a tool for exploring different quantitative methods that could be used in enhanced weathering MRV
- main website: https://carbonplan.org/
- this site: https://carbonplan.org/research/ew-quantification
- explainer article: https://carbonplan.org/research/ew-quantification-explainer
Assuming you already have Node.js installed, you can install the build dependencies as:
npm install .To start a development version of the site, simply run:
npm run devand then visit http://localhost:5001/research/ew-quantification in your browser.
You will need to unlock the Google Sheets key using git-crypt. Unlocking is simplest using a symmetric secret key securely shared by a team member.
Note: If you don't have mamba installed, conda can be used as a environment manager, just expect much longer solving times.
Once you have the gcp credentials stored, you can create a conda environment with the command:
mamba env create --file binder/environment.yml
Once this has been created, you can activate it with:
mamba activate ew
Then run the following python script to generate json data for the legend and quantification approach json data.
cd enhanced-weathering
python QA_to_json.py
Once you have re-generated the .json data. You can create a new branch and push to the repo.
All the code in this repository is MIT-licensed, but we request that you please provide attribution if reusing any of our digital content (graphics, logo, articles, etc.).
CarbonPlan is a nonprofit organization that uses data and science for climate action. We aim to improve the transparency and scientific integrity of climate solutions with open data and tools. Find out more at carbonplan.org or get in touch by opening an issue or sending us an email.