Researchers from the University of Utah, in partnership with the Environmental Defense Fund (EDF), have utilized Google Street View cars to execute an in-depth air quality survey in the Salt Lake Valley. Their innovative approach has unveiled hyper-local air pollution areas and shed light on the issues of environmental justice. This study represents a significant leap in comprehending and tackling the disproportionate effects of urban air pollution.
Using cars equipped with sophisticated air quality measuring instruments, akin to the Google Street View vehicles, the team conducted a thorough survey of the Salt Lake Valley neighborhoods. This extensive data collection revealed distinct variations in air pollution levels across different areas. The study also introduced a new atmospheric modeling method to accurately identify the sources of these emissions.
In 2019, atmospheric scientists from the University of Utah, collaborating with the EDF and other partners, employed an advanced technique for monitoring air quality. They modified two Google Street View cars into mobile air pollution detection units, enabling them to spot highly localized pollution zones.
John Lin, a professor of atmospheric sciences at the university, developed an innovative modeling approach. This method, which integrates wind pattern analysis and statistical techniques, allows for the precise tracing of pollutants to their original sources. This method offers a more detailed level of pollution tracking compared to traditional air quality monitoring approaches, which generally evaluate air quality over vast urban expanses.
The study, led by the University of Utah and the EDF, and recently published in the Atmospheric Environment journal, presents these findings.
Lin, also the associate director of the Wilkes Center for Climate Science & Policy, remarked, “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.”
The researchers equipped the vehicles with air quality sensors and directed drivers to meticulously navigate neighborhood streets, collecting air samples every second. This process resulted in an extensive dataset of air pollutant concentrations in the Salt Lake Valley from May 2019 to March 2020, offering the most detailed map yet of pollution hotspots at a fine scale.
Tammy Thompson, EDF’s senior air quality scientist and co-author of the study, observed, “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.”
As expected, air quality patterns showed higher pollution near traffic and industrial areas. However, neighborhoods with lower average incomes and higher proportions of Black residents exhibited higher pollutant levels, underscoring a longstanding issue of environmental justice. This disparity has roots in historic redlining practices, where certain neighborhoods, often housing People of Color and next to industrial zones, were marked as “hazardous”. Urban planning decisions further aggravated these environmental challenges.
Lin commented, “The legacy of racial discrimination is still there because [the affected neighborhoods] tend to be the under-invested neighborhoods still struggling with air quality problems.”
The researchers’ sophisticated instrumentation in the Google Street View cars could differentiate key air pollutants, such as nitrous oxides, black carbon, fine particulate matter, and methane, by sampling air from various neighborhoods. The data confirmed that pollutant levels were higher along highways and in industrial zones.
The study also included a case analysis using Lin’s atmospheric modeling technique to identify pollution hotspots near known sources, such as landfills and gravel pits. Furthermore, the model identified a previously unknown elevated PM2.5 area near the Salt Lake City airport.
Looking ahead, the researchers hope that other cities will adopt this method to detect pollution hotspots, aiding policymakers in enacting regulations and efficiently allocating resources to protect citizens. Additionally, they aim to apply the atmospheric model in projects like Air Tracker, a web-based tool for identifying local air pollution sources, developed in collaboration with the University of Utah, EDF, and Carnegie Mellon University’s CREATE Lab.
Thompson from the EDF emphasized the importance of understanding air pollution variability and hotspots in different communities to address environmental justice concerns.
The study was funded by the EDF and involved several authors, including Ben Fasoli, Logan Mitchell, Ryan Bares, Francesca Hopkins, and Ramón Alvarez. The research also leveraged the resources of the University of Utah’s Center for High Performance Computing to compute the spatial distribution of pollution and develop the methodology for locating emission sources.
Table of Contents
Frequently Asked Questions (FAQs) about Air Quality Monitoring
What was the main objective of the study using Google Street View cars?
The study aimed to conduct an in-depth air quality survey in the Salt Lake Valley. It focused on unveiling hyper-local air pollution areas and addressing environmental justice issues by using modified Google Street View cars equipped with advanced air quality measuring instruments.
How did the study approach air quality monitoring differently?
Unlike traditional methods that assess air quality over broad urban areas, this study used Google Street View cars to collect highly detailed air quality data street by street. This approach allowed for the identification of hyper-local pollution hotspots and a more accurate understanding of urban air pollution’s uneven impact.
What were the key findings of the air quality study in the Salt Lake Valley?
The study revealed significant spatial variability in air pollution levels within different neighborhoods. It found that areas with lower average incomes and higher proportions of Black residents faced higher pollution levels, highlighting a significant environmental justice issue.
How did the study contribute to the field of environmental science?
The study introduced a novel atmospheric modeling method that combined wind pattern analysis and statistical techniques. This allowed for precise tracing of pollutants to their sources, providing a more detailed level of pollution tracking compared to traditional air quality monitoring methods.
What are the implications of this study for future urban planning and environmental policies?
The findings underscore the need for more localized air quality monitoring and the importance of considering environmental justice in urban planning and policy-making. It suggests that cities could use similar methodologies to identify and address pollution hotspots, leading to more effective environmental regulations and resource allocation.
More about Air Quality Monitoring
- University of Utah Air Quality Study
- Environmental Defense Fund Research Initiatives
- Google Street View Technology
- Atmospheric Environment Journal Publications
- Urban Air Pollution Monitoring Techniques
- Environmental Justice and Air Quality
- Air Tracker Project
5 comments
Didn’t quite get the part about the atmospheric modeling thing, sounds complicated but important. Good to see science making strides in air quality research.
Interesting use of technology here. It’s eye-opening to see how environmental justice plays a role in air quality. Kinda sad that some neighborhoods are more affected than others.
Wow, this is pretty cool stuff Using cars to track air pollution? Genius move by the University of Utah, and those Google cars – just wow. Didn’t know they could do that!
Fascinating read, but kind of worrying too? It’s a bit scary to think about the pollution we’re breathing in every day. Glad someone’s looking into it though.
this is great for understanding pollution but what about solutions? We need to focus on reducing emissions, not just tracking them.