Calibration of Low-Cost NO2 Sensors through Environmental Factor Correction.

Jason Miech,Meiling Gao,Levi Stanton,Matthew Fraser,Joshua Uebelherr,Paolo Micalizzi,Pierre Herckes

doi:10.3390/toxics9110281

Abstract

Low-cost air quality sensors (LCSs) have become more widespread due to their low cost and increased capabilities; however, to supplement more traditional air quality networks, the performance of these LCSs needs to be validated. This study focused on NO2 measurements from eight Clarity Node-S sensors and used various environmental factors to calibrate the LCSs. To validate the calibration performance, we calculated the root-mean-square error (RMSE), mean absolute error (MAE), R2, and slope compared to reference measurements. Raw results from six of these sensors were comparable to those reported for other NO2 LCSs; however, two of the evaluated LCSs had RMSE values ~20 ppb higher than the other six LCSs. By applying a sensor-specific calibration that corrects for relative humidity, temperature, and ozone, this discrepancy was mitigated. In addition, this calibration improved the RMSE, MAE, R2, and slope of all eight LCS compared to the raw data. It should be noted that relatively stable environmental conditions over the course of the LCS deployment period benefited calibration performance over time. These results demonstrate the importance of developing LCS calibration models for individual sensors that consider pertinent environmental factors.

Highlights

Annual ambient NO2 concentrations have been decreasing in many locations in North America, many East Asian countries are seeing increases in the annual meanNO2 concentration [1]
We examined the impact of environmental factors such as temperature, relative humidity, and ozone on the Low-cost air quality sensors (LCSs) and developed calibration methods to correct for these potential influences
By testing eight LCSs, we demonstrated that not all sensors of the same make and model always behave the same, as we saw that LCS #5 and #11 have substantially larger root-mean-square error (RMSE) values and lower R2 values than the other LCSs

Summary

Introduction

Annual ambient NO2 concentrations have been decreasing in many locations in North America, many East Asian countries are seeing increases in the annual mean. The U.S Environmental Protection Agency’s (EPA) current National Ambient Air Quality Standard (NAAQS) for 1-h NO2 is 100 ppbV, while the World Health Organization’s 2005 1-h NO2 guideline value is 200 μg/m3 [4,5]. Even in areas that meet health-based standards to protect against exposure to NO2 , there is still the need to measure ambient NO2 levels, as photochemical reactions of NO2 can result in ground-level ozone and fine particle formation [4]. The main purpose of air monitoring networks is to observe the community’s exposure to air pollutants. In Maricopa County, Arizona, regulatory monitoring includes quantification of ambient levels of NO2 , CO, PM10

Methods

Results

Conclusion