What Happened
A Reddit user’s question about data center heat production has sparked widespread discussion about the environmental costs of our digital infrastructure. The query, posted on the popular “Explain Like I’m Five” forum, asks fundamental questions about server temperatures, cooling alternatives, and potential ways to reuse waste heat from data centers.
The discussion comes as major tech companies face increasing scrutiny over their water consumption. Google’s data centers alone used 5.6 billion gallons of water in 2022, while Microsoft consumed 6.4 billion gallons - equivalent to the annual water usage of several mid-sized cities.
Why It Matters
Data center cooling represents one of the fastest-growing sources of industrial water consumption in the United States. As artificial intelligence and cloud computing expand, this demand is accelerating rapidly. ChatGPT alone requires roughly 500 milliliters of water for every 5-50 questions answered, according to researchers at University of California, Riverside.
The heat generation is substantial: modern servers operate optimally at 68-72°F (20-22°C), but without cooling would quickly reach 175-200°F (79-93°C), causing permanent damage within minutes. A single rack of servers can generate 10-50 kilowatts of heat - equivalent to 35-175 household space heaters running continuously.
This cooling challenge affects communities differently. Data centers often locate in areas with abundant water supplies and cheap electricity, sometimes straining local resources. In drought-prone regions like Arizona and Nevada, new data center construction has faced increasing opposition from residents and environmental groups.
Background
The cooling crisis stems from fundamental physics: computer processors convert nearly all their electrical energy into heat. As chips become more powerful and data centers pack more servers into smaller spaces, heat density has increased exponentially.
Traditional air conditioning proved inadequate for modern data centers, leading to sophisticated liquid cooling systems. These typically use chilled water circulated through cooling plates or immersion tanks, then cooled again using massive chillers that require additional water for heat rejection.
The Reddit user’s questions about alternatives reflect real engineering challenges the industry faces:
Salt water cooling: While seawater contains abundant cooling capacity, its corrosive properties damage equipment. Some coastal facilities use seawater for heat rejection in secondary loops, but direct contact with servers remains impractical.
Heat exchangers: Many facilities already use this approach, circulating clean coolant through servers while rejecting heat to external water sources. However, this still requires substantial water volumes for the external loop.
Waste heat recovery: The low temperature of data center waste heat (typically 80-120°F) makes electricity generation inefficient. However, some facilities provide district heating for nearby buildings or greenhouse operations.
What’s Next
The industry is pursuing multiple solutions to reduce water consumption and environmental impact:
Advanced cooling technologies: Immersion cooling using specialized fluids can reduce water usage by up to 95%. Companies like Microsoft are testing underwater data centers, while others experiment with direct air cooling in cold climates.
Heat reuse initiatives: New projects are emerging to capture and redistribute waste heat. In Finland, data centers heat residential buildings. In the Netherlands, greenhouse operations use data center waste heat for crop production.
Geographic strategies: Companies are increasingly locating facilities in naturally cool climates like Iceland, Norway, and northern Canada, reducing cooling energy requirements.
Regulatory pressure: Several states are considering legislation requiring data centers to report water usage and explore alternatives. The European Union is developing similar requirements.
Tech giants are also investing heavily in renewable energy and more efficient chip designs. Google reports improving its data center energy efficiency by 50% over the past five years, while Amazon Web Services aims for water-positive operations by 2030.
However, the explosive growth of AI and machine learning may outpace these efficiency gains. Training large language models requires enormous computational power, and each improvement in AI capability typically demands exponentially more processing - and cooling.