Preprints
https://doi.org/10.5194/egusphere-2022-200
https://doi.org/10.5194/egusphere-2022-200
 
28 Apr 2022
28 Apr 2022
Status: this preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).

Optimizing co-location calibration periods for low-cost sensors

Misti Levy Zamora1,2,3, Colby Buehler3,4, Abhirup Datta5, Drew R. Gentner3,4, and Kirsten Koehler2,3 Misti Levy Zamora et al.
  • 1University of Connecticut Health Center, Department of Public Health Sciences UConn School of Medicine, 263 Farmington Avenue, Farmington, CT, USA 06032-1941
  • 2Johns Hopkins University Bloomberg School of Public Health, Environmental Health and Engineering 615 N Wolfe St, Baltimore, MD, USA 21205-2103
  • 3SEARCH (Solutions for Energy, Air, Climate and Health) Center, Yale University, New Haven, CT, USA 06520
  • 4Yale University, Chemical and Environmental Engineering, PO Box 208286, New Haven, CT, USA 06520
  • 5Johns Hopkins University Bloomberg School of Public Health, Department of Biostatistics 615 N. Wolfe Street, Baltimore, MD, USA 21205-2103

Abstract. Low-cost sensors are often co-located with reference instruments to assess their performance and establish calibration equations, but limited discussion has focused on whether the duration of this calibration period can be optimized. We placed a multipollutant monitor that contained sensors that measure particulate matter smaller than 2.5 mm (PM2.5), carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), and nitric oxide (NO) at a reference field site for one year. We developed calibration equations using randomly co-location subsets spanning 1 to 180 consecutive days out of the 1-year period and compared the potential root mean square errors (RMSE) and Pearson correlation coefficients (r). The co-located calibration period required to obtain consistent results varied by sensor type, and several factors increased the co-location duration required for accurate calibration, including the response of a sensor to environmental factors, such as temperature or relative humidity (RH), or cross-sensitivities to other pollutants. Using measurements from Baltimore, MD, where a broad range of environmental conditions may be observed over a given year, we found diminishing improvements in the median RMSE for calibration periods longer than about six weeks for all the sensors. The best performing calibration periods were the ones that contained a range of environmental conditions similar to those encountered during the evaluation period (i.e., all other days of the year not used in the calibration). With optimal, varying conditions it was possible to obtain an accurate calibration in as little as one week for all sensors, suggesting that co-location can be minimized if the period is strategically selected and monitored so that the calibration period is representative of the desired measurement setting.

Misti Levy Zamora et al.

Status: open (until 20 Jun 2022)

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Misti Levy Zamora et al.

Misti Levy Zamora et al.

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Short summary
We assessed five pairs of co-located reference and low-cost sensor datasets (PM2.5, O3, NO2, NO, and CO) to make recommendations for best practices regarding the field calibration of low-cost air quality sensors. We found diminishing improvements for calibration periods longer than about six weeks for all the sensors and that co-location can be minimized if the period is strategically selected and monitored so that the calibration period is representative of the desired measurement setting.