Datasets for manuscript "Data engineering for tracking chemicals and releases at industrial end-of-life activities"
Description
The GitHub repository contains a Python code (MC_Case_Study.py) to support and replicate the case study results shown in the manuscript entitled Data engineering for tracking chemicals and releases at industrial end-of-life activities. Also, it indicates the free-available Python libraries that are required for running the code "MC_Case_Study.py." The dataset "EoL_database_for_MC.csv" contains all data to execute the Python code and obtain "Figure 6: 6-level Sankey diagram for the case study", "Figure 7: Box plot for the case study", and "Figure 8: Histogram for the case study." A Table describing the data name entry and data type for the dataset "EoL_database_for_MC.csv" is shown. Also, this dataset information and Python code are provided in the manuscript Supporting Info file (see supporting documents).
This dataset is associated with the following publication:
Hernandez-Betancur, J.D., G.J. Ruiz-Mercado, J.P. Abraham, M. Martin, W.W. Ingwersen, and R.L. Smith. Data engineering for tracking chemicals and releases at industrial end-of-life activities. JOURNAL OF HAZARDOUS MATERIALS. Elsevier Science Ltd, New York, NY, USA, 405: 124270, (2021).
Resources
| Name |
Format |
Description |
Link |
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0 |
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https://github.com/gruizmer/MC_Case_Study |
Tags
- chemical-releases
- chemical-flow-tracking
- end-of-life-stage
- chemical-safety-for-sustainability
- life-cycle-inventory
- life-cycle-environmental-assessment
- chemical-manufacturing
- industrial-end-of-life-activities
- data-engineering
- chemical-risk-evaluation