If homes were equipped with real-time displays showing the fluctuating price of energy throughout the day, the average person could make better choices about when to do laundry or run the dishwasher.
That’s the kind of data-informed decision making that Jessika Trancik, Atlantic Richfield Career Development Associate Professor in Energy Studies at the Institute for Data, Systems and Society, dreams about. The Trancik Lab builds extensive data sets to evaluate the economic and environmental impacts of energy technologies over time—or, as she puts it, “get under the hood of technologies and see how they could improve.”
In a study published in the August 2016 issue of Nature Energy, Trancik and her colleagues found that 87% of day-to-day driving needs could be met by existing, affordable electric vehicles charged only once a day, such as overnight—“which would more than meet near-term US climate targets for personal vehicle travel,” Trancik says.
That conclusion was arrived at by integrating several huge data sets, including second-by-second GPS data from Texas, Georgia, and California, as well as comprehensive national data based on travel surveys. The 87% figure was markedly similar across diverse cities, from densely packed New York City to sprawling Houston.
In 2016, the Trancik Lab also released an app (and accompanying paper in Environmental Science and Technology) demonstrating that the cost of lower-carbon-emitting vehicles—both electric and conventional—isn’t necessarily prohibitive. The app, Carboncounter.com, indicates that cheaper cars, taking into account operating and maintenance costs, are actually the most environmentally friendly.
Similarly, tracking and analyzing dramatic cost reductions in solar panels can reinforce the value of R&D support. And large-scale evaluation of diverse wind and solar energy storage methods can allow for broad cost optimization.
“These problems are often put out there as very difficult problems to solve,” Trancik said on a 2017 episode of NPR’s Outside/In. “They’re actually not, in my view, that difficult to address—but we need to just put all of the numbers on the table.”
This story was originally published in June 2017.