raoulwolf / bayesian-pec-modeling

Complementary repository with data and code for Wolf & Tollefsen, 2021.

Bayesian PEC modeling

This repository contains the data and the R scripts for Wolf & Tollefsen 2021, “A Bayesian approach to incorporating spatiotemporal variation and uncertainty limits into modeling of predicted environmental concentrations (PECs) from chemical monitoring campaigns”. The article will be published in Environmental Science & Technology, doi:10.1021/acs.est.0c06268.

Requirements

To analyze the data, the statistical software R 4.0.1 or higher needs to be installed, as well as Rtools 40 for users operating from Windows.

The package {brms} needs to be installed as well. Within R, execute the following command to install:

install.packages("brms")

Information

All scripts are inside the scripts/ folder of this repository. For each of the three campaigns, a separate R file exists: sorfjord.R for the Sørfjord campaign, kaldvellfjord.R for the Kaldvellfjord campaign, and oslofjord.R for the Oslofjord campaign.

Additionally, the file empirical_prior.R contains a custom function to calculate empirical priors. Detailed information on the modeling procedure and the calculations of the empirical priors are given in the Supporting Information of the publication.