Development of a calibration chamber to evaluate the performance of low-cost particulate matter sensors
Development of a calibration chamber to evaluate the performance of low-cost particulate matter sensors
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DOI：
10.1016/j.envpol.2019.113131
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发表时间：
2019-12-01
影响因子：
8.9
通讯作者：
Kelly, K. E.
中科院分区：
文献类型：
--
作者：
Sayahi, T.;Kaufman, D.;Kelly, K. E.
低成本颗粒物（PM）空气质量传感器正变得广泛可用，并且由于其低成本、紧凑性和提供更高分辨率的时空PM浓度的能力而越来越多地部署在周围和家庭/工作场所环境中。然而，来自这些传感器的PM数据的质量通常是有问题的，并且传感器需要针对它们将进行测量的环境条件单独进行表征。在这项研究中，我们设计和评估了一个具有成本效益的（4700）校准室，能够连续提供一个统一的PM浓度，同时多个低成本的PM传感器和强大的校准关系，是独立的传感器位置。该室的设计和评估与计算流体动力学（CFD）模型和严格的实验协议。然后，我们使用该新室校准了来自两个生产批次（批次I和II）的242个Plantower PMS 3003传感器，其中两种气溶胶类型为：硝酸铵（批次I和II）和氧化铝（批次I）。我们的CFD模型和实验表明，该室能够同时向8个PM传感器提供均匀的PM浓度，误差在6%以内，并且具有出色的可靠性（组内相关系数> 0.771）。该研究确定了两个故障传感器，并表明其余传感器与针对每种气溶胶类型校准的DustTrak监测仪具有高度线性相关性（R-2 > 0.978）。最后，结果揭示了批次I和II传感器对相同气溶胶的响应之间的统计学显著差异（P值
Low-cost particulate matter (PM) air quality sensors are becoming widely available and are being increasingly deployed in ambient and home/workplace environments due to their low cost, compactness, and ability to provide more highly resolved spatiotemporal PM concentrations. However, the PM data from these sensors are often of questionable quality, and the sensors need to be characterized individually for the environmental conditions under which they will be making measurements. In this study, we designed and assessed a cost-effective (4700) calibration chamber capable of continuously providing a uniform PM concentration simultaneously to multiple low-cost PM sensors and robust calibration relationships that are independent of sensor position. The chamber was designed and evaluated with a Computational Fluid Dynamics (CFD) model and a rigorous experimental protocol. We then used this new chamber to calibrate 242 Plantower PMS 3003 sensors from two production lots (Batches I and II) with two aerosol types: ammonium nitrate (for Batches I and II) and alumina oxide (for Batch I). Our CFD models and experiments demonstrated that the chamber is capable of providing uniform PM concentration to 8 PM sensors at once within 6% error and with excellent reliability (intraclass correlation coefficient > 0.771). The study identified two malfunctioning sensors and showed that the remaining sensors had high linear correlations with a DustTrak monitor that was calibrated for each aerosol type (R-2 > 0.978). Finally, the results revealed statistically significant differences between the responses of Batches I and II sensors to the same aerosol (P-value