Last few years the US has been in the news outlets for various important reasons. One of them is its reluctance for fighting the climate change. Last year in 2020, the former President of the US- Donald Trump – officially withdrew from the Paris Accord. An agreement between the world vast majority of the countries to fight the climate change. But the conservative media, experts, and Trump were in denial about the significant effects of the climate change. Citing one of those reasons, the previous administration also objected that the USA is paying a lot more extra than it should as it is essentially covering the cost for the developing nations like India, Pakistan, Vietnam, etc.
In a way, that argument is true. The US indeed agreed to pay billions of dollar, under Obama Administration, to fight the climate change especially when the US is not personally getting affected by it. In my alternative view, the US could indeed excuse themselves if that’s the only case. But the bigger argument which Conservative America seems to be comprehending are two folds: 1) sooner or later every corner of the world is going get engulfed by the effects of Global Warming in an irreversible way. And, 2) I hypothesize that being the largest GDP, as per the data below, strongest nation in the world, the fossil-fuel related policies of the USA are the reason the US being the the leader in emitting CO2 gases over the past 50 years. So, the question is why the US Government shouldn’t take accountability for it.
I want to present world data on Co2 emissions and compare it with the CO2 emitted by the US industries and households in last 50 years. I believe it could give strengthen (or weaken) my views on regardless of the administration the US should take responsibility for Climate Change and contribute for the humanitarianism cause.
Moreover, upon research, I learned that climate change is suspected to be one of the key factors behind the immigration issues the US is facing today. So, I would also like to shed some light on the the CO2 Emissions between the the USA and Latin America. In this article, I want to make some efforts to spread the awareness on how the US and the rest of the world need to control their CO2 emissions, and adopt clean and green energy.
To summarize, the hypotheses and research questions are:
- Being the no. 1 GDP of the world, the US is largely responsible for the CO2 Emissions in past 50 years.
- How is the world doing in last 50 years in total and per capita CO2 emission? Is it alarmingly rising?
- As Trump claimed China (Far-East Asia Region) and India (South Asia Region) are (largely) responsible for the climate change and why should the US pay for it. So, I want to compare the CO2 Emissions between the USA and Far-East and South Asia regions.
- Recently, due to rising sea levels and many other reasons, migrants from the hispanic Island countries (primarily Central America) have been rushing to the US ? I want to see if they facing the wrath of the nature due to their CO2-related policies or of the other countries. I would mainly be comparing the CO2 data of Latin America with the USA.
Initially I wanted to search for the dataset regarding the usage of the solar energy in California but there was no success in finding that even after hours of research. Also, I realized it should rather be more interesting to find out the the trends in the the usage fossil-based fuel and its effect on the environment due to CO2 emitted by such fuel. So, I landed on The World Bank, which provided access to the data for this project.
Then OpenRefine was used to clean the dataset and, finally, Tableau Desktop was used to create compelling visualizations and stories to address my hypotheses and research questions. In the end, I posted the tableau workbook on Tableau Public.
Step 1: After the refinement, I uploaded the .CSV file on the Tableau by clicking on the “Data Source” tab on the bottom as you can see in the picture below.
Step 2: To upload the dataset, I uploaded the .CSV dataset saved in local disk.
Step 3: After uploading the dataset, I went to the “Sheet” tab on the bottom, it gave me wings to play with he data and make them visualize in real-time fashion.
Step 4: Since, it is a region-and-country-based data, I first of all fetched the Longitudinal and Latitudinal data to create a map.
Step 5: Here Tableau automatically creates feasible data visualization in the “Show Me” section on the right hand.
Step 6: Besides the to make the data visualize, I predominantly used 4 blocks shown below. From left to right, the first block denotes the tables and measures. Tables are mainly discreet data and measure are continuous data. The second block let me manipulate the data using the filter the and marks section. Filter section allowed me if I wanted to filter any particular region(s) or countries(s) and “mark” section let me visualize the key data I want to visualize in the visualization panel. The third block is for adding tables into X and Y axis. The fourth block is legend. It allowed me to show the contrast between two ends of the dataset and everything in between.
Note: Step 5 and Step 6 are not linear. There is a lot of iterations and revisiting back and forth to create the perfect visualizations that addressed my hypotheses and research questions.
Step 7: In the end, I created a storyboard that was focus on the storytelling by focusing on 3 key visualizations. Basically, all the visualizations I used were already created in their individual sheets. And, I just synthesized the key screens by highlighting vital information that assist viewers in walking through the stories.
Let me first walk you through the final visualization and how they addressed the research questions that I posed in the interoduction. After, I will go through the Research & Testing Methods, and Revisions I made.
Hypothesis 1: Being the no. 1 GDP of the world, the US is largely responsible for the CO2 Emissions in past 50 years.
Verdict: My hypothesis stands right as the US is quite higher than the world’s average CO2 emission.
Research Question 2: How is the world doing in last 50 years in total and per capita CO2 emission? Is it alarmingly rising?
Answer: For last decade and more the CO2 Emission is alarmingly increasing the shade is getting darker and darker until the pitch black is about to start.
Research Question 3: As Trump claimed China (Far-East Asia Region) and India (South Asia Region)are (largely) responsible for the climate change and why should the US pay for it. So, I want to compare the CO2 Emissions between the USA and Far-East and South Asia regions.
Answer 1: Per capita, America is evidently emitting more CO2 than India and other South Asian Countries.
Answer 2: East-Asian region is home to many industrious countries like HongKong, Taiwan, South Korea, Japan, and China. So it would be interesting to see these countries, at some extent, do pollutes the environment more than the other industrious countries like Canada, Australia, and New Zealand. Yet, the USA is apparently emitting more CO2.
Final Verdict: Contrary to Trump suggested, the data tell otherwise. America is quite comprehensibly emitting CO2 in last 50 years than India and China.
Research Question 4: Recently, due to rising sea levels and many other reasons, migrants from the hispanic Island countries (primarily Central America) have been rushing to the US ? I want to see if they facing the wrath of the nature due to their CO2-related policies or of the other countries. I would mainly be comparing the CO2 data of Latin America with the USA.
Answer: If I believe the data then I can say that immigration issue is largely caused by the US and other industrious countries that has continually risen the sea levels. Latin Americans are facing a consequence that they are not responsible for anyway. As you can see, compare to the US, these countries have been emitting quite less CO2.
Want to see how I came with these final visualizations? Let’s see how research and testing helped me come to these results.
RESEARCH & TESTING METHODS
I adopted a non-linear approach for refining the my designs and visualizations of the projects. Meaning, I didn’t wait for my project to complete to initiate the testing. My philosophy is design, test, refine, repeat. As soon as I hit minimal working design (see below: MVP Features), I talked to my testers to get their feedback.
Also, I had an offline access to both of my research participants. So, many, quick, short testing were made possible.
With each user testing, I jotted down the key points I learned from our discussions about what they value and their purpose while looking at the data visualization.
What my users value?
- Only salient information. Other information is clutter.
- Relevant color codes. They appreciate a color range of Green-Black is being used for this project. Black emblems carbon dioxide and Green symbolizes pro-environment.
- They want only salient but prefer to be told body and loudly. Powerful storytelling precedes the strong emotions. And, strong emotions precedes in act to bring the change.
ITERATIONS & REFINEMENT
Version 1: As shown below, I learned from my users that harmonious colors are not enough. The color should be pertinent to the project. Hence, I decided to denote Black for Carbon Dioxide Emission and Green for Environmental-practices.
COMPARISON B/W TWO REGIONS:
Version 1: I came up with two version and tested them with my users. The first version is as shown below where two regions are in separate from each other.
Version 2: In the second version, I came up with the visualization by comparing the the regions in the same map, adjacently.
My Decision: I would go for the version 2 since Tableau doesn’t have the functionality to zoom in and out different maps separately. With that said that, the version 2 looks cleaner.
Total CO2 Emission & CO2 emission per capita
Version 1: In this version I came up with linear, continuous chart. It’s pretty wide-spread and easy to understand.
Version 2: In this version I came up with linear, jump chart. It doesn’t just shows the progression but also sudden rise and fall as well.
Version 3:In this version, I came up with a little heavy UI where the area below the data-points were also filed with the corresponding color.
My Decision: I liked the version 2 as it shows the linearity, progression as well as sudden rise and fall in the trend. But, the version 3, despite being a little heavy, demonstrates the severity of CO2 Emissions in today’s world. The purpose of the story is to shake people up from their core so they can start acting towards reducing the carbon footprint. Also, the user feedback falls in line with my perspective.
At the end of this project, I am glad that Tableau helped me to address my research questions and hypotheses successfully. This project is eye-opener for me to push myself towards the activism of environment and sustainability. For next phase, I would like to dig further for finding the correlation between the detriments of the climate change and the mass migration from Central America to the US. I would like to look for the data that demonstrates what rate sea level has been rising at, in Central American and Caribbean countries.
Last but not the least, I firmly believe that whether Left or Right, no administration at the White House should undermine the danger of Climate Change and CO2 Emissions. They’r real. If not for any other Central American countries, the US should start thinking for their island territories like Samoa, Puerto Rico, Virgin Islands, etc. If the sea level rises it will cost America as well.