UsesLevel 4 of 6 occupation or activityOccupation or activity, level 4 of 6Calculated with 11 entries, levels 1 and 3Database structure 
6Territories
5Organisations
3Uses
2Machine operations
1Calculation factorsChatGPT Pro, 1 year
A year of ChatGPT Pro subscription, the plan for intensive professional use: about 260 hours of coding agent, 110 deep research tasks, 23 clips of 10 seconds, and 7 other tasks. Projet Celsius estimate.
- Code and agents account for 88% of emissions: "Coding agent hour" weighs as much as 2,200 quick questions.
- About 7,300 requests to AI over the year, or 20 per working day.
- An estimate: the frequencies and the share done with AI are our assumptions.
Sentence to citeChatGPT Pro, 1 year, Projet Celsius estimate: 91 kgCO2e per subscription per year, for 200 kWh of electricity, servers worldwide (458 gCO2e/kWh).
Breakdown of emissions by item
91 kgCO2e in total: 200 kWh of electricity × 458 gCO2e/kWh (servers worldwide).
Inputs of the calculation
PUE of the data centre, Read 1,000 tokens, Re-read from cache, Write 1,000 tokens, Second of video, Deep research, Clip of 10 seconds, Coding agent hour
How the calculation is built
A year of ChatGPT Pro subscription, the plan for intensive professional use: many questions, deep research every week, videos and hours of coding agent. The typical use is an assumption by Projet Celsius.
Comparison with other occupations and activities
Characteristics
| Unit | 1 subscription, 1 year : 365 days |
|---|---|
| Default location | world, 458 gCO2e/kWh (Ember 2025, life cycle); 11 other locations to choose from |
| Counted | the tasks done with AI over a year, including data centre cooling |
| Not counted | server manufacturing, model training, the person's device and the subscription price |
| Status | estimated |
All the characteristics
| Identifier | IA-0320, projetcelsius.com/en/ai/database/IA-0320/ |
|---|---|
| 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 |
|---|---|---|---|---|---|
| Question to ChatGPT | 5,480 | 1.9 kWh | 1 % | ||
| Conversation of 10 exchanges | 548 | 1.9 kWh | 1 % | ||
| Query a PDF | 183 | 860 Wh | 0 % | ||
| Proofread a page | 365 | 220 Wh | 0 % | ||
| Write a page | 146 | 66 Wh | 0 % | ||
| Create an image | 146 | 470 Wh | 0 % | ||
| Deep research | 110 | 11 kWh | 5 % | ||
| Clip of 10 seconds | 23.4 | 7.9 kWh | 4 % | ||
| Browser agent | 46.8 | 540 Wh | 0 % | ||
| Coding agent hour | 260 | 170 kWh | 88 % |
Result for the chosen case
365 days, 10 seconds per video, servers worldwide: 91 kgCO2e, 200 kWh.
For a carbon footprint
| Item | purchases of services (GHG Protocol scope 3, category 1); regulatory BEGES, category 4 |
|---|---|
| Quantity | 1 subscription over a year |
| Factor | 91 kgCO2e per subscription over a year, IA-0320 version 0.1, based on the local grid (location-based), servers worldwide |
| Total | 91 kgCO2e · not counted: server manufacturing, model training, the person's device and the subscription price |
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 |
|---|---|---|---|---|---|
| Coding agent hour | 260 times | 670 Wh | 170 kWh | 88 % | assumption |
| Deep research | 110 times | 99 Wh | 11 kWh | 5 % | assumption |
| Clip of 10 seconds | 23 times | 340 Wh | 7.9 kWh | 4 % | assumption |
| Conversation of 10 exchanges | 550 times | 3.5 Wh | 1.9 kWh | 1 % | assumption |
| Question to ChatGPT | 5,500 times | 0.34 Wh | 1.9 kWh | 1 % | assumption |
| Query a PDF | 180 times | 4.7 Wh | 860 Wh | 0 % | assumption |
| Browser agent | 47 times | 12 Wh | 540 Wh | 0 % | assumption |
| Create an image | 150 times | 3.2 Wh | 470 Wh | 0 % | assumption |
| Proofread a page | 370 times | 0.6 Wh | 220 Wh | 0 % | assumption |
| Write a page | 150 times | 0.45 Wh | 66 Wh | 0 % | assumption |
Entries that use it
No other entry in the database is calculated from this one.
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.
Anthropic · June 2025
Role and limits : Anthropic
What the publication covers. an agent uses about 4 times the tokens of a conversation, a multi-agent system about 15 times
What it does not cover. electricity
Reading by the database. Publisher orders of magnitude, with no absolute value
Deep research → : Re-read from cache →
The context re-read from cache at each of the 40 steps, 40,000 tokens on average
Scope of the figure used. server, convention C4
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
Anthropic · 2026
Role and limits : Anthropic
What the publication covers. tokens of an image according to its size: one patch of 28 × 28 pixels per token, 1,296 for a megapixel
What it does not cover. electricity
Reading by the database. The publisher's billing rule
Analyse an image → : Read 1,000 tokens →
The photo cut into about 1,100 image tokens, read as text
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.
Analyse an image → : Read 1,000 tokens →
Length convention: a photo sent to an AI
Scope of the figure used. A one-megapixel photo, cut into image patches: 765 tokens at OpenAI for GPT-4o, 1,032 at Google, 1,229 for recent OpenAI models, 1,296 at Anthropic
Limit. This publication supports the quantity of text or content processed, not its carbon footprint.
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
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.
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
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.
Google · 2026
Role and limits : Google
What the publication covers. up to hundreds of sites browsed and pages processed per search
What it does not cover. electricity
Reading by the database. A presentation page: a ceiling, not an average
Deep research → : Read 1,000 tokens →
The web pages read, about a hundred by default: Google announces up to hundreds of sites
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.
The 2 other publications in this section
Projet Celsius · November 2026
Tokens per word, per line of code and per cell, measured with 7 public tokenisers
Role and limits
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.
Query a PDF → : 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.
Proofread 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.
Proofread 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.
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.
Deep research → : Write 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.
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
Agent in the browser → : Analyse an image →
A screenshot read at each step, 15 steps: published web agents take 13 on average
Scope of the figure used. image reading on the server; outside 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.
Delavande et al. · September 2025
Role and limits : Delavande et al.
Author. Delavande, Pierrard and Luccioni
What the publication covers. GPU, processor, memory
What it does not cover. data centre
Reading by the database. Seven open models
10-second clip → : Second of video →
A single continuous video costs as much as the square of its duration: 10 seconds is worth 3.4 times the 5.4-second video that was measured
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.
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
Hausfather · Aug. 2026
Role and limits : Hausfather
Author. Zeke Hausfather, The Climate Brink
What the publication covers. intensive personal use of Claude Code, tokens recorded and converted into electricity
Reading by the database. A researcher's personal measurements, not a study
Coding agent hour → : Re-read from cache →
The context re-read from cache at each of the 120 steps of the hour: 96,000 tokens, 96% of a call in the median published session
Scope of the figure used. server, convention C4
Limit. This figure covers part of the calculation; it does not measure the whole entry.
Coding agent hour → : Read 1,000 tokens →
The new tokens of each step (files read, command results): 3,600, 3.6% of a call
Scope of the figure used. server, excluding the data centre
Limit. This figure covers part of the calculation; it does not measure the whole entry.
Coding agent hour → : Write 1,000 tokens →
The tokens written at each step, draft included: 900 on average in the published logs
Scope of the figure used. server, excluding the data centre
Limit. This figure covers part of the calculation; it does not measure the whole entry.
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
OpenAI · June 2025
Role and limits : OpenAI
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. Record R-0004, attached to the ChatGPT block
The other publication in this section
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
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.
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
Query a PDF → : 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.
Proofread 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.
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.
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.
Deep research → : 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.
10-second clip → : 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.
Agent in the browser → : 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.
Coding agent hour → : 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.
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
Question to ChatGPT : 30 per day, 50% with AI in typical use
About 30 occasions to ask a question per day for professional use, assumption; usage cap of the plan not verified.
Conversation of 10 exchanges : 3 per day, 50% with AI in typical use
About 3 long reasoning sessions per day, assumption.
Query a PDF : 1 per day, 50% with AI in typical use
About 1 long document per day, assumption.
Proofread a page : 2 per day, 50% with AI in typical use
About 2 texts to rework per day, assumption.
Write a page : 1 per day, 40% with AI in typical use
About 1 page to write per day, assumption.
Create an image : 1 per day, 40% with AI in typical use
About 1 image request per day, assumption.
Deep research : 1 per day, 30% with AI in typical use
About 1 topic per day that lends itself to in-depth research, assumption; usage cap of the plan not verified.
Clip of 10 seconds : 3 per week, 15% with AI in typical use
About 3 video requests per week, assumption; usage cap of the plan not verified.
Browser agent : 3 per week, 30% with AI in typical use
About 3 online procedures per week that can be entrusted to the agent, assumption.
Coding agent hour : 10 per week, 50% with AI in typical use
About 10 hours per week during which a coding agent can work, the plan being aimed at professional use, assumption; usage cap of the plan not verified.
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.
- 12 November 2026Calculated value, servers worldwide : 64 kgCO2e becomes 91 kgCO2e.Consequence of the new value for the coding agent hour (from 440 to 670 Wh), decided on 12 November 2026; the entry's own data do not change, and its citation carries version 0.4 of the database.
- 31 October 2026Creation of the database, in its first version (0.1).
