Abstract Low-cost particle sensors are rapidly gaining popularity for indoor air quality monitoring, but their accuracy has been shown to vary among products and among environments in which they operate. Previous research has explored the effect of environmental conditions including temperature and humidity on sensor accuracy and found appreciable effects of these variables in many cases. We extend this work to cover some models that have not been previously tested and analyze results in a way to establish the significance of environmental variables on low-cost sensor output. In this study, we conduct a series of laboratory experiments in which temperature and relative humidity (RH) are varied in a precisely controlled chamber and different common particle sources introduced. Eight different brands of low-cost particle sensors, some of which have not been previously analyzed in this manner, measured particle concentration inside the chamber and were compared to research-grade instruments. Comparison of the output of the research-grade instruments with that of the low-cost sensors yielded a few interesting results. First, temperature showed no statistically significant effect on sensor performance in any case, at 99% confidence. Second, RH appears to affect the magnitude of low-cost sensor output but not its correlation to research-grade instruments output, suggesting the possibility of RH-based calibration.

中文翻译：

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温度和相对湿度对八种低成本粒子传感器和器件性能影响的系统研究

摘要 低成本粒子传感器在室内空气质量监测中迅速普及，但其准确性已被证明因产品和运行环境而异。先前的研究探索了包括温度和湿度在内的环境条件对传感器精度的影响，并发现这些变量在许多情况下具有明显的影响。我们将这项工作扩展到涵盖一些先前未经过测试的模型，并以某种方式分析结果，以确定环境变量对低成本传感器输出的重要性。在这项研究中，我们进行了一系列实验室实验，其中温度和相对湿度 (RH) 在精确控制的腔室中发生变化，并引入了不同的常见粒子源。八种不同品牌的低成本粒子传感器，其中一些以前没有以这种方式进行过分析，测量了室内的粒子浓度，并与研究级仪器进行了比较。将研究级仪器的输出与低成本传感器的输出进行比较，得出了一些有趣的结果。首先，在 99% 的置信度下，温度在任何情况下都没有显示出对传感器性能的统计显着影响。其次，RH 似乎影响低成本传感器输出的幅度，但不影响其与研究级仪器输出的相关性，这表明基于 RH 的校准的可能性。将研究级仪器的输出与低成本传感器的输出进行比较，得出了一些有趣的结果。首先，在 99% 的置信度下，温度在任何情况下都没有显示出对传感器性能的统计显着影响。其次，RH 似乎影响低成本传感器输出的幅度，但不影响其与研究级仪器输出的相关性，这表明基于 RH 的校准的可能性。将研究级仪器的输出与低成本传感器的输出进行比较，得出了一些有趣的结果。首先，在 99% 的置信度下，温度在任何情况下都没有显示出对传感器性能的统计显着影响。其次，RH 似乎影响低成本传感器输出的幅度，但不影响其与研究级仪器输出的相关性，这表明基于 RH 的校准的可能性。