Clustering approaches to improve the performance of low cost air pollution sensors

Abstract

Article:Smith, Katie R., Edwards, Peter M. orcid.org/0000-0002-1076-6793, Evans, Mathew J. orcid.org/0000-0003-4775-032X et al. (5 more Low cost air pollution sensors have substantial potential for atmospheric research and for the applied control of pollution in the urban environment, including more localized warnings to the public. The current generation of single-chemical gas sensors experience degrees of interference from other co-pollutants and have sensitivity to environmental factors such as temperature, wind speed and supply voltage. There are uncertainties introduced also because of sensor-to-sensor response variability, although this is less well reported. The sensitivity of Metal Oxide Sensors (MOS) to volatile organic compounds (VOCs) changed with relative humidity (RH) by up to a factor of five over the range 19-90%RH and with an uncertainty in the correction of a factor two at any given RH. The short-term (second to minute) stabilities of MOS and electrochemical CO sensor responses were reasonable. During more extended use inter-sensor quantitative comparability was degraded due to unpredictable variability in individual sensor responses (to either measurand or interference or both) drifting over timescales of several hours to days. For timescales longer than a week identical sensors showed slow, often downwards, drifts in their responses which diverged across six CO sensors by up to 30% after two weeks. The measurement derived from the median sensor within clusters of 6, 8 and up to 21 sensors was evaluated against individual sensor performance and external reference values. The clustered approach maintained the cost competitiveness of a sensor device, but the median concentration from the ensemble of sensor signals largely eliminated the randomised hour-to-day response drift seen in individual sensors and excluded the effects of small numbers of poorly performing sensors that drifted significantly over longer time periods. The results demonstrate that for individual sensors to be optimally comparable to one another, and to reference instruments, they would likely require frequent calibration. The use of a cluster median value eliminates unpredictable medium term response changes, and other longer term outlier behaviours, extending the likely period needed between calibration and making a linear interpolation between calibrations more appropriate. Through the use of sensor clusters rather than individual sensors existing low cost technologies could deliver significantly improved quality of observations.

Development of a general calibration model and long-term performance evaluation of low-cost sensors for air pollutant gas monitoring

“…Current regulatory methods for assessing urban air quality rely on a small network of monitoring stations providing highly precise measurements (at a commensurately high setup and operating cost) of specific air pollutants (e.g., Snyder et al, 2013). The United States Environmental Protection Agency (EPA) determines compliance with national air quality standards at the county level using data collected by local monitoring stations.…”

“…This allows larger numbers of monitors to be employed at a cost similar to that of a more traditional monitoring network as described above. The general goals of low-cost sensing include supplementing existing regulatory networks, monitoring air quality in areas that have lacked this in the past (for example in developing countries), and increasing community involvement in air quality monitoring through the provision of sensors and the resulting data to community volunteers to support more informed public decision-making and engagement in air quality issues (Snyder et al, 2013;Loh et al, 2017;Turner et al, 2017). Several pilot programs of low-cost sensor network deployment have been attempted, in Cambridge, UK (Mead et al, 2013); Imperial Valley, California (Sadighi et al, 2018;English et al, 2017); and Pittsburgh, Pennsylvania (Zimmerman et al, 2018).…”

Opportunities for Low‐Cost Particulate Matter Sensors in Filter Emission Measurements

“…The majority of studies report mixed results of the low‐cost sensors' performance in terms of precision and accuracy . An attempt has been made to find correction factors in order to increase accuracy , . Relative humidity has been identified as one of the main factors contributing to errors in measurement of low‐cost PM sensors , , .…”

“…An attempt has been made to find correction factors in order to increase accuracy , . Relative humidity has been identified as one of the main factors contributing to errors in measurement of low‐cost PM sensors , , . The measured particles are to a certain degree hygroscopic and increase in size as they absorb water from their surroundings.…”

“…Additionally, discrepancies were detected between individual sensors of the same model, introducing a greater amount of uncertainty [14, 19]. To minimize any errors, the appropriate and frequent calibration of low‐cost sensors was suggested , , , . Liu emphasized the importance of a steady‐state particle concentration during the calibration process .…”