UsesLevel 4 of 6 occupation or activityOccupation or activity, level 4 of 6Used to calculate 4 entries, level 6Calculated with 10 entries, levels 1 and 3Database structure 
6Territories
5Organisations
3Uses
2Machine operations
1Calculation factorsSecondary school pupil, 1 year
A school year of work for a lower or upper secondary school pupil who uses AI for homework: about 54 web searches with AI, 22 conversations of 10 exchanges, 90 quick questions, and 6 other tasks. Projet Celsius estimate.
- Search accounts for 49% of emissions: "Web search with AI" weighs as much as 9.2 quick questions.
- About 300 requests to AI over the year, or 1.7 per working day.
- 3.8 times lower than the AI footprint of an office employee, for the same use.
- An estimate: the frequencies and the share done with AI are our assumptions.
Sentence to citeSecondary school pupil, 1 year, Projet Celsius estimate: 150 gCO2e per pupil per year, for 340 Wh of electricity, servers worldwide (458 gCO2e/kWh).
How the calculation is built
A school year of work for a lower or upper secondary school pupil who uses AI for homework: exercises, concepts to understand, essays, presentations, research. The frequencies are assumptions based on 36 weeks of lessons, AI use comes from the Crédoc digital barometer (2026 edition, 2025 data) and from Pew (2025); adjustable.
Comparison with other occupations and activities
Characteristics
| Unit | 1 pupil, 1 year : 180 days |
|---|---|
| Default location | world, 458 gCO2e/kWh (Ember 2025, life cycle); 11 other locations to choose from |
| Counted | homework and schoolwork done with AI over a school year, including data centre cooling |
| Not counted | personal use outside school, counted separately, server manufacturing, model training and the pupil's device |
| Status | estimated |
All the characteristics
| Identifier | IA-0317, projetcelsius.com/en/ai/database/IA-0317/ |
|---|---|
| Version | 0.1 of 2 November 2026 |
| Category | Occupations and activities, one person, one year |
| Choice of the selected value | database calculation from the entries this one is made of, at the quantities of the unit |
| Sources | calculation of the database |
| Licence | CC BY 4.0 |
Usage parameters
Advanced settings
Tasks and frequencies
Frequency and share done with AI, task by task · typical use
Adjust each task
| Task | Frequency | Share with AI | Per year | Electricity | Share |
|---|---|---|---|---|---|
| Quick question | 90 | 27 Wh | 8 % | ||
| Conversation of 10 exchanges | 21.6 | 76 Wh | 23 % | ||
| Write a page | 9 | 4.1 Wh | 1 % | ||
| Summarise 30 pages | 3.6 | 18 Wh | 5 % | ||
| Translate a page | 7.2 | 4.3 Wh | 1 % | ||
| Presentation of 10 slides | 1.8 | 21 Wh | 6 % | ||
| Create an image | 7.2 | 23 Wh | 7 % | ||
| Web search with an AI | 54 | 150 Wh | 44 % | ||
| AI overview of a search | 108 | 14 Wh | 4 % |
Result for the chosen case
180 days, servers worldwide: 150 gCO2e, 340 Wh.
For a carbon footprint
| Item | purchases of services (GHG Protocol scope 3, category 1); regulatory BEGES, category 4 |
|---|---|
| Quantity | 1 pupil over a year |
| Factor | 150 gCO2e per pupil over a year, IA-0317 version 0.1, based on the local grid (location-based), servers worldwide |
| Total | 150 gCO2e · not counted: personal use outside school, counted separately, server manufacturing, model training and the pupil's device |
Typical usage profile
Projet Celsius assumption
The typical pupil asks AI 2 to 3 exercise questions, opens a conversation to understand a concept every 2 weeks, runs an assisted search one day in 3, writes one essay in 4 with it and an image from time to time; they also see 3 generated overviews a week without having asked for them. About 8.4 requests a week. Over the school year, about 340 Wh, the lowest of the activities. Light use, 110 Wh; heavy use, 860 Wh.
Breakdown by item
Quantity, unit value, contribution and nature of the data for each item
| Item | Quantity | Unit value | Contribution | Share | Nature of the data |
|---|---|---|---|---|---|
| Web search with an AI | 54 times | 2.7 Wh | 150 Wh | 44 % | assumption |
| Conversation of 10 exchanges | 22 times | 3.5 Wh | 76 Wh | 23 % | assumption |
| Quick question | 90 times | 0.3 Wh | 27 Wh | 8 % | assumption |
| Create an image | 7.2 times | 3.2 Wh | 23 Wh | 7 % | assumption |
| Presentation of 10 slides | 1.8 times | 11 Wh | 21 Wh | 6 % | assumption |
| Summarise 30 pages | 3.6 times | 4.9 Wh | 18 Wh | 5 % | assumption |
| AI overview of a search | 110 times | 0.13 Wh | 14 Wh | 4 % | assumption |
| Translate a page | 7.2 times | 0.6 Wh | 4.3 Wh | 1 % | assumption |
| Write a page | 9 times | 0.45 Wh | 4.1 Wh | 1 % | assumption |
Entries that use it (4)
Pupils and students, Île-de-France, inhabitants, European Union, inhabitants, World, inhabitants
Sources of the calculation
14 publications, for this entry and those used to calculate it, with the chosen parameters.
The result is calculated by Projet Celsius. The sources below support its uses, its factors and its conversion; they do not all measure this total.
Uses and assumptions
These publications shed light on AI tasks and uses. They do not measure the carbon footprint of the case calculated.
Apec · June 2025
Role and limits : Apec
What the publication covers. frequency of generative AI use at work, 2,000 private-sector managers surveyed in March 2025
What it does not cover. non-managers and the number of requests
Reading by the database. Recent French survey on frequency of use at work; copy read on a specialist press site
Secondary school pupil, 1 year →
Support for the "Typical use" setting
Scope of the figure used. The median user among those who use AI, end of 2026: they turn to it every working day for part of their questions, writing and reading, about 5 to 15 requests per day in an office job. In an organisation or a territory, it also sets the share of employees who use it (25%).
Limit. This setting remains an assumption of the database, not a measurement of the occupation.
Crédoc · 2026
Role and limits : Crédoc
Author. Crédoc for Arcep, Arcom, the CGE and the ANCT
What the publication covers. use of generative AI by people aged 12 and over in France in 2025: who, for what, how often, paid or not
What it does not cover. the number of requests
Reading by the database. The reference survey in France, 4,145 people
Secondary school pupil, 1 year →
Published observation on uses
Scope of the figure used. Users aged 12 to 17 who use AI for homework help and learning (73% among 18 to 24 year olds)
Limit. Survey of 2025 published in 2026, 4,145 people; support for the frequencies and the use
Secondary school pupil, 1 year → : Quick question →
About 10 exercise questions per week, assumption; share done with AI based on the 68% of teenage users who use it for homework (Crédoc, Baromètre du numérique, edition 2026, data 2025).
Scope of the figure used. computation of the response, data centre
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
Secondary school pupil, 1 year → : Conversation of 10 exchanges →
About 3 concepts to understand or revise per week, assumption; share done with AI based on the Crédoc Baromètre du numérique (edition 2026, data 2025).
Scope of the figure used. messages, context re-read from cache, responses, data centre
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
Secondary school pupil, 1 year → : Summarise 30 pages →
About 1 chapter or book to summarise every 2 weeks, assumption; share done with AI based on the Crédoc Baromètre du numérique (edition 2026, data 2025).
Scope of the figure used. document read, summary written, data centre
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
Secondary school pupil, 1 year → : Translate a page →
About 1 language exercise to translate per week, assumption; share done with AI based on the Crédoc Baromètre du numérique (edition 2026, data 2025).
Scope of the figure used. tokens read and written, data centre
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
Secondary school pupil, 1 year → : Create an image →
About 1 image per week for a presentation or homework, assumption; share done with AI based on the Crédoc Baromètre du numérique (edition 2026, data 2025).
Scope of the figure used. server and data centre
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
Secondary school pupil, 1 year → : Web search with an AI →
About 5 searches per week, assumption; share done with AI based on the Crédoc Baromètre du numérique (edition 2026, data 2025).
Scope of the figure used. searches, pages read, response, data centre
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
Epoch AI · February 2025
Role and limits : Epoch AI
What the publication covers. the calculation from the hardware and the assumed size of the model
What it does not cover. actual measurements
Reading by the database. A public, transparent calculation
Reference of the selected value
Scope of the figure used. GPT-4o, 500 tokens written, full scope
Limit. A public calculation, from the hardware and the assumed size of the model
Conversation of 10 exchanges → : Re-read from cache →
The context re-read from cache at each turn: the previous exchanges, and the document already in the conversation if there is one
Scope of the figure used. server, convention C4
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
Pew Research Center · January 2025
About a quarter of U.S. teens have used ChatGPT for schoolwork ↗ (new tab)
Role and limits : Pew Research Center
What the publication covers. 1,391 American teenagers aged 13 to 17, surveyed in autumn 2024
What it does not cover. frequency and other assistants
Reading by the database. American survey, the most recent reviewed on lower and upper secondary school pupils
Secondary school pupil, 1 year →
Published observation on uses
Scope of the figure used. American teenagers aged 13 to 17 who used ChatGPT for their homework (31% at the end of high school, 20% in middle school)
Limit. Supports the pupil's use of AI; American survey of autumn 2024
Secondary school pupil, 1 year → : Write a page →
About 1 essay per week, assumption; share done with AI based on the quarter of American teenagers who use ChatGPT for homework (Pew, 2025).
Scope of the figure used. tokens read and written, data centre
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
Projet Celsius · November 2026
Tokens per word, per line of code and per cell, measured with 7 public tokenisers
Role and limits : Projet Celsius
What the publication covers. 479,888 words from 196 blog articles and their English translation, code from the site and the Python library, a table of measurements; tokenisers of GPT-4o, GPT-4, Llama 3, Gemini (via Gemma 3), Mistral, DeepSeek and Qwen
What it does not cover. the Claude tokeniser, not public
Reading by the database. A measurement on technical texts, figures included; to be repeated if publishers change their tokeniser
Projet Celsius measurement, repeated on request with the public tokenisers
Conversation of 10 exchanges → : Re-read from cache →
Length convention: one page
Scope of the figure used. A report page, headings and paragraphs included: between the 1,500-character sheet (250 words) and a full A4 page in single spacing (about 550 words, at 6.1 characters per word measured on our articles)
Limit. This publication supports the quantity of text or content processed, not its carbon footprint.
Write a page → : Write, with reasoning →
Length convention: one page
Scope of the figure used. A report page, headings and paragraphs included: between the 1,500-character sheet (250 words) and a full A4 page in single spacing (about 550 words, at 6.1 characters per word measured on our articles)
Limit. This publication supports the quantity of text or content processed, not its carbon footprint.
Summarise 30 pages → : Read 1,000 tokens →
Length convention: one page
Scope of the figure used. A report page, headings and paragraphs included: between the 1,500-character sheet (250 words) and a full A4 page in single spacing (about 550 words, at 6.1 characters per word measured on our articles)
Limit. This publication supports the quantity of text or content processed, not its carbon footprint.
Summarise 30 pages → : Write, with reasoning →
Length convention: one page
Scope of the figure used. A report page, headings and paragraphs included: between the 1,500-character sheet (250 words) and a full A4 page in single spacing (about 550 words, at 6.1 characters per word measured on our articles)
Limit. This publication supports the quantity of text or content processed, not its carbon footprint.
Translate a page → : Write, with reasoning →
The translated page, counted as a French page
Scope of the figure used. server, excluding the data centre
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
Translate a page → : Read 1,000 tokens →
Length convention: one page
Scope of the figure used. A report page, headings and paragraphs included: between the 1,500-character sheet (250 words) and a full A4 page in single spacing (about 550 words, at 6.1 characters per word measured on our articles)
Limit. This publication supports the quantity of text or content processed, not its carbon footprint.
Translate a page → : Write, with reasoning →
Length convention: one page
Scope of the figure used. A report page, headings and paragraphs included: between the 1,500-character sheet (250 words) and a full A4 page in single spacing (about 550 words, at 6.1 characters per word measured on our articles)
Limit. This publication supports the quantity of text or content processed, not its carbon footprint.
The other publication in this section
Zhang and Nam · June 2026
HANSEL: Extracting Breadcrumbs from Web Agent Trajectories for Interactive Verification ↗ (new tab)
Role and limits
Author. Yujin Zhang and Daye Nam
What the publication covers. 45 web agent trajectories: 13.16 steps and 6.02 pages visited per task on average
What it does not cover. electricity
Reading by the database. A small sample, which gives the order of magnitude of an agent's steps
Web search with an AI → : Read 1,000 tokens →
The 5 pages found, read by the model, and the question: web agents visit 6 pages per task on average
Scope of the figure used. server, excluding the data centre
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
Energy and factors
The references of the selected values and of the entries used in this calculation.
Role and limits : Google
What the publication covers. chips, host, standby machines, data centre, on-site water
What it does not cover. manufacturing, training
Reading by the database. The only production measurement published by a provider
Reference of the selected value
Scope of the figure used. Median of a text prompt; chips, host, standby machines, data centre
Limit. The only production measurement published by a provider, not audited by a third party
Google · January 2009
Role and limits : Google
What the publication covers. a search, data centre
Reading by the database. Never remeasured
Reference of the selected value
Scope of the figure used. A search, data centre included
Limit. Never publicly remeasured; Google's AI answers are not published
Luccioni et al. · October 2024
Role and limits : Luccioni et al.
Author. Luccioni, Jernite and Strubell
What the publication covers. GPU, processor, memory
What it does not cover. data centre
Reading by the database. Open models only
Create an image → : Generate an image →
One image, of the chosen size: standard by default
Scope of the figure used. GPU, processor, memory; excluding the data centre
Limit. This figure covers part of the calculation; it does not measure the whole entry.
Reference for the variant "Standard image, from 512 to 1,024 pixels per side"
Scope of the figure used. Average of the open models tested, 1,000 images; median 1.35 Wh, maximum 11.49 Wh
Limit. Open models only; closed generators publish nothing
Microsoft Research · 2026
Estimation de l'énergie des requêtes en production (Joule) ↗ (new tab)
Role and limits : Microsoft Research
Author. Microsoft Research, Oviedo et al.
What the publication covers. H100 nodes, production
Reading by the database. Calibrated on production
Reference of the selected value
Scope of the figure used. Median, 500 tokens read and 300 written, H100 nodes
Limit. Not a measurement, but calibrated on production; judges public estimates to be 4 to 20 times too high
ML.ENERGY · February 2026
Role and limits : ML.ENERGY
Author. Chung et al., University of Michigan
What the publication covers. GPU energy per token, per response, per image, in steady state, according to the number of requests served at once
What it does not cover. processors, host memory, data centre cooling, manufacturing
Reading by the database. The best open benchmark: it serves to compare model sizes with each other, not as a production value
Support for the "Small model" setting
Scope of the figure used. A model of about 8 billion active parameters, like Llama 3.1 8B: about 6 times less electricity per token than the medium model, according to the ML.ENERGY benchmark.
Limit. The setting is a convention of the database supported by this publication.
Reference of the variant "Small model, about 8 billion parameters"
Scope of the figure used. Llama 3.1 8B, one H100 GPU, 64 requests at a time, GPU only, per 1,000 tokens written, reading of the question included
Limit. GPU only, on a benchmark: the database keeps only the ratio to the 70 billion model, 1 to 6.7
The measurement covers a different scope; it is not a direct measurement of this entry.
The 2 other publications in this section
OpenAI · June 2025
Role and limits
Author. Sam Altman, OpenAI
What the publication covers. an average query
What it does not cover. method, scope
Reading by the database. One sentence, no method
Reference of the selected value
Scope of the figure used. "An average query", with no published method
Limit. No published scope; consistent with Google
Watershed · Aug. 2026
Estimating GHG Emissions from AI Use: Framework for Corporate-Level Measurement ↗ (new tab)
Role and limits
Author. Bistline, Ulissi, Davis, Glidden, Joyce, Li, Mohsenin and Suh (Watershed)
What the publication covers. factors per 1,000 tokens read and written at the server before PUE (host and standby machines included), PUE separate (1.10 for a large operator, 1.56 for an unknown operator)
What it does not cover. clean measurements, the model and the hardware
Reading by the database. Default factors proposed for review (public data as of June 2026); for a large operator, taken from Google's measurement published in 2025 (Elsworth et al.), which already contains the data centre overhead; constant per token, they underestimate long contexts and agents according to the authors
Reference for the variant "Medium model, Watershed default factor"
Scope of the figure used. Default factor for 1,000 tokens read, medium model, large operator, at the server before PUE (Watershed table 2, public data as of June 2026)
Limit. A default value that Watershed derives from Google's measurement (0.24 Wh for the median text query of the Gemini app), with about 500 tokens per query and a written token costing 3 times a read token; Watershed does not give the split between read and written tokens. The 0.24 Wh already include the overhead of Google's data centre (0.02 Wh, 8%): with 375 tokens read and 125 written, the simplest reading, the factor contains it, and the PUE of 1.10 applied afterwards counts it a second time (about 9%). Values proposed for review, final at the next version of the framework
Reference for the variant "Medium model, Watershed default factor"
Scope of the figure used. Default factor for 1,000 tokens written, medium model, large operator, at the server before PUE (Watershed table 2, public data as of June 2026)
Limit. 3 times the reading factor, based on the ratio between writing and reading selected by Watershed (Patel et al., Splitwise, 2024). Same derivation and same caveat as for reading: Google's 0.24 Wh already include about 8% of data centre. Values proposed for review, final at the next version of the framework
Quick question → : Data centre PUE →
The data centre, convention C3
Scope of the figure used. building cooling and losses
Limit. This figure covers part of the calculation; it does not measure the whole entry.
Reference of the selected value
Scope of the figure used. Default factor for a large operator, from the server to the data centre; 1.56 for an unknown operator
Limit. A default value, not a measurement
Conversation of 10 exchanges → : Data centre PUE →
The data centre, convention C3
Scope of the figure used. building cooling and losses
Limit. This figure covers part of the calculation; it does not measure the whole entry.
Write a page → : Data centre PUE →
The data centre, convention C3
Scope of the figure used. building cooling and losses
Limit. This figure covers part of the calculation; it does not measure the whole entry.
Summarise 30 pages → : Data centre PUE →
The data centre, convention C3
Scope of the figure used. building cooling and losses
Limit. This figure covers part of the calculation; it does not measure the whole entry.
Translate a page → : Data centre PUE →
The data centre, convention C3
Scope of the figure used. building cooling and losses
Limit. This figure covers part of the calculation; it does not measure the whole entry.
Create an image → : Data centre PUE →
The data centre, convention C3
Scope of the figure used. building cooling and losses
Limit. This figure covers part of the calculation; it does not measure the whole entry.
Web search with an AI → : Data centre PUE →
The data centre, convention C3
Scope of the figure used. building cooling and losses
Limit. This figure covers part of the calculation; it does not measure the whole entry.
Reference factor: Medium model, Watershed default factor
Scope of the figure used. Default factor for 1,000 tokens read, medium model, large operator, at the server before PUE (Watershed table 2, public data as of June 2026)
Limit. This measurement concerns the reference variant, not a measurement of "Small model, about 8 billion parameters". A default value that Watershed derives from Google's measurement (0.24 Wh for the median text query of the Gemini app), with about 500 tokens per query and a written token costing 3 times a read token; Watershed does not give the split between read and written. The 0.24 Wh already include the overhead of Google's data centre (0.02 Wh, 8%): with 375 tokens read and 125 written, on the simplest reading, the factor contains it, and the PUE of 1.10 applied afterwards counts it a second time (about 9%). Values proposed for review, to be finalised in the next version of the framework
Reference factor: Medium model, Watershed default factor
Scope of the figure used. Default factor for 1,000 tokens written, medium model, large operator, at the server before PUE (Watershed table 2, public data as of June 2026)
Limit. This measurement concerns the reference variant, not a measurement of "Small model, about 8 billion parameters". 3 times the read factor, based on the write-to-read ratio adopted by Watershed (Patel et al., Splitwise, 2024). Same derivation and same caveat as for reading: Google's 0.24 Wh already include about 8% for the data centre. Values proposed for review, to be finalised in the next version of the framework
Conversion into carbon
The source of the electricity factor of the selected location.
Worldwide: 458 gCO2e/kWh, life cycle.
Role and limits : Ember
Author. Ember, Our World in Data
What the publication covers. electricity generation over the life cycle, by country
What it does not cover. guarantees of origin
Reading by the database. The same source for all countries
Conversion of electricity into carbon: worldwide
Scope of the figure used. the production of electricity over the life cycle, including power plant construction and fuels
Limit. An average for the chosen country, not the electricity contract or the data centre of a specific service.
Nature of the data
Published readings, conventions, assumptions
- Projet Celsius assumptions 100 %
Usage assumptions
Frequency, share done with AI according to adoption, source of each assumption
Quick question : 10 per week, 25% with AI in typical use
About 10 exercise questions per week, assumption; share done with AI based on the 68% of teenage users who use it for homework (Crédoc, Baromètre du numérique, edition 2026, data 2025).
Conversation of 10 exchanges : 3 per week, 20% with AI in typical use
About 3 concepts to understand or revise per week, assumption; share done with AI based on the Crédoc Baromètre du numérique (edition 2026, data 2025).
Write a page : 1 per week, 25% with AI in typical use
About 1 essay per week, assumption; share done with AI based on the quarter of American teenagers who use ChatGPT for homework (Pew, 2025).
Summarise 30 pages : 0.5 per week, 20% with AI in typical use
About 1 chapter or book to summarise every 2 weeks, assumption; share done with AI based on the Crédoc Baromètre du numérique (edition 2026, data 2025).
Translate a page : 1 per week, 20% with AI in typical use
About 1 language exercise to translate per week, assumption; share done with AI based on the Crédoc Baromètre du numérique (edition 2026, data 2025).
Presentation of 10 slides : 6 per year, 30% with AI in typical use
About 6 presentations per year, assumption; use set without a reviewed French survey.
Create an image : 1 per week, 20% with AI in typical use
About 1 image per week for a presentation or homework, assumption; share done with AI based on the Crédoc Baromètre du numérique (edition 2026, data 2025).
Web search with an AI : 5 per week, 30% with AI in typical use
About 5 searches per week, assumption; share done with AI based on the Crédoc Baromètre du numérique (edition 2026, data 2025).
AI overview of a search : 10 per week, 30% with AI in typical use
About 10 searches per week on a search engine that displays an AI-generated overview, assumption; the overview is imposed by the engine and does not depend on the pupil's use.
Published figures in support
Crédoc (2025) : 68 %
Users aged 12 to 17 who use AI for homework help and learning (73% among 18 to 24 year olds)
Pew Research Center (2025): 26% of teenagers
American teenagers aged 13 to 17 who used ChatGPT for their homework (31% at the end of high school, 20% in middle school)
Methodology conventions
With their alternatives
| The working day and year | A working year counts 220 days and 44 weeks, a personal year 365 days; the task lists of occupations give, as a median, about 2 requests to AI per working day at low adoption, 6 at standard adoption, 21 at intensive adoption, excluding code suggestions |
|---|---|
| The default location | Without other information, the servers are in the world, at the world average electricity |
| Electricity, location-based, on a life cycle basis | The kilowatt-hour is that of the servers' country, on a life cycle basis, from a single source for all countries |
| Two significant figures | A calculated value is rounded to two significant figures, a published value is reproduced with the precision of its source; the calculation keeps full precision |
| The formula | the sum of what makes up the entry, then CO2e: electricity (Wh) multiplied by the carbon intensity of the server location (gCO2e/kWh), divided by 1,000 |
| Calculate a case without an entry | The formula, the default values and a step-by-step example |
History
Entry in version 0.1 of 2 November 2026, in the database in version 0.4
- 2 November 2026Version 0.1 of the entry, as of the date of its current value.
- 31 October 2026Creation of the database, in its first version (0.1).
