A groundbreaking study from the University of Utah and EDF used Google Street View cars to conduct detailed monitoring of air quality in the Salt Lake Valley. This study reveals hyperlocal pollution hotspots, highlights environmental justice issues, and marks significant progress in understanding and addressing the uneven impacts of urban air pollution.
In the Salt Lake Valley, cars equipped with advanced air quality measurement tools (similar to Google Street View cars) travel through neighborhoods collecting highly detailed air quality data. This comprehensive sampling revealed clear differences in pollution levels in different areas. Additionally, a novel atmospheric modeling technique was developed to pinpoint the sources of these pollution emissions.
In 2019, a team of atmospheric scientists at the University of Utah, working with the Environmental Defense Fund and other partners, introduced an innovative method of monitoring air quality in the Salt Lake Valley. They equipped two Google Street View cars with mobile air pollution detectors capable of identifying hyperlocal pollution hotspots.
In the months that followed, John Lin, a professor of atmospheric sciences at the university, developed a breakthrough modeling technique. This approach combines wind pattern modeling and statistical analysis to trace contaminants back to their exact source. This technology provides a greater level of detail in tracking pollution than traditional air quality monitoring methods, which typically assess air quality across entire urban areas.
A study led by American universities and the Environmental Defense Fund (EFD) recently published findings in the journal Atmospheric Environment.
"With mobile vehicles, you can actually send them anywhere they can drive to map pollution, including roadside pollution sources that previous monitoring missed," Lin said. "I think the idea of roving sentinels is feasible for many cities."
The researchers installed air quality instruments on vehicles and directed drivers to search residential areas street by street, collecting one air sample every second, thereby establishing a massive data set of air pollutant concentrations in the Salt Lake Valley from May 2019 to March 2020. The observations produced the highest-resolution fine-scale map of pollution hotspots to date - the data captured changes within 200 meters (about two football pitches).
"The big takeaway is that air pollution varies greatly spatially from one end of a neighborhood to the other," said Tammy Thompson, a senior air quality scientist at EDF and a co-author of the study. "The air people breathe can vary greatly, and typical regulatory monitors and the policies the EPA uses to control air pollution cannot capture this scale."
Air quality patterns are as expected, with higher pollution levels around traffic and industrial areas. Contaminant levels are higher in neighborhoods with lower average incomes and higher proportions of black residents, confirming well-known environmental justice concerns. The pattern dates back to redlining policies a century ago, when homeowners' loan companies drew maps that outlined "dangerous" neighborhoods in red ink. Neighborhoods that are redlined often have poorer air quality due to industrial activity surrounding residents, who are often people of color. City planners use these maps to justify building highways and allowing industrial companies in so-called dangerous areas, exacerbating environmental problems.
"Air quality is not a new problem. Air quality problems have been around for decades, and the situation was probably worse back then," Lin said. "All along the I-15 corridor are residential areas that were redlined. Sadly, there is quite a bit of research that proves that the redlined communities of 80 years ago still exist. These communities are still struggling with air quality issues. The legacy of racial discrimination still exists because they tend to be underinvested communities."
Research-grade instruments mounted on Google Street View vehicles measure ambient air drawn in from the surroundings and resolve the chemical signatures of major air pollutants, including nitrous oxide (NOx) emitted by cars, trucks, off-road vehicles, and power plants; black carbon (BC) from incomplete combustion in on- and off-road diesel vehicles and industrial kilns; fine particulate matter (PM2.5) from dust or ash; and methane, primarily from landfills. Researchers directed drivers to sample the air in 26 communities, ranging from industrial areas in North Salt Lake to residential areas as far south as Cottonwood Heights and West Jordan. The neighborhoods selected by the researchers represent vastly different demographic makeup across the valley, including proportions of black residents, average incomes ranging from 34,000 to more than 100,000, and areas dominated by industrial or residential construction.
Most pollutants showed a strong pattern that reinforced what we already knew - elevated levels of NOx, PM2.5, BC and CO2 along highways in the valley. Areas with higher levels of one pollutant are likely to be areas with higher levels of other pollutants, either from a single source emitting multiple pollutants or from overlapping sources.
"It's a bit boring to say 'there's pollution on the road.' Everyone knows it. Right? So, we want to use data to find the sources of pollution beyond the road," Lin said. The authors tested Lin's new atmospheric modeling method with case studies of two well-known pollution sources - one a large landfill methane source and the other a known gravel pit source of PM2.5. They then applied the model to analyze previously unknown areas of elevated PM2.5 in an industrial area south of the Salt Lake City Airport.
The authors hope that other places will use this new method to identify pollution hotspots to make their cities safer, including identifying temporary sources of pollution (such as gas leaks) and permanent sources of pollution (such as industrial pollution sources). Roving sentries can help policymakers develop regulations that use resources more efficiently to mitigate harm to citizens.
The author hopes to use the atmospheric model for projects such as "Air Tracker". Air Tracker is the first web-based tool to help users find possible sources of air pollution in their communities. Air Tracker operates on real-time, trusted scientific models and is integrated with air pollution and weather data. Developed in partnership with American Universities, the European Environment Fund and Carnegie Mellon University’s CREATE laboratory, it helps users learn more about the air they breathe, including pollution concentrations and their potential sources. The air trackers are already live in the Salt Lake City Valley and will be rolled out to more locations across the country in the coming months.
"This work touches on many important environmental justice issues," said the Environmental Development Foundation's Thompson. "We need to understand the average air pollution in different communities and then understand why there are differences, why there are hotspots, so what we can do about it. As we learn more and more about the inequalities in air pollution and the air we breathe across the country, that's really, really important."
Reference: "Ultralocal source identification of urban pollutants by combining mobile measurements with atmospheric modeling" by John C. Lin, Ben Fasoli, Logan Mitchell, Ryan Bares, Francesca Hopkins, Tammy M. Thompson, and Ramón A. Alvarez, published in the journal "Atmospheric Environment" on August 2, 2023.
DOI:10.1016/j.atmosenv.2023.119995
Compiled source: ScitechDaily