Abstract

Monitoring systems are needed to obtain information about particulate matter (PM) concentrations and to make such information accessible to the public. Small, low-cost, optical sensors could be used to improve the spatial and temporal resolution of PM data. The paper presents results of collocated comparison of four low-cost PM sensors and TEOM analyser, conducted from 20-08-2017 to 24-12-2017 in Wrocław, Poland. Plantower PMS7003 and Nova Fitness SDS011 sensors proved to be the best in terms of precision and were linearly correlated with TEOM data. Alphasense OPC-N2 sensors exhibited only moderate precision and linearity. Winsen ZH03A sensors had low repeatability between units and only one copy demonstrated good operation possibilities. All tested sensors had a bias in relation to PM2.5 concentrations obtained from TEOM.

Highlights

  • The term particulate matter (PM) refers to very complex mixtures of small solid particles and liquid droplets suspended in the air [1]

  • Plantower PMS7003 and Nova Fitness SDS011 sensors proved to be the most precise in terms of intra-model variability – the mean coefficient of variation (CV) values were below 7%

  • The trend of PM2.5 concentration changes was generally similar for tapered element oscillating microbalances (TEOMs) device and PM sensors, but bias was observed for all tested sensor models (Table 3)

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Summary

Introduction

The term particulate matter (PM) refers to very complex mixtures of small solid particles and liquid droplets suspended in the air [1]. Standard method for the determination of mass concentration of suspended particulate matter is based on gravimetric measurements [3] This method provides accurate results, only for relatively long periods of sampling (24 hours). Short-term temporal patterns and concentration peaks are masked in this way Complement to this approach is based on automated measuring systems (AMS), applied in routine monitoring networks [12]. In Poland two types of continuous measuring instruments are used in those stations: β-ray attenuation monitors (BAMs) and tapered element oscillating microbalances (TEOMs) Such systems are capable of producing 1-hour average measurement values, that may be used for direct information of the public, e.g. through websites or mobile apps [13]. That kind of comparison takes into account real properties of ambient particulates and could be performed to calibrate any low-cost sensor for air monitoring

Site description
PM sensors measurement setup
Types of data
Precision of sensors
Bias of sensors
Linearity of sensors
Linear correlations between PM sensors and TEOM
Results of linear regression fitting
Humidity influence
Conclusions
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