scholarly journals Calibration Method for Particulate Matter Low-Cost Sensors Used in Ambient Air Quality Monitoring and Research

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3960
Author(s):  
Janani Venkatraman Jagatha ◽  
André Klausnitzer ◽  
Miriam Chacón-Mateos ◽  
Bernd Laquai ◽  
Evert Nieuwkoop ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Low Cost ◽  
Cost Effective ◽  
Ambient Air ◽  
Calibration Method ◽  
Linear Regression Method ◽  
Quantile Mapping ◽  
Indoor Particulate Matter ◽  
Mobile Measurements ◽  
Matter Concentration

Over the last decade, manufacturers have come forth with cost-effective sensors for measuring ambient and indoor particulate matter concentration. What these sensors make up for in cost efficiency, they lack in reliability of the measured data due to their sensitivities to temperature and relative humidity. These weaknesses are especially evident when it comes to portable or mobile measurement setups. In recent years many studies have been conducted to assess the possibilities and limitations of these sensors, however mostly restricted to stationary measurements. This study reviews the published literature until 2020 on cost-effective sensors, summarizes the recommendations of experts in the field based on their experiences, and outlines the quantile-mapping methodology to calibrate low-cost sensors in mobile applications. Compared to the commonly used linear regression method, quantile mapping retains the spatial characteristics of the measurements, although a common correction factor cannot be determined. We conclude that quantile mapping can be a useful calibration methodology for mobile measurements given a well-elaborated measurement plan assures providing the necessary data.

scholarly journals Comparison of Low-Cost Particulate Matter Sensors for Indoor Air Monitoring during COVID-19 Lockdown

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7290
Author(s):  
Miron Kaliszewski ◽  
Maksymilian Włodarski ◽  
Jarosław Młyńczak ◽  
Krzysztof Kopczyński
Keyword(s):  
Particulate Matter ◽  
Low Cost ◽  
Air Monitoring ◽  
Concentration Estimation ◽  
Air Purifier ◽  
Pm2.5 And Pm10 ◽  
Indoor Conditions ◽  
The Relationship ◽  
Beijing China ◽  
Matter Concentration

This study shows the results of air monitoring in high- and low-occupancy rooms using two combinations of sensors, AeroTrak8220(TSI)/OPC-N3 (AlphaSense, Great Notley, UK) and OPC-N3/PMS5003 (Plantower, Beijing, China), respectively. The tests were conducted in a flat in Warsaw during the restrictions imposed due to the COVID-19 lockdown. The results showed that OPC-N3 underestimates the PN (particle number concentration) by about 2–3 times compared to the AeroTrak8220. Subsequently, the OPC-N3 was compared with another low-cost sensor, the PMS5003. Both devices showed similar efficiency in PN estimation, whereas PM (particulate matter) concentration estimation differed significantly. Moreover, the relationship among the PM1–PM2.5–PM10 readings obtained with the PMS5003 appeared improbably linear regarding the natural indoor conditions. The correlation of PM concentrations obtained with the PMS5003 suggests an oversimplified calculation method of PM. The studies also demonstrated that PM1, PM2.5, and PM10 concentrations in the high- to low-occupancy rooms were about 3, 2, and 1.5 times, respectively. On the other hand, the use of an air purifier considerably reduced the PM concentrations to similar levels in both rooms. All the sensors showed that frying and toast-making were the major sources of particulate matter, about 10 times higher compared to average levels. Considerably lower particle levels were measured in the low-occupancy room.

Numerical assessment of the effect of cigarette smoking on indoor PM2.5 distribution and study of ventilation strategies

2016 ◽  
Vol 27 (3) ◽  
pp. 369-379 ◽  
Author(s):  
Zheshu Ma ◽  
Shaozhe Sun
Keyword(s):  
Particulate Matter ◽  
Ambient Air ◽  
Quality Standard ◽  
World Health ◽  
Elevated Concentration ◽  
Breathing Zone ◽  
Ventilation Strategy ◽  
Displacement Ventilation ◽  
Ventilation Strategies ◽  
Indoor Particulate Matter

Elevated concentration of indoor particulate matter (PM) has been linked to adverse effects on human health. To explore how particles from cigarette smoke affect the indoor PM2.5 concentration and whether such circumstance is harmful to people, distribution characteristics of indoor particulate matter in a typical residence with a smoker were numerically studied under different ventilation strategies. The indoor PM2.5 concentration without forced ventilation was shown to far exceed the air quality standard of 75 µg/m3 as recommended by the World Health Organization. In this study, we numerically investigated the performances of the mixing and displacement ventilation strategies in reducing indoor particle levels. Different airflow patterns could significantly influence the movement and deposition of particles in ventilated rooms, even with the same air change rate and particle characteristics. When comparing with the mixing ventilation strategy, the displacement ventilation strategy was shown to have a lower deposition mass and a larger portion of particles leaving the room. Thus, the average indoor PM2.5 concentration in the displacement ventilation strategy was shown to be higher than the mixing ventilation strategy. In spite of this, low particle concentration in the personnel’s breathing zone was shown by our measurement. Displacement ventilation strategy could provide a cleaner ambient air than the mixing one.

scholarly journals Investigating the effect of an open window vs. a closed window on the concentrations of suspended particulate matter in the indoors with respect to the outdoors

2022 ◽  
Author(s):  
Raja Singh ◽  
Tushar Mondal ◽  
Anil Dewan
Keyword(s):  
Particulate Matter ◽  
Working Hours ◽  
Ambient Air ◽  
Substantial Effect ◽  
New Delhi ◽  
Pm 2.5 ◽  
Suspended Particulate ◽  
Open Window ◽  
Indoor Particulate Matter ◽  
Pm 10

A study was conducted to see the effect of an opened window vs. a closed window in New Delhi in peak winters. This is the time when the PM 2.5 and PM 10 concentrations are the highest in the ambient air due to various external factors. A PM 2.5 and PM 10 air quality meter was used at a singular location near the window for 10 days with 9 readings taken during the daily working hours. Contrary to the possible conjectural belief, it was found that the window opened or closed did not have a substantial effect on the concentrations of the indoor levels of PM 2.5 and PM 10. The results showed that opening of the windows does not substantially affect the levels of the indoors with respect to the levels of PM 2.5 and PM 10 in the outdoors. Outdoors may provide the source of the particulate matter in the indoor, but due to diffusive effect, open windows play a key role in the reducing the indoor levels. This study was reconfirmed with options where the windows were opened and then closed and vice-versa. In all cases, the effect of the outdoor was not visible. To curb indoor particulate matter levels, isolation is not the solution. (200 words)

scholarly journals Mobile Measurements of Particulate Matter in a Car Cabin: Local Variations, Contrasting Data from Mobile versus Stationary Measurements and the Effect of an Opened versus a Closed Window

2018 ◽  
Vol 15 (12) ◽  
pp. 2642 ◽  
Author(s):  
Janis Dröge ◽  
Ruth Müller ◽  
Cristian Scutaru ◽  
Markus Braun ◽  
David Groneberg
Keyword(s):  
Particulate Matter ◽  
Human Health Risk ◽  
Ambient Air ◽  
Video Camera ◽  
Coarse Particles ◽  
Frankfurt Am Main ◽  
Characteristic Particle ◽  
Air Quality Monitoring Stations ◽  
Mobile Measurements ◽  
Stationary Measurement

Air pollution of particulate matter (PM) from traffic emissions has a significant impact on human health. Risk assessments for different traffic participants are often performed on the basis of data from local air quality monitoring stations. Numerous studies demonstrated the limitation of this approach. To assess the risk of PM exposure to a car driver more realistically, we measure the exposure to PM in a car cabin with a mobile aerosol spectrometer in Frankfurt am Main under different settings (local variations, opened versus a closed window) and compare it with data from stationary measurement. A video camera monitored the surroundings for potential PM source detection. In-cabin concentrations peaked at 508 µg m−3 for PM10, 133.9 µg m−3 for PM2.5, and 401.3 µg m−3 for coarse particles, and strongly depended on PM size and PM concentration in ambient air. The concentration of smaller particles showed low fluctuations, but the concentration of coarse particles showed high fluctuations with maximum values on busy roads. Several of these concentration peaks were assigned to the corresponding sources with characteristic particle size distribution profiles. The closure of the car window reduced the exposure to PM, and in particular to coarse particles. The mobile measured PM values differed significantly from stationary PM measures, although good correlations were computed for finer particles. Mobile rather than stationary measurements are essential to assess the risk of PM exposure for car passengers.

scholarly journals APPLICATION OF LOW-COST PARTICULATE MATTER SENSORS FOR MEASUREMENT OF POLLUTANTS GENERATED DURING 3D PRINTING

2021 ◽  
Vol 11 (4) ◽  
pp. 75-77
Author(s):  
Jarosław Tatarczak
Keyword(s):  
Particulate Matter ◽  
3D Printing ◽  
Low Cost ◽  
Acrylonitrile Butadiene Styrene ◽  
3D Printer ◽  
Particulate Matter Concentration ◽  
Measurement Results ◽  
Private Homes ◽  
Matter Concentration ◽  
Butadiene Styrene

This work presents measurement results of pollutants generated during 3D printing. The measure of pollutants is the concentration of particulate matter with a diameter of up to 2.5 μm (PM2,5). Materials acrylonitrile-butadiene-styrene (ABS), polyactide (PLA) for a 3D printer and low-cost particulate matter concentration sensors PMS3003, PMS7003 were used in the research. Research results show that  low-cost sensors can be useful for monitoring pollution during 3D printing in offices, laboratories or private homes.

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