https://github.com/Boavizta/environmental-footprint-data
💾 Boavizta.org Data repository
https://github.com/Boavizta/environmental-footprint-data
carbon-emissions carbon-footprint digital-sustainability environment footprint ghg-emissions sustainability
Last synced: 4 days ago
JSON representation
💾 Boavizta.org Data repository
- Host: GitHub
- URL: https://github.com/Boavizta/environmental-footprint-data
- Owner: Boavizta
- Created: 2020-12-30T15:01:59.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2023-02-23T10:26:29.000Z (about 2 years ago)
- Last Synced: 2025-04-05T04:34:39.964Z (14 days ago)
- Topics: carbon-emissions, carbon-footprint, digital-sustainability, environment, footprint, ghg-emissions, sustainability
- Language: Python
- Homepage:
- Size: 16.7 MB
- Stars: 119
- Watchers: 13
- Forks: 36
- Open Issues: 22
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- open-sustainable-technology - Environmental Footprint Data - Aims to reference as much data as possible to help organizations to evaluate the environmental footprint of their information systems, applications and digital services. (Consumption / Computation and Communication)
README
# Boavizta Project - Environmental Footprint Data
This data repository is maintained by [Boavizta](https://www.boavizta.org) and is complementary to Boavizta's environmental footprint evaluation methology. It aims to reference as much data as possible to help organizations to evaluate the environmental footprint of their information systems, applications and digital services.
Boavizta database is quite exclusively derived from PCF (Product Carbon Footprint) sheets provided by the manufacturers. Methodologies used by manufactureres are not transparent and have very large margins of error and the purpose of making these data available is mainly to give ideas of orders of magnitude and to compare different models from the same manufacturer.
Therefore **WE RECOMMAND NOT USING THESE DATA TO MAKE ACCURATE IMPACTS EVALUATIONS** or to compare the impacts of devices from different manufacturers.
In addition, most manufacturers rely on the [PAIA evaluation method](https://msl.mit.edu/projects/paia/main.html) developed by MIT. This method is based on data from non-public studies and Boavizta was therefore unable to evaluate its relevance.
To browse data, you can use https://dataviz.boavizta.org.
## License
This dataset is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Any rights in individual contents of the database are licensed under the Database Contents License: http://opendatacommons.org/licenses/dbcl/1.0/This data can be freely used for any purpose including without using Boavizta's methodology.
## Data sets
At this time, we provide two CSV files grouping together data collected from manufacturers (mainly Product Carbon Footprint reports) publicly avaiblable :
* `boavizta-data-fr.csv`: French version (`;` used as a delimiter, comma as a decimal separator)
* `boavizta-data-us.csv`: English version (`,` used as a delimiter, dot as a decimal separator)
We encourage all manufacturers to provide us with similar data or to correct potential errors in these files.
Boavizta working group works actively to enrich these files with new data :
* from manufacturers
* resulting from its analyzes and intended to provide ratios or average values that would simplify the evaluation
Please refer to [sources.md](sources.md) for a complete list of sources.
## Contribute
People are encouraged to contribute to these files.
You can easily contribute by :
* forking this repo and submitting PRs
* sending us an email to [email protected]
* submitting data through [dedicated form on Boavizta's website](https://boavizta.org/data-form)
If any manufacturers wish to share data with us, we will be happy to discuss with them how we can efficiently synchronize this data.
## Running the code
Download Chromedriver for your version of Chrome: https://chromedriver.chromium.org/downloads and move it to a folder that belongs to your path.
For Mac you can also run
```sh
brew install chromedriver
```
and restart Chrome.
Then create a python3.9 virtual environment, run
```sh
pip install -r tools/requirements.txt
```
to install the required packages and follow the instructions on the [spiders README.md](tools/spiders/README.md) to run a spider and parse the pdfs of the associated brand.
When developing a new parser you can also follow the instructions on the [parsers README.md](tools/parsers/README.md).
## Data format
* `manufacturer`: Manufacturer name, e.g. "Dell" or "HP"
* `name`: Product name
* `category`:
* Workplace: product commonly used in a workplace
* Datacenter: product commonly used in a data center (e.g. server, network switch, etc.)
* `gwp_total`: GHG emissions (estimated as CO2 equivalent, the unit is kgCO2eq) through the total lifecycle of the product (Manufacturing, Transportation, Use phase and Recycling)
* `gwp_use_ratio`: part of the GHG emissions coming from the use phase (the hypothesis for this use phase
are detailed in the other columns, especially the `lifetime` and the `use_location`)
* `yearly_tec`: Yearly estimated energy demand in kWh
* `lifetime`: Expected lifetime (in years)
* `use_location`: The region of the world in which the device usage footprint has been estimated.
* US: United States of America
* EU: Europe
* DE: Germany
* CN: China
* WW: Worldwide
* `report_date`: the date at which the Product Carbon Footprint report of the device was published
* `sources`: the original URLs from which the data for this row was sourced
* `gwp_error_ratio`: the datasheets commonly come with a diagram that shows the error margin for the footprint
* `gwp_manufacturing_ratio` part of the GHG emissions coming from the manufacturing phase
* `weight`: product weight in kg
* `assembly_location`: The region of the world in which the device is assembled
* US: United States of America
* EU: Europe
* CN: China
* Asia: Asia
* `screen_size`: in inches
* `server_type`: the type of server
* `hard_drive`: the hard drive of the device if any
* `memory`: RAM in GB
* `number_cpu`: number of CPUs
* `height`: the height of the device in a datacenter rack, in U
* `added_date`: the date at which this row was added
* `add_method`: how was the data for this row collected
## About Boavizta.org
Boavizta.org is a working group:
* Working to improve and generalize environmental footprint evaluation in organizations
* Federating and connecting stakeholders of the "environmental footprint evaluation" ecosystem
* Helping members to improve their skills and to carry out their own projects
* Leveraging group members initiatives