Perceptible climate warming amplifies how education increases climate concern in the US
With a majority of Americans now believing that climate change is caused by human activities, two prominent predictors of concern in the US are the level of education1,2,3 and perceptible climate change that people experience4,4,5,6,7,8,9,10,11. This concern is moderated by political affiliations12,13,14, economic situations15, value and belief systems2,14,16,17,18,19. In the US, where the two main political parties have quite different climate mitigation platforms, climate concern strongly predicts political affiliation20.
In contrast to these factors that correlate with climate concern, education arguably serves as the more causal factor, by equipping people to understand climate science as a means of explaining observable change16. In advanced economies, people with more education are more likely “to say they are willing to adjust their lifestyles in response to the impact of climate change”21.
Here, we propose that the effect of education should increase with local climate warming. Under this hypothesis, the concern increases due to observable climate-related events9,10,11 combined with education5. Education acts like a lever, in that the higher the average education level in a population, the more climate concern will increase in response to local climate change.
We address this hypothesis by combining data, at the US county level, on climate concern, education level, and health risks of increased heat, together with a measure of climate warming in the state over the last decade.
Data for climate concern use the 2023 county-level estimates from the Yale Program on Climate Change Communication (YPCCC). Since the YPCCC climate opinion data, consisting of 73 related opinion estimates, are highly correlated, we reduced the dimensions through principal component analysis. This yields one major principal component, PC 1, which captures 40% of the variance in the county-level data of YPCCC 2023, with loadings that are clearly indicative of concern about climate change (see Supplementary Table S2). We refer to the PC 1 score as the “climate concern” estimated in each county.
For education levels, we use US Census 5-year (2018-2022, county-level) estimates of percentage bachelor’s degrees for adults 25 and over (see Methods and Data Availability). We also test for an effect at other levels of educational attainment, from 9th grade to graduate degrees.
As a measure of warming, we use the aggregated statistic of mean temperature increase, which serves as a proxy for the more episodic, tangible change that people experience21. A rising mean temperature leads, for example, to more frequent hot summer days6, increased wildfires, flooding, and storm activity22,23, along with prolonged droughts and heatwaves24, and shifting seasons11,25. In Wisconsin, an increase by less than 2 ∘C since 1950 has brought more frequent days above 30 ∘C, heat indices exceeding 40 ∘C, and lakes freezing later in winter. Florida has seen increased hurricane activity, tidal flooding and severe heavy rainfall events.
As a parsimonious proxy for perceptible recent warming, we define “state-level warming” as a fractional measure that compares the past decade of warming in the state to a baseline average. For each state, we use the average the past ten years (2014–2023) of temperature anomaly determinations (in ∘Celsius) determined by NOAA26, Ta, which we then divide by \(\bar{T}\), the mean annual baseline (from 1971 to 2000) temperature (∘C) throughout the state. Since this fraction, \(W={T}_{a}/\bar{T}\), varies geometrically—for a 1 °C increase, it would be 0.2 in Maine (annual ave 5 ∘C) but only 0.05 in Florida (ave 21.5 ∘C)—we take its logarithm, \(\ln (W)\), as human intuition of such statistics tends to be logarithmic27. As a comparison, we also add the Heat and Health Index (HHI) from the US Center for Disease Control and Prevention to capture “communities where people are most likely to feel the effects of heat on their health”28.
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