A web-based interactive scenario builder and visualization application for the rfasst air pollution model, an R version of the air quality reduced-form model TM5-FASST.
Just getting started with rfasstui? We have constructed a tutorial to examine some sample use-cases which are available here: Tutorial
To navigate directly to the rfasstui app CLICK the following image:
To install rfasstui as an R package for local use, please follow these steps in your R command line:
library(devtools)
devtools::install_github("bc3LC/rfasstui")How you launch the app after installation depends on your R environment. See the following.
If you are using RStudio, simply open the server.r or ui.r file and execute Run App.
Start R.exe and enter the following command:
shiny::runApp(system.file("shinyApp", package = "rfasstui"))Users familiar with R Shiny can add new features by working directly in the rfasstui/inst/shinyApp directory.
We welcome contributions to rfasstui from the development community. Join in
on the conversation at the rfasstui GitHub Discussions page or contact us if you want to
collaborate!
For more information about contributing, please contact Clàudia Rodés-Bachs at claudia.rodes@bc3research.org or Jon Sampedro at jon.sampedro@bc3research.org
Read more about the rfasst air pollution model here: rfasst Documentation, detailed in Sampedro et al. 2022. It is an R version of the TM5-FASST model, detailed in Van Dingenen et al. 2018
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Sampedro et al., (2022). "rfasst: An R tool to estimate air pollution impacts on health and agriculture." Journal of Open Source Software, 7(69), 3820, https://doi.org/10.21105/joss.03820
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Van Dingenen, Rita, et al., (2018). "TM5-FASST: a global atmospheric source–receptor model for rapid impact analysis of emission changes on air quality and short-lived climate pollutants." Atmospheric Chemistry and Physics 18.21: 16173-16211.