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reemission

A Python library and a command line interface tool for estimating CO2, CH4 and N2O emissions from water reservoirs.
https://github.com/tomjanus/reemission

Category: Emissions
Sub Category: Emission Observation and Modeling

Keywords

climate greenhouse-gas-emissions hydropower water-resources

Last synced: about 21 hours ago
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Repository metadata

RE-emission is a collection of methods for calculating GHG emisisons from reservoirs

README.md

Contributors
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GPL-3.0 License

About The Library

Re-Emission is a Python library and a command line interface (CLI) tool for estimating CO2, CH4 and N2O emissions from reservoirs.
It calculates full life-cycle emissions as well as emission profiles over time for each of the three greenhouse gases.

🔥 Features

  • Calculates CO2, CH4 and N2O emissions for a single reservoir and for batches of reservoirs.
  • Two reservoir Phosphorus mass balance calculation methods in CO2 emission calculations: G-Res method and McDowell method.
  • Two N2O calculation methods.
  • Model parameters, and presentation of outputs are fully configurable using YAML configuration files.
  • Inputs can be constructed in Python using the Input class or read from JSON files.
  • Outputs in tabular form can be presented in JSON, LaTeX and PDF formats and can be configured by changing settings in the outputs.yaml configuration file.
  • Integrates with the upstream catchment and reservoir delineation package GeoCARET (formerly HEET), whcih is currently in Beta version and undergoing development.
  • Combines tabular and GIS inputs from catchment delineation with gas emission outputs and visualizes the combined data in interactive maps.

A quick demo of results from RE-Emission using input data from catchment delineation tool GeoCARET

Preliminary results of our first case study (for presentation use only), are shown in https://tomjanus.github.io/mya_emissions_map/. The case study looks into an assessment of gas emissions from existing and planned hydroelectric reservoirs in Myanmar. A snapshot of the map is presented below.

Requirements

Python Version

RE-Emission requires Python 3.10 or newer.

LaTeX Installation (Optional)

If you would like to generate output documents in a PDF format, you will need to install LaTeX. Without LaTeX, upon an attempt to compile the generated LaTeX source code to PDF, pylatex library implemented in this software will throw pylatex.errors.CompilerError. LaTeX source file with output results will still be created but it will not be able to get compiled to PostScript or PDF.

LaTeX installation guidelines can be found alonside the software installation guidelines in the documentation Documentation

Basic Installation

From GitHub

  1. Clone the repository using either:
    • HTTPS
    git clone https://github.com/tomjanus/reemission.git
    
    • SSH
    git clone [email protected]:tomjanus/reemission.git
    
  2. Install from source:
    • for development
      pip install -r requirements.txt -e .
      
    • or as a build
      pip install .
      

Usage

As a toolbox

For calculation of emissions for a number of reservoirs with input data in test_input.json file and output configuration in outputs.yaml file.

import pprint
# Import reemission utils module
import reemission.utils as utils
# Import EmissionModel class from the `model` module
from reemission.model import EmissionModel
# Import Inputs class from the `input` module
from reemission.input import Inputs
# Run a simple example input file from the /examples/ suite
input_data = Inputs.fromfile(utils.get_package_file('../../examples/simple_example/test_input.json'))
output_config = utils.get_package_file('config/outputs.yaml')
model = EmissionModel(inputs=input_data, config=output_config)
model.calculate()
pprint.pprint(model.outputs)

Jupyter Notebook Examples

Open In Colab

Using Command Line Interface (CLI)

RE-Emission has two CLI interfaces: reemission for performing greenhouse gas emission calculations and reemission-geocaret for processing outputs obtained from an upstream reservoir and catchment delineation tool GeoCARET (formerly HEET) and creating input files to RE-Emission.
For more information about the usage, type in Terminal/Console:

reemission --help

and

reemission-geocaret --help

For more examples, please refer to the Documentation

📚 Documentation

The software documentation can be accessed here

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repository and create a pull request. You can also simply open an issue with the tag "enhancement".
Don't forget to give the project a star! Thanks again!

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

License

GPL-3.0

Citing

If you use RE-Emission for academic research, please cite the library using the following BibTeX entry.

@misc{reemission2022,
 author = {Tomasz Janus, Christopher Barry, Jaise Kuriakose},
 title = {RE-Emission: Python tool for calculating greenhouse gas emissions from man-made reservoirs},
 year = {2022},
 url = {https://github.com/tomjanus/reemission},
}

📬 Contact

Project Link: https://github.com/tomjanus/reemission

Acknowledgments

Institutions

Development of this software was funded, to a large degree, by the University of Manchester and the FutureDams project.

Resources

References

[1] Marco Aurelio dos Santos, Luiz Pinguelli Rosa, Bohdan Sikar, Elizabeth Sikar, Ednaldo Oliveira dos Santos. (2006). Gross greenhouse gas fluxes from hydro-power reservoir compared to thermo-power plants. Energy Policy, Volume 34, Issue 4, pp. 481-488, ISSN 0301-421. https://doi.org/10.1016/j.enpol.2004.06.015

[2]
Beaulieu, J. J., Tank, J. L., Hamilton, S. K., Wollheim, W. M., Hall, R. O., Mulholland, P. J., Dahm, C. N. (2011). Nitrous oxide emission from denitrification in stream and river networks. Proceedings of the National Academy of Sciences of the United States of America, 108(1),
214–219. https://doi.org/10.1073/pnas.1011464108

[3]
Scherer, Laura and Pfister, Stephan (2016) Hydropower's Biogenic Carbon Footprint. PLOS ONE, Volume 9, 1-11, https://doi.org/10.1371/journal.pone.0161947.

[4]
Yves T. Prairie, Sara Mercier-Blais, John A. Harrison, Cynthia Soued, Paul del Giorgio, Atle Harby, Jukka Alm, Vincent Chanudet, Roy Nahas (2021) A new modelling framework to assess biogenic GHG emissions from reservoirs: The G-res tool. Environmental Modelling & Software, Volume 143, 105-117, ISSN 1364-8152, https://doi.org/10.1016/j.envsoft.2021.105117.

[5] Prairie YT, Alm J, Harby A, Mercier-Blais S, Nahas R. 2017. The GHG Reservoir Tool (G-res) Technical documentation. Updated version 3.0 (2021-10-27). UNESCO/IHA research
project on the GHG status of freshwater reservoirs. Joint publication of the UNESCO Chair in Global Environmental Change and the International Hydropower Association. 73 pages.

Contributors ✨

This project follows the all-contributors specification. Contributions of any kind welcome!

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
title: "RE-Emission: Python tool for estimation of greenhouse gas emissions from reservoirs"
authors:
  - family-names: Janus
    given-names: Tomasz
  - family-names: Barry
    given-names: Christopher
  - family-names: Kuriakose
    given-names: Jaise 
version: 0.0.1
date-released: "2022-05-20"
license: GPL-3.0
repository-code: "https://github.com/tomjanus/reemission"
doi: 

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Dependencies

ci/requirements.txt pypi
  • pip >=19.1.1
  • setuptools >=18.0.1
  • six >=1.14.0
  • tox *
  • virtualenv >=16.6.0
docs/requirements.txt pypi
  • sphinx >=1.3
  • sphinx-rtd-theme *
requirements.txt pypi
  • PyYAML *
  • click *
  • coverage *
  • gdown *
  • matplotlib *
  • notebook *
  • numpy *
  • openpyxl *
  • pandas *
  • pyfiglet *
  • pylatex *
  • pytest *
  • pyyaml *
  • quantities *
  • unittest *
pyproject.toml pypi
setup.py pypi

Score: 3.871201010907891