#energyconsumption — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #energyconsumption, aggregated by home.social.
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Developers eye #NativeNations, tribal communities for new #Datacenter projects
by Madyson Fitzgerald, 9/12/2026
"Officials in #PageAZ, a small city near the Glen Canyon Dam, passed a land sale agreement last fall that establishes a framework for future construction of a data center.
"The sale of the 500-acre parcel about a mile away from the Colorado River’s #HorseshoeBend — one of the most visited natural landmarks in the #GlenCanyon National Recreation Area — to #HuntleyLLC for $7 million specifies that the company intends to build a 1 gigawatt data center.
"Residents have been pushing back and launched a petition earlier this year to stop the planned data center from being built.
"About 5 miles south of the city, a group of tribal leaders began to take notice. The proposed data center borders the #LeChee Chapter of the #NavajoNation, located in the northwest corner of the Navajo Reservation. "
#NoDatacenters #NativeAmericanNews #Dine #Dineh #EnvironmentalRacism #Hyperscale #CorporateColonialism #USPol #NoisePollution #WaterIsLife #EnergyConsumption #Arizona
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Developers eye #NativeNations, tribal communities for new #Datacenter projects
by Madyson Fitzgerald, 9/12/2026
"Officials in #PageAZ, a small city near the Glen Canyon Dam, passed a land sale agreement last fall that establishes a framework for future construction of a data center.
"The sale of the 500-acre parcel about a mile away from the Colorado River’s #HorseshoeBend — one of the most visited natural landmarks in the #GlenCanyon National Recreation Area — to #HuntleyLLC for $7 million specifies that the company intends to build a 1 gigawatt data center.
"Residents have been pushing back and launched a petition earlier this year to stop the planned data center from being built.
"About 5 miles south of the city, a group of tribal leaders began to take notice. The proposed data center borders the #LeChee Chapter of the #NavajoNation, located in the northwest corner of the Navajo Reservation. "
#NoDatacenters #NativeAmericanNews #Dine #Dineh #EnvironmentalRacism #Hyperscale #CorporateColonialism #USPol #NoisePollution #WaterIsLife #EnergyConsumption #Arizona
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Developers eye #NativeNations, tribal communities for new #Datacenter projects
by Madyson Fitzgerald, 9/12/2026
"Officials in #PageAZ, a small city near the Glen Canyon Dam, passed a land sale agreement last fall that establishes a framework for future construction of a data center.
"The sale of the 500-acre parcel about a mile away from the Colorado River’s #HorseshoeBend — one of the most visited natural landmarks in the #GlenCanyon National Recreation Area — to #HuntleyLLC for $7 million specifies that the company intends to build a 1 gigawatt data center.
"Residents have been pushing back and launched a petition earlier this year to stop the planned data center from being built.
"About 5 miles south of the city, a group of tribal leaders began to take notice. The proposed data center borders the #LeChee Chapter of the #NavajoNation, located in the northwest corner of the Navajo Reservation. "
#NoDatacenters #NativeAmericanNews #Dine #Dineh #EnvironmentalRacism #Hyperscale #CorporateColonialism #USPol #NoisePollution #WaterIsLife #EnergyConsumption #Arizona
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Developers eye #NativeNations, tribal communities for new #Datacenter projects
by Madyson Fitzgerald, 9/12/2026
"Officials in #PageAZ, a small city near the Glen Canyon Dam, passed a land sale agreement last fall that establishes a framework for future construction of a data center.
"The sale of the 500-acre parcel about a mile away from the Colorado River’s #HorseshoeBend — one of the most visited natural landmarks in the #GlenCanyon National Recreation Area — to #HuntleyLLC for $7 million specifies that the company intends to build a 1 gigawatt data center.
"Residents have been pushing back and launched a petition earlier this year to stop the planned data center from being built.
"About 5 miles south of the city, a group of tribal leaders began to take notice. The proposed data center borders the #LeChee Chapter of the #NavajoNation, located in the northwest corner of the Navajo Reservation. "
#NoDatacenters #NativeAmericanNews #Dine #Dineh #EnvironmentalRacism #Hyperscale #CorporateColonialism #USPol #NoisePollution #WaterIsLife #EnergyConsumption #Arizona
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Developers eye #NativeNations, tribal communities for new #Datacenter projects
by Madyson Fitzgerald, 9/12/2026
"Officials in #PageAZ, a small city near the Glen Canyon Dam, passed a land sale agreement last fall that establishes a framework for future construction of a data center.
"The sale of the 500-acre parcel about a mile away from the Colorado River’s #HorseshoeBend — one of the most visited natural landmarks in the #GlenCanyon National Recreation Area — to #HuntleyLLC for $7 million specifies that the company intends to build a 1 gigawatt data center.
"Residents have been pushing back and launched a petition earlier this year to stop the planned data center from being built.
"About 5 miles south of the city, a group of tribal leaders began to take notice. The proposed data center borders the #LeChee Chapter of the #NavajoNation, located in the northwest corner of the Navajo Reservation. "
#NoDatacenters #NativeAmericanNews #Dine #Dineh #EnvironmentalRacism #Hyperscale #CorporateColonialism #USPol #NoisePollution #WaterIsLife #EnergyConsumption #Arizona
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#Texas Gov. #GregAbbott on #AIDataCenter Backlash: 'They Dug Their Own Grave'
Jennifer Oliver O'Connell, August 23, 2026
"#NewYork Gov. #KathyHochul (D) and #Kentucky Gov. #AndyBeshear (D) have pushed back against the expansion of #AIDataCenters in their respective states. But with the increasing backlash from communities and individuals toward new #datacenter construction and expansion, even governors that have embraced the #AIRevolution, like #Pennsylvania's #JoshShapiro (D), are now moderating and talking about scaling back.
"Texas Gov. Greg Abbott (R) is one governor whose state has embraced the data center expansion. In November 2025, Abbott declared that Texas is the 'epicenter of AI development' in his announcement of #Google building three data center campuses to the tune of $40 million dollars.
"Fast forward to August of 2026, and Abbott acknowledges that much of the community resistance to the construction of new and existing data centers is the fault of the AI companies."
[...]
"Abbott is not wrong. According to a report from #DataCenterWatch, 64 billion in data center projects have been blocked or delayed in #Arizona, #Utah, #Missouri, #Oregon, and #California, to name a few. Even formerly friendly #Virginia is pushing back. #CommunityOpposition surrounds the lack of information provided and the lack of accountability taken towards the citizens who will be most affected.
"Water and power concerns loom large. Many of the newer development concepts, like entrepreneur #KevinOLeary 's 9 megawatt #StratosProject in #Utah, will have their own self-sustaining water and power systems. However, this did not prevent the backlash by #environmentalists and local activists to shut the Stratos Project down, and Utah state lawmakers ultimately backpedaled from their original approval and requested O'Leary cut the project's 400,000-acre footprint down to 10,000, about 75 percent. "
#AISucks #AIDataCenters #AIResistance #USPol #WorldPol #Datacenters #Datacentres #AIDatacentres #WaterIsLife #NoisePollution #LandIsLife #EnergyConsumption
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#Texas Gov. #GregAbbott on #AIDataCenter Backlash: 'They Dug Their Own Grave'
Jennifer Oliver O'Connell, August 23, 2026
"#NewYork Gov. #KathyHochul (D) and #Kentucky Gov. #AndyBeshear (D) have pushed back against the expansion of #AIDataCenters in their respective states. But with the increasing backlash from communities and individuals toward new #datacenter construction and expansion, even governors that have embraced the #AIRevolution, like #Pennsylvania's #JoshShapiro (D), are now moderating and talking about scaling back.
"Texas Gov. Greg Abbott (R) is one governor whose state has embraced the data center expansion. In November 2025, Abbott declared that Texas is the 'epicenter of AI development' in his announcement of #Google building three data center campuses to the tune of $40 million dollars.
"Fast forward to August of 2026, and Abbott acknowledges that much of the community resistance to the construction of new and existing data centers is the fault of the AI companies."
[...]
"Abbott is not wrong. According to a report from #DataCenterWatch, 64 billion in data center projects have been blocked or delayed in #Arizona, #Utah, #Missouri, #Oregon, and #California, to name a few. Even formerly friendly #Virginia is pushing back. #CommunityOpposition surrounds the lack of information provided and the lack of accountability taken towards the citizens who will be most affected.
"Water and power concerns loom large. Many of the newer development concepts, like entrepreneur #KevinOLeary 's 9 megawatt #StratosProject in #Utah, will have their own self-sustaining water and power systems. However, this did not prevent the backlash by #environmentalists and local activists to shut the Stratos Project down, and Utah state lawmakers ultimately backpedaled from their original approval and requested O'Leary cut the project's 400,000-acre footprint down to 10,000, about 75 percent. "
#AISucks #AIDataCenters #AIResistance #USPol #WorldPol #Datacenters #Datacentres #AIDatacentres #WaterIsLife #NoisePollution #LandIsLife #EnergyConsumption
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#Texas Gov. #GregAbbott on #AIDataCenter Backlash: 'They Dug Their Own Grave'
Jennifer Oliver O'Connell, August 23, 2026
"#NewYork Gov. #KathyHochul (D) and #Kentucky Gov. #AndyBeshear (D) have pushed back against the expansion of #AIDataCenters in their respective states. But with the increasing backlash from communities and individuals toward new #datacenter construction and expansion, even governors that have embraced the #AIRevolution, like #Pennsylvania's #JoshShapiro (D), are now moderating and talking about scaling back.
"Texas Gov. Greg Abbott (R) is one governor whose state has embraced the data center expansion. In November 2025, Abbott declared that Texas is the 'epicenter of AI development' in his announcement of #Google building three data center campuses to the tune of $40 million dollars.
"Fast forward to August of 2026, and Abbott acknowledges that much of the community resistance to the construction of new and existing data centers is the fault of the AI companies."
[...]
"Abbott is not wrong. According to a report from #DataCenterWatch, 64 billion in data center projects have been blocked or delayed in #Arizona, #Utah, #Missouri, #Oregon, and #California, to name a few. Even formerly friendly #Virginia is pushing back. #CommunityOpposition surrounds the lack of information provided and the lack of accountability taken towards the citizens who will be most affected.
"Water and power concerns loom large. Many of the newer development concepts, like entrepreneur #KevinOLeary 's 9 megawatt #StratosProject in #Utah, will have their own self-sustaining water and power systems. However, this did not prevent the backlash by #environmentalists and local activists to shut the Stratos Project down, and Utah state lawmakers ultimately backpedaled from their original approval and requested O'Leary cut the project's 400,000-acre footprint down to 10,000, about 75 percent. "
#AISucks #AIDataCenters #AIResistance #USPol #WorldPol #Datacenters #Datacentres #AIDatacentres #WaterIsLife #NoisePollution #LandIsLife #EnergyConsumption
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#Texas Gov. #GregAbbott on #AIDataCenter Backlash: 'They Dug Their Own Grave'
Jennifer Oliver O'Connell, August 23, 2026
"#NewYork Gov. #KathyHochul (D) and #Kentucky Gov. #AndyBeshear (D) have pushed back against the expansion of #AIDataCenters in their respective states. But with the increasing backlash from communities and individuals toward new #datacenter construction and expansion, even governors that have embraced the #AIRevolution, like #Pennsylvania's #JoshShapiro (D), are now moderating and talking about scaling back.
"Texas Gov. Greg Abbott (R) is one governor whose state has embraced the data center expansion. In November 2025, Abbott declared that Texas is the 'epicenter of AI development' in his announcement of #Google building three data center campuses to the tune of $40 million dollars.
"Fast forward to August of 2026, and Abbott acknowledges that much of the community resistance to the construction of new and existing data centers is the fault of the AI companies."
[...]
"Abbott is not wrong. According to a report from #DataCenterWatch, 64 billion in data center projects have been blocked or delayed in #Arizona, #Utah, #Missouri, #Oregon, and #California, to name a few. Even formerly friendly #Virginia is pushing back. #CommunityOpposition surrounds the lack of information provided and the lack of accountability taken towards the citizens who will be most affected.
"Water and power concerns loom large. Many of the newer development concepts, like entrepreneur #KevinOLeary 's 9 megawatt #StratosProject in #Utah, will have their own self-sustaining water and power systems. However, this did not prevent the backlash by #environmentalists and local activists to shut the Stratos Project down, and Utah state lawmakers ultimately backpedaled from their original approval and requested O'Leary cut the project's 400,000-acre footprint down to 10,000, about 75 percent. "
#AISucks #AIDataCenters #AIResistance #USPol #WorldPol #Datacenters #Datacentres #AIDatacentres #WaterIsLife #NoisePollution #LandIsLife #EnergyConsumption
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#Texas Gov. #GregAbbott on #AIDataCenter Backlash: 'They Dug Their Own Grave'
Jennifer Oliver O'Connell, August 23, 2026
"#NewYork Gov. #KathyHochul (D) and #Kentucky Gov. #AndyBeshear (D) have pushed back against the expansion of #AIDataCenters in their respective states. But with the increasing backlash from communities and individuals toward new #datacenter construction and expansion, even governors that have embraced the #AIRevolution, like #Pennsylvania's #JoshShapiro (D), are now moderating and talking about scaling back.
"Texas Gov. Greg Abbott (R) is one governor whose state has embraced the data center expansion. In November 2025, Abbott declared that Texas is the 'epicenter of AI development' in his announcement of #Google building three data center campuses to the tune of $40 million dollars.
"Fast forward to August of 2026, and Abbott acknowledges that much of the community resistance to the construction of new and existing data centers is the fault of the AI companies."
[...]
"Abbott is not wrong. According to a report from #DataCenterWatch, 64 billion in data center projects have been blocked or delayed in #Arizona, #Utah, #Missouri, #Oregon, and #California, to name a few. Even formerly friendly #Virginia is pushing back. #CommunityOpposition surrounds the lack of information provided and the lack of accountability taken towards the citizens who will be most affected.
"Water and power concerns loom large. Many of the newer development concepts, like entrepreneur #KevinOLeary 's 9 megawatt #StratosProject in #Utah, will have their own self-sustaining water and power systems. However, this did not prevent the backlash by #environmentalists and local activists to shut the Stratos Project down, and Utah state lawmakers ultimately backpedaled from their original approval and requested O'Leary cut the project's 400,000-acre footprint down to 10,000, about 75 percent. "
#AISucks #AIDataCenters #AIResistance #USPol #WorldPol #Datacenters #Datacentres #AIDatacentres #WaterIsLife #NoisePollution #LandIsLife #EnergyConsumption
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Press Release: Rising #Emissions, Depleting #Water and Vanishing #Land—UN Scientists: #AI Is Threatening #NaturalResources for Billions
By 2030, AI's water use will match the needs of 1.3 billion people while its power use triples that of 650 million, UN University investigation warns
Date Published
3 Jun 2026Excerpt: "Inference, efficiency, and the rebound effect
"Public discussion has largely focused on the energy required to train massive models. Training GPT-3 was estimated to require 1.3 gigawatt-hours (GWh) of electricity, while estimates suggest GPT-4 consumed between 50 and 70 GWh. However, the report reveals this framing is outdated. Once a model is deployed, inference—the continuous running of models to answer everyday user prompts—becomes the dominant cost, accounting for 80 to 90 per cent of total #AI energy use. ChatGPT alone is estimated to process around 2.5 billion prompts per day, translating to roughly 383 GWh of electricity per year for a single product. Offsetting associated carbon emissions would require 2.6 million tree seedlings grown for 10 years, enough trees to cover a land area the size of Manhattan. The water footprint is equivalent to the minimum annual domestic water needs of roughly 500,000 people in Sub-Saharan Africa, and the land footprint is equal to over 800 football fields."
Read more:
https://unu.edu/inweh/news/environmental-cost-of-AIs-Enrgy-use-carbon-water-and-land-footprints#AIBoom #Electricity #Hyperscale #BigTech #BigData #CarbonFootprint #EnvironmentalRacism #EnvironmentalDegradation #NoisePollution #LightPollution #WaterIsLife #AIAgents #BotTraffic #GreenSpaces #Farmland #Prairies #Woodland #TechGiants #ProtectNature #NoDatacenters #EnergyConsumption #USPol #WorldPol #Datacentres
#DatacenterMoratoriums #ArtificialIntelligence -
Press Release: Rising #Emissions, Depleting #Water and Vanishing #Land—UN Scientists: #AI Is Threatening #NaturalResources for Billions
By 2030, AI's water use will match the needs of 1.3 billion people while its power use triples that of 650 million, UN University investigation warns
Date Published
3 Jun 2026Excerpt: "Inference, efficiency, and the rebound effect
"Public discussion has largely focused on the energy required to train massive models. Training GPT-3 was estimated to require 1.3 gigawatt-hours (GWh) of electricity, while estimates suggest GPT-4 consumed between 50 and 70 GWh. However, the report reveals this framing is outdated. Once a model is deployed, inference—the continuous running of models to answer everyday user prompts—becomes the dominant cost, accounting for 80 to 90 per cent of total #AI energy use. ChatGPT alone is estimated to process around 2.5 billion prompts per day, translating to roughly 383 GWh of electricity per year for a single product. Offsetting associated carbon emissions would require 2.6 million tree seedlings grown for 10 years, enough trees to cover a land area the size of Manhattan. The water footprint is equivalent to the minimum annual domestic water needs of roughly 500,000 people in Sub-Saharan Africa, and the land footprint is equal to over 800 football fields."
Read more:
https://unu.edu/inweh/news/environmental-cost-of-AIs-Enrgy-use-carbon-water-and-land-footprints#AIBoom #Electricity #Hyperscale #BigTech #BigData #CarbonFootprint #EnvironmentalRacism #EnvironmentalDegradation #NoisePollution #LightPollution #WaterIsLife #AIAgents #BotTraffic #GreenSpaces #Farmland #Prairies #Woodland #TechGiants #ProtectNature #NoDatacenters #EnergyConsumption #USPol #WorldPol #Datacentres
#DatacenterMoratoriums #ArtificialIntelligence -
Press Release: Rising #Emissions, Depleting #Water and Vanishing #Land—UN Scientists: #AI Is Threatening #NaturalResources for Billions
By 2030, AI's water use will match the needs of 1.3 billion people while its power use triples that of 650 million, UN University investigation warns
Date Published
3 Jun 2026Excerpt: "Inference, efficiency, and the rebound effect
"Public discussion has largely focused on the energy required to train massive models. Training GPT-3 was estimated to require 1.3 gigawatt-hours (GWh) of electricity, while estimates suggest GPT-4 consumed between 50 and 70 GWh. However, the report reveals this framing is outdated. Once a model is deployed, inference—the continuous running of models to answer everyday user prompts—becomes the dominant cost, accounting for 80 to 90 per cent of total #AI energy use. ChatGPT alone is estimated to process around 2.5 billion prompts per day, translating to roughly 383 GWh of electricity per year for a single product. Offsetting associated carbon emissions would require 2.6 million tree seedlings grown for 10 years, enough trees to cover a land area the size of Manhattan. The water footprint is equivalent to the minimum annual domestic water needs of roughly 500,000 people in Sub-Saharan Africa, and the land footprint is equal to over 800 football fields."
Read more:
https://unu.edu/inweh/news/environmental-cost-of-AIs-Enrgy-use-carbon-water-and-land-footprints#AIBoom #Electricity #Hyperscale #BigTech #BigData #CarbonFootprint #EnvironmentalRacism #EnvironmentalDegradation #NoisePollution #LightPollution #WaterIsLife #AIAgents #BotTraffic #GreenSpaces #Farmland #Prairies #Woodland #TechGiants #ProtectNature #NoDatacenters #EnergyConsumption #USPol #WorldPol #Datacentres
#DatacenterMoratoriums #ArtificialIntelligence -
Press Release: Rising #Emissions, Depleting #Water and Vanishing #Land—UN Scientists: #AI Is Threatening #NaturalResources for Billions
By 2030, AI's water use will match the needs of 1.3 billion people while its power use triples that of 650 million, UN University investigation warns
Date Published
3 Jun 2026Excerpt: "Inference, efficiency, and the rebound effect
"Public discussion has largely focused on the energy required to train massive models. Training GPT-3 was estimated to require 1.3 gigawatt-hours (GWh) of electricity, while estimates suggest GPT-4 consumed between 50 and 70 GWh. However, the report reveals this framing is outdated. Once a model is deployed, inference—the continuous running of models to answer everyday user prompts—becomes the dominant cost, accounting for 80 to 90 per cent of total #AI energy use. ChatGPT alone is estimated to process around 2.5 billion prompts per day, translating to roughly 383 GWh of electricity per year for a single product. Offsetting associated carbon emissions would require 2.6 million tree seedlings grown for 10 years, enough trees to cover a land area the size of Manhattan. The water footprint is equivalent to the minimum annual domestic water needs of roughly 500,000 people in Sub-Saharan Africa, and the land footprint is equal to over 800 football fields."
Read more:
https://unu.edu/inweh/news/environmental-cost-of-AIs-Enrgy-use-carbon-water-and-land-footprints#AIBoom #Electricity #Hyperscale #BigTech #BigData #CarbonFootprint #EnvironmentalRacism #EnvironmentalDegradation #NoisePollution #LightPollution #WaterIsLife #AIAgents #BotTraffic #GreenSpaces #Farmland #Prairies #Woodland #TechGiants #ProtectNature #NoDatacenters #EnergyConsumption #USPol #WorldPol #Datacentres
#DatacenterMoratoriums #ArtificialIntelligence -
Press Release: Rising #Emissions, Depleting #Water and Vanishing #Land—UN Scientists: #AI Is Threatening #NaturalResources for Billions
By 2030, AI's water use will match the needs of 1.3 billion people while its power use triples that of 650 million, UN University investigation warns
Date Published
3 Jun 2026Excerpt: "Inference, efficiency, and the rebound effect
"Public discussion has largely focused on the energy required to train massive models. Training GPT-3 was estimated to require 1.3 gigawatt-hours (GWh) of electricity, while estimates suggest GPT-4 consumed between 50 and 70 GWh. However, the report reveals this framing is outdated. Once a model is deployed, inference—the continuous running of models to answer everyday user prompts—becomes the dominant cost, accounting for 80 to 90 per cent of total #AI energy use. ChatGPT alone is estimated to process around 2.5 billion prompts per day, translating to roughly 383 GWh of electricity per year for a single product. Offsetting associated carbon emissions would require 2.6 million tree seedlings grown for 10 years, enough trees to cover a land area the size of Manhattan. The water footprint is equivalent to the minimum annual domestic water needs of roughly 500,000 people in Sub-Saharan Africa, and the land footprint is equal to over 800 football fields."
Read more:
https://unu.edu/inweh/news/environmental-cost-of-AIs-Enrgy-use-carbon-water-and-land-footprints#AIBoom #Electricity #Hyperscale #BigTech #BigData #CarbonFootprint #EnvironmentalRacism #EnvironmentalDegradation #NoisePollution #LightPollution #WaterIsLife #AIAgents #BotTraffic #GreenSpaces #Farmland #Prairies #Woodland #TechGiants #ProtectNature #NoDatacenters #EnergyConsumption #USPol #WorldPol #Datacentres
#DatacenterMoratoriums #ArtificialIntelligence -
The #EnvironmentalCost of #ArtificialIntelligence: #Carbon, #Water, and #LandFootprints
#AI’s rapid growth drives huge energy, water, and land use, raising environmental and equity challenges across its global infrastructure.
Date Published 3 Jun 2026
UNU-INWEH Report: Aczel, M., Chamanara, S., Matin, M., Farsi, A., Marwala, T., Madani, K. (2026).
"This report, Environmental Cost of Artificial Intelligence: Carbon, Water and Land Footprints, by the #UnitedNationsUniversity Institute for Water, Environment and Health ( #UNU - #INWEH ) on its 30th anniversary, examines one of the most underexplored consequences of AI’s rapid expansion: the environmental footprints of the energy required to power it. As artificial intelligence becomes embedded in economies, public services, research, communication, and everyday life, it depends on a growing physical infrastructure of #datacenters, advanced #chips, #CoolingSystems, #ElectricityGrids, #WaterResources, land, and #CriticalMineral supply chains. The report shows that AI is not only a digital technology, but also a material system with measurable #EnvironmentalCosts.
"The report moves beyond a carbon-only lens by quantifying the carbon, water, and land footprints associated with the electricity used to train, deploy, and operate AI systems at scale. Its central finding is that AI’s environmental costs depend not only on how much electricity is used, but also on where that electricity is generated and which energy sources power it. Every kilowatt-hour used by AI carries carbon, water, and land implications, and these footprints do not always move in the same direction: low-carbon electricity is not automatically low-water or low-land. The report also shows that AI’s footprint is shaped by both major infrastructure trends, including the rapid growth of data centers, and everyday use patterns, including model choice, output length, modality, and the growing use of text, image, and video generation.
"Importantly, the report frames AI’s environmental footprint as a governance and justice challenge, not only a technical problem. The benefits of AI often flow across borders and sectors, while the environmental burdens of data center siting, electricity demand, water withdrawals, #LandUse, MineralExtraction, and #EWaste can be concentrated in specific communities and regions. To address these risks, the report calls for a responsible AI ecosystem grounded in transparency, efficiency by design, equity and #EnvironmentalJustice, lifecycle responsibility, global cooperation, and sustainable use. By making AI’s carbon, water, and land footprints visible and comparable, the report provides a practical basis for integrating AI into energy, climate, water, and land-use planning, ensuring that innovation advances without shifting environmental costs onto vulnerable communities."
Download PDF:
https://unu.edu/inweh/collection/environmental-cost-of-AIs-Enrgy-Use-Carbon-water-and-land-footprints#AIBoom #Electricity #Hyperscale #BigTech #BigData #CarbonFootprint #EnvironmentalRacism #EnvironmentalDegradation #NoisePollution #LightPollution #WaterIsLife #AIAgents #BotTraffic #GreenSpaces #Farmland #Prairies #Woodland #TechGiants #ProtectNature #NoDatacenters #EnergyConsumption #USPol #WorldPol #Datacentres
#DatacenterMoratoriums -
The #EnvironmentalCost of #ArtificialIntelligence: #Carbon, #Water, and #LandFootprints
#AI’s rapid growth drives huge energy, water, and land use, raising environmental and equity challenges across its global infrastructure.
Date Published 3 Jun 2026
UNU-INWEH Report: Aczel, M., Chamanara, S., Matin, M., Farsi, A., Marwala, T., Madani, K. (2026).
"This report, Environmental Cost of Artificial Intelligence: Carbon, Water and Land Footprints, by the #UnitedNationsUniversity Institute for Water, Environment and Health ( #UNU - #INWEH ) on its 30th anniversary, examines one of the most underexplored consequences of AI’s rapid expansion: the environmental footprints of the energy required to power it. As artificial intelligence becomes embedded in economies, public services, research, communication, and everyday life, it depends on a growing physical infrastructure of #datacenters, advanced #chips, #CoolingSystems, #ElectricityGrids, #WaterResources, land, and #CriticalMineral supply chains. The report shows that AI is not only a digital technology, but also a material system with measurable #EnvironmentalCosts.
"The report moves beyond a carbon-only lens by quantifying the carbon, water, and land footprints associated with the electricity used to train, deploy, and operate AI systems at scale. Its central finding is that AI’s environmental costs depend not only on how much electricity is used, but also on where that electricity is generated and which energy sources power it. Every kilowatt-hour used by AI carries carbon, water, and land implications, and these footprints do not always move in the same direction: low-carbon electricity is not automatically low-water or low-land. The report also shows that AI’s footprint is shaped by both major infrastructure trends, including the rapid growth of data centers, and everyday use patterns, including model choice, output length, modality, and the growing use of text, image, and video generation.
"Importantly, the report frames AI’s environmental footprint as a governance and justice challenge, not only a technical problem. The benefits of AI often flow across borders and sectors, while the environmental burdens of data center siting, electricity demand, water withdrawals, #LandUse, MineralExtraction, and #EWaste can be concentrated in specific communities and regions. To address these risks, the report calls for a responsible AI ecosystem grounded in transparency, efficiency by design, equity and #EnvironmentalJustice, lifecycle responsibility, global cooperation, and sustainable use. By making AI’s carbon, water, and land footprints visible and comparable, the report provides a practical basis for integrating AI into energy, climate, water, and land-use planning, ensuring that innovation advances without shifting environmental costs onto vulnerable communities."
Download PDF:
https://unu.edu/inweh/collection/environmental-cost-of-AIs-Enrgy-Use-Carbon-water-and-land-footprints#AIBoom #Electricity #Hyperscale #BigTech #BigData #CarbonFootprint #EnvironmentalRacism #EnvironmentalDegradation #NoisePollution #LightPollution #WaterIsLife #AIAgents #BotTraffic #GreenSpaces #Farmland #Prairies #Woodland #TechGiants #ProtectNature #NoDatacenters #EnergyConsumption #USPol #WorldPol #Datacentres
#DatacenterMoratoriums -
The #EnvironmentalCost of #ArtificialIntelligence: #Carbon, #Water, and #LandFootprints
#AI’s rapid growth drives huge energy, water, and land use, raising environmental and equity challenges across its global infrastructure.
Date Published 3 Jun 2026
UNU-INWEH Report: Aczel, M., Chamanara, S., Matin, M., Farsi, A., Marwala, T., Madani, K. (2026).
"This report, Environmental Cost of Artificial Intelligence: Carbon, Water and Land Footprints, by the #UnitedNationsUniversity Institute for Water, Environment and Health ( #UNU - #INWEH ) on its 30th anniversary, examines one of the most underexplored consequences of AI’s rapid expansion: the environmental footprints of the energy required to power it. As artificial intelligence becomes embedded in economies, public services, research, communication, and everyday life, it depends on a growing physical infrastructure of #datacenters, advanced #chips, #CoolingSystems, #ElectricityGrids, #WaterResources, land, and #CriticalMineral supply chains. The report shows that AI is not only a digital technology, but also a material system with measurable #EnvironmentalCosts.
"The report moves beyond a carbon-only lens by quantifying the carbon, water, and land footprints associated with the electricity used to train, deploy, and operate AI systems at scale. Its central finding is that AI’s environmental costs depend not only on how much electricity is used, but also on where that electricity is generated and which energy sources power it. Every kilowatt-hour used by AI carries carbon, water, and land implications, and these footprints do not always move in the same direction: low-carbon electricity is not automatically low-water or low-land. The report also shows that AI’s footprint is shaped by both major infrastructure trends, including the rapid growth of data centers, and everyday use patterns, including model choice, output length, modality, and the growing use of text, image, and video generation.
"Importantly, the report frames AI’s environmental footprint as a governance and justice challenge, not only a technical problem. The benefits of AI often flow across borders and sectors, while the environmental burdens of data center siting, electricity demand, water withdrawals, #LandUse, MineralExtraction, and #EWaste can be concentrated in specific communities and regions. To address these risks, the report calls for a responsible AI ecosystem grounded in transparency, efficiency by design, equity and #EnvironmentalJustice, lifecycle responsibility, global cooperation, and sustainable use. By making AI’s carbon, water, and land footprints visible and comparable, the report provides a practical basis for integrating AI into energy, climate, water, and land-use planning, ensuring that innovation advances without shifting environmental costs onto vulnerable communities."
Download PDF:
https://unu.edu/inweh/collection/environmental-cost-of-AIs-Enrgy-Use-Carbon-water-and-land-footprints#AIBoom #Electricity #Hyperscale #BigTech #BigData #CarbonFootprint #EnvironmentalRacism #EnvironmentalDegradation #NoisePollution #LightPollution #WaterIsLife #AIAgents #BotTraffic #GreenSpaces #Farmland #Prairies #Woodland #TechGiants #ProtectNature #NoDatacenters #EnergyConsumption #USPol #WorldPol #Datacentres
#DatacenterMoratoriums -
The #EnvironmentalCost of #ArtificialIntelligence: #Carbon, #Water, and #LandFootprints
#AI’s rapid growth drives huge energy, water, and land use, raising environmental and equity challenges across its global infrastructure.
Date Published 3 Jun 2026
UNU-INWEH Report: Aczel, M., Chamanara, S., Matin, M., Farsi, A., Marwala, T., Madani, K. (2026).
"This report, Environmental Cost of Artificial Intelligence: Carbon, Water and Land Footprints, by the #UnitedNationsUniversity Institute for Water, Environment and Health ( #UNU - #INWEH ) on its 30th anniversary, examines one of the most underexplored consequences of AI’s rapid expansion: the environmental footprints of the energy required to power it. As artificial intelligence becomes embedded in economies, public services, research, communication, and everyday life, it depends on a growing physical infrastructure of #datacenters, advanced #chips, #CoolingSystems, #ElectricityGrids, #WaterResources, land, and #CriticalMineral supply chains. The report shows that AI is not only a digital technology, but also a material system with measurable #EnvironmentalCosts.
"The report moves beyond a carbon-only lens by quantifying the carbon, water, and land footprints associated with the electricity used to train, deploy, and operate AI systems at scale. Its central finding is that AI’s environmental costs depend not only on how much electricity is used, but also on where that electricity is generated and which energy sources power it. Every kilowatt-hour used by AI carries carbon, water, and land implications, and these footprints do not always move in the same direction: low-carbon electricity is not automatically low-water or low-land. The report also shows that AI’s footprint is shaped by both major infrastructure trends, including the rapid growth of data centers, and everyday use patterns, including model choice, output length, modality, and the growing use of text, image, and video generation.
"Importantly, the report frames AI’s environmental footprint as a governance and justice challenge, not only a technical problem. The benefits of AI often flow across borders and sectors, while the environmental burdens of data center siting, electricity demand, water withdrawals, #LandUse, MineralExtraction, and #EWaste can be concentrated in specific communities and regions. To address these risks, the report calls for a responsible AI ecosystem grounded in transparency, efficiency by design, equity and #EnvironmentalJustice, lifecycle responsibility, global cooperation, and sustainable use. By making AI’s carbon, water, and land footprints visible and comparable, the report provides a practical basis for integrating AI into energy, climate, water, and land-use planning, ensuring that innovation advances without shifting environmental costs onto vulnerable communities."
Download PDF:
https://unu.edu/inweh/collection/environmental-cost-of-AIs-Enrgy-Use-Carbon-water-and-land-footprints#AIBoom #Electricity #Hyperscale #BigTech #BigData #CarbonFootprint #EnvironmentalRacism #EnvironmentalDegradation #NoisePollution #LightPollution #WaterIsLife #AIAgents #BotTraffic #GreenSpaces #Farmland #Prairies #Woodland #TechGiants #ProtectNature #NoDatacenters #EnergyConsumption #USPol #WorldPol #Datacentres
#DatacenterMoratoriums -
The #EnvironmentalCost of #ArtificialIntelligence: #Carbon, #Water, and #LandFootprints
#AI’s rapid growth drives huge energy, water, and land use, raising environmental and equity challenges across its global infrastructure.
Date Published 3 Jun 2026
UNU-INWEH Report: Aczel, M., Chamanara, S., Matin, M., Farsi, A., Marwala, T., Madani, K. (2026).
"This report, Environmental Cost of Artificial Intelligence: Carbon, Water and Land Footprints, by the #UnitedNationsUniversity Institute for Water, Environment and Health ( #UNU - #INWEH ) on its 30th anniversary, examines one of the most underexplored consequences of AI’s rapid expansion: the environmental footprints of the energy required to power it. As artificial intelligence becomes embedded in economies, public services, research, communication, and everyday life, it depends on a growing physical infrastructure of #datacenters, advanced #chips, #CoolingSystems, #ElectricityGrids, #WaterResources, land, and #CriticalMineral supply chains. The report shows that AI is not only a digital technology, but also a material system with measurable #EnvironmentalCosts.
"The report moves beyond a carbon-only lens by quantifying the carbon, water, and land footprints associated with the electricity used to train, deploy, and operate AI systems at scale. Its central finding is that AI’s environmental costs depend not only on how much electricity is used, but also on where that electricity is generated and which energy sources power it. Every kilowatt-hour used by AI carries carbon, water, and land implications, and these footprints do not always move in the same direction: low-carbon electricity is not automatically low-water or low-land. The report also shows that AI’s footprint is shaped by both major infrastructure trends, including the rapid growth of data centers, and everyday use patterns, including model choice, output length, modality, and the growing use of text, image, and video generation.
"Importantly, the report frames AI’s environmental footprint as a governance and justice challenge, not only a technical problem. The benefits of AI often flow across borders and sectors, while the environmental burdens of data center siting, electricity demand, water withdrawals, #LandUse, MineralExtraction, and #EWaste can be concentrated in specific communities and regions. To address these risks, the report calls for a responsible AI ecosystem grounded in transparency, efficiency by design, equity and #EnvironmentalJustice, lifecycle responsibility, global cooperation, and sustainable use. By making AI’s carbon, water, and land footprints visible and comparable, the report provides a practical basis for integrating AI into energy, climate, water, and land-use planning, ensuring that innovation advances without shifting environmental costs onto vulnerable communities."
Download PDF:
https://unu.edu/inweh/collection/environmental-cost-of-AIs-Enrgy-Use-Carbon-water-and-land-footprints#AIBoom #Electricity #Hyperscale #BigTech #BigData #CarbonFootprint #EnvironmentalRacism #EnvironmentalDegradation #NoisePollution #LightPollution #WaterIsLife #AIAgents #BotTraffic #GreenSpaces #Farmland #Prairies #Woodland #TechGiants #ProtectNature #NoDatacenters #EnergyConsumption #USPol #WorldPol #Datacentres
#DatacenterMoratoriums -
🤖 Oh, the #irony of "optimizing" algorithms to save a few nickels while burning through enough electricity to power a small nation. ⚡️ Let's all pretend this paper isn't just a roadmap to making AI slightly less ruinous on the way to the inevitable robot uprising. 🤡
https://arxiv.org/abs/2508.12631 #optimizingalgorithms #AIimpact #energyconsumption #robotuprising #HackerNews #ngated -
The Environmental Impact of 3D Printing: Can It Be Sustainable in the Future?
1,661 words, 9 minutes read time.
In recent years, 3D printing has captured the imagination of industries, innovators, and creators alike. Its potential to revolutionize manufacturing, medicine, architecture, and even art has made it a fascinating technological breakthrough. But as we dive deeper into this world of innovation, it’s crucial to assess the environmental impact of 3D printing. Is this cutting-edge technology sustainable, or does it come with hidden ecological costs? In this article, we will explore both the positive and negative environmental aspects of 3D printing, with a focus on its material usage, energy consumption, emissions, and future sustainability.
The rise of 3D printing has been nothing short of remarkable. The process, known as additive manufacturing, involves creating objects layer by layer, based on a digital model. Unlike traditional manufacturing, which often involves subtracting material from a larger block, 3D printing uses only the necessary amount of material, which suggests that it could reduce waste. However, a closer inspection of the environmental impact reveals complexities that go beyond the apparent efficiency of the process.
Material Usage and Waste: The Hidden Costs of 3D Printing
One of the key environmental advantages of 3D printing is its ability to reduce material waste. Traditional manufacturing methods like injection molding or CNC machining often result in significant amounts of discarded material. Since 3D printing only uses the material required to create a part or product, there is the potential for a reduction in waste. However, this doesn’t necessarily mean that 3D printing is entirely free from waste concerns.
The materials commonly used in 3D printing, particularly plastics such as PLA, ABS, and PETG, pose environmental challenges. Most of these materials are derived from petroleum, a non-renewable resource. While PLA (Polylactic Acid) is often touted as an eco-friendly alternative because it is derived from renewable plant resources like corn starch, it is still a plastic that does not break down easily in natural environments. The reality is that many 3D printers use plastics that are non-biodegradable and can contribute to long-term waste issues if not recycled properly.
Moreover, the nature of 3D printing can lead to material inefficiency in certain cases. Support structures, which are used to stabilize objects during printing, are often discarded after the print job is completed. These supports can account for a significant portion of the material used, and while they can be minimized with more advanced printing techniques, they still contribute to waste. Additionally, when a print fails, the material used is often wasted as the object is discarded, leading to further inefficiencies.
Energy Consumption: Is 3D Printing as Energy-Efficient as It Seems?
Another concern regarding the sustainability of 3D printing is the energy consumption associated with the process. While it’s true that 3D printing has the potential to be more energy-efficient than traditional manufacturing, this is not always the case. The energy required for the process depends on various factors, such as the type of 3D printer used, the material being printed, and the complexity of the object being created.
For example, industrial 3D printers, especially those used for metal printing or large-scale manufacturing, can consume significant amounts of energy. A study conducted by researchers at the University of Cambridge found that 3D printing can use more energy than traditional manufacturing in certain cases, particularly when printers are left running for long hours or when complex objects require prolonged processing times. This suggests that while the additive nature of 3D printing can reduce waste, it may not always be the most energy-efficient option, especially when considering the full lifecycle of the printing process.
However, it’s important to note that there are energy-efficient 3D printing technologies and practices emerging. New developments in energy-saving 3D printers, such as those that use less power or utilize alternative energy sources, are being introduced to reduce the environmental footprint. The shift towards solar-powered 3D printers, for example, offers promising potential for minimizing the energy burden of 3D printing.
Emissions and Pollution: Is 3D Printing Contributing to Air Pollution?
Another often-overlooked aspect of the environmental impact of 3D printing is the potential emissions that occur during the printing process. Certain materials, particularly plastics like ABS, release volatile organic compounds (VOCs) and ultrafine particles into the air when heated. These emissions can contribute to air pollution and pose health risks for those working in poorly ventilated spaces.
While the emissions from a typical 3D printer may not be as severe as those from industrial factories, they are still a concern in smaller or confined environments. Research has shown that the process of heating plastics to their melting point can release harmful chemicals into the air, including styrene, which is a potential carcinogen. This makes it essential for users of 3D printers, particularly in industrial settings, to ensure that proper ventilation systems are in place.
It’s worth noting, however, that there are emerging technologies aimed at reducing emissions. Filaments that are less prone to releasing VOCs are being developed, and air filtration systems for 3D printers are also becoming more common. As awareness of these environmental and health issues grows, it’s likely that the industry will continue to evolve toward cleaner, more sustainable solutions.
Environmental Benefits: A Glimmer of Hope
Despite the challenges, 3D printing does offer some undeniable environmental benefits. One of the most promising aspects of additive manufacturing is its ability to reduce material waste. Since 3D printers build objects layer by layer, only the precise amount of material needed for the object is used. This can lead to significant reductions in material waste compared to traditional manufacturing, which often requires cutting, molding, or casting materials from larger blocks.
In addition to reducing material waste, 3D printing allows for more efficient designs. The ability to create complex geometries and lightweight structures that are not possible with traditional manufacturing methods can reduce the overall amount of material needed. For example, in the aerospace industry, 3D printing is being used to create lighter parts, reducing the overall weight of aircraft and, consequently, improving fuel efficiency. The impact of such innovations could have significant environmental benefits, particularly in industries where weight and material usage are critical factors.
Furthermore, 3D printing can enable localized production, which helps reduce the carbon footprint associated with transportation. By producing goods closer to their point of consumption, companies can reduce the need for long-distance shipping and its associated environmental costs. This shift toward decentralized manufacturing is one of the ways in which 3D printing can contribute to a more sustainable future.
Case Studies and Real-World Applications: 3D Printing in Action
Several industries are already reaping the benefits of 3D printing while addressing environmental concerns. In the automotive sector, for instance, companies like Ford and BMW have adopted 3D printing for producing lightweight, energy-efficient car parts. This not only helps reduce material waste but also contributes to more fuel-efficient vehicles. By utilizing 3D printing to create parts that are optimized for strength and weight, manufacturers can significantly reduce the environmental impact of their products.
The construction industry has also explored 3D printing as a sustainable solution. Companies are using large-scale 3D printers to create buildings and homes using eco-friendly materials, such as recycled concrete or biodegradable plastics. 3D-printed homes are often faster to construct, more affordable, and have a smaller environmental footprint than traditional construction methods. For example, a 3D-printed house built by the startup ICON in Austin, Texas, was created using a specially designed concrete mix and completed in just 24 hours. These innovations highlight the potential for 3D printing to disrupt industries in ways that reduce environmental impact.
Looking Toward the Future: Advancements in Sustainability
While 3D printing may not be entirely sustainable yet, the future looks promising. Research into alternative, sustainable materials is already underway. Biodegradable filaments made from organic materials such as algae, hemp, and even food waste are being developed and tested. These innovations could help address the environmental challenges of plastic-based 3D printing, allowing for a future where the production of goods is both environmentally friendly and resource-efficient.
Additionally, the development of energy-efficient 3D printers is a key area of focus. By improving the energy efficiency of 3D printers, reducing energy consumption, and utilizing renewable energy sources like solar power, the environmental impact of 3D printing could be greatly minimized.
As 3D printing technology continues to evolve, it will likely become more sustainable. Increased recycling capabilities, better material science, and cleaner manufacturing practices all point toward a future where 3D printing can play a significant role in reducing waste, improving efficiency, and promoting sustainability.
Conclusion: Can 3D Printing Become Sustainable?
In conclusion, 3D printing presents both significant challenges and promising opportunities when it comes to environmental sustainability. While it does have a role in reducing material waste, creating efficient designs, and enabling localized production, it also faces hurdles related to energy consumption, emissions, and the environmental costs of materials.
However, the future of 3D printing looks bright. As innovations in materials, energy efficiency, and emissions reduction continue to emerge, 3D printing has the potential to become a cornerstone of sustainable manufacturing. By addressing these challenges head-on, we can unlock the full environmental benefits of 3D printing and ensure that it plays a positive role in the future of sustainable production.
D. Bryan King
Sources
- Cornish start-up lands big customers by recycling fishing nets – The Times
- Environmental Impact of 3D Printing: A Study by University of Cambridge – Cambridge University Press
- Why 3D Printing is Quickly Becoming More Energy-Efficient – Forbes
- The Environmental Impact of 3D Printing: An Overview – NIH
- The Future of 3D Printing in Construction – Architectural Digest
- How 3D Printing Could Revolutionize Manufacturing – BBC News
- Sustainability in 3D Printing: A Review of Current Challenges and Solutions – ScienceDirect
- Environmental Impact of Additive Manufacturing in Industry – Hindawi
Disclaimer:
The views and opinions expressed in this post are solely those of the author. The information provided is based on personal research, experience, and understanding of the subject matter at the time of writing. Readers should consult relevant experts or authorities for specific guidance related to their unique situations.
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The Bavarian Research Foundation is funding our new research alliance BayWater with 2 million euros. The aim is to reduce #waterdemand as well as costs and #energyconsumption in #industrialproduction processes: http://go.tum.de/486366
📷A.Heddergott
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Ethereum's Lifetime Energy Use Before the Merge Equaled Switzerland's for a Year - If Bitcoin’s energy consumption can be thought of as a skyscraper, Ethereum’s energy use ... - https://www.coindesk.com/tech/2023/04/26/ethereums-lifetime-energy-use-before-the-merge-equaled-switzerlands-for-a-year/?utm_medium=referral&utm_source=rss&utm_campaign=headlines #energyconsumption #technology #themerge #ethereum #news