A Global Perspective on CO2 Emissions
by Alan Tram, Mylinh Lac, and Swethaa Narasimma
Time and time again we’ve heard about ever-increasing CO2 emissions and their effect on global temperatures. From the personal level of everyday habits to courses of action as large as country policies, reducing CO2 emissions is possible. But where should we perhaps be focusing our energy? To what extent is this current issue? Are there associated patterns we can refer to in order to answer these questions? We will be taking a look at, globally, where CO2 emissions are concentrated and subsequently the proportion between the top contributors and the rest of the world. In doing so, we can collectively gain a better understanding of the source of CO2 emissions and perhaps the urgency of the matter.
Policymaking with Data
Paolo Raineri and Francesco Molinari are the authors of “Innovation in Data visualization” and seek to introduce to their readers the relationship between data visualization and public policymaking. The authors make evident that it’s challenging attempting to fulfill policy-making goals as well as empowering makers in a way that shortens decision process time. This idea of crossing policymaking and data visualization is important for our analysis of CO2 emissions here. Raineri and Molinari believe pairing data with decisions is the most optimal process in coming to sound conclusions. Data visualization is increasingly having more of an influence in decision making. As data vis is relevant for communicating large amounts of data to facilitate understanding, decision-making, and taking action. As you read through our post, you’ll begin to see just how intertwined data is with decision-making (even globally scaled issues such as global warming).
Data is not simply a data science or a technology facet, as the authors have motivated us to believe that data has evolved to encompass almost every discipline of work. It is the data that best shows such relationships and it can be the data that decides what decisions are made among the policymakers of the world. In our case of CO2 emissions, does the stark contrast in the number of emissions between China/US and the rest of the world make enough of a case to promote immediate action taken by global powers?
A Holistic Look at Population vs CO2 Emissions
At a first glance clearly, the large countries, the US and China, are in the list of both topmost highly populated countries and the highest total CO2 emission contributors (Figure 1). To follow this trend, the third-biggest contributor of CO2 emissions is India which happens to be the second most populous nation. The rest of the world is tinted varying shades of a lighter turquoise, indicating that the amount of Carbon Dioxide emissions there are on the far lower end. For context, the metric is in millions of metric tons. A USA Today article discusses these rankings while focusing mainly on the burning of fossil fuels as it is the heaviest contributor. Looking at history since 2006, “while U.S. emissions have declined since China’s emissions have steadily increased” (Frolich). China is the country that no other comes close to in terms of CO2 emissions. The main source here is coal production, tied to powering electricity. Although this information confirms our hypothesis that the most populous countries would be to blame for the most CO2 emissions, we believed surely the rest of the world would together comprise quite a bit of emission too.
The Gravity of the Situation
It is unquestionable that climate change is prevalent and only getting worse. Burning fossil fuels such as coal and oil have only increased the concentration of atmospheric carbon dioxide. This affects the global temperature, making certain regions increasingly warmer and vulnerable to undesirable living conditions (NASA). Furthermore, Figure 1 illustrates countries with the highest CO2 emission rates; to be specific, we can identify countries like the U.S. and China to be major contributors. We initially hypothesized that countries with higher populations would tend to have more of an influence on overall Carbon Dioxide emissions. After analyzing data derived from The World Bank within the preloaded extract in Tableau for ‘World Development Indicators,’ we found that there is a drastic difference between countries in terms of CO2 emissions. This difference was more significant than we had previously speculated. After generating additional graphs on Tableau (Figure 2), we found that, as predicted, China and the U.S. are high contributors of CO2 emissions; specifically, within the years 2000–2012, these countries together have emitted up to nearly 7,000,000 metric tons of CO2. When comparing this contribution to the rest of the regions of the world, we see just how drastic this difference is. Figure 2 also describes the average CO2 emissions of global regions, excluding China and the U.S. These regions as a whole have emitted up to 91,000 metric tons of CO2. Our initial speculation was in line with the idea that higher populated countries tend to have more of a contribution to CO2 emissions; however, we were originally unaware of its severity until recent analysis through the use of Tableau. With this in mind, we wanted to go more in-depth to understand the general distribution and global inequalities in CO2 emissions. This inequality lies at the center of why international agreement on climate change has been so controversial. In order to determine the collective carbon dioxide emissions, it’s important to consider two separate parameters including the number of people, and the quantity emitted by each person. With this in mind, we can confront which countries can make a further impact; either rich countries with high per capita emissions or those with higher populations. Furthermore, we can see that “North America is home to only five percent of the world population but emits nearly 18 percent of CO2 (almost four times as much)” (Ritchie). Global inequalities in CO2 emissions, as we have discovered, are a result of various factors — one of them being our initial prediction of the population of certain countries. Other factors include income and world region, as mentioned earlier (controversy surrounding the international agreement on climate change).
A New Outlook
The method applied to our data visualizations is a popular approach among Designers known as “Storytelling”. Robert Kosara, an accomplished computer scientist and a specialist in information visualization, emphasizes the importance of an ordered sequence of steps as well as knowing the fine line between innovation and distraction.
Kosara states, “Storytelling features in this case often include providing different views of the same data features to make them easier to understand, but are less concerned with the overall structure of stories.”
Utilizing Tableau, we initially created a visualization of how prevalent Carbon Dioxide emissions are in which regions of the world, with the US and China being the not so surprising culprits. However, following the principles of
sequence Kosara preaches, we furthered our initial findings by isolating the major culprits with the rest of the world. We then see an alarming discrepancy where the US and China’s emissions hover 8000k while
the rest of the world barely breaks 100k. Ordering these two visualizations, we hope to make apparent how emphatic the difference is going from a general global view to a more numbers-based line chart.
As we initially thought, population plays a major factor in carbon emissions. However, we were not aware of the sheer difference between solely the US and China in comparison to the rest of the world. We draw on a plethora of resources from educated minds that are well-versed in data science, information visualization, design, and CO2 emissions mean environmentally. Combining the major ideas of these sources as well as our own analysis using our data visualization skills; we hoped that we created a post that will allow readers to better view the urgency of the situation from a raw numbers point of view. As well, we hope to have created a more approachable setting to the huge problem of CO2 emissions by embedding engaging data visualizations that, on their own, can depict the analysis made here.
Frohlich, T. C., & Blossom, L. (2019, July 14). These countries produce the most CO2 emissions. USA Today. https://www.usatoday.com/story/money/2019/07/14/china-us-countries-that-produce-the-most-co-2-emissions/39548763/.
Kosara, R., & Mackinlay, J. (2013). Storytelling: The Next Step for Visualization. Computer, 46(5), 44–50. https://doi.org/10.1109/mc.2013.36
NASA. (2018, August 8). The Causes of Climate Change. Climate Change: Vital Signs of the Planet; NASA. https://climate.nasa.gov/causes/
Raineri, P., & Molinari, F. (2021). Innovation in Data Visualisation for Public Policy Making. The Data Shake, 47–59. https://doi.org/10.1007/978-3-030-63693-7_4
Ritchie, H. (2018, October 16). Global inequalities in CO2 emissions [Review of Global inequalities in CO2 emissions]. ; Our World in Data. https://ourworldindata.org/co2-by-income-region