This repository contains the general code for the geospatial cost-benefit clean cooking tool, OnStove. OnStove calculates the net-benefits of different stove options in a given geography and compares all stoves to one another with regards to their net-benefit.
OnStove is developed by the division of Energy Systems at KTH together with partners. The tool is a geospatial, raster-based tool determining the net-benefit of different cooking solutions selected by the user for raster grid cell of a given study area. The tool takes into account four benefits of adopting clean cooking: reduced morbidity, mortality, emissions and time saved, as well as three costs: capital, fuel as well as operation and maintenance (O&M) costs. In each grid cell of the study area the stove with the highest net-benefit is chosen.
OnStove produces scenarios depicting the “true” cost of clean cooking. The scenarios benefits and costs of produced by the tool are to be interpreted as the benefits and costs one could expect if the clean cooking transition was to happen now (overnight change). Results from OnStove are to be interpreted as an upper bound of net-benefits following a switch to cleaner stoves. OnStove can be used by planners and policy makers to identify whether various combinations of interventions in their settings would be worth the potential benefits that could be captured
First, you need to install a python distribution using Anaconda or Miniconda (recomended).
The easiest way of installing and using OnStove is through conda. After installing a distribution of conda,
Open an Anaconda Prompt and run:
> conda create -n onstove -c conda-forge onstove
Now you will have a new conda environment called onstove with OnStove installed on it. To use it open an Anaconda Prompt
in the root folder of your analysis and activate the environment with:
> conda activate onstove
If you rather download the development version of OnStove and install the development environment, open an Anaconda Prompt
and download the source code with:
> conda install git
> git clone https://github.com/Open-Source-Spatial-Clean-Cooking-Tool/OnStove.git
Then use the jupyter_env.yaml in the envs folder to install the environment by writing:
> cd OnStove
> conda env create --name onstove --file envs/jupyter_env.yaml
> conda activate onstove
Now your environment onstove is available to use. Note that you need to activate it
always before conducting any analysis.
Access the latest documentation in read the docs.
Publication on sub-Saharan Africa
Khavari, Babak, Camilo Ramirez, Marc Jeuland and Francesco Fuso Nerini (12 January 2023).
"A geospatial approach to understanding clean cooking challenges in sub-Saharan Africa".
Nature Sustainability. 1–11. ISSN 2398-9629. doi:10.1038/s41893-022-01039-8.
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