isorropiar is an R package to interact with the aerosol thermodynamical equilibrium ISORROPIA II model. ISORROPIA II is used for modelling aerosol-gas systems. A common application is to use ISORROPIA II to explore the partitioning of total reduced nitrogen (NHx) into the gas (ammonia; NH3) and aerosol (ammonium; NH4+) phases. The main reference for ISORROPIA II is an Atmospheric Chemistry and Physics article.
For a usage example see:
Grange, S. K., Sintermann, J., and Hueglin, C. (2023). Meteorologically normalised long-term trends of atmospheric ammonia (NH3) in Switzerland/Liechtenstein and the explanatory role of gas-aerosol partitioning. Science of the Total Environment 900, p. 165844.
The development version of the isorropiar package can be easily installed with the remotes package:
# Install isorropiar
remotes::install_packages("skgrange/isorropiar")
The ISORROPIA II programme itself is not provided in the isorropiar R package and needs to be downloaded from official websites for licencing reasons. The ISORROPIA II source code can be requested for use on Unix systems or a Windows executable can downloaded from here or here. If the source code is downloaded, the Fortran code will require compilation for your particular system before using.
On my Ubuntu (Unix) system, the ISORROPIA II programme directory structure looks like this:
source/
|-- DEMO.dat
|-- DEMO.INP
|-- DEMO.txt
|-- isocom.for
|-- ISOFWD.FOR
|-- isorev.for
|-- isorropia
|-- isrpia.cnf
|-- isrpia.inc
|-- main.for
`-- main.inc
My directory where the ISORROPIA II programme is located is called source, but this can change depend on your preferences and the executable programme is called isorropia.
On Windows systems, the only file that is required is called isrpia2.exe. I have kept the same directory name (ISO2_1Bin) that is downloaded and will look like this:
ISO2_1Bin/
|-- DEMO.INP
|-- isrpia2.exe
`-- ISRPIA.CNF
Running ISORROPIA II only requires two things:
- A data table formatted in the correct way
- The compiled ISORROPIA II programme (
isorropia) or the Windowsisrpia2.exefile and knowledge where either of these programmes is on your file system
Demo data that only varies sulfate concentrations are included in isorropia and these data can be loaded with the read_isorropia_demo_data function.
If the complied ISORROPIA II source is available, modelling can be done like this:
# Load the packages
library(dplyr)
library(isorropiar)
# Load demo data
data_demo <- read_isorropia_demo_data()
# Run the ISORROPIA II model with demo data
data_isorropia <- run_isorropia(
data_demo,
directory_isorropia = "source/",
verbose = TRUE
)
#> 2022-04-07 08:22:21.636 CEST: Running ISORROPIA II: `echo 1649312541_isorropia_run.txt | ./isorropia`...
# Print the result
data_isorropia
#> # A tibble: 1 × 10
#> # Rowwise: date_model_run
#> date_model_run system_type isorropia_programme version n_input input messages error_messages output combined
#> <dttm> <chr> <chr> <chr> <int> <list> <list> <chr> <list> <list>
#> 1 2022-04-07 08:22:21 unix isorropia 2.1 (0… 15 <tibble> <chr> NO ERRORS DET… <tibble> <tibble>If the Windows executable is to be used, only the directory_isorropia argument needs to be changed:
# Load the packages
library(dplyr)
library(isorropiar)
# Load demo data
data_demo <- read_isorropia_demo_data()
# Run the ISORROPIA II model with demo data
data_isorropia <- run_isorropia(
data_demo,
directory_isorropia = "C:/isorropia/ISO2_1Bin",
verbose = TRUE
)The data_isorropia object is a nested tibble object that contains the input passed to ISORROPIA II and the outputs produced by ISORROPIA II. These units can be extracted from the nested structure and can be used within the R analysis ecosystem. For example, to extract ISORROPIA II's output, the reframe function can do this rather easily:
# Extract the model's output
data_isorropia %>%
reframe(output)
#> # A tibble: 15 × 50
#> date_model_run NATOT SO4TOT NH4TOT NO3TOT CLTOT CATOT KTOT MGTOT RH TEMP GNH3 GHCL GHNO3 CNACL
#> <dttm> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 2022-04-06 17:27:00 0 1 2 2 0 1 0 0 0.75 280 1.96 3.65e-13 6.3 e-13 5.85e-13
#> 2 2022-04-06 17:27:00 0 2 2 2 0 0 0 0 0.75 280 0.868 0 3.75e- 1 0
#> 3 2022-04-06 17:27:00 0 3 2 2 0 0 0 0 0.75 280 0.545 0 4.61e- 1 0
#> 4 2022-04-06 17:27:00 0 4 2 2 0 0 0 0 0.75 280 0.264 0 7.00e- 1 0
#> 5 2022-04-06 17:27:00 0 5 2 2 0 0 0 0 0.75 280 0.0785 0 1.26e+ 0 0
#> 6 2022-04-06 17:27:00 0 6 2 2 0 0 0 0 0.75 280 0 0 1.86e+ 0 0
#> 7 2022-04-06 17:27:00 0 7 2 2 0 0 0 0 0.75 280 0 0 1.97e+ 0 0
#> 8 2022-04-06 17:27:00 0 8 2 2 0 0 0 0 0.75 280 0 0 1.98e+ 0 0
#> 9 2022-04-06 17:27:00 0 9 2 2 0 0 0 0 0.75 280 0 0 1.99e+ 0 0
#> 10 2022-04-06 17:27:00 0 10 2 2 0 0 0 0 0.75 280 0 0 1.99e+ 0 0
#> 11 2022-04-06 17:27:00 0 11 2 2 0 0 0 0 0.75 280 0 0 1.99e+ 0 0
#> 12 2022-04-06 17:27:00 0 12 2 2 0 0 0 0 0.75 280 0 0 1.99e+ 0 0
#> 13 2022-04-06 17:27:00 0 13 2 2 0 0 0 0 0.75 280 0 0 2.00e+ 0 0
#> 14 2022-04-06 17:27:00 0 14 2 2 0 0 0 0 0.75 280 0 0 2.00e+ 0 0
#> 15 2022-04-06 17:27:00 0 15 2 2 0 0 0 0 0.75 280 0 0 2.00e+ 0 0
#> # … with 35 more variables: CNANO3 <dbl>, CNA2SO4 <dbl>, CNAHSO4 <dbl>, CNH4CL <dbl>, CNH4NO3 <dbl>, CNH42S4 <dbl>,
#> # CNH4HS4 <dbl>, CLC <dbl>, CCASO4 <dbl>, CCANO32 <dbl>, CCACL2 <dbl>, CK2SO4 <dbl>, CKHSO4 <dbl>, CKNO3 <dbl>,
#> # CKCL <dbl>, CMGSO4 <dbl>, CMGNO32 <dbl>, CMGCL2 <dbl>, HLIQ <dbl>, NALIQ <dbl>, NH4LIQ <dbl>, CLLIQ <dbl>,
#> # SO4LIQ <dbl>, HSO4LIQ <dbl>, NO3LIQ <dbl>, CaLIQ <dbl>, KLIQ <dbl>, MgLIQ <dbl>, NH4AER <dbl>, CLAER <dbl>,
#> # NO3AER <dbl>, WATER <dbl>, LMASS <dbl>, SMASS <dbl>, CASE <chr>