A recent study co-authored by Minghao Qiu, an assistant professor at Stony Brook University, has found that the climate benefits of solar power in the United States differ significantly depending on location. The research, published in Science Advances, shows that a 15 percent increase in solar generation nationwide could reduce annual carbon dioxide emissions by 8.54 million metric tons. However, the impact varies across regions.
“We wanted to go beyond the national average and understand the finer details of how solar generation affects carbon emissions hour by hour, region by region,” said Qiu, who holds joint appointments with the School of Marine and Atmospheric Sciences and the Program in Public Health. “It’s about producing clean electricity, but also about knowing when and where that electricity replaces the dirtiest generation sources.”
The study was led by Rutgers University with contributions from Harvard T.H. Chan School of Public Health. Researchers analyzed five years of hourly data from the U.S. Energy Information Administration and divided the country into 13 geographic regions to model changes in CO₂ emissions based on increased solar output.
Results indicated substantial differences between regions. In states such as California, Florida, Texas, and those in the mid-Atlantic and Midwest, even small increases in solar power were linked to notable emission reductions. Other areas like New England and Tennessee saw smaller impacts for similar increases.
“If you have limited resources to invest in solar, you want to place those resources where they displace the most fossil-fuel-based electricity,” Qiu said. “That’s where you get the biggest bang for your buck, both for emissions reductions and for public health benefits from improved air quality.”
The interconnected nature of the U.S. power grid means that clean energy produced in one region can lower fossil fuel use elsewhere. For example, a 15 percent boost in California’s solar capacity resulted in daily CO₂ reductions exceeding 900 metric tons in the northwest and nearly 2,000 metric tons in the southwest.
“This interconnectedness means that clean energy investments can have benefits far beyond the state or region where they’re installed,” Qiu explained. “It shows the value of coordinated efforts between regions and across state lines.”
Qiu specializes in analyzing environmental impacts related to energy policies using computational models developed for this project. These models tracked immediate emission reductions when solar replaced fossil fuels as well as delayed effects hours later due to shifts within power plant operations.
In California specifically, a midday increase of 15 percent solar output reduced CO₂ emissions by 147 metric tons during the first hour and another 16 metric tons eight hours later—a result attributed to dynamic adjustments among power plants throughout each day.
“Electricity systems are dynamic,” he said. “When you add solar in the middle of the day, it doesn’t just reduce emissions right away, it can also affect which power plants are running in the evening, which changes the emissions profile later on. Our model was able to capture those subtler, downstream effects.”
These downstream effects have implications for public health since fossil fuel combustion produces fine particulate matter linked to respiratory issues and heart disease.
Qiu believes these findings can guide policy decisions at both federal and state levels as well as inform private sector investments: “Utilities, grid operators, and investors all have a stake in making solar deployment as effective as possible,” he said. “This kind of analysis provides a roadmap for where investments will have the highest returns in terms of CO₂ reduction.”
He emphasized that strategic placement is crucial alongside expanding renewable capacity: “We’re going to need a lot more clean energy to meet our climate targets, but we also need to be strategic,” he said. “The same amount of solar power can have dramatically different impacts depending on where and when it’s generated.”
For companies investing through power purchase agreements aiming for sustainability goals—targeting high-impact regions could maximize climate benefits according to Qiu’s data-driven approach.
Transmission infrastructure is another factor; sometimes excess renewable energy cannot be delivered due to grid limitations resulting in curtailment—unused potential clean energy—which could be addressed through grid upgrades allowing exportation across regions.
Timing is also important since peak demand often occurs after daylight hours when fossil fuels fill gaps left by declining solar output; pairing storage solutions with renewables may help address this issue.
“These findings are directly applicable to decisions being made right now about where to put solar farms, how to design energy storage systems, and how to coordinate clean energy policies across regions,” Qiu explained.
He added that their modeling techniques could extend beyond solar—to wind or hydropower—and simulate combined impacts from multiple technologies working together: “As the energy transition accelerates, we need tools that can help us navigate complexity,” he said. “Our work demonstrates how big data and computational modeling can provide the clarity needed to make informed, impactful choices.”
“This study is about making sure we get the most out of every solar panel we build,” Qiu said. “If we can target our investments to the places where they make the biggest difference, we can accelerate the transition to a cleaner, healthier, more sustainable energy future.”
