Introduction
Global warming is a vital problem in today’s world which is attributed in large proportion to the emissions of greenhouse gasses. In this lab I have attempted to create map visualizations that account for various quantities related to greenhouse gasses produced by the countries of the world. Furthermore, I also created dashboards for these visualizations so that they can be compared amongst each other.
Inspiration
Our World Data has created a data explorer for its users to quickly compare the different quantities in countries from their CO₂ and GHG Emission Dataset. This data explorer is interactive and provides line graphs of various quantities across time. This explorer also allows users to select which countries to include in the comparison.
Our world data also provides a map interface for the same data explorer which provides the user with choropleth maps for the selected metric. I wanted to make a comparative visualization dashboard so I decided to do similar designs for choropleth maps for my visualizations as done on the data explorer by Our World Data.
Dataset, Software & Tools
Dataset: Since my visualizations were based on the data explorer done by Our World Data, I decided to use the same CO₂ and GHG Emission Dataset used by them.
Tableau Public: I used Tableau Public, which is a free version of Tableau, for creating the visualizations for this project.
Method
I wanted to look at GHGs emissions from the countries of the world so I started first by creating a choropleth of GHG per capita. I did not use the sum of the GHG per capita for all the years in the dataset since that can be misleading. For this I filtered the data by year and since 2018’s data was the last complete data for GHG per capita in the dataset, I used the data for that year.
Further I wanted to compare this with the total GHGs emissions, so I created another choropleth of the total GHG for the same year (2018).
Since GHGs contribute significantly towards global warming, I used a Gold-Red color scale of warm colors in both the choropleths to give the visual perception of warming for more emissions.
Further, I wanted to do the comparison between primary energy consumption and share of global CO₂ for all the countries. So I started with creating a choropleth of primary energy consumption. I used the data for the year 2020 for this visualization.
To compare this with the share of global CO₂ I created another choropleth for the same year (2020) to keep statistical consistency.
For the primary energy consumption choropleth I used a blue color scale to signify power consumption. As for the global CO₂ choropleth I chose a gray color scale to signify the carbon-dioxide share. This was also to create a visual perception of more pollution for a higher share of carbon dioxide which in turn translated to a darker shade of gray.
Finally, once these four visualizations were made, I created two dashboards for the corresponding comparison between the visualizations.
Results & Interpretation
The final results are in the form of Dashboards in Tableau Public
1. Dashboard #1: GHGs Per Capita vs Total GHGs
In this dashboard it can clearly be seen that the countries with high populations (China, India, USA) have a higher total GHGs emissions. But the per capita GHGs tell a different story, with the per capita GHGs to be high for most developed countries. So it can be inferred that the developed countries (which have high per capita GHGs) have a high rate of emissions, which is not directly proportional to the population of the country.
2. Dashboard #2: Primary Energy Consumption vs Share Global CO₂
This dashboard shows the primary energy consumption and Share of global CO₂ for the year 2020 for all the countries. These two visualizations have a directly proportional relationship with higher energy consumption countries having higher share of the global carbon dioxide.
Reflection & Future Direction
I wanted to compare the choropleths of two metric simultaneously in one visualization, unlike the ones done by Our World Data where only one metric can be seen at a time. Since the comparative visualizations were fruitful this experiment is a success.
For future work in this project I would like to create similar visualizations with other metrics that can be compared. Similar comparisons with quantities like cement CO₂, Coal CO₂, Gas CO₂, Oil CO₂, Nitrous oxide etc. are possible from the same dataset.
It would be also interesting to do the video timeline visualization as done by Our World Data but instead of just one metric (single choropleth) do it with two comparable metric as done in this project. With the correct tools and softwares this can also be a possible direction to further this project.