The poorest third of U.S. counties will likely lose up to 20 percent of their incomes, and regions such as the Pacific Northwest and New England will gain economically over the Gulf and Southern states, if climate change continues unmitigated through the end of the century, according to a new study co-led by two UC Berkeley researchers and published today in the journal Science.
The researchers, who examined the economic consequences of climate change for the country, conclude that for every 1-degree Fahrenheit increase in global temperatures, the U.S. economy stands to lose about 0.7 percent of its Gross Domestic Product, with each degree of warming costing more than the last.
Widening U.S. economic inequality
The study’s co-authors describe the country’s future as being on par with the Great Recession or, in the Midwest, akin to the Dust Bowl of the 1930s, possibly resulting in the nation’s largest-ever transfer of wealth from the poor to the rich.
The analysis was led by two researchers from UC Berkeley: Solomon Hsiang, Chancellor’s Associate Professor of Public Policy and principal investigator for the Global Policy Lab at the Goldman School of Public Policy; and James Rising, a Ciriacy-Wantrup Postdoctoral Fellow in Berkeley’s Energy and Resources Group.
“Climate change is going to be like a huge transfer of wealth from some people to others,” said Hsiang. “This is kind of analogous to a tech boom in one region of the country and industry collapsing in another region. It’s going to make the current economic cleavages in this country even bigger.”
Other study contributors included leading climate researchers, economists and risk assessment experts from the University of Chicago, Rutgers University and the Rhodium Group — members of the Climate Impact Lab consortium with the Berkeley team — along with researchers from Princeton University and RMS. Co-lead author Amir Jina, of the University of Chicago, was previously a visiting researcher at Berkeley’s Goldman School of Public Policy.
Together, they combined 116 climate change forecasts and numerous economic analyses developed by scientists around the world to assess costs and benefits of unmitigated climate change on crime, agriculture, energy, labor, coastal communities and mortality.
Their key findings include:
- Rising mean sea levels linked to stronger, more frequent tropical cyclones will amplify storm tide heights and extend floodplains, worsening problems for low-lying coastal cities. The severe weather will inflict direct annual economic damages of 0.6 to 1.3 percent of GDP for South Carolina, Louisiana and Florida in the median scenario.
- Agricultural yields in the Midwest will decline dramatically with rising global mean surface temperatures.
- Annual national mortality rates will rise by roughly five deaths per 100,000 people for each degree Celsius increase in temperature.
- Electricity demands will increase for all regions except the Rockies and Pacific Northwest, as rising demand due to hot days will more than offset falling demand from cool days.
- The number of hours worked will decline about 0.11 percent for each additional degree in rising global mean surface temperature for workers who are not generally exposed to outdoor temperatures, and by 0.53 percent for high-risk, outside workers. The high-risk employees account for about 23 percent of workers in sectors such as agriculture, construction, manufacturing and mining.
- Property crimes will increase in the Northeast as the number of cold days decreases. Meanwhile, violent crime rates will increase across the country at about 0.9 percent per each additional degree Celsius in global mean surface temperature.
Focusing on high-value targets
The study results can help everyone from policy-makers and public utilities officials to farmers and law enforcement officials, as well as those in the tourist industry and disaster relief organizations.
“This helps us focus on high-value targets,” said Rising. “And while agricultural impacts are quite big, human health turns out to be most important.”
In their study, the researchers note that populations may relocate or businesses may opt to move their operations, but the adjustments are unlikely to substantially change the study’s projections.
Another major finding, Hsiang said, is a forecast for extremely uneven distribution of the costs of climate change across the country.
For example, higher and higher temperatures in the South, which is already very hot, will cause climate change to take an even bigger toll in human lives in that region than in others. And much of the farming in the Midwest, long considered the nation’s breadbasket, will literally dry up under increasing heat.
Building a global model
The researchers used a flexible, high-resolution, county-by-county model – the first of its kind – that is based on the scale and structure of the country’s population and economy in 2012. They were able to calculate the impacts of a business-as-usual approach to climate change in the U.S. through the end of the century, primarily reporting results for the benchmark period 2080 to 2099. They estimate their results’ reliability at 90 percent.
Rising, a former software engineer, said that the pioneering study would not have been possible without advances in computing and big data.
While the researchers are excited about the help that their findings can offer for the United States, they are just as enthusiastic about the scalability of their model and are working to go global with it, applying updates from new econometric results and climate model projections still in the making. Their model also could be expanded to cover additional sectors such as social conflict and human migration.
Co-lead authors Hsiang, Rising, Jina and Robert Kopp, a professor of earth and planetary sciences at Rutgers University-New Brunswick, are members of the Climate Impact Lab, a consortium behind the efforts to expand the model globally.
“There are thousands of people around the world working on this problem,” said Hsiang. “What we are trying to do is to build a system, stitching together all the different models and building ‘the machine in the middle’ to bring it all together. This is how we should be doing policy, as a society.”