US EditionUK Agencies Urge Residents to Delete Emails and Photos to Save Water
The Environment Agency urges mass deletion of old emails to reduce water use by data centers, while traditional water-saving methods remain more effective, with a 20% demand drop seen in Severn Trent area.
- The UK government declared a nationally significant water shortage and urged the public to delete old emails and photos to reduce water usage amid ongoing drought conditions.
- The government announced this following a prolonged dry period, with five areas in England officially declared in drought and six additional regions experiencing extended dry conditions during the most severe half-year drought recorded since 1976.
- Data centers use large amounts of water for cooling, but experts noted that deleting emails has minimal impact compared to overall data processing energy demands.
- Helen Wakeham, director of water at the Environment Agency, emphasized the serious nature of the situation nationwide and urged all individuals to contribute to easing the strain on water resources.
- The situation implies that water companies must fix leaks and that individuals should prioritize traditional water-saving methods, as deleting emails alone may not significantly save water.
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56 Articles
56 Articles
With an unusual appeal to the population, Great Britain wants to combat water scarcity in the country.
·Zürich, Switzerland
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The United Kingdom is experiencing one of the worst droughts in recent years, it advises to implement several measures to reduce water consumption.
·Madrid, Spain
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The Environmental Agency asks that people delete long-stored images and texts, because the data centers need water for cooling.
·Vienna, Austria
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England is currently experiencing the driest half of the year since 1976, with devastating consequences for nature and people. The Environmental Agency therefore shares a number of unusual measures to save water.
Coverage Details
Total News Sources56
Leaning Left10Leaning Right7Center7Last UpdatedBias Distribution42% Left
Bias Distribution
- 42% of the sources lean Left
42% Left
L 42%
C 29%
R 29%
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