Evaluation of Three Low-Cost Particulate Matter (PM2.5) Sensors for Ambient and High Exposure Conditions in Arba Minch, Ethiopia

Abstract

The burden of disease from ambient and indoor air pollution is highest in low-income countries, while their resources for monitoring air pollutants are the lowest. PM2.5 is the primary indicator of air pollution. Reference monitors of PM2.5 are expensive, but there is an increased use of low-cost sensors (LCS). Three LCS, the UCB-PATS+ (PATS), Airvisual Pro (IQAV) and Sensirion SPS30 (SPSA) are being used in Arba Minch, Ethiopia, but their quality has not yet been evaluated under circumstances common to low-income countries, and the variety of metrics used in evaluation studies make comparisons difficult. This study aims to evaluate the three LCS under circumstances encountered in Arba Minch, with metrics commonly used and officially prescribed. Measurements were conducted with the LCS at 2 ambient and 4 high exposure (kitchen) concentrations, and at four of those locations with the gravimetric reference method as well. The quality of the three LCS was evaluated within identical, with reference, and between different types, with commonly reported (regression slope and R2) and officially prescribed (Pearson correlation, bias, accuracy, expanded uncertainty) metrics. The SPSA has low within variation in both ambient and high-exposure situations, meets official requirements compared to the reference, and shows a stable bias across different time and concentration levels. The IQAV and PATS within variations are not up to official standards but show strong linear associations. The IQAVs as a group, and PATSs individually, meet official reference requirements at daily level. Between comparison reveals that all LCS show strong linear associations even at 10-minute average level. For SPSA the association is similar across all ranges, and for the others the association is strong when different ranges are taken into account. Generally, all LCS are a good alternative for expensive reference methods. The strong linear associations suggest the possibility of correcting LCS measurement data based on other studies’ results and based on other LCS, across different concentration ranges. Projects with a budget of $600 can already supply 10 measurement locations. Higher-budget projects can contribute to the quality of low-budget projects when they do not only use expensive monitors, but also LCS at the same location.