Like many air pollution problems, black carbon does not affect everyone equally. Created by the incomplete combustion of some fossil fuels and biomass, black carbon causes health problems such as respiratory and cardiovascular disease, cancer, and even birth defects. Those effects are most pronounced in people who live near black carbon hotspots such as freeways, concrete factories, and roads frequented by large trucks.
At Caltech, an ongoing student project has modeled concentrations of black carbon levels down to individual streets and city blocks. Now that work has grown into a larger effort to build affordable sensors that would help communities and neighborhoods calculate their risk by showing how much dangerous black carbon is present.
The project started with Peter Kulits, a senior studying computer science, who wanted to find a project at the intersection of computer vision and sustainability for Chemical Engineering 142, Challenges in Data Science for Chemical Systems, a data-science-focused course. Mike Vicic, teaching professor in chemical engineering, suggested he reach out to Caltech alum Robert Griffin (PhD ’00), now the dean of the School of Engineering, Computing and Construction Management at Roger Williams University, who had worked with Google to place various pollution trackers, including black carbon sensors, on the company’s Street View vehicles. As the cars drove around Houston, Texas, to map the city streets, they simultaneously mapped many of the metropolis’s black carbon hotspots.
The instruments used for Griffin’s study are expensive and difficult to obtain, however, which makes it difficult to expand that work elsewhere.
“My project was to extend their work,” Kulits says, “to make it possible to identify potential hotspots but without all of the expensive equipment, hopefully just from public data sources.”
Vicic says such a model would be transferrable to other cities, including Caltech’s hometown of Pasadena. But Kulits’s plans to model the black carbon in Pasadena ran into a different issue: no one had measured black carbon levels around Pasadena, and so there were no data against which Kulits’s model could be compared to confirm its accuracy. Vicic then came to another realization: such a task could make an ideal project for his fall term class, Chemical Engineering Laboratory 126.
With support from the Caltech Innovation in Education fund, Vicic bought a state-of-the-art black carbon detector, which costs about $10,000, for his students so they could take measurements around town. However, he knew Caltech could create a much more robust data set if his students could use more affordable tools to make more readings and get tools into the hands of more people. So, he set them to work on instrumentation design, tasking eight students to create black carbon detectors that could be built for a fraction of the cost.
The devices those students built this fall are considerably less expensive because they don’t need to match the performance of the best available instrument, Vicic says. The top-of-the-line black carbon sensor can measure very low black carbon concentrations (down to 0.1 microgram per cubic meter). For this project, the student detectors need only to detect those higher levels of black carbon that are worrying for human health. Thus, the student designs use less-expensive air pumps, emitters, detectors, data-acquisition electronics, and other components. Vicic says a good analogy would be to compare a residential carbon monoxide detector to a scientific instrument used to measure carbon monoxide concentration in air.
Each student-made detector looks wildly different, he says, because the students took different approaches to the idea. “I tell them, ‘Frankensteins are good,'” Vicic says. “Because they’re all proofs of concepts. You’re trying to get through the whole design process quickly to learn what you don’t know you don’t know.”
One prototype uses mirrors to bounce light back and forth through a chamber of gas and a sensor to detect how much of the light is absorbed to reveal how much black carbon is present. “I have another person who wants to do a system that’s a sampler that people would send back to the manufacturer-kind of like a radon detector,” Vicic says. “He wanted to have a different spot for every day so he could measure how much black carbon was persistent over time or whether the levels changed day to day.”
These quick-and-dirty detectors from Vicic’s class are ideal for this job because what matters is getting good-enough instruments into the hands of people living in neighborhoods affected by black carbon hotspots. With affordable detectors, people could take black carbon measurements and have hard data to show to policymakers. In this way, the two sides of the project-affordable detectors and a black carbon model that’s transferrable to many different cities-have the potential to make a serious impact on this environmental justice issue.
“You find an area that’s been identified as a potential persistent black carbon hotspot from a model,” Vicic says, “then, you deploy the sensors to residents in that area so you can say, ‘Yes, many of us are being exposed to black carbon.’ It’s not just one sensor in one house.”