Data Source

Data Source

These figures utilize data from the Climate Change in the American Mind (CCAM) project. Led by the Yale Program on Climate Change Communication and the George Mason Center for Climate Change Communication, CCAM consists of national survey data on climate change beliefs collected between 2008 and 2018 (excluding 2009) and includes over 20,000 data points.

Raleigh Goodwin created the plots on this page using the ggplot package.

Citations:

Yale Program on Climate Change Communication (YPCCC) & George Mason University Center for Climate Change Communication (Mason 4C). (2020). Climate Change in the American Mind: National survey data on public opinion (2008-2018) [Data file and codebook]. doi: 10.17605/OSF.IO/JW79P

Ballew, M. T., Leiserowitz, A., Roser-Renouf, C., Rosenthal, S. A., Kotcher, J. E., Marlon, J. R., Lyon, E., Goldberg, M. H., & Maibach, E. W. (2019). Climate Change in the American Mind: Data, tools, and trends. Environment: Science and Policy for Sustainable Development, 61(3), 4-18. doi: 10.1080/00139157.2019.1589300

Plot 1

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Final Version

Version 1

Version 2

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About

In 2018, I ran a pilot study examining the effects of framing on pro-environmental behaviors, including donation to a pro-environmental organization. The results of this experiment showed that only voter status predicted the amount participants were willing to donate. This figure shows a similar, yet more complex, relationship within this data: The effect of voter registration on climate change concern is influenced by one’s party affiliation. Simply put, among republicans, participants who did not know if they were registered to vote showed higher levels of concern regarding climate change than those who knew they were registered to vote. For democrats, independents, and those with no party affiliation, this relationship was opposite; those who did not know if they were registered to vote were less concerned. While democrats were most concerned about climate change, they only reported being “somewhat worried” on average.

Error bars show +/- standard error. For information on the number of participants represented by each bar, see the table below. It is important to note that the number of people who did not know if they were registered to vote was small for each political leaning, reflected in the much larger standard errors.

Table

Average Worry by Voter Registration and Political Affiliation

Registered Voter?	N	Average Worry
Republican
Yes	1651	2.12
No	77	2.27
Don't know	29	2.48
Democrat
Yes	1882	3.18
No	122	3.14
Don't know	25	3.00
Independent/Other
Yes	435	2.48
No	41	2.59
Don't know	13	2.23
No party/Apolitical
Yes	184	2.58
No	172	2.59
Don't know	56	2.09

Version History

Version 1 is the default plot generated by very basic ggplot code. For Version 2, I created meaningful labels and titles for the plot, changed the colorscheme to be colorblind friendly, and added error bars to facilitate comparisons of values. I also changed the theme for aesthetic purposes. For the final version, in order to allocate more space to the plot itself, I relocated the legend to the top of the plot. For aesthetics, I added transparency to the bars. For clarity, I created more meaningful labels for the y-axis and added a subtitle that displayed the survey question.

Plot 2

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Final Version

Version 1

Version 2

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About

Participants may be reporting less concern in Plot 1 because they erroneously do not percieve themselves to be at personal risk due to climate change. Over time, participants progressively predicted higher levels of risk for plants and animals, future generations, and developing countries. However, participants continuously underestimated the risk posed by climate change to themselves and their own country (the USA).

Version History

Version 1 of this plot is once again default ggplot output. For Version 2, I changed the theme and cleaned up labels for the axes, legend, and facets. For the final version, I switched to a colorblind friendly palette, changed the theme again to match the other plots on my dashboard, and moved the legend into the empty space on the bottom right. I also added a title and subtitle to help with plot interpretation and percent signs to the y-axis labels.

Plot 3

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Final Version

Version 1

Version 2

Version 3

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About

Despite arguably underestimating the risk posed by climate change, as illustrated in Plots 1 and 2, participants in 2018 largely supported policies aimed at mitigating the effects of global warming. All four policies included in the survey recieved support from the majority of participants.

Table

2018 Support for Four Climate Change Mitigation Policies

Policy	N	Strongly Support	Somewhat Support	Somewhat Oppose	Strongly Oppose
Fund Renewable Energy Research	2355	47%	41%	8%	4%
Regulate Carbon Dioxide Emissions	2350	34%	46%	13%	7%
Regulate Coal Power Plant Emissions	2363	26%	46%	17%	10%
Regulate Utility Energy Sources	2353	28%	40%	20%	12%

Version History

Version 1 is once again the default ggplot output. For Version 2, I switched to a colorblind friendly palette, fixed messy axis labels, and flipped the plot on its side to help with readability of the policy labels. For Version 3, I fixed axes labels to incorporate percent signs and a more in-depth description of each policy. I also added a title to orient the audience on the survey question and changed the theme to match the other plots. Because the bars add to 100%, I stacked them to make comparisons between policies easier. For the final version of this plot, I added transparency to the bars, fixed the subscripts in the y-axis labels, and moved the legend to the top of the plot to give the plot itself more room. I also changed the title to aid in interpretation of the visual and added a subtitle that shows the survey question.