An evaluation tool kit of air quality micro-sensing units

Abstract

Recent developments in sensory and communication technologies have made the development of portable air-quality (AQ) micro-sensing units (MSUs) feasible. These MSUs allow AQ measurements in many new applications, such as ambulatory exposure analyses and citizen science. Typically, the performance of these devices is assessed using the mean error or correlation coefficients with respect to a laboratory equipment. However, these criteria do not represent how such sensors perform outside of laboratory conditions in large-scale field applications, and do not cover all aspects of possible differences in performance between the sensor-based and standardized equipment, or changes in performance over time. This paper presents a comprehensive Sensor Evaluation Toolbox (SET) for evaluating AQ MSUs by a range of criteria, to better assess their performance in varied applications and environments. Within the SET are included four new schemes for evaluating sensors' capability to: locate pollution sources; represent the pollution level on a coarse scale; capture the high temporal variability of the observed pollutant and their reliability. Each of the evaluation criteria allows for assessing sensors' performance in a different way, together constituting a holistic evaluation of the suitability and usability of the sensors in a wide range of applications. Application of the SET on measurements acquired by 25 MSUs deployed in eight cities across Europe showed that the suggested schemes facilitates a comprehensive cross platform analysis that can be used to determine and compare the sensors' performance. The SET was implemented in R and the code is available on the first author's website.

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“…The data for PM 2.5 concentrations from the AURN station are not yet available for the 13 th -16 th February. Table IV gives the Root Mean Square Error (RMSE) and the Pearson coefficient (R 2 ) of the sensor data compared when using "Southampton centre" monitoring station as a reference using a sensor evaluation toolbox [34]. The Plantower…”

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“…Unfortunately, Table 2 also shows that RMSE is mainly unreportable in the literature. As already mentioned above, integrated indicators, such as the IPI [34], would breach our objective to use solely quantitative and comparable indicators. Additionally, it is impossible to compute IPIs a posteriori, since time series are mainly not available in literature.…”

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“…A current search for “air pollution monitor” in crowdsourcing websites such as Indigogo, Kickstarter, or GoFundMe reveal hundreds of new air pollution monitors under development. The issue of un-validated air pollution sensors has been highlighted in other commentaries [9,18,19] and toolkits proposed for evaluating new monitors [20]. Determining the capabilities of new sensors to accurately capture pollutant concentrations is essential for ensuring individual measurements are valid and can be used for scientific research.…”