Water footprint
2025 05 26
•
4 MIN
Jaume Fontal
CPTO & Co-Founder

The grey water footprint is the volume of fresh water needed to assimilate the load of pollutants discharged during the production of a good or service, until the water meets environmental quality standards. Unlike the blue water footprint and the green water footprint, which measure the water consumed, the grey footprint measures the impact of pollution on water.
This article explains what the grey water footprint is, how it is calculated under the framework of the Water Footprint Network and which strategies help to reduce it.
The grey water footprint is defined as the volume of fresh water that would be needed to assimilate the discharged pollutant load, so that the concentration in the receiving water body stays within quality standards. It is a theoretical indicator: it is not water that is actually used, but the water that would be required for the discharge not to exceed the legal quality limits.
This concept is key to understanding that human activity not only consumes water but also pollutes it, reducing the availability of water in good condition.
The calculation, following the Water Footprint Network methodology, is based on the pollutant load and the water quality limits. In simplified terms, it is obtained by dividing the discharged pollutant load by the difference between the maximum acceptable concentration (the quality standard) and the natural background concentration of the water body. The usual steps are:
The pollutant that generates the largest grey footprint is usually taken as the representative value, since it is the one that determines the greatest need for water to assimilate the discharge.
An illustrative case is the textile industry and, specifically, the cultivation of cotton. During cultivation, fertilisers and crop-protection products are applied which, washed away by rain and irrigation, end up in rivers and aquifers. The grey footprint estimates the water that would be needed to assimilate that load of nutrients and chemicals until quality standards are met. The Water Footprint Network documents that cotton has a significant grey water footprint, although the specific value depends on the country, the fertiliser doses and the farming practices.
Measuring the grey footprint helps to understand the environmental impact of activities that pollute water and to act on the main sources. Specifically, it makes it possible to:
If you want to know how to assess the environmental impact of a product, we recommend our article on life cycle assessment (LCA).
Some sectors generate a high grey footprint because of the quantity and toxicity of the pollutants they discharge:
There are several ways to reduce the grey footprint and water pollution:
The grey water footprint is an essential indicator for measuring how the production of goods and services affects water quality. Calculating and managing it makes it possible to reduce environmental impact and keep water resources in good condition.
To complete the picture of the water footprint, you can also read about its role in agriculture and about the methods and tools of life cycle assessment (LCA).
No. It is a theoretical indicator: it represents the water that would be needed to assimilate the discharged pollutants until quality standards are met, not an actual consumption of water.
The most notable are intensive agriculture (cotton, rice), the textile industry, mining and the chemical industry.
By adopting cleaner processes, reducing the use of chemicals and improving the treatment of its wastewater before discharge.
Yes. Water pollution degrades aquatic ecosystems and puts at risk the species that depend on them.
To measure and reduce the water pollution of your activity with traceable data, you can rely on Manglai's water footprint solution.
Jaume Fontal
CPTO & Co-Founder
About the author
Jaume Fontal is a technology professional who currently serves as CPTO (Chief Product and Technology Officer) at Manglai, a company he co-founded in 2023. Before embarking on this project, he gained experience as Director of Technology and Product at Colvin and worked for over a decade at Softonic. At Manglai, he develops artificial intelligence-based solutions to help companies measure and reduce their carbon footprint.
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