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#landuse — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #landuse, aggregated by home.social.

  1. "Data centers represent 27% of development sites in the U.S. this year. It’s the second-highest category after apartment buildings..."

    Land prices are up 79% from last year.

    And "home builders cannot bid in that market, because a builder’s land budget is capped by what home buyers can afford. A data center operator faces no such constraint. The result is ... no homes at all."

    #USA #AI #DataCenters #LandUse #housing #farming
    ---
    cnbc.com/2026/09/06/ai-data-ce

  2. "Data centers represent 27% of development sites in the U.S. this year. It’s the second-highest category after apartment buildings..."

    Land prices are up 79% from last year.

    And "home builders cannot bid in that market, because a builder’s land budget is capped by what home buyers can afford. A data center operator faces no such constraint. The result is ... no homes at all."


    ---
    cnbc.com/2026/09/06/ai-data-ce

  3. "Data centers represent 27% of development sites in the U.S. this year. It’s the second-highest category after apartment buildings..."

    Land prices are up 79% from last year.

    And "home builders cannot bid in that market, because a builder’s land budget is capped by what home buyers can afford. A data center operator faces no such constraint. The result is ... no homes at all."

    #USA #AI #DataCenters #LandUse #housing #farming
    ---
    cnbc.com/2026/09/06/ai-data-ce

  4. "Data centers represent 27% of development sites in the U.S. this year. It’s the second-highest category after apartment buildings..."

    Land prices are up 79% from last year.

    And "home builders cannot bid in that market, because a builder’s land budget is capped by what home buyers can afford. A data center operator faces no such constraint. The result is ... no homes at all."

    #USA #AI #DataCenters #LandUse #housing #farming
    ---
    cnbc.com/2026/09/06/ai-data-ce

  5. "Data centers represent 27% of development sites in the U.S. this year. It’s the second-highest category after apartment buildings..."

    Land prices are up 79% from last year.

    And "home builders cannot bid in that market, because a builder’s land budget is capped by what home buyers can afford. A data center operator faces no such constraint. The result is ... no homes at all."

    #USA #AI #DataCenters #LandUse #housing #farming
    ---
    cnbc.com/2026/09/06/ai-data-ce

  6. The Radiative Effects Of Water Vapour From Terrestrial Evapotranspiration
    --
    doi.org/10.1088/1748-9326/adde <-- shared paper/letter
    --
    zenodo.org/records/15413219 | zenodo.org/records/15416936 <-- shared open data, for “Model information and output for "The radiative effects…” ”
    --
    doi.org/10.1007/s11269-025-041 <-- shared paper
    --
    H/T @jan Umsonst | Earth System Nerd
    “Water vapour accounts for roughly 50% of the modern greenhouse effect. Over continental regions, evapotranspiration (ET) is often limited by water availability. In this study, [the authors] spatially quantify how much of the total atmospheric water vapour evaporated most recently from land and calculate the relative contribution of that water vapour to the atmospheric radiative budget. Using a combination of tracer-enabled Earth system model simulations and radiative transfer calculations, [they were] able to explicitly quantify the 3D distribution of terrestrial vs. oceanic water vapour, and the spatial contribution of each to the surface and top of atmosphere radiative budgets. [They found] that over many continental regions, more than half of the total column-integrated water vapour originates from land ET, and that this vapour contributes up to 30 W/m² of longwave radiation into the surface in the annual mean (about 10% of the total). Understanding how terrestrial ET impacts the base-state of water vapour distribution and the water vapour greenhouse effect is critical to understanding how and where changes in terrestrial ET, driven by climate change, land use, etc, will modify the radiative properties of the atmosphere and thus the climate system…”
    #water #hydrology #greehouseeffect #highperformancecomputing #HPC #evapotranspiration #Radiative #WaterVapour #spatial #spatialanalysis #spatiotemporal #atmosphere #model #modeling #earthsystemmodelling #terrestrial #oceanic #vapour #climatechange #landuse #changes #climatesystem

  7. Adherence to an adapted Planetary Health Diet (more fruits & #legumes; less #dairy, red #meat, animal fats & added #sugar) in China was linked to reduced GHG #emissions, water use & #landuse, as well as lower risk of all-cause mortality: doi.org/10.1007/s003... #environment #health #footprint

  8. #Mining sub-Saharan Africa is expanding rapidly. This poses a key threat to tropical forests.

    "For every hectare of direct deforestation due to the mine footprint, mining triggers, on average, 34 hectares of additional offsite loss within five years through ancillary activities, including agriculture and settlements. Mines extracting cobalt and copper—key energy transition minerals—caused the highest amount of additional deforestation."

    Morton et al. (2026). "Mining triggers extensive additional deforestation in sub-Saharan Africa" doi.org/10.1038/s41586-026-105 🧩 🧵

    #extraction #landscape #pollution #cobalt #copper #gold #climateChange #rivers #deforestation #soil #carbon #causality #land #footprint #forests #landLoss #landUse #Africa #Congo #DRC #Centrafrique #Zambia #ZA #SouthAfrica

  9. 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:
    unu.edu/inweh/collection/envir

    #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