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.

scholarly journals Use of low-cost PM-sensors to determine the infiltration of outdoor particles into indoor environments

2019 ◽  
Vol 111 ◽  
pp. 02026
Author(s):  
Jan Drzymalla ◽  
Andreas Henne
Keyword(s):  
Particulate Matter ◽  
Low Cost ◽  
Indoor Environments ◽  
Research Project ◽  
Private Households ◽  
Particulate Matter Concentration ◽  
High Concentrations ◽  
Pm2.5 And Pm10 ◽  
The Relationship ◽  
Matter Concentration

Whether due to traffic, industry or private households – particulate matter enters our air every day and pollutes the air we breathe. When the term air pollution is used, hardly anyone ever thinks of the air inside their own home. However, many urban residences are located in the immediate vicinity of busy roads with high concentrations of particulate matter. Consequently, the outside concentration of fine dust has considerable influence on the indoor concentration. Given the fact that many people spend more than 90 % of their lifetime indoors, it is important to measure and understand particle transport from the outside to the inside in order to assess the effects of exposure to outdoor particles on human health. A two-room apartment near a main road in Leverkusen, North Rhine-Westphalia, Germany was used in the investigation in this research project. Particulate matter concentrations for PM2.5 and PM10 were measured simultaneously inside and outside of the building. Results are size-specific deposition rates, indoor/outdoor ratios and infiltration factors, which provide information on the relationship between internal and external concentrations and the associated health consequences. The particulate matter concentration was measured using low-cost PM-sensors, which were developed and calibrated within the scope of this research project.

scholarly journals Pre-harvest cane burning and health: the association between school absences and burning sugarcane fields

2015 ◽  
Vol 49 (0) ◽  
Author(s):  
Carla Cabrini Mauro ◽  
Vera Lúcia Silveira Bota Ferrante ◽  
Marcos Abdo Arbex ◽  
Maria Lúcia Ribeiro ◽  
Romeu Magnani
Keyword(s):  
Particulate Matter ◽  
Respiratory Diseases ◽  
Total Concentration ◽  
Southeastern Brazil ◽  
Respiratory Problems ◽  
Suspended Particulate ◽  
School Absences ◽  
The Relationship ◽  
The City ◽  
Matter Concentration

The objective of this study was to investigate an association between pre-harvest sugarcane burning and respiratory diseases in children under five years of age. The following data were collected in five schools in the city of Araraquara, SP, Southeastern Brazil, between March and June 2009: daily records of absences and the reasons stated for these absences, total concentration of suspended particulate matter (µg/m3), and air humidity. The relationship between the percentage of school absences due to respiratory problems and the concentration of particulate matter in March and from April to June presented a distinct behavior: absences increased alongside the increase in particulate matter concentration. The use of school absences as indicators of this relationship is an innovative approach.

scholarly journals Spatio-Temporal Characteristics and Variation Pattern of the Atmospheric Particulate Matter Concentration: A Case Study of the Beijing–Tianjin–Hebei Region, China

Atmosphere ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 120
Author(s):  
Haoran Zhai ◽  
Jiaqi Yao ◽  
Guanghui Wang ◽  
Xinming Tang
Keyword(s):  
Particulate Matter ◽  
Measurement Data ◽  
Atmospheric Particulate Matter ◽  
Temporal Characteristics ◽  
Double Peaks ◽  
Spatio Temporal ◽  
Pm2.5 And Pm10 ◽  
Air Quality Monitoring Stations ◽  
Matter Concentration

Based on measurement data from air quality monitoring stations, the spatio-temporal characteristics of the concentrations of particles with aerodynamic equivalent diameters smaller than 2.5 and 10 μm (PM2.5 and PM10, respectively) in the Beijing–Tianjin–Hebei (BTH) region from 2015 to 2018 were analysed at yearly, seasonal, monthly, daily and hourly scales. The results indicated that (1) from 2015 to 2018, the annual average values of PM2.5 and PM10 concentrations and the PM2.5/PM10 ratio in the study area decreased each year; (2) the particulate matter (PM) concentration in winter was significantly higher than that in summer, and the PM2.5/PM10 ratio was highest in winter and lowest in spring; (3) the PM2.5 and PM10 concentrations exhibited a pattern of double peaks and valleys throughout the day, reaching peak values at night and in the morning and valleys in the morning and afternoon; and (4) with the use of an improved sine function to simulate the change trend of the monthly mean PM concentration, the fitting R2 values for PM2.5 and PM10 in the whole study area were 0.74 and 0.58, respectively. Moreover, the high-value duration was shorter, the low-value duration was longer, and the concentration decrease rate was slower than the increase rate.

scholarly journals Field Evaluation of Low-Cost Particulate Matter Sensors in Beijing

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4381 ◽  
Author(s):  
Han Mei ◽  
Pengfei Han ◽  
Yinan Wang ◽  
Ning Zeng ◽  
Di Liu ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Low Cost ◽  
Field Evaluation ◽  
Dust Storms ◽  
Relative Bias ◽  
Miniaturized Sensors ◽  
Beijing China ◽  
Pm2.5 Concentration

Numerous particulate matter (PM) sensors with great development potential have emerged. However, whether the current sensors can be used for reliable long-term field monitoring is unclear. This study describes the research and application prospects of low-cost miniaturized sensors in PM2.5 monitoring. We evaluated five Plantower PMSA003 sensors deployed in Beijing, China, over 7 months (October 2019 to June 2020). The sensors tracked PM2.5 concentrations, which were compared to the measurements at the national control monitoring station of the Ministry of Ecology and Environment (MEE) at the same location. The correlations of the data from the PMSA003 sensors and MEE reference monitors (R2 = 0.83~0.90) and among the five sensors (R2 = 0.91~0.98) indicated a high accuracy and intersensor correlation. However, the sensors tended to underestimate high PM2.5 concentrations. The relative bias reached −24.82% when the PM2.5 concentration was >250 µg/m3. Conversely, overestimation and high errors were observed during periods of high relative humidity (RH > 60%). The relative bias reached 14.71% at RH > 75%. The PMSA003 sensors performed poorly during sand and dust storms, especially for the ambient PM10 concentration measurements. Overall, this study identified good correlations between PMSA003 sensors and reference monitors. Extreme field environments impact the data quality of low-cost sensors, and future corrections remain necessary.

scholarly journals Inline Infrared Chemical Identification of Particulate Matter

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4193 ◽  
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.

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.

scholarly journals Low-cost Air Purifier Prototype using a Ventilating Fan and Pump against COVID-19 and Haze Pollution

2021 ◽  
Author(s):  
Arnon Jumlongkul
Keyword(s):  
Particulate Matter ◽  
Ultrasonic Wave ◽  
Low Cost ◽  
Reduction Rate ◽  
Minimum Cost ◽  
Water Pump ◽  
Haze Pollution ◽  
Co2 Levels ◽  
Air Cleaners ◽  
Air Purifier

Purpose: This study aimed to focus on the design and development of low-cost DIY air purifiers, using a ventilating fan, air pump, water pump, and an ultrasonic generator, with regard to filtration efficacy and also cost-effectiveness that can be used during the COVID-19 pandemic and haze pollution. Methods: Six types of household air purifiers, incorporating a HEPA filter, a HEPA filter & electrostatic fiber, an air pump, an air pump & ultrasonic wave, a water pump, and a water pump & ultrasonic wave, were fabricated. The amount of particulate matter (PM) and CO2 levels were recorded at 0, 10, 20, 30, and 60 min, then, repeated 3 times. After 10 min of the 3rd experiment of each study, the last measurement of air pollution would be recorded. Results: At 60 min, the HEPA filter & electrostatic fiber showed the best performance regarding reduction of PM and CO2 levels. The highest PM reduction rate had occurred at 30 min using an air pump procedure (99.330 to 100%). The CO2 levels of all experiments had fluctuated at different times. After 10 min of a closed machine, HEPA filter & electrostatic fiber revealed the highest rate of PM elevation, while PM levels of all water-based purifier systems were decreased. A water pump and air pump were the cheapest air cleaners, when taking into account maintenance expenses and electricity charges. Conclusion: An air pump is the optimum method for reducing particulate matter at minimum cost but without the benefit of reduced humidity, while the HEPA filter & electrostatic fiber is the best system to decrease PM levels, but this requires an enclosed structure at the inlet to prevent dust coming back into the room. As filtration efficiency is increased by the use of filters & electrostatic fiber mechanisms, the more expensive the system becomes.

scholarly journals Assessment of the Accuracy of Analyzers for Automatic Determination of PM10 and PM2.5 Particulate Matter in Ambient Air

2020 ◽  
Vol 71 (1) ◽  
pp. 83-87
Author(s):  
Elena Bucur ◽  
Radu Motisan ◽  
Andrei Vasile ◽  
Gheorghita Tanase ◽  
Luoana Florentina Pascu ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Pearson Correlation ◽  
Reference Method ◽  
Ambient Air ◽  
Data Series ◽  
Test Results ◽  
Particulate Matter Concentration ◽  
Pm2.5 And Pm10 ◽  
Matter Concentration

The paper presents the test results regarding the evaluation of the accuracy of the PM2.5 and PM10 particulate matter concentration measurement performed with the uRADMonitor A3 fixed air quality monitoring station produced by SC MAGNASCI SRL. The procedure involves the calculation of the accuracy elements: trueness and precision, based on the experimental data obtained by measuring the concentration of particulate matter using the tested analysers in parallel with the reference method, SR EN 12341: 2014, and analysis of data series by Pearson correlation and linear regression.

scholarly journals Reliability Validation of a Low-Cost Particulate Matter IoT Sensor in Indoor and Outdoor Environments Using a Reference Sampler

2019 ◽  
Vol 11 (24) ◽  
pp. 7220 ◽  
Author(s):  
Sergio Trilles ◽  
Ana Belen Vicente ◽  
Pablo Juan ◽  
Francisco Ramos ◽  
Sergi Meseguer ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Linear Model ◽  
Low Cost ◽  
Additive Model ◽  
Quality Data ◽  
Outdoor Environments ◽  
Pm2.5 And Pm10 ◽  
Indoor And Outdoor Environments ◽  
Indoor And Outdoor

A suitable and quick determination of air quality allows the population to be alerted with respect to high concentrations of pollutants. Recent advances in computer science have led to the development of a high number of low-cost sensors, improving the spatial and temporal resolution of air quality data while increasing the effectiveness of risk assessment. The main objective of this work is to perform a validation of a particulate matter (PM) sensor (HM-3301) in indoor and outdoor environments to study PM2.5 and PM10 concentrations. To date, this sensor has not been evaluated in real-world situations, and its data quality has not been documented. Here, the HM-3301 sensor is integrated into an Internet of things (IoT) platform to establish a permanent Internet connection. The validation is carried out using a reference sampler (LVS3 of Derenda) according to EN12341:2014. It is focused on statistical insight, and environmental conditions are not considered in this study. The ordinary Linear Model, the Generalized Linear Model, Locally Estimated Scatterplot Smoothing, and the Generalized Additive Model have been proposed to compare and contrast the outcomes. The low-cost sensor is highly correlated with the reference measure ( R 2 greater than 0.70), especially for PM2.5, with a very high accuracy value. In addition, there is a positive relationship between the two measurements, which can be appropriately fitted through the Locally Estimated Scatterplot Smoothing model.

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