aarshbatra / explained.media.work

Working with explained.media on some interesting data-viz stories

Data visualization focussed story telling

Story 1: Understanding the state of global air quality data, research and funding infrastructure

• All code for the story can be found in the global.air.quality.infra.story.Rmd script at the root of this repo. Each story corresponds to a one Rmd and each chunk of any given Rmd corresponds to one visualization, within a given story.

• The helper script for the code can be found in the R/ folder at the root.

• The datasets used in the code are not pushed to GitHub due to space limitations. Those can be downloaded from the following drive folder. Read notes on the datasets below.

• Visualizations are stored in the output/ folder at the root of the repo.

• Notes on data files present in the drive folder above:

  • There are 3 final processed files that come out of the AQLI data pipeline. Each of these files contain population weighted annual average PM2.5 data and corresponding life years lost (or potential gains in life expectancy: see the last point) data at country (gadm0 file), state (gadm1 file) and district/county (gadm2 file). These are present in the final processed CSVs sub-folder in the drive folder above.

  • Corresponding to the 3 files above there are 3 shapefiles, which can be found in the shapefiles sub-folder.

  • Apart from this, there are couple other files that the helper script loads, all of which are also present in the folder above.

  • The helper script loads the aqverse pacakge, which is used in the plotting code.

  • The code book for AQLI datasets is uploaded as a text file named aqli_code_book at the root of this repo.

  • All AQLI pollution data is measured in micrograms per cubic meter.

  • The AQLI data story can be told in 2 ways that convey the same message and a mix of both are used in the AQLI Annual Report 2023. Here is an example of Delhi, India:

    • Potential gains in years of life expectancy for a Delhi resident is 11.9 years if WHO PM2.5 guideline is met (default for the the AQLI interactive map and the data visualization in the output folder of this repo).
    • An average Delhi resident is losing 11.9 years of life as a result sustained long term exposure to breathing air that is not in compliance with the WHO guideline.