University of Maryland geographical sciences researchers are the first to use highly detailed consumer data to see how specific segments of the U.S. population affect climate change.
In a new research paper published in Environmental Research Letters, Associate Professor Giovanni Baiocchi and Associate Professor Kuishuang Feng paired highly detailed data about Americans’ geographical locations and lifestyle tendencies with information about their carbon dioxide emissions. They worked with Klaus Hubacek, a former department professor now at the Netherlands’ University of Groningen.
Such variables were more telling than income alone, the current go-to for researchers hoping to better understand individuals’ estimated emissions contributions.
“We basically use the same data as marketing people trying to sell products,” said Hubacek. “[As a result], rather than one-size-fits-all approaches, we are able to differentiate households based on location-specific variables to better design emission mitigation strategies.”
They used the Environmental Systems Research Institute Community Tapestry Segmentation System, a data set that classifies every U.S. census tract into one of 65 descriptively named segments such as “Sophisticated Squires” or “Inner City Tenants.” Segment classifications are based on consumers’ dominant socioeconomic variables, including income; household location, size and type; population density; commuting information; education level and race.
Consistent with prior research, the researchers found that higher-income groups are the greatest emissions contributors. They also found that the most emission-intensive Americans tend to live in larger suburban homes, own multiple vehicles and commute solo to work.
However, other segments with relatively high household incomes, like those labeled as “Laptops and Lattes” and “Metro Renters” often have less environmental impact because they live in densely populated areas in smaller dwellings.
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