Abstract
Abstract. The use of low-cost air quality sensors for air pollution research has outpaced our understanding of their capabilities and limitations under real-world conditions, and there is thus a critical need for understanding and optimizing the performance of such sensors in the field. Here we describe the deployment, calibration, and evaluation of electrochemical sensors on the island of Hawai`i, which is an ideal test bed for characterizing such sensors due to its large and variable sulfur dioxide (SO2) levels and lack of other co-pollutants. Nine custom-built SO2 sensors were co-located with two Hawaii Department of Health Air Quality stations over the course of 5 months, enabling comparison of sensor output with regulatory-grade instruments under a range of realistic environmental conditions. Calibration using a nonparametric algorithm (k nearest neighbors) was found to have excellent performance (RMSE < 7 ppb, MAE < 4 ppb, r2 > 0.997) across a wide dynamic range in SO2 (< 1 ppb, > 2 ppm). However, since nonparametric algorithms generally cannot extrapolate to conditions beyond those outside the training set, we introduce a new hybrid linear–nonparametric algorithm, enabling accurate measurements even when pollutant levels are higher than encountered during calibration. We find no significant change in instrument sensitivity toward SO2 after 18 weeks and demonstrate that calibration accuracy remains high when a sensor is calibrated at one location and then moved to another. The performance of electrochemical SO2 sensors is also strong at lower SO2 mixing ratios (< 25 ppb), for which they exhibit an error of less than 2.5 ppb. While some specific results of this study (calibration accuracy, performance of the various algorithms, etc.) may differ for measurements of other pollutant species in other areas (e.g., polluted urban regions), the calibration and validation approaches described here should be widely applicable to a range of pollutants, sensors, and environments.
Highlights
The last several years have seen an explosion in the use of low-cost sensor technologies for air pollution monitoring efforts (Snyder et al, 2013)
The low cost, small size, and low power consumption of these sensors offer the promise of distributed measurements over wide geographical areas, with potential applications for topics such as air quality (AQ) monitoring, source attribution, human exposure and epidemiology, and atmospheric chemistry
Nine sensor nodes were installed at the Pahala AQ station for no less than 48 h each over a 4-day period (15–19 January 2017) for initial calibration. (Two additional nodes lost power for some fraction of this calibration period and are not included in this study.) At the end of this calibration period, two nodes were re-located to the Hilo AQ station (23 January 2017 – ongoing as of August 2017), and three nodes remained at Pahala
Summary
The last several years have seen an explosion in the use of low-cost sensor technologies for air pollution monitoring efforts (Snyder et al, 2013). Accurate AQ measurements and estimates of human exposure to volcanic pollution (“vog”) require a relatively dense monitoring network; the present calibration study is part of a planned island-wide AQ sensor network This location represents an ideal test bed for sensor characterization and validation, since air pollution is dominated by SO2, with no interfering gas-phase co-pollutants (H2S emissions from Kılauea are generally quite low; Edmonds et al, 2013), and the dynamic range in SO2 can be very large (varying from < 1 ppb to > 1 ppm). We investigate the performance of the calibrations given practical constraints (e.g., the possibility that measurement conditions may be different from those of the calibration period) and examine how sensitivity changes over a period of several months
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