This model simulates the concentration of two PCB congeners: PCB 4 and PCB 19 in both the aqueous and gas phases within laboratory-scale bioreactors containing PCB-contaminated sediment. The script incorporates experimental passive sampler measurements and uses a least-squares minimization approach to estimate congener-specific sampling rates for both passive samplers.
Additionally, the model can simulate the decrease in volatile PCB release from sediment to air due to the presence of an aerobic PCB-degrading microorganism, with a known biotransformation rate for PCBs.
Licenses/restrictions: licensed under the 2-Clause BSD License - see the LICENSE file for details.
Deposit Title: Polychlorinated Biphenyl (PCB) Reactive Transport Model
This README file was generated on March 10, 2025 by Andres Martinez.
Contributor information:
Andres Martinez, PhD University of Iowa - Department of Civil & Environmental Engineering Iowa Superfund Research Program (ISRP) [email protected] ORCID: 0000-0002-0572-1494
Principal Investigator: Timothy Mattes, PhD Principal Investigator email: [email protected]
This work was supported by the National Institutes of Environmental Health Sciences (NIEHS) grant #P42ES013661. The funding sponsor did not have any role in study design; in collection, analysis, and/or interpretation of data; in creation of the dataset; and/or in the decision to submit this data for publication or deposit it in a repository.
This R project is part of the paper: Ramotowski D, Martinez A, Marek RF, Hornbuckle KC and Mattes TE (2025) Paraburkholderia xenovorans strain LB400 Significantly Decreased Volatilization of Polychlorinated Biphenyls (PCBs) from Freshwater and Saline Sediments. ES&T Water
Subject: Polychlorinated Biphenyls; Contaminant fate and transport; Paraburkholderia xenovorans LB400; Kinetic phase passive sampling; Bioremediation; Biodegradation; Biosurfactants; Bioavailability; GC-MS/MS
GeoLocation: The sediment used in this study was taken from a PCB-contaminated emergency overflow lagoon located in Altavista, VA (37°06'52"N, 79°16'21"W), and New Bedford Harbor, MA. Laboratory and analytical work was done at the University of Iowa in Iowa City, IA, USA.
This section of the ReadMe file lists the necessary software required to run codes in "R".
Software:
- Any web browser (e.g., Google Chrome, Microsoft Edge, Mozilla Firefox, etc.)
- R-studio for easily viewing, editing, and executing "R" code as a regular "R script" file: https://www.rstudio.com/products/rstudio/download/
This section of the ReadMe file provides short instructions on how to download and install "R Studio". "R Studio" is an open source (no product license required) integrated development environment (IDE) for "R" and completely free to use. To install "R Studio" follow the instructions below:
- Visit the following web address: https://www.rstudio.com/products/rstudio/download/
- Click the "download" button beneath RStudio Desktop
- Click the button beneath "Download RStudio Desktop". This will download the correct installation file based on the operating system detected.
- Run the installation file and follow on-screen instructions.
It is recommended to create a project in R (e.g., PCB-Aerobic-Bioaugmentation-Study2.Rproj). Download the project file (.Rproj) and the R subfolder where the scripts are located, and the Subfolders.R file. Run first the Subfolder.R file, which will generate all the subfolders for this project. The structure of this project includes an R subfolder where all the R scripts are located, as previously indicated. There is a Data subfolder where the data are storage, and then an Output subfolder, where the results are located.
SPME and PUF data for individual PCB4 and PCB19 can be found at https://doi.org/10.25820/data.007563. The file 06_Dataset_final_PCBmass.csv needs to be downloaded and saved in the Data folder of the project.