Low-complexity methods to mitigate the impact of environmental variables on low-cost UAS-based atmospheric carbon dioxide measurements

Abstract

This article assesses the individual and joint impact of pressure, temperature, and relative humidity on the accuracy of atmospheric CO2 measurements collected by unmanned aerial systems (UASs) using low-cost commercial non-dispersive infrared (NDIR) sensors. We build upon previous experimental results in the literature and present a new dataset with increased gradients for each environmental variable to match the abrupt changes found in UAS-based atmospheric vertical profiles. As a key contribution, we present a low-complexity correction procedure to mitigate the impact of these variables and reduce errors in this type of atmospheric CO2 measurement. Our findings support the use of low-cost NDIR sensors for UAS-based atmospheric CO2 measurements as a complementary in situ tool for many scientific applications.