Carbon Emissions and Respiratory Illness

Climate change is an intensely complex phenomenon. It proceeds at an unsteady pace, scientists still struggle to determine the long-term effects, and while research is prevalent, exactly how to solve this issue remains to be decided. Even so, the sum of evidence paints a clear (and terrifying) picture: our Earth is warming and the consequences are becoming increasingly destructive. Scientists have high confidence that the warming temperatures and unstable weather patterns will continue, especially as the production of greenhouse gases remains unhindered. For the United States, this can look like sustained wildfires in the West, rising sea levels, stronger hurricanes, and other environmental repercussions. While those can all be seen as the ramifications on our Earth, it is also important to look at how humans specifically are impacted by greenhouse emissions. Furthermore, the diverse and varied population and demographics of the United States dictates what is already known: the effects will not be the same for everyone.

According to the American Lung Association’s State of the Air, a yearly report based on official air quality data, almost 5 in 10 people live in counties where the air is unhealthy to breathe. Further, the impacts of the air quality varies for different groups of people. Those with preexisting health conditions, in poverty, who belong to a community of color, and more have been shown to be more likely to be at risk. Exactly what this might look like is difficult to determine, but there has been a great deal of research that measures how certain factors can dictate who is affected.

Our project looks at the respiratory illness mortality rate per state against a number of different factors, including carbon emissions, educational attainment rates, and median household income. With this information, we hoped to see how mortality rates varied between states and whether we could see a correlation between that and carbon emission rates. By examining how educational attainment and income might influence these rates, we also want to see how class and other societal indicators might be relevant. Of course, our findings do not indicate any direct causation between these variables, but rather show how some level of correlation might be at play.

Respiratory Disease Mortality Rate

Here, we examine how different factors influence the respiratory disease mortality rate per state. After the removal of two outliers (Texas, California), the following scatterplot measures the mortality rate percentage against carbon dioxide emission rates per millions of metric tons. Here we see a curved, nonlinear pattern with a insignificant correlation coefficient of 0.103. While in our initial hypothesis, we stipulated that higher emission rates would consequently show higher mortality rates, we next test measures of class and wealth as influencing factors.

Income vs. Mortality Rate

The scatterplot below measures the mortality rate against median income. Now, the relationship appears to be much more linear, with a correlation coefficient of -0.709. As the median income increases, the percentage of mortality rate tends to decrease.

% of BAs vs. Mortality Rate

The scatterplot below measures the mortality rate against educational attainment through the percentage of adults aged 25 and older with a Bachelor’s Degree. Once again, there is a negative linear relationship, with a correlation coefficient of -0.074.

The more significant correlation coefficents in the previous two graphs have interesting implications for our research. Regularly considered to be definitive indicators of class, income and educational attainment seem to have a stronger relationship with mortality rates than carbon emissions. While there is not sufficient evidence to claim a causal association, these results do support well-known figures about the discriminatory housing policy history in the United States. After years of redlining and gentrification, particularly in cities, communities of color and low-income families tend to make up the majority of those living in closest proximity to energy plants and refineries (see 1).

Respiratory Disease Death Rate vs Political Party Majority per State

From the box and whisker plot below, we see that the death rate for respiratory diseases is, on average, much lower among democratic-majority states than republican-majority states. The first quartile for republican-majority states, about 43%, is higher than even the third quartile of the democratic-majority states, which is about 42%.

States that have a democratic majority tend to be states with large cities; this implies that democratic-majority states may typically contain more pollution than republican-majority states, which tend to be more rural. Due to this connection, we may want to consider other factors for why republican-majority states seem to have a higher death rate.

One consideration is that the Republican Party places less of an emphasis on the importance of climate control and air pollution than the Democratic Party. Due of this, republican-majority states may in turn place less of an emphasis on controlling pollution. As a result, there may be more cases of respiratory disease, and thus, a higher death rate.

Education and Public Health: A Carbon Emissions Point of View

Climate-induced disruptions are increasing in frequency and intensity, in part due to human activity. It has been shown that public health issues can be linked to such disruptions; The CDC has found that “the health effects of [climate-induced] disruptions include increased respiratory and cardiovascular disease, injuries and premature deaths related to extreme weather events, changes in the prevalence and geographical distribution of food- and water-borne illnesses and other infectious diseases, and threats to mental health.”2 Thus, if we care about public health, it seems to make sense to care about reducing carbon emissions.

Solutions aimed at carbon emission reduction tend to focus on mitigation and adaptation measures, and successful implementation of either strategy requires an informed and educated citizenry. Several studies have demonstrated the potential efficacy of education programs developed specifically for climate change mitigation (see 3, 4). However, since targeted climate change education is less common at present than other forms of higher education, we wanted to explore the potential connection between general educational attainment and carbon emissions.

At the state level, how does individual educational attainment affect carbon emissions?

As the plot shows, there seems to be a slight negative relationship between attainment of higher educational degrees and per capita carbon emissions. This result serves to support the notion that even general higher education programs, producing a more educated populus, can be an important step towards reducing carbon emissions to a more sustainable level.

Proximal Measure of Education

What about a proximal measurement for education–income–and it’s relationship with per capita C02 emissions?

We can see that the distribution of median income looks very similar to that of Educational Attainment. Again, there appears to be a slight negative correlation between median income and per capita carbon emissions.

Why is this result important? Though this graph may suggest that higher income can lead to lower carbon emissions, this is unlikely to be the case given that there is significant evidence to support the opposite conclusion. Several studies have shown the association between income and carbon emissions is positive in the US (and the rest of the world), meaning that higher earners tend to be responsible for higher yearly emissions (see 5, 6).

Limitations and Future Exploration

The findings that attaining a higher level of education may serve to mitigatory tactic to reduce the citizenry’s carbon footprint are preliminary. Our data limits us to groupings by each state. State groupings were not the best way to determine any association between income and per capita carbon emissions, so there is reason to suspect they may not be the best way to measure the degree to which general education affects carbon emissions, either. Perhaps a better method would be is to first stratify by income, and compare the carbon emissions of earners within each income group, separated by level of educational attainment. Controlling for income as a preliminary measure could provide a more precise answer to the question during future exploration.

In Conclusion: What Are The Next Steps?

After analyzing a number of different variables, we see that there may be multiple factors that link to death from respiratory illnesses; in particular, educational attainment level, median income, and the dominant political view of each state seemed to be significant factors. However, our initial hypothesis–that carbon emissions per state were a leading cause to the death rate from respiratory illnesses–did not seem to be as significant as we thought. Nevertheless, the links we found imply that ignorance may be at the root of everything. If people are not aware of the damaging effects of climate change, we cannot effectively prevent the effects from taking place.

If there truly do lie links to a higher death rate from respiratory illnesses, then educating people about the importance of climate control and the negative effects pollution has on both yourself and the environment could be an important step to take. However, we cannot simply generalize from our analyses–there may have been lurking variables that hadn’t been accounted for that produced these results. Nevertheless, it is still important to raise awareness on the already-researched issue of global warming and pollution. We may be able to save lives and make the earth a better place to live if more and more people are aware of the damages of air pollution.