Google Street View cars were recently used to detect hyper-local air pollution hotspots in Salt Lake Valley.
These “roving sentinels,” as they’ve been termed, were equipped to sample air quality at an unprecedented fine scale, thereby capturing the varying pollution levels within neighborhoods.
The initiative, a collaborative effort between University of Utah atmospheric scientists, the Environmental Defense Fund (EDF), and other partners, began in 2019.
Two Google Street View cars were introduced as innovative air quality monitors. Their principal advantage over traditional monitors was their mobility and ability to detect pollution levels that were previously undetectable.
John Lin, a professor of atmospheric sciences at the University of Utah, further advanced this initiative by devising a new modeling technique that combined modeled wind-patterns and statistical analysis to trace pollution to its exact source.
“With mobile vehicles, you can literally send them anywhere that they could drive to map out pollution, including sources that are off the road that previous monitoring missed,” said Professor Lin. “I think the roving sentinel idea would be quite doable for a lot of cities.”
The mobile labs journeyed through neighborhoods, taking an air sample every second, which accumulated a large dataset of air pollutant concentrations.
This method enabled the research team to craft the most detailed pollution map yet, revealing differences even within a 200-meter radius.
Senior air quality scientist for EDF and study co-author, Tammy Thompson, emphasized the significance of this finding.
“The big takeaway is that there is a lot of spatial variability of air pollution from one end of a block to another. There can be big differences in what people are breathing, and that scale is not captured by the typical regulatory monitors and the policy that the U.S. EPA uses to control air pollution,” said Thompson.
Furthermore, this study confirmed the troubling correlation between lower income neighborhoods and higher pollution levels.
This disparity has historical roots tracing back to redlining policies from a century ago, which marked neighborhoods as “hazardous” based on racial and economic demographics.
These areas typically had worse air quality due to nearby industrial activities. Professor Lin emphasized the lasting repercussions of these policies.
“Air quality is not a new issue. It’s been around for decades and decades, and was probably much worse back then,” said Lin.
“The I-15 corridor follows these redlined neighborhoods. And sadly, there’s a fair bit of research supporting the fact that redline neighborhoods, from 80 years ago, still matters. Those are in the neighborhoods still struggling with air quality problems. The legacy of racial discrimination is still there because they tend to be the under-invested neighborhoods.”
The instruments used in the Google Street View cars could differentiate chemical signatures of key pollutants such as nitrous oxides (NOx), black carbon (BC), fine particulate matter (PM2.5), and methane. Their findings also shed light on previously unknown sources of pollution.
The next step for these researchers is to inspire other cities to adopt this novel method of tracking pollution, aiming for safer urban environments.
An exciting application of this new atmospheric model is its integration into a unique web-based tool, Air Tracker, which provides users with real-time information on air quality in their vicinity.
“There are a lot of important environmental justice aspects to this work,” said Thompson. “We need to be able to understand what average air pollution looks like in different communities, and then understand why there is variability and why there are hotspots, and therefore what we can do about it.”
“It’s really, really important as we learn more and more about inequity in air pollution and what we’re breathing across the country.”
The research is published in the journal Atmospheric Environment.
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