The Hidden Environmental Cost of Data

An email instead of a letter, online shopping instead of driving to a mall, a video conference instead of an in-person meeting. Are these activities as green as we think, or do they hide an environmental footprint?

Data Pollution · Technology · Carbon Emissions · Energy · Climate Change ·

Data has become an integral part of our daily lives, helping us to make better decisions and to improve our quality of life. However, the increasing amount of data that we generate and process requires an enormous volume of energy, which has negative social, economic, and environmental impacts. 

Data processes are all over. From sending emails and video streaming to browsing cookies, our reliance on data is driving up energy consumption at an alarming rate. The good news is that there are ways to mitigate this impact.

Key Concepts

Environmental experts and organizations have been warning for some time about the polluting effects of technological production and waste. On one hand there’s the extraction of the materials and the energy used in the production itself, both frequently in situations of exploitation. On the other hand, there’s the early discarding of products due to planned obsolescence, and the subsequent contamination of technological waste that is often transferred to countries in the Global South with a considerable negative environmental and social impact. These processes produce what is known as direct emissions.

This type of pollution is easily recognizable, however, there are other kinds. The emissions from our daily data processes are not directly visible, and therefore make us less aware of the contamination they generate, both through the energy required by our electronic devices, and that necessary to power the data centers where all the information is stored. These are indirect emissions.

What direct and indirect emissions have in common is the unequal environmental impact (and the social one that goes hand in hand with it) they have, with the Global South always receiving the worst part.


CO2 from top websites cookies per year


CO2 from search queries per year & person (5 billion internet users)


ad related activities in top 350 sites (1 ad impression: 1gr emissions)


CO2 from the Bitcoin network per year

Our Reports in a nutshell

The Hidden Cost of Data

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The polluted world of personal data

Data pollution is the carbon footprint derived from data processes, from its generation, collection, processing, exchange, consumption, storage, etc. Concrete examples go from sending an email, to streaming a TV show, having  a video conference, etc.

The Information and Communication Technology (ICT) industry has been found to have a significant impact on the global carbon footprint, with estimates ranging from 2-3.9% of total emissions, and energy consumption of data centers is expected to continue to increase in the coming years. To add to this problem, there’s still no agreement on which method to adopt to measure the environmental impact of data flows and processes.

Data centers store all the digital information in massive facilities that need huge amounts of electricity to power them, and water to keep them cool (data centers with 15 MW of IT capacity can consume between 80 and 130 million gallons per year). They can have both positive impacts, like job creation and investment, but they also amount to  more than 2% of the world’s electricity consumption, and generate the same volume of carbon emissions as the global airline industry. To that, we need to add the waste they generate.  

There are some efforts being made to reduce the environmental impact of data centers, but overall, they need to become more sustainable in order to mitigate their negative impact on the environment.

The environmental impact of data centers

Lowering polluting data

There are mitigation measures to lower data pollution. One of them is data minimization, which consists of collecting only the minimum amount of personal data necessary to achieve a specific purpose. Apart from reducing pollution by reducing the amount of information stored, minimizing data can also improve the quality of data processing outcomes.

Other mitigation measures include green Machine Learning methods like AI modular blocks to simplify training processes, reducing the amount of time and energy required; spam filtering to reduce the quantity of emails received saving up to 135 TWh of electricity per year; and PoS replacing PoW for Crypto pollution. Regarding data centers, using renewable energy sources and implementing energy-efficient technologies are some of the solutions that are beginning to be implemented.

Accounting for the Environmental Impact of Data Processes

History of environmental impact taxation in the US and Europe.

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Data Centers as Taxable Property

A feasibility report on taxation schemes on the amount of data kept in data centers.

Read here

Data Brokerage Tax

A feasibility report on applying a sales tax to online transations of personal data.

Read here

The environmental cost of the vast amount of data processed everyday needs to be acknowledged.

When we agree on how to measure data pollution, we will be able to find solutions to make technology a true green option that doesn’t contribute to climate change, but helps us fight against it.