Long-term field evaluation of the Plantower PMS low-cost particulate matter sensors
Long-term field evaluation of the Plantower PMS low-cost particulate matter sensors
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DOI：
10.1016/j.envpol.2018.11.065
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发表时间：
2019-02-01
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.;Butterfield, A.;Kelly, K. E.
基于光散射的颗粒物（PM）传感器的低成本和紧凑尺寸为改进时空分辨PM测量提供了机会。然而，这些廉价的传感器具有局限性，需要在现实条件下进行表征。本研究评估了两台Plantower PMS（颗粒物传感器）1003和两台PMS 5003在犹他湖城户外320天（2016年1月至2016年2月和2015年12月至2017年10月）内的多个季节和各种PM2.5升高事件，包括冬季冷空气池（CAP）、烟花和野火。PMS 1003/5003传感器通常跟踪PM2.5浓度，与同位置参考空气监测器（一个锥形元件振荡微量天平，TEOM和一个重量联邦参考方法，FRM）相比。不同的PMS传感器型号和相同传感器型号的集合表现出一些传感器内变异性。在2017年冬季，两个PMS 1003始终高估PM2.5 1.89倍（TEOM PM2.5 0.87）和24小时ERM测量值（R-2 > 0.88），而在2017年春季（3 - 6月）和野火季节（6 - 10月），相关性较差（R-2分别为0.18-0.32和0.48-0.72）。PMS 1003在冬季部署一年后保持了较高的传感器内一致性，然而，一个PMS 1003传感器从2017年3月开始出现显著漂移，并在研究结束时继续恶化。总体而言，这项研究表明，PMS传感器和参考监测器在冬季，传感器性能的季节性差异，一些传感器内的变异性和漂移在一个传感器之间的良好的相关性。当使用来自低成本PM传感器网络的测量值时，应考虑这些类型的因素。(C)2018爱思唯尔有限公司版权所有
The low-cost and compact size of light-scattering-based particulate matter (PM) sensors provide an opportunity for improved spatiotemporally resolved PM measurements. However, these inexpensive sensors have limitations and need to be characterized under realistic conditions. This study evaluated two Plantower PMS (particulate matter sensor) 1003s and two PMS 5003s outdoors in Salt Lake City, Utah over 320 days (1/2016-2/2016 and 12/2015-10/2017) through multiple seasons and a variety of elevated PM2.5 events including wintertime cold-air pools (CAPs), fireworks, and wildfires. The PMS 1003/5003 sensors generally tracked PM2.5 concentrations compared to co-located reference air monitors (one tapered element oscillating microbalance, TEOM, and one gravimetric federal reference method, FRM). The different PMS sensor models and sets of the same sensor model exhibited some intrasensor variability. During winter 2017, the two PMS 1003s consistently overestimated PM2.5 by a factor of 1.89 (TEOM PM2.5 0.87) and 24-h ERM measurements (R-2 > 0.88) while in spring (March-June) and wildfire season (June-October) 2017, the correlations were poorer (R-2 of 0.18-0.32 and 0.48-0.72, respectively). The PMS 1003s maintained high intra-sensor agreement after one year of deployment during the winter seasons, however, one PMS 1003 sensor exhibited a significant drift beginning in March 2017 and continued to deteriorate through the end of the study. Overall, this study demonstrated good correlations between the PMS sensors and reference monitors in the winter season, seasonal differences in sensor performance, some intra-sensor variability, and drift in one sensor. These types of factors should be considered when using measurements from a network of low-cost PM sensors. (C) 2018 Elsevier Ltd. All rights reserved.