Formaldehyde is a key air pollutant and known human carcinogen. Each year over 25 million Americans are exposed to formaldehyde at levels exceeding the US Environmental Protection Agency (EPA) cancer risk threshold. This is a particularly urgent problem in northern Utah because formaldehyde levels are 50 times greater than the cancer risk threshold on average. Combating this problem requires controlling emission sources, which are largely unknown in northern Utah. Identifying emission source(s) requires a large number of samples over space and time. The expense of performing these measurements limits data collection, making it nearly impossible to identify the source(s). This CAREER project will address this issue by developing lower cost nanofiber sensors. These sensors will be deployed in dense arrays in northern Utah using advanced analytical techniques and a community-based network. The results are anticipated to lead to identification of sources for eventual control and improvement of air quality. Technological developments resulting from this project will be broadly applicable nationwide for communities, policy makers, and researchers to identify and address pollutant sources to protect human health. This project will also develop a rich framework for attracting and retaining engineering students to enhance the Nation’s STEM workforce. This effort will be focused particularly on students from under-represented populations through the development and delivery of engaging, place-based educational activities.
The goal of this CAREER project is to provide innovative solutions to reduce the expense of collecting time-resolved, chemically speciated, air-quality measurements. This will be achieved through the development of cost-effective carbon nanofiber sensors, with complementary data analytics and community-engaged measurements to solve critical air-quality issues. The sensors will be deployed in a high-resolution sensor network capable of geolocating air pollution sources. Formaldehyde, a human carcinogen, is the focus of the project because it is an urgent problem in northern Utah due to local ambient levels that are 50 times greater than US EPA’s cancer risk threshold. The objectives of the research project are to develop: (1) A broadly applicable set of techniques and principles for identifying a pollutant source that leverages a distributed network of validated, cost-effective, carbon-nanofiber-based, air-quality sensors; (2) Cost-effective techniques to differentiate between primary and secondary pollutant sources; and (3) Versatile data analytics for integrating meteorological information with measurements of key chemical species. Data analytics will include multivariate data analysis techniques, forward and back trajectory modeling, conditional bivariate probability functions, and cluster analysis. Together, these novel developments will be applied to a low-cost sensor dataset to detect formaldehyde source(s) in northern Utah. The proposed research will be broadly impactful as the general nature of the approach will work across numerous domains, including smart and connected cities, community-engaged science, chemical threat detection, indoor-air quality, environmental justice, and education. This project also provides a rich framework for STEM education and sustainable opportunities for attracting and retaining engineering students, particularly those from under-represented populations through the development and delivery of engaging, place-based educational activities.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
