Urban bicyclists and outdoor sports enthusiasts may soon learn more about the air pollution they breathe and its health risks as an unusual 3-year study gets underway. This week, the project is scheduled to equip its first cohort of volunteer bike commuters in New York City with pollution sensors as well as a sophisticated array of health monitors. The equipment will ultimately track 150 riders’ vital signs while they’re on the move and, in a step beyond what prior similar studies have done, estimate each individual’s pollution exposure.
The “traditional metrics” are just pollutant concentrations, said Steven Chillrud, a research professor at Columbia University’s Lamont-Doherty Earth Observatory in Palisades, N.Y., who is one of the leaders of the research. Pollution is typically measured by how much of it is in the air, as micrograms per cubic meter, for example. But a jogger or cyclist breathes harder than someone sitting still, and that can drastically affect how much pollution a person actually inhales.
A more accurate way to look at exposure would consider dosage, said Chillrud, an environmental geochemist with an interest in public health. In a smaller pilot study of 40 individuals, the researchers found that their subjects’ bike commutes “tend[ed] to dominate their overall air pollution exposure,” said Darby Jack, a professor of environmental health at the Mailman School of Public Health in New York City, also within Columbia University, who coleads the study with Chillrud.
Would the same hold true for a more statistically significant sample? Chillrud and Jack aim to find out.
Focusing on Particulates
Although New York City overall has cleaned up its air in recent years, its skies still rank among the dirtiest in the United States, according to the American Lung Association. This poor air quality makes the city a pollution laboratory, the researchers note.
The Columbia project focuses on fine particulate matter, called PM2.5 because it is smaller than 2.5 micrometers—about 1/20 the width of a human hair. It further focuses on black carbon, a subset of PM2.5 produced by burning organic matter. Most black carbon in cities comes from diesel exhaust. Long-term exposure to black carbon has been linked to an increased risk of heart failure and respiratory problems, but “looking at briefer exposures, the literature is thinner,” Jack said. “I don’t think anyone would say it’s benign,” but going from that to knowing exactly what the health effects are is a long step.
Today, the researchers expect to outfit the first small group of volunteers with two sensors to measure PM2.5 and black carbon, a GPS device, a biometric shirt called a Hexoskin that measures breathing rates and heart-rate variability, and an automatic blood-pressure reader. These volunteers are to wear the shirt and blood pressure reader for six 24-hour periods over a 3-week window while the bike-mounted sensors collect data on their commute. The volunteers must return the equipment after 3 weeks for the researchers to collect the data, and then the devices will be given to a new set of volunteers, 150 in all over the course of the study.
Past air pollution monitoring studies often used expensive, bulky sensors mounted on buildings or poles. However, the recent advent of smaller, cheaper sensors is making it possible for pollution researchers to deploy many more sensors than before and to mount them on people or small vehicles like bicycles. As a result, scientists can measure concentrations at the street level at scales fine enough to look at individuals’ exposures.
In studies similar to the new one starting up in New York, clean air activists in Pittsburgh’s Group Against Smog and Pollution equip volunteer cyclists in the city with electronic air particle counters; a similar project is ongoing in Toronto, Ontario, and nearby Hamilton.
However, these projects don’t take dosage into account, Chillrud said.
Although the second phase of the study launching today will be more comprehensive, the pilot study of 40 riders has already revealed some key information, such as how unevenly pollution is distributed in space and time: “It turns out there are locations in the city that are fairly high pollution…and there are other places that are pretty clean, and there are times of day that are more polluted,” Jack said.
The researchers, who say they’re working with public radio station WNYC to help get the word out about the study and its results, have created an interactive online map from their pilot program data. With this map, other bike riders can upload a GPS file of a biking route to the interactive map and get an estimate of personal exposure to pollution on the ride. Jack and Chillrud hope to refine those estimates after the full study gets underway.
Jack said that he hopes the full study’s data will ultimately help inform policy. “We’re thinking of it as a message to city planners…that it’s important that air pollution be one of several design criteria” considered when building new infrastructure. He speculates that their study might also serve as a call to cyclists to change their behavior by taking a different route, commuting at a different time, or even pedaling slower through the dirtiest part of their commute.
To Bike or Not to Bike
So far, the pollution data haven’t caused any volunteers to stop biking, and Chillrud and Jack agree that the data shouldn’t. The exercise benefits from biking almost certainly outweigh the pollution exposure, they said.
That view is supported by a study published last year in Preventive Medicine, which modeled the relative trade-offs between active transportation and pollution exposure for a variety of concentration levels.
The study found that “even in the most polluted environments you’re better off doing a little activity rather than no activity,” said coauthor and public health modeler James Woodcock of the University of Cambridge in the United Kingdom.
—Rachel Kaufman (email: email@example.com; @rkaufman), Freelance Science Journalist
Kaufman, R. (2017), Novel air pollution study gauges individual cyclists’ risks, Eos, 98, https://doi.org/10.1029/2017EO075893. Published on 13 June 2017.
Text © 2017. The authors. CC BY-NC-ND 3.0
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