You see it spewing out of all types of vehicles―trucks, trains, marine vessels. Black carbon, known as soot, is produced by the incomplete combustion of fuels and significantly contributes to air pollution, particularly in urban areas.
Up to now, the expense of existing sensors has made black carbon difficult to track. But researchers at the U.S. Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab), collaborating with UC Berkeley, have developed a more affordable sensor network that able to track this particulate matter. The research team installed more than 100 custom-built sensors installed across West Oakland for 100 days.
A full description of the 100 x 100 air quality network was published in the journal Environmental Science and Technology.
The project was launched to address a persistent concern in the community: the need for better tools to monitor black carbon across time and space. Expanding on prior research at Berkeley Lab, the team addressed this challenge by building the Aerosol Black Carbon Detector (ABCD).
“We generated a technology that didn’t exist to make this invisible problem visible,” said Thomas Kirchstetter, who leads the Energy Analysis and Environmental Impacts Division at Berkeley Lab, and is an Adjunct Professor of Civil and Environmental Engineering at UC Berkeley.
The ABCD is a compact, inexpensive air quality monitor that can measure the concentration of black carbon in an air sample. “We had to create a sensor that was as accurate as high-grade, expensive instrumentation, but low enough in cost that we could distribute 100 of them throughout the community,” said Kirchstetter. Thanks to design innovations that coauthor Julien Caubel developed during his PhD research, which help the sensors withstand changes in temperature and humidity, the ABCD can produce reliable data when left outside for extended time periods. The materials for each ABCD cost less than $500, compared to commercially available instruments that measure black carbon cost many thousands of dollars.
The fleet of sensors was deployed throughout West Oakland, a 15 square kilometer mixed-use neighborhood surrounded by freeways and impacted by emissions from the Port of Oakland and other industrial activities. Six land-use categories were designated for sensor placement: upwind, residential, industrial, near highway, truck route, and port locations.
To track the individual sensors in real time, including their operating status, and collect measurements, coauthor Troy Cados built a custom website and database. Every hour, the devices sent black carbon concentrations to the database using 2G, the mobile wireless network. The study produced approximately 22 million lines of data, yielding insights about the nature of air pollution on a local scale. The data, now available for download, is also being used by collaborators from UC Berkeley, the Bay Area Air Quality Management District, and other institutions to improve air pollution modeling tools.
The researchers found that black carbon varied sharply over distances as short as 100 meters and time spans as short as one hour. The highest and most variable levels were associated with truck activity along Maritime Street, typically low in the pre-dawn hours when the Port of Oakland was closed and peaking at the start of business, around eight in the morning. The lowest black carbon concentrations in the study area were recorded on Sundays, when truck activity is typically lowest, and at upwind sites near the bay, west of the freeways and the city’s industrial activity. Most of the sensors were able to collect data sufficient to establish pollution patterns during the first 30 days of the study, suggesting that similar – and shorter – studies could provide other communities with valuable information about their air quality.
Kirchstetter said his team is currently working to advance this technology, making it more robust and easier to use so that it can be deployed for longer periods of time at other locations.