scholarly journals Low-Cost Air Quality Measurement System Based on Electrochemical and PM Sensors with Cloud Connection

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6228
Author(s):  
Patricia Arroyo ◽  
Jaime Gómez-Suárez ◽  
José Ignacio Suárez ◽  
Jesús Lozano
Keyword(s):  
Air Quality ◽  
Low Cost ◽  
Pearson Correlation ◽  
Quality Measurement ◽  
Measurement Unit ◽  
Published Data ◽  
Time Data ◽  
Cost System ◽  
Particle Matter ◽  
Pm2.5 And Pm10

This paper presents a portable device for outdoor air quality measurement that provides concentration values for the main pollutants: NO2, NO, CO, O3, PM2.5 and PM10, and other values such as temperature, humidity, location, and date. The device is based on the use of commercial electrochemical gas and optical particle matter sensors with a careful design of the electronics for reducing the electrical noise and increasing the accuracy of the measurements. The result is a low-cost system with IoT technology that connects to the Internet through a GSM module and sends all real-time data to a cloud platform with storage and computational potential. Two identical devices were fabricated and installed on a mobile reference measurement unit and deployed in Badajoz, Spain. The results of a two-month field campaign are presented and published. Data obtained from these measurements were calibrated using linear regression and neural network techniques. Good performance has been achieved for both gaseous pollutants (with a Pearson correlation coefficient of up to 0.97) and PM sensors.

Solution to the Problem of Calibration of Low-Cost Air Quality Measurement Sensors in Networks

ACS Sensors ◽  
2018 ◽  
Vol 3 (4) ◽  
pp. 832-843 ◽  
Author(s):  
Georgia Miskell ◽  
Jennifer A. Salmond ◽  
David E. Williams
Keyword(s):  
Air Quality ◽  
Low Cost ◽  
Quality Measurement

scholarly journals Low-Cost Air Quality Sensors: One-Year Field Comparative Measurement of Different Gas Sensors and Particle Counters with Reference Monitors at Tušimice Observatory

Atmosphere ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 492 ◽  
Author(s):  
Petra Bauerová ◽  
Adriana Šindelářová ◽  
Štěpán Rychlík ◽  
Zbyněk Novák ◽  
Josef Keder
Keyword(s):  
Air Quality ◽  
Gas Sensors ◽  
Low Cost ◽  
Monitoring Network ◽  
Field Testing ◽  
Ambient Air ◽  
Monitoring Networks ◽  
Comparative Measurement ◽  
One Year ◽  
Pm2.5 And Pm10

With attention increasing regarding the level of air pollution in different metropolitan and industrial areas worldwide, interest in expanding the monitoring networks by low-cost air quality sensors is also increasing. Although the role of these small and affordable sensors is rather supplementary, determination of the measurement uncertainty is one of the main questions of their applicability because there is no certificate for quality assurance of these non-reference technologies. This paper presents the results of almost one-year field testing measurements, when the data from different low-cost sensors (for SO2, NO2, O3, and CO: Cairclip, Envea, FR; for PM1, PM2.5, and PM10: PMS7003, Plantower, CHN, and OPC-N2, Alphasense, UK) were compared with co-located reference monitors used within the Czech national ambient air quality monitoring network. The results showed that in addition to the given reduced measurement accuracy of the sensors, the data quality depends on the early detection of defective units and changes caused by the effect of meteorological conditions (effect of air temperature and humidity on gas sensors and effect of air humidity with condensation conditions on particle counters), or by the interference of different pollutants (especially in gas sensors). Comparative measurement is necessary prior to each sensor’s field applications.

scholarly journals Semantic Traffic Sensor Data: The TRAFAIR Experience

2020 ◽  
Vol 10 (17) ◽  
pp. 5882
Author(s):  
Federico Desimoni ◽  
Sergio Ilarri ◽  
Laura Po ◽  
Federica Rollo ◽  
Raquel Trillo-Lado
Keyword(s):  
Air Quality ◽  
Real Time ◽  
Smart Cities ◽  
Low Cost ◽  
Semantic Annotation ◽  
Open Data ◽  
Transportation Systems ◽  
Sensor Data ◽  
Time Data ◽  
Future Evolution

Modern cities face pressing problems with transportation systems including, but not limited to, traffic congestion, safety, health, and pollution. To tackle them, public administrations have implemented roadside infrastructures such as cameras and sensors to collect data about environmental and traffic conditions. In the case of traffic sensor data not only the real-time data are essential, but also historical values need to be preserved and published. When real-time and historical data of smart cities become available, everyone can join an evidence-based debate on the city’s future evolution. The TRAFAIR (Understanding Traffic Flows to Improve Air Quality) project seeks to understand how traffic affects urban air quality. The project develops a platform to provide real-time and predicted values on air quality in several cities in Europe, encompassing tasks such as the deployment of low-cost air quality sensors, data collection and integration, modeling and prediction, the publication of open data, and the development of applications for end-users and public administrations. This paper explicitly focuses on the modeling and semantic annotation of traffic data. We present the tools and techniques used in the project and validate our strategies for data modeling and its semantic enrichment over two cities: Modena (Italy) and Zaragoza (Spain). An experimental evaluation shows that our approach to publish Linked Data is effective.

scholarly journals Design and Implementation of Portable Outdoor Air Quality Measurement System using Arduino

2018 ◽  
Vol 8 (1) ◽  
pp. 280 ◽  
Author(s):  
Teddy Surya Gunawan ◽  
Yasmin Mahira Saiful Munir ◽  
Mira Kartiwi ◽  
Hasmah Mansor
Keyword(s):  
Air Quality ◽  
Measurement System ◽  
Low Cost ◽  
Public Awareness ◽  
Quality Measurement ◽  
Cost Effective ◽  
Ground Level ◽  
Air Pollutant ◽  
Ground Level Ozone ◽  
Air Quality Monitoring Stations

Recently, there is increasing public awareness of the real time air quality due to air pollution can cause severe effects to human health and environments. The Air Pollutant Index (API) in Malaysia is measured by Department of Environment (DOE) using stationary and expensive monitoring station called Continuous Air Quality Monitoring stations (CAQMs) that are only placed in areas that have high population densities and high industrial activities. Moreover, Malaysia did not include particulate matter with the size of less than 2.5μm (PM2.5) in the API measurement system. In this paper, we present a cost effective and portable air quality measurement system using Arduino Uno microcontroller and four low cost sensors. This device allows people to measure API in any place they want. It is capable to measure the concentration of carbon monoxide (CO), ground level ozone (O3) and particulate matters (PM10 & PM2.5) in the air and convert the readings to API value. This system has been tested by comparing the API measured from this device to the current API measured by DOE at several locations. Based on the results from the experiment, this air quality measurement system is proved to be reliable and efficient.

scholarly journals Wireless Sensor Network for Low-cost Air Quality Measurement

2018 ◽  
Vol 1065 ◽  
pp. 192004 ◽  
Author(s):  
M Carratù ◽  
M Ferro ◽  
A Pietrosanto ◽  
P Sommella
Keyword(s):  
Wireless Sensor Network ◽  
Air Quality ◽  
Sensor Network ◽  
Low Cost ◽  
Quality Measurement ◽  
Wireless Sensor

An Online Low-Cost System for Air Quality Monitoring, Prediction, and Warning

2019 ◽  
pp. 311-324
Author(s):  
Rishi Sharma ◽  
Tushar Saini ◽  
Praveen Kumar ◽  
Ankush Pathania ◽  
Khyathi Chitineni ◽  
...  
Keyword(s):  
Air Quality ◽  
Low Cost ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Cost System

scholarly journals An Integrated System for Simultaneous Monitoring of Traffic and Pollution Concentration—Lessons Learned for Bielsko-Biała, Poland

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 8028
Author(s):  
Krzysztof Brzozowski ◽  
Artur Ryguła ◽  
Andrzej Maczyński
Keyword(s):  
Air Quality ◽  
Meteorological Data ◽  
Low Cost ◽  
Background Level ◽  
Lessons Learned ◽  
Integrated System ◽  
Network Information ◽  
Transit Times ◽  
Pm2.5 And Pm10 ◽  
The Impact

The challenge of maintaining the required level of mobility and air quality in cities can be met by deploying an appropriate management system in which the immediate vicinity of roads is monitored to identify potential pollution hotspots. This paper presents an integrated low-cost system which can be used to study the impact of traffic related emission on air quality at intersections. The system was used for three months in 2017 at five locations covering intersections in the centre of a mid-sized city. Depending on the location, pollution hotspots with high PM2.5 and PM10 concentrations occurred 5–10% of the time. It was shown that despite the close mutual proximity of the locations, traffic and the immediate surroundings lead to significant variation in air quality. At locations with adverse ventilation conditions a tendency towards more frequent occurrences of moderate and sufficient air quality was observed than at other locations (even those with more traffic). Based on the results, a practical extension of the system was also proposed by formulating a model for the prediction of PM2.5 concentration using a neural network. Information on transit times, meteorological data and the background level of PM10 concentration were used as model input parameters.

scholarly journals Understanding the ability of low-cost MOx sensors to quantify ambient VOCs

2018 ◽  
Author(s):  
Ashley M. Collier-Oxandale ◽  
Jacob Thorson ◽  
Hannah Halliday ◽  
Jana Milford ◽  
Michael Hannigan
Keyword(s):  
Air Quality ◽  
New Technologies ◽  
Low Cost ◽  
Quality Measurement ◽  
Proton Transfer Reaction ◽  
Unique Challenge ◽  
Mox Sensors ◽  
The Impact ◽  
Insight Into ◽  
Resolution Data

Abstract. Volatile organic compounds (VOCs) present a unique challenge in air quality research given their importance to human and environmental health, and their complexity to monitor resulting from the number of possible sources and mixtures. New technologies, such as low-cost air quality sensors have the potential to support existing air quality measurement methods by providing high time and spatial resolution data. This higher resolution data could provide greater insight into specific events, sources, and local variability. Furthermore, given the potential for differences in selectivities for sensors, leveraging multiple sensors in an array format may even be able to provide insight into which VOCs or types of VOCs are present. During the FRAPPE/DISCOVER-AQ monitoring campaigns, our team was able to co-locate two sensor systems, using metal oxide (MOx) VOC sensors, with a proton-transfer-reaction mass spectrometer (PTR-MS) providing speciated VOC data. This dataset provided the opportunity to explore the ability of sensors to estimate specific VOCs and groups of VOCs in real-world conditions, e.g., dynamic temperature and humidity. Moreover, we were able to explore the impact of changing VOC compositions on sensor performance as well as the difference in selectivities of sensors in order to consider how this could be utilized. From this analysis, it seems that systems using multiple VOC sensors are able to provide VOC estimates at ambient levels for specific VOCs or groups of VOCs, it also seems that this performance is fairly robust to changing VOC mixtures, and it was confirmed that there are consistent and useful differences in selectivities between the two MOx sensors studied. While this study was fairly limited in scope, the results suggest that there is the potential for low-cost VOC sensors to support highly resolved, ambient hydrocarbon measurements. The availability of this technology could enhance research and monitoring for public health and communities impacted by air toxics, which in turn could support a better understanding of exposure and actions to reduce harmful exposure.

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