Scientists develop environmental justice lens to identify neighborhoods vulnerable to climate change

A new ability to identify urban settlements, down to the levels of blocks and buildings that are most vulnerable to climate change, could help ensure that mitigation and resilience programs reach the people who need them most.

This method, developed by the Oak Ridge National Laboratory of the Ministry of Energy, is based on research into environmental justice - a key aspect of the federal government’s strategy to manage the negative effects of climate change. But so far, scientists have had limited tools to assess and ultimately predict socioeconomic risks in environmental events, especially when multiple forms of vulnerability interact.

“Climate modelers are very good at telling us exactly when and where bad things will happen in the physical world. But we also have to think about where people are, “said Christa Brelsford of ORNL. “Most of the world’s population lives in cities. To analyze climate risk, we need to think about impacts and vulnerabilities - and there are many vulnerabilities in the urban environment. “

ORNL project leader Nagendra Singh said that climate modeling mainly focuses on “where things like a one-degree increase in temperature will happen, or where there will be more heat waves in our climate models.” But we have not emphasized the fine details of these impacts — how climate events will disproportionately affect different communities. Applying this geodemographic data to models is a good approach to generating the information needed by decision makers. “

ORNL scientists used microdata from the U.S. Census to create a synthetic population, bringing together the individual composition of urban communities to assess the vulnerability and ability of settlements to adapt to climate events. The team collected demographic information from census databases such as income level, age, gender, ethnicity, and housing. They generated data on the characteristics of the building to determine whether the structure was an office, shop, apartment building or other type of structure by applying machine learning techniques to satellite images. The combined data generated a high-resolution analysis of different impacts on socio-economic groups down to street level.

ORNL scientists developed and tested the platform using data from the Atlanta metropolitan area to characterize neighborhoods, and then assessed the potential impacts of urban heat islands on various demographically defined groups.

The methodology is based on ORNL’s long-standing expertise in measuring population and environmental change, including the Laboratory Institute for Climate Change Science and tools for modeling human dynamics developed as part of national security research.

“Infrastructure is absolutely important for cities. People are absolutely important for cities. So is the environment and climate and all the natural physical characteristics,” Brelsford said. “We cannot understand cities as a whole without thinking about how all these different sectors interact.

When science brings together climate factors, people, buildings and infrastructure, “we get a theoretically sound and rigorous way of understanding all three of the main characteristics that make up cities,” Brelsford said. “You have to do everything, because cities do not make sense without the interaction of people, goods, environment and ideas. Cities are hubs of multisectoral interactions. “

“One of the roles in the national laboratories of DOE is” to make sure that the most endangered among us are equally, fairly and accurately represented in science, and we do not achieve that when we look only at urban aggregates. “We have to look at the differences at the city level in order to do that well,” Brelsford added.

“A serious empirical view of the heterogeneity of cities is a critical step in understanding how all the major risks we face in the coming decades come down to real people,” she said.

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