Datasets for manuscript "Data engineering for tracking chemicals and releases at industrial end-of-life activities"

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).

[
  "020:00"
]

[
  "020:095"
]

[
  "https://doi.org/10.1016/j.jhazmat.2020.124270",
  "https://pasteur.epa.gov/uploads/10.23719/1518810/documents/Updated_SI_chemicals_EoL_06-09-20_after_363review_-_QAClean.docx"
]