Assessing the accuracy of low-cost optical particle sensors using a physics-based approach.
Assessing the accuracy of low-cost optical particle sensors using a physics-based approach.
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DOI：
10.5194/amt-13-6343-2020
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发表时间：
2020
影响因子：
3.8
通讯作者：
Kroll JH
中科院分区：
文献类型：
--
作者：
Hagan DH;Kroll JH
用于测量颗粒物（PM）的低成本传感器提供了在时空尺度上了解人类暴露于空气污染的能力，这在以前是不切实际的。然而，这种低成本的PM传感器往往特征不佳，并且它们的质量浓度测量可能受到相当大的误差。最近的研究调查了个体因素如何导致这种误差，但这些研究主要基于经验比较，通常不会同时检查多个因素的作用。在这里，我们提出了一个新的基于物理的框架和开源软件包（opcsim），用于评估低成本光学粒子传感器（光学粒子计数器和浊度计）准确表征气溶胶粒子的大小分布和/或质量负载的能力。该框架使用Mie理论计算给定传感器对给定粒子群的响应，用于估计给定相对湿度、气溶胶光学特性和潜在粒径分布变化的不同传感器类型的质量加载分数误差。结果表明，这种误差可能很大，取决于传感器技术（浊度计与光学粒子计数器）、单个传感器的具体参数，以及用于校准传感器和被测量气溶胶之间的差异。我们总结了不同传感器类型、环境条件和颗粒类别的可能误差来源，并提供了在不同测量场景下选择校准剂的一般建议。
Low-cost sensors for measuring particulate matter (PM) offer the ability to understand human exposure to air pollution at spatiotemporal scales that have previously been impractical. However, such low-cost PM sensors tend to be poorly characterized, and their measurements of mass concentration can be subject to considerable error. Recent studies have investigated how individual factors can contribute to this error, but these studies are largely based on empirical comparisons and generally do not examine the role of multiple factors simultaneously. Here, we present a new physics-based framework and open-source software package (opcsim) for evaluating the ability of low-cost optical particle sensors (optical particle counters and nephelometers) to accurately characterize the size distribution and/or mass loading of aerosol particles. This framework, which uses Mie theory to calculate the response of a given sensor to a given particle population, is used to estimate the fractional error in mass loading for different sensor types given variations in relative humidity, aerosol optical properties, and the underlying particle size distribution. Results indicate that such error, which can be substantial, is dependent on the sensor technology (nephelometer vs. optical particle counter), the specific parameters of the individual sensor, and differences between the aerosol used to calibrate the sensor and the aerosol being measured. We conclude with a summary of likely sources of error for different sensor types, environmental conditions, and particle classes and offer general recommendations for the choice of calibrant under different measurement scenarios.