Through a complex data analysis corroborated by thorough on-the-ground reporting, NPR and the Howard Center showed how the most vulnerable people in dozens of major U.S. cities – the urban poor, who are often disproportionately people of color – are exposed to far more heat day after day than their wealthier counterparts.
Our stories were picked up by news services across the country and specifically cited in a House Oversight Committee hearing. The city government in Chesapeake, Va., used our data to inform decisions made by its community arborist. And after these stories ran, the Louisville city government considered an ordinance that would require developers to leave a certain percentage of trees in place.
The series won an innovative storytelling award from the National Press Foundation, and the Howard Center specifically won a grand prize from the Online News Association that will allow the center to help other news organizations build on our work next summer. The Investigative Reporters and Editors Philip Meyer Awards also recognized the series with an honorable mention.
We discovered academic research by a team from the Science Museum of Virginia and Portland State University showing huge disparities in temperature between poorer and richer neighborhoods in Baltimore, and set out to discover the reason for the disparities. In 2018, Capital News Service applied for – and received – a grant to underwrite the construction of temperature sensors that we placed inside of homes in East Baltimore to collect minute-by-minute temperature readings the following summer.
In collaboration with the Howard Center, NPR analyzed 97 of the most populous U.S. cities using the median household income from the U.S. Census Bureau and thermal satellite images from NASA and the U.S. Geological Survey. NPR open-sourced the computer code used to acquire and analyze the data, as well as the data itself. In more than three-quarters of those cities, we found that heat is not distributed evenly across a city, and where it’s hotter, it also tends to be poorer.
The Howard Center for Investigative Journalism did all of its work using QGIS, R, RStudio, Carto, Leaflet. The NPR analysis was automated in Python using Mapshaper, GDAL, GeoPandas and other libraries. To visualize the data, NPR used QGIS, Tableau Public, d3.js and Adobe Illustrator. NPR’s data editor wrote more about the process on their team blog, and the University of Maryland gave a look behind the scenes on its project website.
Data sources we used included:
What was the hardest part of this project?
This series was a unique collaboration between student journalists at the University of Maryland and professional journalists at the University of Maryland and at National Public Radio.
We used more than a dozen discrete data sets to tell this story, each of which required extensive cleaning, verification and reporting to guide our analysis. This included historical temperature and humidity data, data describing the urban heat island in Baltimore, U.S. census data, tree canopy data, redlining data, hospital visit data, emergency medical visit data, and more. The two most complex data challenges came in two areas: collecting data from our temperature and humidity sensors and determining the link between heat and poverty in nearly 100 U.S. cities.
Baltimore was the first city we mapped, and the first place we saw that troubling pattern. There, the hottest neighborhoods in that city can differ by as much as 10 degrees from the coolest. Those areas also had higher rates of poverty, according to the Howard Center’s analysis of U.S. census data and air temperature data obtained from Portland State University and the Science Museum of Virginia.
But Baltimore is only the tip of the iceberg: At least 69 of the cities NPR mapped had an even stronger relationship between heat and income than Baltimore. That extra heat can have deadly health consequences, which we found confirmed in Baltimore’s high rates of emergency calls when the heat index rose to dangerous levels and in the city’s patterns of hospital admission rates.
What can others learn from this project?
We aren’t the only journalists who have covered the intersection between climate change and rising heat in urban environments. We were inspired by the work done by KQED, which published on Oct. 29, 2018, and focused on heat in Los Angeles; and work done by WNYC, which published a series on heat in Harlem throughout the summer of 2016. Both outlets used sensors in telling stories about hot homes in their respective cities. Our innovation was using these techniques to show the disproportionate impact on people in the poorest areas of cities and to show that these trends were in evidence in cities across the U.S.