Understanding Areas for Environmental Public Policy
Introduction
In recent years, increased awareness over climate change and the crises that the planet is facing has led to a better understanding of how various factors affect the planet. Often, CO2 emissions are a part of the conversation when thinking about climate issues. Additionally, there has been debate in both the political and public spheres about energy sources and if renewable energy sources are needed to help the planet. So, are CO2 emissions and energy usage related? Are there other related factors as well? According to the World Development Indicators dataset from the World Bank, CO2 emissions and energy usage seem to be highly correlated, more so than other potential factors. This general correlation is illustrated in the data, but more specifically, key differences in the rate of increase for China and the United States suggest how different policies can help improve the climate crisis.
Understanding the relationship between energy usage and CO2 emissions
There is a clear relationship between energy usage and carbon emissions data from the World Bank dataset. More specifically, plotting energy usage and CO2 emissions show an increasing and relatively linear trend. After plotting the trendline in figure 1, we see that the correlation coefficient is 0.978, indicating that there is a very strong positive correlation between the two variables. Evidently, energy usage is related to CO2 emissions, which presents an area in which policies can be created to help reduce the impact of human actions on the planet.
Figure 1: Energy Usage vs. CO2 Emissions, Logarithmically Transformed
Understanding other factors
There are a variety of potential underlying related factors of the increase in energy usage and CO2 emissions to also be investigated. Firstly, by plotting the population data across all regions of the world from the dataset across time, we see that there is a steady increase in population across the world from 2002 and 2012. Knowing this, we can hypothesize that with the growing world population, energy usage and also CO2 emissions will naturally increase, simply because there is more demand for energy in the world. Sure enough, when plotting population against CO2 emission and energy usage data, we see that as population increases, energy usage and carbon emissions also increase. Indeed, “the global emission of CO2… is steadily increasing since the beginning of the industrial revolution” (Homberg & Erdemir, 2015, p. 181). Unsurprisingly, the relationship is nearly identical for both energy usage and CO2 emissions, because we already know that these two variables have very similar trends. It should be noted that the relationships we see are not very linear, however there still appears to be a pattern of increase in the data points. When logarithmically transforming the data, we get a better view of the positive correlation between the variables (figure 2). However, controlling population to improve the climate could be impactful, but not very ethical and would present many potential issues for policy making.
Figure 2: Population vs. carbon emissions and energy usage (logarithmic)
Another variable, internet usage as shown in figure 3, is statistically significant with CO2 emissions and energy usage, however the rate of increase is very different from that of the prior mentioned variables. Internet usage is not as strong of a correlation to CO2 emissions than energy usage. Therefore, internet usage could be a secondary area to create policy changes or investigate for climate change research, but energy usage and CO2 emissions still remain the strongest correlation and thus the focal point for climate issues from this data exploration.
Figure 3: Year vs. Internet Usage, CO2 Emissions and Energy Usage, Aggregated
Additionally, when plotting GDP across all countries in the dataset against year, we see a significant increase in GDP across all countries in the world throughout the years. From here we can hypothesize that as a nation’s GDP increases, so will their energy usage and CO2 emissions. Again, the relationship between GDP and energy usage is not linear, but we still see an increasing pattern of data points as GDP increases in general. When viewing the logarithmically transformed data, we have a better idea of the positive correlation between GDP and energy usage (figure 4). This presents an area of exploration for looking into different GDPs around the world and seeing if there are differences in CO2 emissions and energy usage that could be explained by differences in public policies towards climate change.
Figure 4: GDP vs energy usage (log)
Looking closer at China and the United States
By looking specifically at certain countries, the effects of public policy that we have discussed thus far are illustrated. We can view a bubble plot of countries, with carbon emissions as the size of the circle, and the nation’s GDP with the hue of the circle. This technique is similar to the popular Gapminder bubble charts by Hans Rosling that use simple encoding to help illustrate multiple values (Kosara & Mackinlay, 2013, p. 47). We see that the United States and China are significantly bigger than the other countries, indicating that they produce the most carbon emissions (figure 5). Interestingly, looking at the hue of the circles, we see that the United States actually has significantly higher GDP compared to China.
Figure 5: GDP and emissions vs. country bubble plot (size = emissions, hue = GDP)
Specifically looking at China and the United States, we see that both countries have increased GDP over the years (figure 6). The United States’ GDP ranges much higher than that of China’s, however China’s GDP is increasing at a faster rate, and will most likely catch up to the United States. Interestingly, we also see that both energy usage and CO2 emissions are increasing at a rapid rate for China, but we do not see that same trend for the United States. Instead, the relationship between energy usage and carbon emissions versus time seem to be relatively flat for the United States. In this dataset, we see that although China has much lower GDP than the United States, their carbon emissions and energy usage has risen above that of the United States in recent years.
One reason that may explain why China exhibited a rapid increase in energy usage and CO2 emissions, “is its energy structure, which is dominated by coal” (Peng et. al, 2018, p. 428). Out of concern for “self-sufficiency and energy security”, China rapidly used and produced coal (Peng et. al, 2018, p. 429). This helps to answer the question of why China’s energy usage increased so quickly compared to the United States. A reason why the United States shows a relatively flat line is because of regulatory laws in place. Under the Clean Air Act, it is required that “EPA (U.S. Environmental Protection Agency) [develops] regulations for categories of sources that cause or significantly contribute to air pollution that may endanger public health or welfare” (Durkay, 2017). Thus, this could contribute to the carbon emissions coming from the U.S. to maintain a steady rate. This distinction in rate between the United States and China, even though globally, the trends appear to all show increasing CO2 emissions with increased energy usage, illustrates the importance of viewing trends and patterns on both general and specific levels (Makulec, 2020). This also further emphasizes the ability of policy to have a positive impact on these environmental factors.
Figure 6: GDP, energy usage and CO2 Emissions vs year for China and United States
Reflection on factors and conclusion
Although other variables also show statistically significant relationships with CO2 emissions, energy usage is the only variable with such an identical trend and such a strong magnitude. For instance, looking at three different sets of data in a time series, we see that CO2 emissions and energy usage have very similar plots, in fact it is so similar that we actually see the same dips for years 2002 and 2009 for both of these sets of data. Thus, we believe that this correlation between energy usage and CO2 emissions represents one of the most impactful areas for investigation to improve the climate crisis by targeting policies towards decreasing energy usage and CO2 emissions together, according to this dataset. Other variables with correlations to CO2 emissions, such as internet usage, also present areas for public policies and further research into best environmental practices. We also see how looking at GDP can further illustrate the relationship between CO2 emissions and energy usage in two leading countries, the United States and China. From researching current energy use policies for both countries, the difference in increase rate can be explained. Therefore, energy usage appears to be the most directly correlated to CO2 emissions, and thus the most impactful potential place to create positive changes for the environment.
Works Cited
Holmberg, K., & Erdemir, A. (2015). Global impact of friction on energy consumption, economy and environment. FME Transactions, 43(3), 181–185.
https://www.mas.bg.ac.rs/_media/istrazivanje/fme/vol43/3/01_kholmberg.pdf.
Jocelyn Durkay, G. D. B. (2017, December 28). States’ Reactions to EPA Greenhouse Gas Emissions Standards. National Conference of State Legislatures.
Kosara, R., & Mackinlay, J. (2013, January 15). Storytelling: The Next Step for Visualization. Computer, Vol 46, no. 5, pp. 44–50.
Makulec, A. (2020, March 11). Ten Considerations Before You Create Another Chart About COVID-19. Medium.
Peng, X., Adams, P. D., & Liu, J. (2018, December 13). China’s new growth pattern and its effect on energy demand and greenhouse gas emissions. Global Energy Interconnection.
https://www.sciencedirect.com/science/article/pii/S209651171830063X.
