A groundbreaking study conducted by the University of Utah and EDF used Google Street View vehicles to closely monitor air quality in the Salt Lake Valley. This study revealed highly localized pollution hotspots, highlighted issues of environmental justice, and represents a major advance in understanding and addressing the uneven impacts of urban air pollution.
In the Salt Lake Valley, vehicles equipped with advanced air quality measurement tools similar to Google Street View vehicles drove through neighborhoods and collected highly detailed air quality data. This comprehensive sampling revealed clear variations in pollution levels within different regions. Additionally, new atmospheric modeling techniques have been developed to accurately identify these sources of pollution emissions.
In 2019, a team of atmospheric scientists at the University of Utah, in collaboration with the Environmental Defense Fund and other partners, introduced an innovative approach to air quality monitoring in the Salt Lake Valley. They equipped two Google Street View cars with air quality measurement tools, creating mobile air pollution detectors capable of identifying hyper-local pollution hotspots.
Over the next few months, John Lin, a professor of atmospheric science at the university, developed a breakthrough modeling technique. The method combined wind pattern modeling and statistical analysis to trace pollutants to their exact source. This technology provided a level of detail in pollution tracking that exceeded the more extensive and less accurate methods of traditional air quality monitoring, which typically assessed air quality across urban areas.
According to a study led by the United States and the Environmental Defense Fund (EFD) recently published in the journal atmospheric environment, the results are out. “With mobile vehicles, you can literally send them anywhere you can drive and find out more about pollution, including off-road sources that traditional monitoring has missed,” said Lin, who is also deputy director of the Wilkes Climate Science Center. “We can put up a map,” he said. policy. “I think the idea of patrolling lifeguards is pretty viable in many cities.”
Researchers equipped vehicles with air quality instruments and asked drivers to explore their neighborhoods street by street, taking air samples once every second, from May 2019 to March 2020. This created a huge dataset of air pollutant concentrations in the Salt Lake Valley. It is the highest-resolution map showing pollution hotspots at a detailed scale, with data capturing fluctuations within 200 meters, or about the width of two football fields.
The air quality pattern was as expected, with higher pollution around traffic and industrial areas. Neighborhoods with lower average incomes and higher proportions of black residents had more pollutants, confirming well-known issues of environmental justice. This pattern traces its legacy to his century-old redlining policy, in which Homeowner’s Loan Corp. created maps outlining “dangerous” areas in red ink.
“Air quality is not a new problem. It’s been around for decades, and it was probably worse back then,” Lin said. “The Interstate 15 corridor runs along red-light districts. And sadly, there is quite a bit of research supporting the fact that the red-light districts of 80 years ago are still important. These areas still struggle with air quality issues. These areas tend to be underinvested, so the legacy of racism remains.”
Research-grade equipment in Google Street View vehicles measures the ambient air that is pumped in from the surrounding area and detects major emissions. The researchers tested Lin’s new atmospheric modeling approach using two case studies of well-known pollution sources. The model was then applied to analyze previously unknown areas of PM elevation.2.5
The authors hope to use atmospheric models for projects such as Air Tracker, a web-based tool developed in partnership with EDF and Carnegie Mellon University that helps users find possible sources of air pollution in their neighborhood.
This research was funded by the Environmental Defense Fund. Other authors of this article are also cited, and the study utilized the resources of the National Center for High Performance Computing.
Source: scitechdaily.com
