Researchers from the University of Washington and the University of Georgia have unveiled an affordable paper-based sensor paired with a smartphone reader that can now give individuals near real-time measurements of their personal smoke exposure by detecting specific biomarkers excreted in urine. The research, published in ACS Applied materials and Interfaces, can be found here:
Yang, Z., Li, X., Fu, Y., Song, Y., Simpson, C. D., Naeher, L. P., Lin, Y., & Du, D. (2025). Mesoporous Pd@Pt Nanoparticle Label/Lateral Flow Immunoassay Integrated with a 3D-Printed Smartphone Reader for Detection of Wood Smoke Biomarkers. ACS Applied Materials & Interfaces. https://doi.org/10.1021/acsami.5c02147
Wildfire smoke contains a complex mix of particulates and volatile organic compounds linked to respiratory and cardiovascular diseases, as well as DNA damage from compounds like benzene. Exposure estimates rely on satellite data, weather models and stationary monitors, which can miss localised variations and cannot account for individual metabolism of pollutants. Annie Du, a research professor in WSU’s School of Mechanical and Materials Engineering who is leading the project said:
“You’re exposed to smoke when you breathe in the polluted air, but your body changes that to a metabolite and introduces changes to your DNA, that’s why we are focused on early detection. We want to catch biological changes before clinical symptoms appear.”
The core of the news system developed by the research team is a lateral flow immunoassay strip labeled with mesoporous palladium–platinum nanoparticles that bind to s-phenylmercapturic acid (S-PMA), a key benzene metabolite in urine. The flower-like palladium–platinum particles catalyse a colour change proportional to the S-PMA concentration, amplifying the signal for sensitive detection. Du stated:
“Our goal is to quickly identify the exposure onsite in real time and report it with a smartphone reader, so agencies can quickly identify the exposure level and location and make decisions for a hazard prevention strategy,”
In laboratory tests, the paper sensor achieved a limit of detection down to 0.32 ng mL⁻¹ S-PMA, with a linear quantification range of 0.25–30 ng mL⁻¹ and storage stability of at least one year at room temperature. These performance metrics match or exceed those of conventional lab-based assays, while reducing cost and equipment needs.
To make the assay field-ready, the team designed a custom 3D-printed housing that holds a smartphone camera in a fixed position over the test strip. A companion app analyses the strip’s colourimetric change, logs the result alongside GPS coordinates, and uploads data to a secure server for mapping exposure hotspots.
Field trials with wildland firefighters will begin this summer, comparing on-site readings to standard laboratory measurements before expanding to other at-risk communities.
By quantifying personal exposure on demand, this platform could enable early detection of biologically relevant pollutant levels; long before clinical symptoms arise, and guide decisions on protective actions, work-rest cycles, or evacuation in high-risk zones.
The project was carried out by a multidisciplinary team of researchers: Zhansen Yang, Xinyi Li, Yonghao Fu, Yang Song, Christopher D. Simpson, Luke P. Naeher, Yuehe Lin and Annie Du; bringing together expertise in nanoparticle synthesis, immunoassay development, and field deployable sensor design.
Hassan graduated with a Master’s degree in Chemical Engineering from the University of Chester (UK). He currently works as a design engineering consultant for one of the largest engineering firms in the world along with being an associate member of the Institute of Chemical Engineers (IChemE).
