AI carbon footprint

From Nature Nov 2025 sustainability

The rapidly increasing demand for generative artificial intelligence (AI) models requires extensive server installation with sustainability implications in terms of the compound energy–water–climate impacts. Here we show that the deployment of AI servers across the United States could generate an annual water footprint ranging from 731 to 1,125 million m3 and additional annual carbon emissions from 24 to 44 Mt CO2-equivalent between 2024 and 2030, depending on the scale of expansion. Other factors, such as industry efficiency initiatives, grid decarbonization rates and the spatial distribution of server locations within the United States, drive deep uncertainties in the estimated water and carbon footprints. We show that the AI server industry is unlikely to meet its net-zero aspirations by 2030 without substantial reliance on highly uncertain carbon offset and water restoration mechanisms. Although best practices may reduce emissions and water footprints by up to 73% and 86%, respectively, their effectiveness is constrained by current energy infrastructure limitations. These findings underscore the urgency of accelerating the energy transition and point to the need for AI companies to harness the clean energy potential of Midwestern states. Coordinating efforts of private actors and regulatory interventions would ensure the competitive and sustainable development of the AI sector.

Devera AI

Global data centre electricity use is expected to reach 945 TWh by 2030, up from 415 TWh in 2024. A large share of this growth comes from the rising demand for AI inference, especially from generative models. Estimates suggest that AI alone may account for 652 TWh (69%) by 2030, nearly an 80-fold jump from 2024 levels.

Earth911

Only two companies have disclosed specific per-query energy figures. In June 2025, OpenAI CEO Sam Altman stated that an average ChatGPT query uses about 0.34 watt-hours of electricity. In August 2025, Google published a detailed methodology showing the median Gemini text prompt consumes about 0.24 watt-hours and produces 0.03 grams of CO₂e. No other company in this guide has published comparable data.

Major consumption is on one time training, ballpark figure ~ 0.5 to 1 million USD, ~ 1 million kwh

Reference

Earth911

Jason riddell ( data may be outdated)

留言

這個網誌中的熱門文章

CMOS sensor trends and astrophotography, from amateur astronomers perspective

Nowadays, even in low light conditions, digital camera can quality pictures with higher ISO, noise and hot pixels have been gradually reduced. Sony has introduced back illumination process for consumer market. Sony BSI sensors evolved from Exmor to now Exmor RS( stacked) technology. This stacked technology allows further chip size reduction, which has strong demands in smartphone camera market. Digital astrophotography is also benefited from such advances, utilising Back Side Illumination technology Exmor: Within the CMOS sensor, it outputs low-noise digital signals by "on-chip column AD conversion" and "dual noise reduction" to suppress noise in the first half of the process In low light conditions, when a wide aperture is desirable to collect as much light as possible. At apertures wider than f/2.0, back-illuminated Exmor R sensors are significantly more efficient at collecting light than conventional, front-illuminated sensor...

閱讀完整內容

ultrafast rendezvous to ISS

14 Oct 2020, being the first to use a new “ultrafast” rendezvous” scheme with the ISS. Following a flawless ascent to the correct orbit, Soyuz 2 .1a , Soyuz MS-17 caught up with the orbiting laboratory in only two orbits (three hours), halving the time it takes for crew to get to the Station. The three space travelers of the Soyuz MS-17 mission launched on a six-month mission the International Space Station. previous 3/4 orbit rendezvous: Soyuz MS-16 4 orbit rendezvous A three-orbit profile was deemed possible without major flight design changes after inauguration of the Soyuz 2-1A rocket that provides a much higher orbit injection accuracy than its predecessors and would allow the two correction maneuvers on Orbit #2 to be eliminated while the Automated Rendezvous Phase would still remain untouched. The deletion of the Orbit #2 maneuvers was expected to slightly tighten the already restrictive phase angle window from and upper limit of 30-35° to 25-28°...

閱讀完整內容

Scythians 斯泰基塞種西古提人

900 BC - 200 AD British museum Tomb of scythe prince, Buktarma valley, 1200 masl, Google map Herodotus 絲路上的帝國 Biblegeography 哥羅西書 3：11 在此並不分希利尼人、猶太人、受割禮的、未受割禮的、化外人、西古提人、為奴的、自主的．惟有基督是包括一切、又住在各人之內。塞種塞迦 saka 史記漢書西域傳：塞種 ctext 昔匈奴破大月氏，大月氏西君大夏，而塞王南君罽賓。塞種分散，往往為數國。自疏勒以西北，休循、捐毒之屬，皆故塞種也。匈奴列傳 Ctext ：塞王《史記》在《大宛列傳》與《匈奴列傳》中，詳細記錄了中亞至天山一帶的塞種（塞王、塞地）狀況。例如，文中記載了月氏西破走塞王，導致塞人南遷越過懸度（今帕米爾高原及克什米爾一帶） Baike Genetic history Genetics Nih griffin ? Scytho-Siberian world 塞迦 saka wiki Disappeared? Sarmatians （薩爾馬泰，奄蔡史記 , Aorsi ）and goths YouTube

閱讀完整內容

Hello!! It's Joseph

搜尋此網誌