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.

scholarly journals Air Quality in Buraydah, Saudi Arabia

2020 ◽  
Vol 9 (5) ◽  
pp. 856-861
Keyword(s):  
Saudi Arabia ◽  
Particulate Matter ◽  
Air Quality ◽  
Environmental Parameters ◽  
Indoor Environments ◽  
Adverse Health Effects ◽  
Outdoor Environments ◽  
Different Seasons ◽  
Indoor And Outdoor Environments ◽  
Indoor And Outdoor

Exposure to outdoor and indoor air particles (also known as particulate matter or PM) has attracted the interest of the scientific researchers around the world, this is because of the adverse health effects that particles have on the human. Smaller fractions of particulate matter (repairable range, ≤10 µm) give the greatest health problem, because they have the ability to reach deeper parts of the human respiratory system. Many countries have paid attention to the air pollution and made regulations to improve their indoor and outdoor air quality, Saudi Arabia, particularly Qassim region, has not given much attention to the problem of air contaminants in the ambient and indoor environments. In addition, ambient environmental parameters will be recorded. The results obtained from the indoor and outdoor measurements will help us to evaluate the air quality in Buraydah city for different seasons in the indoor and outdoor environments.

scholarly journals Measurements of Indoor and Outdoor Fine Particulate Matter during the Heating Period in Jinan, in North China: Chemical Composition, Health Risk, and Source Apportionment

Atmosphere ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 885
Author(s):  
Xiaomei Gao ◽  
Weidong Gao ◽  
Xiaoyan Sun ◽  
Wei Jiang ◽  
Ziyi Wang ◽  
...  
Keyword(s):  
Particulate Matter ◽  
North China ◽  
Fine Particulate Matter ◽  
Vulnerable Groups ◽  
Chemical Components ◽  
Fine Particulate ◽  
Outdoor Environments ◽  
Indoor And Outdoor Environments ◽  
Indoor Pm2.5 ◽  
Indoor And Outdoor

Fine particulate matter (PM2.5) was simultaneously collected from the indoor and outdoor environments in urban area of Jinan in North China from November to December 2018 to evaluate the characteristics and sources of indoor PM2.5 pollution. The concentrations of indoor and outdoor PM2.5 were 69.0 ± 50.5 µg m−3 and 128.7 ± 67.9 µg m−3, respectively, much higher than the WHO-established 24-h standards for PM2.5, indicating serious PM2.5 pollution of indoor and outdoor environments in urban Jinan. SO42−, NO3−, NH4+, and organic carbon (OC) were the predominant components, which accounted for more than 60% of the PM2.5 concentration. The total elemental risk values in urban Jinan for the three highly vulnerable groups of population (children (aged 2–6 years and 6–12 years) and older adults (≥70 years)) were nearly 1, indicating that exposure to all of the elements in PM2.5 had potential non-carcinogenic risks to human health. Further analyses of the indoor/outdoor concentration ratios, infiltration rates (FINF), and indoor-generated concentration (Cig) indicated that indoor PM2.5 and its major chemical components (SO42−, NO3−, NH4+, OC, and elemental carbon) were primarily determined by outdoor pollution. The lower indoor NO3−/SO42− ratio and FINF of NO3− relative to the outdoor values were due to the volatility of NO3−. Positive matrix factorization (PMF) was performed to estimate the sources of PM2.5 using the combined datasets of indoor and outdoor environments and revealed that secondary aerosols, dust, cement production, and coal combustion/metal smelting were the major sources during the sampling period.

scholarly journals Comprehensive Multi-Model Framework for establishing correlation between Particulate Matter in Residential and Commercial regions of Lucknow

2021 ◽  
Vol 9 (VII) ◽  
pp. 3386-3393
Author(s):  
Shivam Srivastava
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Regression Model ◽  
Uttar Pradesh ◽  
Quality Parameters ◽  
Quality Data ◽  
Model Framework ◽  
Cubic Curve ◽  
Beta Coefficient ◽  
Pm2.5 And Pm10

Our Country India is a developing Country and with the onset of heavy production, urbanization and Industrialization in the recent years has imposed a heavy threat on the Environment, The direct impact of which could be seen in the deteriorating Air Quality. Since air pollution continues to rise at an alarming rate, it affects economies and inhabitants quality of life leading to health emergency situations. This paper presents the Air Quality data interpretation and modelling to study for correlation between different Air Quality Parameters specifically Particulate Matter in Residential and Commercial regions of Lucknow-The Second largest city of Uttar Pradesh. The levels of PM2.5 and PM10 was found to be exceeding than 24 Hrs avg as well as Annual Average value (as set by NAAQS ) in Commercial Region , while in Residential Region the levels of PM2.5 and PM10 were almost in acceptable range as set by NAAQS . Later on studying the comprehensive correlation between the PM2.5 and PM10 by applying various regression models, As per the levels of PM as obtained in commercial region , Compound Curve Regression Model seems to be of highest significance showing 92.1% relation response with highest Standardized Beta Coefficient having value of 2.611 . While for Residential region as per the levels of PM obtained, Cubic Curve Regression Model gave best suited result depicting 77.9% relation response amongst PM2.5 and PM10 with highest Standardized Beta Coefficient Value of 3.028 .

scholarly journals APPLICATION OF LOW-COST OPTICAL PM SENSOR FOR MONITORING OF PARTICULATE MATTER AIR POLLUTION IN THE URBAN ENVIRONMENT: A CASE STUDY IN ESPLANĀDE HOUSING ESTATE, DAUGAVPILS CITY

2021 ◽  
Vol 1 ◽  
pp. 223-229
Author(s):  
Juris Soms ◽  
Haralds Soms
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Urban Environment ◽  
Meteorological Data ◽  
Low Cost ◽  
Average Concentration ◽  
Environmental Data ◽  
Housing Estate ◽  
Spatial Coverage ◽  
Pm2.5 And Pm10

The harmful health effects of airborne particulate matter (PM) pollutants are well-known. However, the spatial coverage of automated air quality observation stations of Latvian Environment, Geology and Meteorology Centre (LEGMC) is sparse. Therefore the capability for PM concentration detection was examined by using the low-cost optical PM sensor to improve the spatial resolution of environmental data. The aim of the study was to perform 24h/7d measurements of PM2.5 and PM10 concentrations during a period of one year and to identify air quality in Esplanāde housing estate, Daugavpils city. For data obtaining on the concentration of PM2.5 and PM10 particles measurements have been performed by optical sensor Nova SDS011; meteorological data were obtained using the database of LEGMC; for processing, analysis and visualization of obtained data statistical methods were applied. Evaluation of PM2.5 and PM10 daily average concentration variability in 2020 indicates that air quality in the urban environment could be assessed as good. A well-expressed statistical correlation between meteorological factors (t°C, relative humidity) and the average concentration of PM particles was not found. It highlights the necessity of further research.

scholarly journals Low-Cost Air Quality Stations’ Capability to Integrate Reference Stations in Particulate Matter Dynamics Assessment

Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1065
Author(s):  
Lorenzo Brilli ◽  
Federico Carotenuto ◽  
Bianca Patrizia Andreini ◽  
Alice Cavaliere ◽  
Andrea Esposito ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Measurement Accuracy ◽  
Low Cost ◽  
Reference Station ◽  
Anthropogenic Emissions ◽  
High Temporal Resolution ◽  
Industrial Sites ◽  
Valid Data ◽  
Pm2.5 And Pm10

Low-cost air quality stations can provide useful data that can offer a complete picture of urban air quality dynamics, especially when integrated with daily measurements from reference air quality stations. However, the success of such deployment depends on the measurement accuracy and the capability of resolving spatial and temporal gradients within a spatial domain. In this work, an ensemble of three low-cost stations named “AirQino” was deployed to monitor particulate matter (PM) concentrations over three different sites in an area affected by poor air quality conditions. Data of PM2.5 and PM10 concentrations were collected for about two years following a protocol based on field calibration and validation with a reference station. Results indicated that: (i) AirQino station measurements were accurate and stable during co-location periods over time (R2 = 0.5–0.83 and RMSE = 6.4–11.2 μg m−3; valid data: 87.7–95.7%), resolving current spatial and temporal gradients; (ii) spatial variability of anthropogenic emissions was mainly due to extensive use of wood for household heating; (iii) the high temporal resolution made it possible to detect time occurrence and strength of PM10 concentration peaks; (iv) the number of episodes above the 1-h threshold of 90 μg m−3 and their persistence were higher under urban and industrial sites compared to the rural area.

scholarly journals ASSESSMENT OF LOW-COST PARTICULATE MATTER SENSORS

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 671-677
Author(s):  
K. Lehmann ◽  
A. Minhans ◽  
M. K. Fajari ◽  
M. Hahn
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Meteorological Parameters ◽  
Low Cost ◽  
The State ◽  
Quality Monitoring ◽  
Quality Data ◽  
Air Quality Monitoring ◽  
Low Costs ◽  
German Cities

Abstract. The effect of particulate matter is increasingly gaining significance due to its harmful effects on human and urban ecosystems. In view of it, many communities worldwide are collecting air quality data privately to influence their policy makers to make stricter provisions for reducing harmful emissions and thereby improving their quality of life. Likewise, in many German cities, a community of air quality monitors which rely on low-cost PM Sensors is gathering momentum. Such communities possess privately-owned & low-cost air quality monitoring devices that claim to accurately measure PM concentrations and are openly accessible via internet. One such initiative is an air quality monitoring network viz. “luftdaten.info”, which contains of more than 300 low-cost sensors that consistently obtains PM data, colloquially referred as fine dust, in the city of Stuttgart as well as its surrounding districts. Besides, eight stations are continuously monitoring PM concentration in Stuttgart; these are operated by the State Environmental Agency (LuBW- Landesanstalt für Umwelt Baden-Württemberg). Stuttgart University of Applied Sciences (HFT) has currently installed 7 low-cost PM sensors to monitor and study PM concentration in one of its projects. This study endeavors to relate PM 2.5 and PM 10.0 using low-cost sensors. It intends to investigate the reliability of the measured PM concentration using such low-costs sensors once these are placed horizontally and vertically apart and comparing the measures of the 7 sensors. Another objective is to compare the PM concentration measurements with a meteorological station operated by the State of Baden-Wuerttemberg in the vicinity. A correlation analysis is performed to develop understanding of relationships of PM concentration with meteorological parameters, viz. with respect to ambient temperature, air pressure, humidity, wind speed and wind direction. Furthermore, it attempts to develop a regression model using above listed meteorological parameters. Finally, deficiencies in the measurement of low-costs and its placement effects are commented. Further suggestions are made for improving the data capturing and analytical procedures while using low-cost sensors.

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