| 11 Jul 2025
Recalibration of low-cost air pollution sensors: Is it worth it?
Abstract. The appropriate period of collocation of a low-cost air sensor (LCS) with reference measurements is often unknown. Previous low-cost air sensor studies have shown that due to sensor ageing and seasonality of environmental interferences periodical sensor calibration needs to be performed to guarantee sufficient data quality. While the limitations are well-established it is still unclear how often a recalibration of a sensor needs to be carried out. In this study, we aim to demonstrate how frequently widely used air sensors for the relevant air pollutants O3 and PM2.5 by two manufacturers (Alphasense and Sensirion) should be recalibrated. Sensor calibration functions were built using Multiple Linear Regression, Ridge Regression, Random Forest and Extreme Gradient Boosting. We use state-of-the-art test protocols for air sensors provided by the United States Environmental Protection Agency (EPA) and the European Committee for Standardization (CEN) for evaluative guidance. We conducted a yearlong collocation campaign at an urban background air and climate monitoring station next to the University Hospital Augsburg, Germany. LCS were exposed to a wide range of environmental conditions, with air temperatures between -10 and 36 °C, relative air humidity between 19 and 96 % and air pressure between 937 and 983 hPa. The ambient concentration ranges for O3 and PM2.5 were up to 83 ppb and 153 µg m-3, respectively. For the baseline single training of 5 months, the calibrated O3 and PM2.5 sensors were able to reflect the hourly reference data well during the training (R2: O3 = 0.92–1.00; PM2.5 = 0.93–0.98) and the following test period (R2: O3 = 0.93–0.97; PM2.5 = 0.84–0.93). Additionally, the sensor errors were generally acceptable during the training (RMSE: O3 = 0.80–4.35 ppb; PM2.5 = 1.45–2.51 µg m-3) and the following test period (RMSE: O3 = 3.62–5.84 ppb; PM2.5 = 2.04–3.02 µg m-3). By investigating different recalibration cycles using a pairwise calibration strategy, our results indicate that a regular in-season recalibration is required to obtain the highest quantitative validity for the analysed low-cost air sensors, with monthly recalibrations appearing to be the most suitable approach. In contrast, an extension of the training period for the calibration models had only a minor overall impact on improving the low-cost air sensors’ ability to capture temporal variations in observed O3 concentrations and PM2.5 concentrations. The measurement uncertainty of the calibrated O3 LCS and PM2.5 LCS were able to meet the data quality objective (DQO) for indicative measurements for different calibration models. Compared to one-time pre-deployment sensor calibration, in-season recalibration can broaden the scope of application for a LCS (indicative measurements, objective estimation, non-regulatory supplemental and informational monitoring).
First of all, I would like congratulate the authors for the work carried out and presented in this paper. After having read the full document, I'm not sure that the conclusion or the study really answer the question asked in the title. In fact, the author ask the question of the need of re-calibration of low-cost senors but they do not really answer it in the document as the present an interesting use of sensor for ambient air monitoring ("pairwise calibration strategy") based on a monthly exchange of LCS between a collocation site and a measurement site. This strategy, somehow interesting when looking at the sensors performances is much more time consuming than a classic network installation as, at the end, 2 LCS are always running adding the necessity of installation/removal every month. However, the interesting comparison of calibration results using several training length against both US-EPA and European standards brings a lot of valuable information.
I also made some minor comment along the document listed below:
- Line 153: length of this stabilization phase ?
- Line 155: coma could be removed.
- Line 157: The 3 of O3 should be in subscript.
- Line 165: Are the daily means for LCS based on the hourly values or on the raw values ? The end of this paragraph suggest that the daily means has been calculated using hourly values. Did you check the impact on the data ?
- Line 183: This PM sensor sentence seems to me to be not in the right paragraph as the PM data has been discussed on the previous one.
- Line184-189: This explanation could maybe be moved a after the first paragraph of 2.4 where the use of T and RH in the calibration models is explained. It was somehow confusing to me to read first that the data from the BME280 were not used to then see that they are finally used. Only on a second read I pay attention to the fact that the BME280 data were not used for the gas sensors.
- Table 1: the first row is not the easiest to read, in particular for O3 and NO2 as there is not a clear separation between the T (end of O3) and VNO2 (beginning of NO2).
- Line 218: what do you mean by merging the data by hour ? is it the mean calculation ?
- Line 395: you should mention in the previous paragraph 2.7 Performance metrics and target values that the measurement thus the evaluation has been carried out only for a urban background site whereas the CEN document ask for different testing site, for example a rural site for O3.
- Figure 8, 9, 10 and 11: I would advice the authors to write the title of the different graphs on a clearer way, at a first look, it is not easy to see the difference between each plot.