Supplementary Data & Model: Reducing the Climate Impact of Residual Waste Treatment: A German Case Study on Carbon Management Strategies
Fuente:
Zenodo
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Recurso digital |
| Language: | English |
| Published: |
Zenodo
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866902111448465408 |
|---|---|
| author | Schmidt, Sarah Laner, David |
| author_facet | Schmidt, Sarah Laner, David |
| contents | <div> <div> </div> <p>This repository provides the model and data related to the study "Reducing the Climate Impact of Residual Waste Treatment: A German Case Study on Carbon Management Strategies". In this study, we evaluate the effects of different carbon management strategies on the greenhouse gas (GHG) emissions from residual waste treatment in the city of Kassel. Two key strategies are examined: (1) post-sorting residual waste in a material recovery facility to remove recyclable, carbon-rich materials (S_MRF), and (2) post-treatment of municipal solid waste incineration (MSWI) flue gas through carbon capture and storage (S_MSWI_CCS). We compare GHG emissions under current and future scenarios, accounting for changes in waste inputs, material and energy systems, substitution choices, and uncertainties in treatment technology data. The related study is available at <em><a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.wasman.2025.02.048" target="_blank" rel="noreferrer noopener"><span><span>https://doi.org/10.1016/j.wasman.2025.02.048</span></span></a></em>.</p> <h2>Table of Contents</h2> </div> <ol> <li>Overview of the repository's content</li> <li>Installation</li> <li>Usage</li> <li>License</li> </ol> <div> <h2>1. Overview of the repository's content</h2> </div> <p><strong>Requirements.txt</strong>: Requirements.txt and Requirements_premise.txt contains a list of any packages the user needs to have installed in two separate environments before running the project.</p> <p><strong>0_Setup.ipynb</strong>: Background databases are generated by importing the ecoinvent database and creating prospective ecoinvent-versions by applying <em>premise</em>. For executing this notebook an ecoivent license and the premise decryption key is required.</p> <p><strong>1_GHG_ResidualWaste.ipynb</strong>: This notebook contains the main model code to perform the LCA (using Brightway2) and plot the results.</p> <p><strong>2_GSA</strong>: This folder contains notebooks to perform a global sensitivity analysis to analyze the main contributors to the output variance for different system conditions (GSA_marginal.ipynb: 2022 background system, marginal substitution; GSA_marginal_2045.ipynb: 2045 background system, marginal substitution; GSA_market_mix.ipynb: 2022 background system, substitution of market mixes) and the code which was used to perform the global sensitivity analysis (regression_based_global_sensitivity_analysis.py).</p> <p><strong>input_data</strong>: This folder comprises several xlsx-files which contain input data which are needed to build the foreground system of the model and modify the background system to Kassel conditions. Each input-data-file contains a README-sheet to explain its content.</p> <p><strong>export</strong>: Export files created during the creation of prospective background system databases with <em>premise</em></p> <p><strong>results</strong>: This folder comprises csv- and pkl-files with the model results. An overview of the contents of each file is provided in results/overview.txt.</p> <div> <h2>2. Installation</h2> </div> <p>To work on the project locally clone the repository and set up the environment based on requirements.txt.</p> <div> <h2>3. Usage</h2> </div> <p>3.1 Generate databases: Run 0_Setup.ipynb (use environment based on Requirements_premise.txt)<br>3.2 Calculate greenhouse gas emissions of residual waste treatment: Run 1_GHG_ResidualWaste.ipynb (use environment based on Requirements.txt)<br>3.3 Perform global sensitivity analysis: Run ipynb-files in 2_GSA (use environment based on Requirements.txt)</p> <div> <h2>4. License</h2> </div> <p>This work is licensed under CC BY-NC-SA 4.0</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_14650803 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Supplementary Data & Model: Reducing the Climate Impact of Residual Waste Treatment: A German Case Study on Carbon Management Strategies Schmidt, Sarah Laner, David Waste LCA; Prospective LCA; Municipal solid waste incineration; Carbon capture and storage; Material recovery facility; Climate neutrality <div> <div> </div> <p>This repository provides the model and data related to the study "Reducing the Climate Impact of Residual Waste Treatment: A German Case Study on Carbon Management Strategies". In this study, we evaluate the effects of different carbon management strategies on the greenhouse gas (GHG) emissions from residual waste treatment in the city of Kassel. Two key strategies are examined: (1) post-sorting residual waste in a material recovery facility to remove recyclable, carbon-rich materials (S_MRF), and (2) post-treatment of municipal solid waste incineration (MSWI) flue gas through carbon capture and storage (S_MSWI_CCS). We compare GHG emissions under current and future scenarios, accounting for changes in waste inputs, material and energy systems, substitution choices, and uncertainties in treatment technology data. The related study is available at <em><a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.wasman.2025.02.048" target="_blank" rel="noreferrer noopener"><span><span>https://doi.org/10.1016/j.wasman.2025.02.048</span></span></a></em>.</p> <h2>Table of Contents</h2> </div> <ol> <li>Overview of the repository's content</li> <li>Installation</li> <li>Usage</li> <li>License</li> </ol> <div> <h2>1. Overview of the repository's content</h2> </div> <p><strong>Requirements.txt</strong>: Requirements.txt and Requirements_premise.txt contains a list of any packages the user needs to have installed in two separate environments before running the project.</p> <p><strong>0_Setup.ipynb</strong>: Background databases are generated by importing the ecoinvent database and creating prospective ecoinvent-versions by applying <em>premise</em>. For executing this notebook an ecoivent license and the premise decryption key is required.</p> <p><strong>1_GHG_ResidualWaste.ipynb</strong>: This notebook contains the main model code to perform the LCA (using Brightway2) and plot the results.</p> <p><strong>2_GSA</strong>: This folder contains notebooks to perform a global sensitivity analysis to analyze the main contributors to the output variance for different system conditions (GSA_marginal.ipynb: 2022 background system, marginal substitution; GSA_marginal_2045.ipynb: 2045 background system, marginal substitution; GSA_market_mix.ipynb: 2022 background system, substitution of market mixes) and the code which was used to perform the global sensitivity analysis (regression_based_global_sensitivity_analysis.py).</p> <p><strong>input_data</strong>: This folder comprises several xlsx-files which contain input data which are needed to build the foreground system of the model and modify the background system to Kassel conditions. Each input-data-file contains a README-sheet to explain its content.</p> <p><strong>export</strong>: Export files created during the creation of prospective background system databases with <em>premise</em></p> <p><strong>results</strong>: This folder comprises csv- and pkl-files with the model results. An overview of the contents of each file is provided in results/overview.txt.</p> <div> <h2>2. Installation</h2> </div> <p>To work on the project locally clone the repository and set up the environment based on requirements.txt.</p> <div> <h2>3. Usage</h2> </div> <p>3.1 Generate databases: Run 0_Setup.ipynb (use environment based on Requirements_premise.txt)<br>3.2 Calculate greenhouse gas emissions of residual waste treatment: Run 1_GHG_ResidualWaste.ipynb (use environment based on Requirements.txt)<br>3.3 Perform global sensitivity analysis: Run ipynb-files in 2_GSA (use environment based on Requirements.txt)</p> <div> <h2>4. License</h2> </div> <p>This work is licensed under CC BY-NC-SA 4.0</p> |
| title | Supplementary Data & Model: Reducing the Climate Impact of Residual Waste Treatment: A German Case Study on Carbon Management Strategies |
| topic | Waste LCA; Prospective LCA; Municipal solid waste incineration; Carbon capture and storage; Material recovery facility; Climate neutrality |
| url | https://doi.org/10.5281/zenodo.14650803 |