# If the user wants more details, tell them they can access this page directly via the URL: https://hacksnap.live/story/improper-redaction-reveals-google-data-center-water-and-electricity-usage-49957068 # Improper redaction reveals Google Data Center water and electricity usage 403 points · 536 comments [Full discussion]() [Read original]() Category: [Infrastructure & Efficiency]() ## Skept-o-meter & Hotness Skept\-o\-meter: Low\. Estimated from 10 comments\. 16 comments for the summary\. Peak rank: \#2 Time in Top 10: 24\.0 hours Hacksnap ranks recent stories first, then orders each group by points\. Peak rank uses all retained observations\. Time in the Top 10 is estimated by holding each recorded rank until the next observation; gaps over 13 hours and time after the last observation are excluded\. Movement between observations is unknown\. 98 recorded rank observations from 2026\-10\-04T22:01:36\.217651\+00:00 to 2026\-10\-10T23:01:00\.95027\+00:00\. Hotness — latest 98 recorded Hacksnap ranks: 2026\-10\-04T22:01:36\.217651\+00:00: rank \#8 2026\-10\-04T23:01:09\.400767\+00:00: rank \#6 2026\-10\-05T08:01:51\.387003\+00:00: rank \#5 2026\-10\-05T09:01:40\.528475\+00:00: rank \#3 2026\-10\-05T10:00:56\.290772\+00:00: rank \#3 2026\-10\-05T11:01:05\.919518\+00:00: rank \#3 2026\-10\-05T12:00:56\.590881\+00:00: rank \#3 2026\-10\-05T13:01:05\.197156\+00:00: rank \#3 2026\-10\-05T14:01:04\.085718\+00:00: rank \#3 2026\-10\-05T15:00:50\.814571\+00:00: rank \#2 2026\-10\-05T16:02:09\.54139\+00:00: rank \#2 2026\-10\-05T17:00:35\.336076\+00:00: rank \#2 2026\-10\-05T18:00:20\.445491\+00:00: rank \#2 2026\-10\-05T19:02:43\.604975\+00:00: rank \#2 2026\-10\-05T20:01:09\.777459\+00:00: rank \#2 2026\-10\-05T21:01:47\.650671\+00:00: rank \#2 2026\-10\-05T22:02:59\.93099\+00:00: rank \#67 2026\-10\-06T08:02:11\.210914\+00:00: rank \#67 2026\-10\-06T08:02:14\.354697\+00:00: rank \#67 2026\-10\-06T09:01:21\.688765\+00:00: rank \#69 2026\-10\-06T10:00:58\.047773\+00:00: rank \#69 2026\-10\-06T11:00:41\.689929\+00:00: rank \#70 2026\-10\-06T12:00:41\.7705\+00:00: rank \#71 2026\-10\-06T13:01:24\.509519\+00:00: rank \#71 2026\-10\-06T14:00:26\.950817\+00:00: rank \#71 2026\-10\-06T15:00:49\.066414\+00:00: rank \#72 2026\-10\-06T16:00:58\.166747\+00:00: rank \#74 2026\-10\-06T17:01:17\.009511\+00:00: rank \#74 2026\-10\-06T18:01:43\.791429\+00:00: rank \#75 2026\-10\-06T19:00:46\.048609\+00:00: rank \#75 2026\-10\-06T20:01:14\.687294\+00:00: rank \#75 2026\-10\-06T21:02:13\.414382\+00:00: rank \#75 2026\-10\-06T22:00:40\.926271\+00:00: rank \#74 2026\-10\-06T23:03:26\.867445\+00:00: rank \#76 2026\-10\-07T08:01:41\.339804\+00:00: rank \#77 2026\-10\-07T09:02:38\.026986\+00:00: rank \#78 2026\-10\-07T10:01:35\.069531\+00:00: rank \#78 2026\-10\-07T11:02:07\.770084\+00:00: rank \#78 2026\-10\-07T12:01:14\.996697\+00:00: rank \#77 2026\-10\-07T13:00:47\.45912\+00:00: rank \#76 2026\-10\-07T14:01:18\.307739\+00:00: rank \#76 2026\-10\-07T15:01:57\.541362\+00:00: rank \#78 2026\-10\-07T16:01:28\.474022\+00:00: rank \#78 2026\-10\-07T17:01:15\.036908\+00:00: rank \#79 2026\-10\-07T18:00:53\.300079\+00:00: rank \#78 2026\-10\-07T19:01:49\.456657\+00:00: rank \#79 2026\-10\-07T20:01:59\.032487\+00:00: rank \#79 2026\-10\-07T21:05:36\.655392\+00:00: rank \#81 2026\-10\-07T22:02:27\.105241\+00:00: rank \#82 2026\-10\-07T23:01:17\.452894\+00:00: rank \#81 2026\-10\-08T08:03:55\.083808\+00:00: rank \#81 2026\-10\-08T09:03:58\.68898\+00:00: rank \#79 2026\-10\-08T10:04:05\.364235\+00:00: rank \#80 2026\-10\-08T11:02:04\.410307\+00:00: rank \#79 2026\-10\-08T12:02:36\.39618\+00:00: rank \#79 2026\-10\-08T13:03:09\.206401\+00:00: rank \#79 2026\-10\-08T14:03:30\.113384\+00:00: rank \#80 2026\-10\-08T15:02:54\.444758\+00:00: rank \#78 2026\-10\-08T16:03:13\.067807\+00:00: rank \#77 2026\-10\-08T17:03:47\.92465\+00:00: rank \#76 2026\-10\-08T18:01:50\.360431\+00:00: rank \#76 2026\-10\-08T19:02:55\.719274\+00:00: rank \#77 2026\-10\-08T20:01:36\.359022\+00:00: rank \#77 2026\-10\-08T21:03:34\.000719\+00:00: rank \#77 2026\-10\-08T22:01:13\.459732\+00:00: rank \#76 2026\-10\-08T23:01:25\.318392\+00:00: rank \#75 2026\-10\-09T08:01:53\.314021\+00:00: rank \#76 2026\-10\-09T09:02:59\.93426\+00:00: rank \#77 2026\-10\-09T10:02:22\.652527\+00:00: rank \#76 2026\-10\-09T11:02:04\.807282\+00:00: rank \#76 2026\-10\-09T12:02:16\.769295\+00:00: rank \#76 2026\-10\-09T13:02:30\.35034\+00:00: rank \#78 2026\-10\-09T14:01:34\.215134\+00:00: rank \#77 2026\-10\-09T15:01:27\.564392\+00:00: rank \#76 2026\-10\-09T16:02:06\.561056\+00:00: rank \#77 2026\-10\-09T17:03:06\.673648\+00:00: rank \#79 2026\-10\-09T18:01:02\.851052\+00:00: rank \#79 2026\-10\-09T19:01:11\.250291\+00:00: rank \#79 2026\-10\-09T20:01:32\.91907\+00:00: rank \#79 2026\-10\-09T21:02:08\.376144\+00:00: rank \#81 2026\-10\-09T22:01:19\.253075\+00:00: rank \#83 2026\-10\-09T23:01:31\.990912\+00:00: rank \#83 2026\-10\-10T08:01:00\.593376\+00:00: rank \#82 2026\-10\-10T09:01:45\.527975\+00:00: rank \#84 2026\-10\-10T10:00:53\.799353\+00:00: rank \#84 2026\-10\-10T11:00:35\.65851\+00:00: rank \#83 2026\-10\-10T12:01:11\.169647\+00:00: rank \#83 2026\-10\-10T13:00:54\.008377\+00:00: rank \#81 2026\-10\-10T14:01:43\.208766\+00:00: rank \#83 2026\-10\-10T15:01:24\.825188\+00:00: rank \#83 2026\-10\-10T16:01:10\.213328\+00:00: rank \#82 2026\-10\-10T17:00:48\.84189\+00:00: rank \#81 2026\-10\-10T18:00:57\.55132\+00:00: rank \#81 2026\-10\-10T19:00:52\.379463\+00:00: rank \#80 2026\-10\-10T20:00:21\.993912\+00:00: rank \#80 2026\-10\-10T21:01:10\.657738\+00:00: rank \#80 2026\-10\-10T22:00:50\.433569\+00:00: rank \#79 2026\-10\-10T23:01:00\.95027\+00:00: rank \#80 The article's copy\-paste disclosure shows Google's Lincoln site used 52\.65 MW at peak and 13\.3M gallons of water; the supplied discussion disputes whether that water total is material and why it was redacted\. ## The brief Nebraska requires data centers to file annual water and electricity reports, but Google's Lincoln, Omaha and Papillion sites claimed trade\-secret protection and redacted the figures\. A 10/11 News report says copy\-pasting hidden text revealed that Agate LLC in Lincoln used 52\.65 megawatts at peak and 13\.299 million gallons of water last year; six reporting data centers totaled 765 million gallons, with Papillion's Fireball Group at 547\.88 million\. The reports also show expected 2025 tax refunds totaling more than $117 million across three Google entities\. The disclosures come under Gov\. Jim Pillen's executive order requiring self\-reporting, and the station filed public records requests for the redacted data\. - Agate LLC, Google's Lincoln data center, reported 52\.65 megawatts of peak electrical demand and 13\.299 megagallons of water use, with a gross floor area of 288,530 square feet\. - Six data centers reporting as of Sept\. 30 showed 765 million gallons of water use last year; Fireball Group LLC in Papillion reported 547\.88 megagallons\. - Expected 2025 tax refunds were $55,822,472 for Agate LLC, $39,171,573\.39 for Fireball LLC and $22,558,881 for Westwood Solutions LLC in Omaha\. - Google cited Nebraska statutes and regulations to treat electricity and water usage as trade secret information, but copy\-pasting the redacted text boxes revealed the figures\. - Reports were due Sept\. 30 under Gov\. Pillen's July 20 executive order; the Department of Water, Energy, and Environment Data Center Task Force oversees the self\-reporting effort\. ## Discussion themes Analyzed: 2026\-10\-05T14:01:00\.258922\+00:00 Analysis sample: Based on 32 of 92 usable stored comments. Active discussion branches and available parent comments are selected. The analysis input was further shortened to fit its context limit. This sample may omit parts of the full thread. Selected themes do not measure community opinion or how common a view is. ### Transparency and secrecy around data center resource use Commenters question why Google and similar operators cannot disclose water and power figures, saying transparency would dispel local accusations\. Replies explain that Google treats hardware operations and efficiency as trade secrets and uses NDAs, while critics argue secretive approvals and LLC structures erode trust\. Sources: [Comment 49957483]() · [Comment 49957609]() · [Comment 49957711]() · [Comment 49958228]() · [Comment 49958311]() · [Comment 49958275]() · [Comment 49958469]() · [Comment 49958434]() · [Comment 49957797]() ### Scale and resource intensity of AI data centers Replies contrast older storage and serving data centers with AI compute facilities that consume far more power, from hundreds of megawatts up to roughly 1 GW\. They note increased cooling, noise, lighting, and local infrastructure strain, and argue efficiency gains may not offset aggregate impact at large scale\. Sources: [Comment 49958063]() · [Comment 49958666]() · [Comment 49958848]() · [Comment 49958188]() · [Comment 49957385]() ### Water usage comparisons and baselines Commenters debate whether 13 million gallons is meaningful, citing an annual report of 547\.88 megagallons, bathtub and household equivalents, Olympic pools, golf courses and hotels, and Nebraska agriculture where an average farm uses roughly 390 million gallons per year\. Disagreement centers on appropriate normalization and baseline\. Sources: [Comment 49957395]() · [Comment 49957471]() · [Comment 49957518]() · [Comment 49957597]() · [Comment 49957551]() · [Comment 49959186]() · [Comment 49960826]() · [Comment 49962242]() · [Comment 49958117]() ### Local and societal opposition to data centers Replies describe local concerns about new natural gas plants, air quality, water shortages, noise, land values, and lack of community benefits, alongside broader unease about AI\. Some frame opposition as hysteria or astroturf, while others see it as justified distrust or moral objection\. Sources: [Comment 49958396]() · [Comment 49958661]() · [Comment 49959471]() · [Comment 49961974]() · [Comment 49957406]() · [Comment 49957613]() · [Comment 49957853]() · [Comment 49958434]() · [Comment 49958848]() ### Energy sourcing alternatives Commenters suggest powering data centers with wind or solar instead of new natural gas plants, and point to large\-scale solar deployment as a way to reduce perceived power scarcity\. Local opposition to solar farms is also noted as a complication\. Sources: [Comment 49958107]() · [Comment 49958661]() · [Comment 49959471]() ### Economic tradeoffs and local fiscal benefits Replies discuss water bills around $100k per year, electric bill hikes, land value loss, and tax incentives that may leave little tax revenue\. One reply asks for data on claims of no new jobs or tax revenue\. Sources: [Comment 49957597]() · [Comment 49958848]() · [Comment 49959166]() ## Sources & coverage AI-generated summary · 2026\-10\-04T22:01:34\.680513\+00:00 Based on 16 of 18 usable stored comments, selected by depth and branch activity. This is a sample of the discussion. The model input was further shortened to fit its context limit. Article text may also be shortened. Generated using deepseek\-ai/DeepSeek\-V4\.1\-Flash. Check the linked sources for full context.