Air pollution is a major public health problem: the World Health Organization has estimated that it causes more than 4 million premature deaths worldwide each year. Yet it is not always widely measured. But now an MIT research team is rolling out an open-source version of a low-cost mobile pollution detector that could allow people to track air quality more broadly.
The detector, called Flatburn, can be made by 3D printing or by ordering inexpensive parts. Researchers have now tested and calibrated it against existing state-of-the-art machines, and publicly release all the information about it – how to build it, use it, and interpret the data.
“The goal is for community groups or individual citizens to be able to measure local air pollution, identify its sources, and ideally create feedback loops with officials and stakeholders to create cleaner conditions,” says Carlo Ratti, director of MIT’s Senseable City. Laboratory.
“We have carried out several pilot projects around the world and we have refined a set of prototypes, with hardware, software and protocols, to ensure that the data we collect is robust from a life science point of view. environment”, says Simone Mora. , a researcher at Senseable City Lab and co-author of a recently published paper detailing the scanner testing process. The Flatburn device is part of a larger project, known as City Scanner, which uses mobile devices to better understand city life.
“Hopefully, with the release of open source Flatburn, we can get grassroots groups, as well as communities in less developed countries, to follow our approach and develop and share knowledge,” says An Wang, researcher at Senseable City Lab and another of the journal’s co-authors.
The article, “Leveraging Machine Learning Algorithms to Advance the Calibration of Low-Cost Air Sensors in Stationary and Mobile Settings,” appears in the journal Atmospheric environment.
Besides Wang, Mora and Ratti, the authors of the study are: Yuki Machida, former researcher at Senseable City Lab; Priyanka deSouza, assistant professor of urban and regional planning at the University of Colorado at Denver; Tiffany Duhl, a researcher with the Massachusetts Department of Environmental Protection and a research associate at Tufts University at the time of the project; Neelakshi Hudda, assistant research professor at Tufts University; John L. Durant, professor of civil and environmental engineering at Tufts University; and Fabio Duarte, senior researcher at Senseable City Lab.
The Flatburn concept at Senseable City Lab dates back to around 2017, when MIT researchers began prototyping a mobile pollution detector, originally intended to be deployed on garbage trucks in Cambridge, Massachusetts. The detectors are battery powered and rechargeable, from power sources or a solar panel, with data stored on a card in the remotely accessible device.
The current expansion of this project involved testing the devices in New York and the Boston area, observing their performance against pollution detection systems already in operation. In New York, researchers used 5 detectors to collect 1.6 million data points over four weeks in 2021, working with state officials to compare results. In Boston, the team used mobile sensors, evaluating Flatburn devices against a state-of-the-art system deployed by Tufts University with a state agency.
In both cases, the detectors were configured to measure the concentrations of fine particles as well as nitrogen dioxide, over an area of approximately 10 meters. Fine particular matter refers to tiny particles often associated with burning materials, from power plants, internal combustion engines in automobiles and fires, etc.
The research team found that the mobile detectors estimated slightly lower fine particle concentrations than the devices already in use, but with a strong enough correlation that, with adjustments for weather conditions and other factors, the Flatburn devices can produce reliable results.
“After following their rollout for a few months, we can confidently say that our low cost monitors should behave similarly. [as standard detectors]Wang said. “We have a big vision, but we still need to make sure the data we collect is valid and can be used for regulatory and policy purposes,”
Duarte adds, “If you follow these procedures with low-cost sensors, you can still acquire data good enough to go back to [environmental] agencies with him, and say, “Let’s talk about it.”
The researchers found that using the units in a mobile environment – on top of automobiles – means they will currently have a lifespan of six months. They also identified a series of potential issues that people will face when using Flatburn detectors in general. These include what the research team calls “drift,” the gradual change in detector readings over time, as well as “aging,” the more fundamental deterioration in a unit’s physical condition.
Still, the researchers believe the units will work fine, and they provide full instructions in their version of Flatburn as an open source tool. It even includes tips for working with managers, communities and stakeholders to process findings and try to shape action.
“It is very important to engage with communities, to allow them to reflect on the sources of pollution,” says Mora.
“The original idea of the project was to democratize environmental data, and that’s still the goal,” adds Duarte. “We want people to have the skills to analyze data and engage with communities and officials.”