This dataset is provided as an example to run the IsotopeRead_Picarro Matlab software.


Open the IsotopeRead_Picarro.mlapp file and ensure you are in the same working folder. 

Next, the data should be imported as follows:

Picarro G5131-i data file: "data_20240306_Picarro_G5131i_Instrum1.dat"
Picarro G2041 data file (optional): "data_20240306_Picarro_G2401.dat"

MPV position/interval timestamps can be imported from either:

"data_20240306_Picarro_G5131i_Instrum2_MPV" (select "PICARRO data file"), or 
"intervals_example.csv"	(select "generic CSV file")

A default set of sample gas names can be imported from "gasnames_example.txt"

Pre-processed data in Matlab format is also provided ("data_20240306_preprocessed.mat")




Extended documentation:

1) Open the MATLAB App

Open the file IsotopeRead_Picarro.mlapp in MATLAB.
Ensure that the current MATLAB working folder is the same folder where this file and the dataset are located.
The app will open in a separate window, not as a regular MATLAB script.

2) Import the data

Select the appropriate data files and click the “Import” button in the app.
Import the following files:

Picarro G5131-i data file: data_20240306_Picarro_G5131i_Instrum1.dat

Picarro G2401 data file (optional): data_20240306_Picarro_G2401.dat


3) Import MPV positions and gas names

Import MPV (multi-position valve) position or interval timestamps from one of the following sources:

data_20240306_Picarro_G5131i_Instrum2_MPV (select “PICARRO data file”), or

intervals_example.csv (select “generic CSV file”).


4) On the next tab, import default gas names from gasnames_example.txt.
First, click “Auto”, then upload the example file.
After import, save the pre-processed data for faster reloading later via Fan 2 (Pre-processing) using the “Save pre-processed data” option.
The saved MATLAB data file can later be reloaded via the “MATLAB data file” button on the Input tab (Fan 1).

Pre-processed data are also provided directly as:
data_20240306_preprocessed.mat

4) Perform corrections and calibration

Run the desired corrections and calibrations for both concentration and isotope data.
Update the default correction parameters to match the specific dataset.
Set the Anchor (also sometimes called Cal-1 in literature) as the primary calibration gas.
Select which corrections to apply by ticking or unticking the corresponding checkboxes.

5) Perform uncertainty propagation (optional)

Run the uncertainty propagation to estimate total measurement uncertainty.
Include uncertainties from correction slopes, calibration gases, and any additional or poorly constrained effects.
This step is optional but recommended for comprehensive data evaluation.

6) Save the results

After processing, save the results under a chosen file name.
The app will generate:

Text files containing all reduced and corrected data.

A log file summarising the exact processing and correction steps applied.

