The number of solar panels at the shortest distance from a house is the most important factor in determining the likelihood that that house has a solar panel, relative to a host of socio-economic and demographic variables. This is shown by a new study by scientists using satellite and census data from the city of Fresno in the United States and using machine learning. Although peer effects are known to be relevant for sustainable energy choices, very high resolution data combined with artificial intelligence techniques were needed to underscore the overarching importance of proximity. The result is relevant for policies that aim at a wide deployment of solar panels to replace unsustainable fossil energy production.
“It’s almost like seeing a solar panel out of the window, you decide to install one on your own roof as well,” says study author Leonie Wenz of the Potsdam Institute for Research. on the impact of climate (PIK) in Germany. “Of course, you would think that other factors are more relevant, for example income or education, or word of mouth within the same social network such as a school district. So we compared all these different options, and we were amazed at the result. Turns out no, geographic distance is really the most important factor. The more signs there are in a short radius around my house, the more I’m likely to have one too. “
The peer effect halves the distance from a football field
“The probability of putting a solar panel on your roof drops to about half the distance from a football field,” says Anders Levermann of PIK and LDEO at Columbia University in New York City, who is also the author of the study. “The contagion effect is strongest for a short radius around a house with a solar panel and decreases exponentially the further the panels are moved away. This is a remarkable robust characteristic that is more pronounced in low income neighborhoods.
Scientists have just made the data talk. “We combined the population census data for each district with high-resolution satellite data capable of identifying all of the solar panels in Fresno,” says study author Kelsey Barton-Henry of PIK. “Next, we trained several machine learning algorithms to find the relationship between people’s socio-economic background and their likelihood of having a solar panel.”
“Seeding solar panels where few exist can overthrow a community”
“The results suggest that seeding solar panels in areas where there are few, can overthrow a community,” Levermann concludes. “If more solar panels lead to more solar panels that can generate some sort of tipping point – a good one this time. The climate system has a number of extremely dangerous tipping points from the West Antarctic ice cap to the North Atlantic Current. ” Wenz adds: “Therefore, researching climate decisions to identify positive social tipping points, large and small, is important to ensure a secure future for all.”
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Material provided by Potsdam Climate Impact Research Institute (PIK). Note: Content can be changed for style and length.