Supplementary material to "Laboratory evaluation of particle size-selectivity of optical low-cost particulate matter sensors"

Abstract. Low-cost particulate matter sensors (PM) have been under investigation due to their prospective nature regarding spatial extension of measurement coverage. While majority of the existing literature highlights that low-cost sensors can be useful in achieving this goal, it is often reminded that the risk of sensor misuse is still high, and that the data obtained from the sensors is only representative of the specific site and its ambient conditions. This implies that there are underlying reasons yet to be characterized which are causing inaccuracies in sensor measurements. The objective of this study was to investigate the particle size-selectivity of low-cost sensors. Evaluated sensors were Plantower PMS5003, Nova SDS011, Sensirion SPS30, Sharp GP2Y1010AU0F, Shinyei PPD42NS, and Omron B5W-ld0101. The investigation of size-selectivity was carried out in laboratory using a novel reference aerosol generation system capable of steadily producing monodisperse particles of different sizes on-line. The results of the study showed that none of the low-cost sensors adhered exactly to the detection ranges declared by the manufacturers, and moreover, cursory comparison to a mid-cost aerosol spectrometer (GRIMM 1.108) indicated that the sensors could only achieve independent responses for 1–2 size bins whereas the spectrometer could sufficiently characterize particles with 15 different size bins. These observations provide insight and evidence to the notion that particle size-selectivity may have an essential role in the error source analysis of sensors.

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Review of Kuula et al. "Laboratory evaluation of particle size-selectivity of optical low-cost particulate matter sensors"

10.5194/amt-2019-422-rc2 ◽

2020 ◽

Author(s):

Anonymous

Keyword(s):

Particle Size ◽

Particulate Matter ◽

Low Cost ◽

Laboratory Evaluation ◽

Size Selectivity

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Laboratory evaluation of particle-size selectivity of optical low-cost particulate matter sensors

Atmospheric Measurement Techniques ◽

10.5194/amt-13-2413-2020 ◽

2020 ◽

Vol 13 (5) ◽

pp. 2413-2423 ◽

Cited By ~ 9

Author(s):

Joel Kuula ◽

Timo Mäkelä ◽

Minna Aurela ◽

Kimmo Teinilä ◽

Samu Varjonen ◽

...

Keyword(s):

Particle Size ◽

Particulate Matter ◽

Low Cost ◽

Laboratory Evaluation ◽

Ambient Conditions ◽

Size Selectivity ◽

Aerosol Generation ◽

Measurement Tools ◽

On Line ◽

Cost Efficient

Abstract. Low-cost particulate matter (PM) sensors have been under investigation as it has been hypothesized that the use of low-cost and easy-to-use sensors could allow cost-efficient extension of the currently sparse measurement coverage. While the majority of the existing literature highlights that low-cost sensors can indeed be a valuable addition to the list of commonly used measurement tools, it often reiterates that the risk of sensor misuse is still high and that the data obtained from the sensors are only representative of the specific site and its ambient conditions. This implies that there are underlying reasons for inaccuracies in sensor measurements that have yet to be characterized. The objective of this study is to investigate the particle-size selectivity of low-cost sensors. Evaluated sensors were Plantower PMS5003, Nova SDS011, Sensirion SPS30, Sharp GP2Y1010AU0F, Shinyei PPD42NS, and Omron B5W-LD0101. The investigation of size selectivity was carried out in the laboratory using a novel reference aerosol generation system capable of steadily producing monodisperse particles of different sizes (from ∼0.55 to 8.4 µm) on-line. The results of the study show that none of the low-cost sensors adhered to the detection ranges declared by the manufacturers; moreover, cursory comparison to a mid-cost aerosol size spectrometer (Grimm 1.108, 2020) indicates that the sensors can only achieve independent responses for one or two size bins, whereas the spectrometer can sufficiently characterize particles with 15 different size bins. These observations provide insight into and evidence of the notion that particle-size selectivity has an essential role in the analysis of the sources of errors in sensors.

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Characterization of the emission behavior of pulse-jet cleaned filters using a low-cost particulate matter sensor/Charakterisierung der Emission von druckstoßgereinigten Oberflächenfiltern mit einem Low-Cost-Feinstaubsensor

Gefahrstoffe ◽

10.37544/0949-8036-2019-11-12-49 ◽

2019 ◽

Vol 79 (11-12) ◽

pp. 443-450

Author(s):

P. Bächler ◽

J. Meyer ◽

A. Dittler

Keyword(s):

Particle Size ◽

Particulate Matter ◽

Particle Size Distribution ◽

Size Distribution ◽

Low Cost ◽

Particle Emission ◽

Filter Medium ◽

Emission Measurement ◽

Pm2.5 Concentration ◽

Pulse Jet

The reduction of fine dust emissions with pulse-jet cleaned filters plays an important role in industrial gas cleaning to meet emission standards and protect the environment. The dust emission of technical facilities is typically measured “end of pipe”, so that no information about the local emission contribution of individual filter elements exists. Cheap and compact low-cost sensors for the detection of particulate matter (PM) concentrations, which have been prominently applied for immission monitoring in recent years have the potential for emission measurement of filters to improve process monitoring. This publication discusses the suitability of a low-cost PM-sensor, the model SPS30 from the manufacturer Sensirion, in terms of the potential for particle emission measurement of surface filters in a filter test rig based on DIN ISO 11057. A Promo® 2000 in combination with a Welas® 2100 sensor serves as the optical reference device for the evaluation of the detected PM2.5 concentration and particle size distribution of the emission measured by the low-cost sensor. The Sensirion sensor shows qualitatively similar results of the detected PM2.5 emission as the low-cost sensor SDS011 from the manufacturer Nova Fitness, which was investigated by Schwarz et al. in a former study. The typical emission peak after jet-pulse cleaning of the filter, due to the penetration of particles through the filter medium, is detected during Δp-controlled operation. The particle size distribution calculated from the size resolved number concentrations of the low-cost sensor yields a distinct distribution for three different employed filter media and qualitatively fits the size distribution detected by the Palas® reference. The emission of these three different types of filter media can be distinguished clearly by the measured PM2.5 concentration and the emitted mass per cycle and filter area, demonstrating the potential for PM emission monitoring by the low-cost PM-sensor. During the period of Δt-controlled filter aging, a decreasing emission, caused by an increasing amount of stored particles in the filter medium, is detected. Due to the reduced particle emission after filter aging, the specified maximum concentration of the low-cost sensor is not exceeded so that coincidence is unlikely to affect the measurement results of the sensor for all but the very first stage of filter life.

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Developing a Relative Humidity Correction for Low-Cost Sensors Measuring Ambient Particulate Matter

Sensors ◽

10.3390/s18092790 ◽

2018 ◽

Vol 18 (9) ◽

pp. 2790 ◽

Cited By ~ 35

Author(s):

Andrea Di Antonio ◽

Olalekan Popoola ◽

Bin Ouyang ◽

John Saffell ◽

Roderic Jones

Keyword(s):

Particle Size ◽

Particulate Matter ◽

Relative Humidity ◽

Particle Size Distribution ◽

Size Distribution ◽

Low Cost ◽

Monitoring Networks ◽

Ambient Particulate Matter ◽

Correction Algorithm ◽

Ambient Conditions

There is increasing concern about the health impacts of ambient Particulate Matter (PM) exposure. Traditional monitoring networks, because of their sparseness, cannot provide sufficient spatial-temporal measurements characteristic of ambient PM. Recent studies have shown portable low-cost devices (e.g., optical particle counters, OPCs) can help address this issue; however, their application under ambient conditions can be affected by high relative humidity (RH) conditions. Here, we show how, by exploiting the measured particle size distribution information rather than PM as has been suggested elsewhere, a correction can be derived which not only significantly improves sensor performance but which also retains fundamental information on particle composition. A particle size distribution–based correction algorithm, founded on κ -Köhler theory, was developed to account for the influence of RH on sensor measurements. The application of the correction algorithm, which assumed physically reasonable κ values, resulted in a significant improvement, with the overestimation of PM measurements reduced from a factor of ~5 before correction to 1.05 after correction. We conclude that a correction based on particle size distribution, rather than PM mass, is required to properly account for RH effects and enable low cost optical PM sensors to provide reliable ambient PM measurements.

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Inline Infrared Chemical Identification of Particulate Matter

Sensors ◽

10.3390/s20154193 ◽

2020 ◽

Vol 20 (15) ◽

pp. 4193 ◽

Cited By ~ 1

Author(s):

Javier Núñez ◽

Yunqi Wang ◽

Stefan Bäumer ◽

Arjen Boersma

Keyword(s):

Particle Size ◽

Particulate Matter ◽

Chemical Nature ◽

State Of The Art ◽

Low Cost ◽

Infrared Light ◽

Hollow Waveguide ◽

Health And Environmental Effects ◽

Clear Differentiation ◽

Pm2.5 And Pm10

The health and environmental effects of particulate matter (PM) in the air depend on several parameters. Besides particle size, shape, and concentration, the chemical nature of the PM is also of great importance. State-of-the-art PM sensors only detect the particle size and concentration. Small, low-cost sensors only identify PM according to PM2.5 and PM10 standards. Larger detectors measure the complete particle size distribution. However, the chemical composition of PM is not often assessed. The current paper presents the initial stages of the development of an infrared-based detector for the inline assessment of the chemistry of PM in the air. By combining a mini cyclone that is able to concentrate the particles at least a thousand fold and a hollow waveguide that aligns the flow of particles with infrared light, the feasibility of the concept was shown in this study. A clear differentiation between amorphous and crystalline silica was demonstrated at outdoor PM levels of lower than 1 mg per cubic meter.

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Evaluation and Application of a Novel Low-Cost Wearable Sensing Device in Assessing Real-Time PM2.5 Exposure in Major Asian Transportation Modes

Atmosphere ◽

10.3390/atmos12020270 ◽

2021 ◽

Vol 12 (2) ◽

pp. 270

Author(s):

Wen-Cheng Vincent Wang ◽

Shih-Chun Candice Lung ◽

Chun-Hu Liu ◽

Tzu-Yao Julia Wen ◽

Shu-Chuan Hu ◽

...

Keyword(s):

Particulate Matter ◽

Real Time ◽

Mean Absolute Error ◽

Low Cost ◽

Absolute Error ◽

Laboratory Evaluation ◽

Sensing System ◽

Transportation Modes ◽

Pm2.5 Exposure ◽

Device Location

Small low-cost sensing (LCS) devices enable assessment of close-to-reality PM2.5 exposures, though their data quality remains a challenge. This work evaluates the precision, accuracy, wearability and stability of a wearable particle LCS device, Location-Aware Sensing System (LASS, with Plantower PMS3003), which is 104 × 66 × 46 mm3 in size and less than 162 g in weight. Real-time particulate matter (PM) exposures in six major Asian transportation modes were assessed. Side-by-side laboratory evaluation of PM2.5 between a GRIMM aerosol spectrometer and sensors yielded a correlation of 0.98 and a mean absolute error of 0.85 µg/m3. LASS readings collected in the summer of 2016 in Taiwan were converted to GRIMM-comparable values. Mean PM2.5 concentrations obtained from GRIMM and converted LASS values of the six different transportation microenvironments were 16.9 ± 11.7 (n = 1774) and 17.0 ± 9.5 (n = 3399) µg/m3, respectively, showing a correlation of 0.93. The average one-hour PM2.5 exposure increments (concentration increase above ambient levels) from converted LASS values for Mass Rapid Transit (MRT), bus, car, scooter, bike and walk were 15.6, 6.7, −19.2, 8.1, 6.1 and 7.1 µg/m3, respectively, very close to those obtained from GRIMM. This work is one of the earliest studies applying wearable particulate matter (PM) LCS devices in exposure assessment in different transportation modes.

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