ChatGPT (whether that’s just down to their perception or based in reality isn’t yet certain).

Sacrificing performance to reduce ecological impact seems unlikely. But we need to rethink AI’s use – and fast. Technology analysts Gartner believe that by 2025, unless a radical rethink takes place in how we develop AI systems to better account for their environmental impact, the energy consumption of AI tools will be greater than that of the entire human workforce. By 2030, machine learning training and data storage could account for 3.5% of all global electricity consumption. Pre-AI revolution, datacentres used up 1% of all the world’s electricity demand in any given year.

So what should we do? Treating AI more like cryptocurrency – with an increased awareness of its harmful environmental impacts, alongside awe at its seemingly magical powers of deduction – would be a start.

https://www.theguardian.com/technol...rtificial-intelligence?CMP=Share_iOSApp_Other
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Cryptocurrency is nothing like AI (and AI shouldn't be treated as such). Is there a cost in the extra computing from a processing/energy component? Sure. But you'd have to look at the net impact, not just the negative, right? What about how AI will efficiently route planes, trucks and ships for minimal energy usage - as a start? I've been reading article after article how AI will drive efficiencies across the board in transportation. Shouldn't we consider the positive side of the equation as well?

Ricter · Aug 10, 2023

Tsing Tao said:
Cryptocurrency is nothing like AI (and AI shouldn't be treated as such). Is there a cost in the extra computing from a processing/energy component? Sure. But you'd have to look at the net impact, not just the negative, right? What about how AI will efficiently route planes, trucks and ships for minimal energy usage - as a start? I've been reading article after article how AI will drive efficiencies across the board in transportation. Shouldn't we consider the positive side of the equation as well?
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A fair point. Though keeping Jevons Paradox in mind, overall consumption (and pollution) would go up... hmm. I mean, we're a lot more efficient today than we were 50 years ago, and the condition of the biosphere is worse.

Tsing Tao · Aug 10, 2023

Ricter said:
A fair point. Though keeping Jevons Paradox in mind, overall consumption (and pollution) would go up... hmm. I mean, we're a lot more efficient today than we were 50 years ago, and the condition of the biosphere is worse.
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We're a lot more efficient, but there are a lot more of us as well, using a lot more of resources. Again, its a multi-variable equation - but we do have to consider all the variables to make a smart decision.

Ricter · Aug 12, 2023

"Devastating data from National Oceanic and Atmospheric Administration (@NOAA) show 2020s are averaging only 18 days between each billion-dollar disaster … cost of each event adjusted for inflation and disasters include droughts, flooding, cyclones, winter storms, wildfires, etc."

ph1l · Aug 13, 2023

This video makes a lot of sense to a layperson.

See also
https://growthzonesitesprod.azureed.../sites/1449/2021/11/ChristyJR_20211118_v1.pdf
A Practical Guide to Climate Change in Alabama