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This article can be cited before page numbers have been issued, to do this...

deSouza, P., K. Barkjohn, A. Clements, J. Lee, R. Kahn, B. Crawford, and P. Kinney (2023), This article can be cited before page numbers have been issued, to do this please use: P. N. deSouza, K., View Article Online, doi:10.1039/D2EA00142J.

Low-cost sensors (LCS) are increasingly being used to measure fine particulate matter

(PM2.5) concentrations in cities around the world. One of the most commonly deployed

LCS is the PurpleAir with ~ 15,000 sensors deployed in the United States. PurpleAir

measurements are widely used by the public to evaluate PM2.5 levels in their

neighborhoods. PurpleAir measurements are also increasingly being integrated into

models by researchers to develop large-scale estimates of PM2.5. However, the change

in sensor performance over time has not been well studied. It is important to understand

the lifespan of these sensors to determine when they should be replaced, and when

measurements from these devices should or should not be used for various

applications. This paper fills in this gap by leveraging the fact that: (1) Each PurpleAir

sensor is comprised of two identical sensors and the divergence between their

measurements can be observed, and (2) There are numerous PurpleAir sensors within

~ 50 meters of regulatory monitors allowing for the comparison of measurements

between these instruments. We propose empirically-derived degradation outcomes for

the PurpleAir sensors and evaluate how these outcomes change over time. On

average, we find that the number of ‘flagged’ measurements, where the two sensors

within each PurpleAir sensor disagree, increases with time to ~ 4% after 4 years of

operation. Approximately, 2 percent of all PurpleAir sensors were permanently

degraded. The largest fraction of permanently degraded PurpleAir sensors appeared to

be in the hot and humid climate zone, suggesting that sensors in this location may need

to be replaced sooner. We also find that the bias of PurpleAir sensors, or the difference

between corrected PM2.5 levels and the corresponding reference measurements,

changed over time by -0.12 μg/m3 (95% CI: -0.13 μg/m3, -0.11 μg/m3) per year. The

average bias increases dramatically after 3.5 years. Climate zone is a significant

modifier of the association between degradation outcomes and time.

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Research Program: 
Applied Sciences Program (ASP)
Atmospheric Composition
Atmospheric Composition Modeling and Analysis Program (ACMAP)