New $1000 Sensor Measuring Gases and Particulates in Delhi (MIT)

Glimpses of blue sky are becoming a rare sight in Delhi, India’s capital, particularly in wintertime, when a thick white haze smothers the city. David Hagan, an MIT PhD candidate studying atmospheric chemistry and a Fellow in the MIT Tata Center for Technology and Design, says that the city’s air quality is now quantifiably among the worst in the world.

Hagan and his advisor, Associate Professor Jesse Kroll of the Department of Civil and Environmental Engineering, saw this complexity as motivation to design a compact, low-cost air quality sensor that they hope will be deployed in dense networks across cities like Delhi, logging accurate, real-time data on the chemistry of the air.

“Air quality monitoring is often discussed as an either-or situation,” says Kroll. “One can have expensive, regulatory-grade monitors or else distributed, low-cost sensors. But in reality it’s a continuum, with a tradeoff between cost, size, and power on one hand, and accuracy, precision, and sensitivity on the other. We’re somewhere in the middle of the continuum, with enough accuracy and precision to provide quantitative measurements.”

Kroll and Hagan already have several prototypes on the ground in India, reporting data to a remote server every 30 seconds. Two units are located at Nehru Place in south Delhi, and four are near Connaught Place in central Delhi, co-located with a regulatory-grade sensor for calibration. Two are in the city of Pune, near Mumbai, and one is mobile — Hagan can frequently be seen taking it on rickshaw rides around Delhi.

A regulatory-grade sensor, of which there are roughly 20 in Delhi, costs between $50,000 and $100,000. Kroll and Hagan’s sensor costs “on the order of $1,000” per unit, says Hagan, and offers comparable performance, measuring six types of gases (O3, NO, NO2, SO2, CO, and volatile organic compounds) and 16 size groups, or “bins,” of particles, ranging from coarse to fine. The lower cost makes it feasible for these sensors to be deployed in large volumes, creating an opportunity to map pollutant distribution at greater levels of detail.

Read the full article @ the MIT News