The geometry is imported as 8 polygons: Rajasthan, West Bengal, Punjab, Bihar, Delhi, Haryana, UP, IGP. Additional, 9th entry is the whole region of India obtained from the LSIB dataset (Large Scale International Boundary Polygons, Simplified).

In the first lines of the scripts, the user can specify their parameters. The region of the interests as a variable region is specified in common with the start and finish date of the observations (start and finish variables). The format of the provided data is YYYY-MM-DD. In the same sector, the variable scales is defined as an integer which indicates the number of meters per pixels. The cloudFraction variable indicates allowed in percents cloud contents on the pictures (value between 0-1) Note: setting the custom cloud content is not available for each species due to the lack of the detection of the cloudiness for the particular gases.  The regionborders variable is created to store the actual borders of the region to generate the KMZ file.

In the next part of the script, if the region of the interests is set as India, UP, IGP (i.e. huge region with the complicated geometry, their geometry is simplified to the rectangle. And the scale is chosen arbitrarily by changing the variable scales. However,  the generated KMZ file contains the original geometry of the region.

The function masking clouds is created, and a suitable collection of the Sentinel-5p images is filtered by the date. Additionally, the bands are chosen. Then, It is mapped over the cloud mask (if apply).  The variable with prefix band_viz is set the maximum and minimum values (what can be customized by advancer user by the analyse of the minimum and maximum values of the chart created in the later part of the script) and colour palette necessary to display the map and the legend. 

The mean value of the gas is calculated using reducers what let to operate on the bigger sets of the data and clipped to the region of the interests.

The chart is generated based on the image collection, region of the interest, band of the interest over the time sourced from the first satellite picture made in the choose start date.

The generation of the layer is similar to the generation of the chart, however, this time instead of direct referencing to the band by the original band name, the band is chosen as 0 (after reducing the size of the collection, the image lost their primary band names which are now substituted by the numbers and can be viewed by printing the collection i.e. print(XXmeanclipped)).

In the next part of the code, the legend is generated. It is a long-winded process, although not described here since it is created nearly only based on the setting adequate visual parameters such as the font size, pagination, margins etc..

Finally, the last part of the code includes the data to export the image to the drive: colour pallette (same as before), min and max values. The variable toexport is introduced as the merged collection with choose band. The instruction .visualize() with a visualized parameter inside let the image to obtain the colours after the export.

Finally, the map and the KMZ file is exported. The crs instruction inside the function which is exporting the map indicates that the picture is fitted in whole on the one picture (to avoid dividing the picture into the parts by the program).