Code for the data journalism project hosted here.
To analyze the current literature for iodine levels and its consequences on ozone.
Iodine levels became 3x higher over the past 60 years. When you factor in the impact it has on ozone levels, it could explain why the ozone layer is not healing as expected. One interesting concept was comparing conditions that preceded the highest iodine levels to the current scenario.
- The northern Atlantic Ocean had a surface temperature of 16°C. That is only 2°C greater than its temperature in 2022. The global temperature is projected to rise 3-4°C by 2100.
- The Arctic region had "almost ice-free summers". Ice-free Arctic summers are predicted by 2050.
- Read academic papers, mainly this one and this one.
- Data was in the form of tables in these papers, so no scraping or cleaning was involved.
- Sorted the iodine levels dataframe by year. Made a quick preliminary line chart to see how levels have changed.
- Sorted mean iodine vs ozone levels by time as well. Made a line chart to explore the data.
- Plotted the mean iodine vs ozone levels on a calendar heatmap.
- Creating a calendar heatmap in Python
- Using Rawgraphs
- Using Figma to polish a chart - moved Y axis to the right too!
- Making a graphic to compare the conditions that preceded the highest iodine levels to the current scenario effectively.
- Annotate the heatmaps to highlight highest and lowest values or to highlight springtime.