OpenAirClim

Description

OpenAirClim is an open-source response model for quantifying the climate impact of air traffic emissions. Rather than explicitly simulating physical processes, it uses response functions derived from comprehensive climate-chemistry models. This makes OpenAirClim particularly fast and efficient, with individual runs taking seconds to minutes on a conventional computer.

Motivation

Aviation operations account for around 3.5% of Effective Radiative Forcing and its share is expected to grow. A large part of aviation's impact arises from non-CO2 effects, in particular nitrogen oxide emissions and the formation of contrails. The impact of non-CO2 effects is highly dependent on the location and time of the emission, as well as on the characteristics of the emitting aircraft. Emerging aircraft and fuels (e.g. SAF, hydrogen, hybrid-electric) demand new, open and efficient tools to quantify their climate impacts. However, existing models are either closed, too general or computationally intense.

OpenAirClim and its add-ons constitute an open-source framework to rapidly model aviation emissions and their climate response: supporting science, industry and policy. Development is being led by the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt, DLR) and includes various research and industry partners.

Highlights

OpenAirClim builds upon the previous AirClim framework. Compared to AirClim, the new OpenAirClim framework:

• Provides standardised, open formats for the simulation configuration file, emission inventories and results
• Provides a Graphical User Interface (GUI) for interactive configuration and results exploration
• Handles multiple emission inventories over time (4D dependence)
• Allows attribution of climate impact to specific aircraft or fleets
• Implements tagging for atmospheric chemistry
• Extends contrail calculations to novel aviation fuels
• Enables the calculation of parametric scenarios at post-processing level, e.g. climate optimised routing
• Provides uncertainty and robustness metrics (work in progress)
• Provides various outputs, including time series of radiative forcing and temperature change, various climate metrics and sea-level rise

Typical use cases

OpenAirClim is aimed both at research and industry. Typical research questions that can be answered by using OpenAirClim relate to:

• fleet-wide scenarios, e.g. the introduction of a new aircraft type; climate impact of operations from a specific airline or airport
• aviation industry scenarios, e.g. the introduction of a new fuel type; climate-optimal distribution of SAF
• operational procedures, e.g. intermediate stop operations; flying lower and slower

Layout

Documentation

Please refer to openairclim.org for the documentation of the OpenAirClim framework. The documentation includes installation manuals, quickstart, user and developer guides, example demonstrations, an API reference, as well as information on the scientific background and OpenAirClim governance.

Installation

OpenAirClim is available from PyPI, conda-forge and from source. OpenAirClim supports installation via pip, uv, conda and pixi.

For Users

If you are a user of OpenAirClim and are not planning on developing the model, use one of the following setups. See our user installation documentation for more details. If you are a developer, see the next section.

pip install openairclim

# install with optional dependencies (gui, docs, test, dev)
pip install openairclim[dev]

uv pip install openairclim

# install with optional dependencies (gui, docs, test, dev)
uv pip install openairclim[dev]

conda install -c conda-forge openairclim

# to add to a local project
pixi add openairclim

# to install globally
pixi global install openairclim

For Developers

If you are planning on developing OpenAirClim, you will need extra files and data not available in the releases on PyPI and conda-forge. Therefore, start by cloning the repository from GitHub:

cd path/to/working/dir
git clone https://github.com/dlr-pa/oac.git

We recommend using pixi for development. However, there are many other options, depending on your setup. See our developer guide for a more complete overview. We recommend using Python 3.13 for development.

cd oac
pixi install --all

cd oac
conda env create -f environment_dev.yaml
conda activate oac
pip install -e .

cd oac
python3.13 -m venv .venv
source .venv/bin/activate  # or for Windows: .venv\Scripts\activate
pip install --upgrade pip
pip install -e ".[dev]"

Download repository data

OpenAirClim's response surfaces and background concentration scenarios are published separately, in dlr-pa/oac-data. This data is required by users and developers alike. To download the data to a shared cache, use:

oac-download-data

See the user guide for override options.

Getting started

See the quickstart guide for a simple OpenAirClim simulation setup.

Graphical User Interface

OpenAirClim ships with an optional GUI for creating, loading and editing configuration files, inspecting input data, running simulations and exploring results. Provided the gui dependencies have been installed, it can be launched using:

oac-gui

Run OpenAirClim

OpenAirClim can be run from the command line using:

cd path/to/working/directory
oac-run <config-name>.toml

Note that if there are any relative links in the config file (e.g. dir = input/), you must be in the right working directory for OpenAirClim to run successfully.

Roadmap

The scheduling of major software releases and milestone planning are partially dependent on the contractual framework with our stakeholders. For the version history of the completed releases, see the changelog. The full development stage as currently planned is shown in the layout.

Contributing

Contributions are very welcome. Please read our contribution guidelines to get started. For more detailed information, see our developer guide.

License

OpenAirClim is licensed under Apache 2.0, a copy of which can be found here.