MIRTHE Mobile Sensor Systems Hit the Road
A new mobile environmental sensor system developed by the NSF-funded Engineering Research Center (ERC) for Mid-Infrared Technologies for Health and the Environment (MIRTHE), based at Princeton University, has traveled over 2700 miles in California to chemically fingerprint the air at unprecedented spatial resolution.
Data collected in this project, and in the future through broader application, will help to address the spatial/temporal patterns of trace gas emissions and their implications on air quality and climate change. Ultimately this information will enhance our understanding of the makeup, sources, and distribution of air pollution and its relationship to climate change. This first demonstration of the MIRTHE mobile sensor suggests the possibility that someday soon, the public will be able to get real-time smog readings directly off online Google maps.
This project fits into the broader efforts of MIRTHE to implement novel optical sensing systems for atmospheric measurement applications relevant for broader environmental studies. The sensor system uses high-sensitivity quantum cascade lasers to achieve high-sensitivity and fast measurements. The spatial distributions of the four most important greenhouse gases—water vapor, carbon dioxide, methane and nitrous oxide—as well as critical air pollutants carbon monoxide and ammonia were mapped in the California central valley and the San Francisco Bay area as part of the NASA DISCOVER-AQ and AJEX field experiments in January/February 2013. This area was selected because it has a mix of intense agricultural and urban sources, leading to substantial greenhouse gas emissions and air quality degradation. The route traveled was simultaneously monitored by NASA aircraft and satellites, so data collected by MIRTHE’s prototype sensor platform was integrated with a wide suite of other measurements.
At the technical level, lessons learned from the California deployment will bring the next-generation prototype closer to commercial use. The project also develops technology for integrating sensor systems into sensor networks.