Evaluation of Low-Cost Sensors for Ambient PM2.5 Monitoring
Evaluation of Low-Cost Sensors for Ambient PM2.5 Monitoring
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DOI：
10.1155/2018/5096540
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发表时间：
2018-01-01
影响因子：
1.9
通讯作者：
Modzel, Piotr
中科院分区：
文献类型：
--
作者：
Badura, Marek;Batog, Piotr;Modzel, Piotr
低成本传感器是提高颗粒物数据的空间和时间分辨率的机会。然而，在采取任何监测行动之前，应在接近最终条件的条件下对这些传感器进行校准。本文介绍了四种型号的低成本光学传感器与TEOM 1400 a分析仪的搭配比较的结果。在本研究中使用SDS 011（Nova Fitness）、ZH 03 A（Winsen）、PMS 7003（Plantower）和OPC-N2（Alphasense）传感器。将每个传感器型号的三个副本放置在一个共同的盒子中，以比较相同测量条件下的传感器性能。从2017年8月21日至2018年2月19日，在弗罗茨瓦夫（波兰）对PM2.5进行了近半年的监测。根据变异系数（CV）评估传感器单元之间的重现性。SDS 011和PMS 7003传感器的CV值低于7%，OPC-N2装置的CV值等于20%。ZHO 3A的CV高于50%，主要是由于故障。在测量过程中，从传感器的输出的趋势一般类似于TEOM数据，但观察到的传感器原始数据的PM2.5浓度显着高估。对于PMS 7003传感器（R-2约为0.83-0.89）、SDS 011装置（R-2约为0.79-0.86）和1个ZHO 3A装置（R-2约为0.74-0.81）的1 min、15 min和1小时平均数据，注意到TEOM和传感器之间的高度线性关系。PMS 7003、SDS 011和ZHO 3A的日平均值的R-2值分别为0.91-0.93、0.87-0.90和0.89。OPC-N2与TEOM只有中等程度的线性关系（日数据的R-2约为0.53-0.69，较短时间平均值的R-2约为0.43-0.61）。在低于20-30 μ g/m的浓度范围内，观察到数据的分散性很大，PM 2.5估计的相对误差很高（3）。观察到SDS 011和OPC-N2设备的高相对湿度水平的影响-在80%RH以上观察到输出明显高估。
Low-cost sensors are an opportunity to improve the spatial and temporal resolution of particulate matter data. However, such sensors should be calibrated under conditions close to the final ones before any monitoring actions. The paper presents the results of a collocated comparison of four models of low-cost optical sensors with a TEOM 1400a analyser. SDS011 (Nova Fitness), ZH03A (Winsen), PMS7003 (Plantower), and OPC-N2 (Alphasense) sensors were used in this research. Three copies of each sensor model were placed in a common box to compare the sensor performance under the same measurement conditions. Monitoring of the PM2.5 fraction was conducted for almost half a year from 21 August 2017 to 19 February 2018 in Wroclaw (Poland). Reproducibility between sensor units was assessed on the basis of coefficient of variation (CV). CV values were lower than 7% in the case of SDS011 and PMS7003 sensors and equal to 20% for OPC-N2 units. CV was higher than 50% for ZHO3A, mainly due to malfunctions. During the measurements, the trends of outputs from sensors were generally similar to TEOM data, but significant overestimation of PM2.5 concentrations was observed for the sensor raw data. A high linear relationship between TEOM and sensors was noticed for 1 min, 15 min, and 1-hour averaged data for PMS7003 sensors (R-2 approximate to 0.83-0.89), for SDS011 units (R-2 approximate to 0.79-0.86), and for one unit of ZHO3A (R-2 approximate to 0.74-0.81). R-2 values for daily averages were at the level 0.91-0.93 for PMS7003, 0.87-0.90 for SDS011, and 0.89 for ZHO3A. OPC-N2 had only a moderate linear relationship with TEOM (R-2 approximate to 0.53-0.69 for daily data and 0.43-0.61 for shorter time averages). Quite large dispersion of data and high relative errors of PM 2.5 estimation were observed for concentration ranges below 20-30 mu g/m(3) . The impact of high relative humidity level was observed for SDS011 and OPC-N2 devices-clear overestimation of outputs was observed above 80% RH.