Clustering approaches to improve the performance of low cost air pollution sensors.
Clustering approaches to improve the performance of low cost air pollution sensors.
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DOI：
10.1039/c7fd00020k
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发表时间：
2017-08
影响因子：
3.4
通讯作者：
Katie R Smith;P. Edwards;M. Evans;James D. Lee;M. Shaw;F. Squires;S. Wilde;A. Lewis
中科院分区：
文献类型：
--
作者：
Katie R Smith;P. Edwards;M. Evans;James D. Lee;M. Shaw;F. Squires;S. Wilde;A. Lewis
低成本的空气污染传感器在大气研究和城市环境污染的应用控制方面具有很大的潜力，包括向公众发出更多的局部警告。当前一代的单一化学气体传感器会受到其他共同污染物的不同程度的干扰，并对温度、风速和电源电压等环境因素敏感。由于传感器对传感器响应的可变性，也引入了不确定性，尽管这一点报道较少。金属氧化物传感器（MOS）对挥发性有机化合物（VOC）的灵敏度随相对湿度（RH）的变化而变化，在19- 90%RH的范围内最多可达5倍，并且在任何给定RH下校正系数为2的不确定性。MOS和电化学CO传感器响应的短期（秒到分钟）稳定性是合理的。在更长时间的使用过程中，由于单个传感器响应（对被测变量或干扰或两者）在数小时至数天的时间尺度上漂移的不可预测的变异性，传感器间定量可比性降低。对于超过一周的时间尺度，相同的传感器显示出缓慢的，往往是向下的，漂移在他们的反应，其中分歧在六个CO传感器高达30%，两周后。根据单个传感器性能和外部参考值，对6、8和多达21个传感器集群中的中值传感器得出的测量值进行评价。聚类方法保持了传感器设备的成本竞争力，但传感器信号集合的中值浓度在很大程度上消除了单个传感器中出现的随机化的逐时响应漂移，并排除了少量性能差的传感器的影响，这些传感器在较长的时间段内显著漂移。结果表明，为了使各个传感器彼此之间以及与参考仪器之间具有最佳可比性，它们可能需要频繁校准。集群中值的使用消除了不可预测的中期响应变化和其他长期异常值行为，延长了校准之间可能需要的时间，并使校准之间的线性插值更加合适。通过使用传感器集群而不是单个传感器，现有的低成本技术可以大大提高观测质量。
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 of 19-90% RH and with an uncertainty in the correction of a factor of 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.