dpmfa_nl_eu

Microplastics and Macroplastics Material Flow Model for estimating release to the environment

https://github.com/rivm-syso/dpmfa_nl_eu

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 3 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (14.0%) to scientific vocabulary

Keywords

emissions-model plastics
Last synced: 7 months ago · JSON representation ·

Repository

Microplastics and Macroplastics Material Flow Model for estimating release to the environment

Basic Info
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Topics
emissions-model plastics
Created over 2 years ago · Last pushed 10 months ago
Metadata Files
Readme License Citation

README.Rmd

---
title: "README"
output: github_document
editor_options: 
  markdown: 
    wrap: 72
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.12636554.svg)](https://doi.org/10.5281/zenodo.12636554)

Dynamic probabilistic material flow analysis (DPMFA) model for the
Netherlands and the EU. Based on code by EMPA and data in collaboration
with TNO.

Author: Institute of Public Health and the Environment (RIVM)

## Model description

This model is used to calculate micro- and macroplastic emissions for
certain product groups and polymers to the environment. The input needed
to run the model is present in MainInputfile.xlsx. The plastic emissions
to environmental sinks are calculated over time and probabilistically by
using Monte Carlo simulations.

## Dependencies

-   Python (version 3.11.7)
-   Numpy (version 1.26.4)
-   Pandas (version 2.4.1)
-   dpmfa (version 1.1)
-   sqlite (version 3.41.2)
-   Anaconda (needed to create and run batch files)

## How to run the model

To run the model, please follow these steps:

1.  Change the directory at the top of the main.py, write_metadata.py
    and CaseStudy_Runner.py scripts to the folder where the model code
    is located on your computer.

2.  In Create_batch_files.py, change the directory in line 65 to the
    directory where programs are installed on your computer. Usually
    this is :/C, so this probably does not need to be changed.

3.  Set the parameters to your preferences in config.py. Comment line 12
    or 13 depending on your operating system. Comment line 16 or 17
    depending on whether you want to run a dynamic probabilistic MFA or
    a probabilistic MFA. Comment line 20 or 21 depending on the region
    for which you want to run the model.

4.  Run main.py. This will create: 1) the databases needed as input for
    the model 2) CaseStudy_Runner files for each of the source-material
    combinations 3) a batch file to run all CaseStudy_Runner files at
    once named 'Run_all'.

5.  Navigate to the Run_all.bat file in your file explorer and double
    click in order to run it. All output files can be found in the
    folder 'output' that has been created in the directory you provided
    in step 1.

## Output

Within the output folder is a folder for each category that the model
has run for. Within each of these folders, there is a folder for each
material within the category. In these material folders are the CSV\
files containing the output. There are 4 types of CSVs:

-   Inflow: logged inflow into each compartment in kilotonnes

-   Outflow: logged outflow from one compartment to another in\
    kilotonnes

-   Sink: logged inflows into the sinks (final compartments in MFA)\
    in kilotonnes

-   Stock: logged quantities of material present in a stock\
    compartment.

Within the CSV files, the rows represent the number of runs (as\
defined in config.py), and the columns represent the years.

------------------------------------------------------------------------

Licensed under Attribution-NonCommercial-ShareAlike CC BY-NC-SA
()

Reason for license is this work being based on DPMFA package and other
work by EMPA.


Owner

  • Name: Rijksinstituut voor Volksgezondheid en Milieu
  • Login: rivm-syso
  • Kind: organization
  • Email: info@rivm.nl
  • Location: Bilthoven, The Netherlands

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- affiliation: National Institute for Public Health and the Environment
  family-names: Hids
  given-names: Anne
  orcid: 'https://orcid.org/0009-0006-0325-5924'
- affiliation: National Institute for Public Health and the Environment
  family-names: Quik
  given-names: Joris T.K.
  orcid: 'https://orcid.org/0000-0002-7964-3652'
- affiliation: National Institute for Public Health and the Environment
  family-names: Steenmeijer
  given-names: Michelle A.
  orcid: 'https://orcid.org/0000-0003-0278-1077'
- affiliation: National Institute for Public Health and the Environment
  family-names: Mellink
  given-names: Yvette
  orcid: 'https://orcid.org/0000-0003-4838-8932'
- affiliation: National Institute for Public Health and the Environment
  family-names: van Bruggen
  given-names: Anne
  orcid: 'https://orcid.org/0000-0003-0621-714X'
license: "CC-BY-NC-SA-4.0"
type: software
title: "DPMFA_NL_EU"
doi: 10.5281/zenodo.12636553
url: "https://github.com/rivm-syso/DPMFA_NL_EU"

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