scholarly journals Field Evaluation of Low-Cost PM Sensors (Purple Air PA-II) Under Variable Urban Air Quality Conditions, in Greece

Atmosphere ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 926 ◽  
Author(s):  
Iasonas Stavroulas ◽  
Georgios Grivas ◽  
Panagiotis Michalopoulos ◽  
Eleni Liakakou ◽  
Aikaterini Bougiatioti ◽  
...  
Keyword(s):  
Air Quality ◽  
Urban Forest ◽  
Low Cost ◽  
Field Evaluation ◽  
Urban Environments ◽  
Spatiotemporal Variability ◽  
Monitoring Networks ◽  
Fire Event ◽  
Ambient Relative Humidity ◽  
Reference Measurements

Recent advances in particle sensor technologies have led to an increased development and utilization of low-cost, compact, particulate matter (PM) monitors. These devices can be deployed in dense monitoring networks, enabling an improved characterization of the spatiotemporal variability in ambient levels and exposure. However, the reliability of their measurements is an important prerequisite, necessitating rigorous performance evaluation and calibration in comparison to reference-grade instrumentation. In this study, field evaluation of Purple Air PA-II devices (low-cost PM sensors) is performed in two urban environments and across three seasons in Greece, in comparison to different types of reference instruments. Measurements were conducted in Athens (the largest city in Greece with nearly four-million inhabitants) for five months spanning over the summer of 2019 and winter/spring of 2020 and in Ioannina, a medium-sized city in northwestern Greece (100,000 inhabitants) during winter/spring 2019–2020. The PM2.5 sensor output correlates strongly with reference measurements (R2 = 0.87 against a beta attenuation monitor and R2 = 0.98 against an optical reference-grade monitor). Deviations in the sensor-reference agreement are identified as mainly related to elevated coarse particle concentrations and high ambient relative humidity. Simple and multiple regression models are tested to compensate for these biases, drastically improving the sensor’s response. Large decreases in sensor error are observed after implementation of models, leading to mean absolute percentage errors of 0.18 and 0.12 for the Athens and Ioannina datasets, respectively. Overall, a quality-controlled and robustly evaluated low-cost network can be an integral component for air quality monitoring in a smart city. Case studies are presented along this line, where a network of PA-II devices is used to monitor the air quality deterioration during a peri-urban forest fire event affecting the area of Athens and during extreme wintertime smog events in Ioannina, related to wood burning for residential heating.

scholarly journals Assessing a low-cost methane sensor quantification system for use in complex rural and urban environments

2018 ◽  
Author(s):  
Ashley Collier-Oxandale ◽  
Michael P. Hannigan ◽  
Joanna Gordon Casey ◽  
Ricardo Piedrahita ◽  
John Ortega ◽  
...  
Keyword(s):  
Air Quality ◽  
Los Angeles ◽  
Oil And Gas ◽  
Spatial Scales ◽  
Low Cost ◽  
Complex Mixture ◽  
Urban Environments ◽  
Monitoring Networks ◽  
Linear Calibration ◽  
Spatial And Temporal Scales

Abstract. Low-cost sensors have the potential to facilitate the exploration of air quality issues on new temporal and spatial scales. Here we evaluate a low-cost sensor quantification system for methane through its use in two different deployments. The first, a one-month deployment along the Colorado Front Range includes sites near active oil and gas operations in the Denver-Julesberg basin. The second deployment in an urban Los Angeles neighborhood, an subject to complex mixture of air pollution sources including oil operations. Given its role as a potent greenhouse gas, new low-cost methods for detecting and monitoring methane may aid in protecting human and environmental health. In this paper, we assess a number of linear calibration models to convert raw sensor signals into ppm concentration values. We also examine different choices that can be made during calibration and data processing, and explore cross-sensitivities that impact this sensor type. The results illustrate the accuracy of the Figaro TGS 2600 sensor when methane is quantified from raw signals using the techniques described. The results also demonstrate the value of these tools for examining air quality trends and events on small spatial and temporal scales as well as their ability to characterize an area – highlighting their potential to provide preliminary data that can inform more targeted measurements or supplement existing monitoring networks.

scholarly journals Field Evaluation of Low-Cost Particulate Matter Sensors for Measuring Wildfire Smoke

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4796
Author(s):  
Amara L. Holder ◽  
Anna K. Mebust ◽  
Lauren A. Maghran ◽  
Michael R. McGown ◽  
Kathleen E. Stewart ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Low Cost ◽  
Field Evaluation ◽  
Eastern United States ◽  
Monitoring Networks ◽  
Wildfire Smoke ◽  
Sensor Package ◽  
The Impact ◽  
Mean Square Errors

Until recently, air quality impacts from wildfires were predominantly determined based on data from permanent stationary regulatory air pollution monitors. However, low-cost particulate matter (PM) sensors are now widely used by the public as a source of air quality information during wildfires, although their performance during smoke impacted conditions has not been thoroughly evaluated. We collocated three types of low-cost fine PM (PM2.5) sensors with reference instruments near multiple fires in the western and eastern United States (maximum hourly PM2.5 = 295 µg/m3). Sensors were moderately to strongly correlated with reference instruments (hourly averaged r2 = 0.52–0.95), but overpredicted PM2.5 concentrations (normalized root mean square errors, NRMSE = 80–167%). We developed a correction equation for wildfire smoke that reduced the NRMSE to less than 27%. Correction equations were specific to each sensor package, demonstrating the impact of the physical configuration and the algorithm used to translate the size and count information into PM2.5 concentrations. These results suggest the low-cost sensors can fill in the large spatial gaps in monitoring networks near wildfires with mean absolute errors of less than 10 µg/m3 in the hourly PM2.5 concentrations when using a sensor-specific smoke correction equation.

scholarly journals Assessing a low-cost methane sensor quantification system for use in complex rural and urban environments

2018 ◽  
Vol 11 (6) ◽  
pp. 3569-3594 ◽  
Author(s):  
Ashley Collier-Oxandale ◽  
Joanna Gordon Casey ◽  
Ricardo Piedrahita ◽  
John Ortega ◽  
Hannah Halliday ◽  
...  
Keyword(s):  
Air Quality ◽  
Los Angeles ◽  
Oil And Gas ◽  
Spatial Scales ◽  
Low Cost ◽  
Urban Environments ◽  
Monitoring Networks ◽  
Linear Calibration ◽  
Spatial And Temporal Scales ◽  
Rural And Urban

Abstract. Low-cost sensors have the potential to facilitate the exploration of air quality issues on new temporal and spatial scales. Here we evaluate a low-cost sensor quantification system for methane through its use in two different deployments. The first was a 1-month deployment along the Colorado Front Range and included sites near active oil and gas operations in the Denver-Julesburg basin. The second deployment was in an urban Los Angeles neighborhood, subject to complex mixtures of air pollution sources including oil operations. Given its role as a potent greenhouse gas, new low-cost methods for detecting and monitoring methane may aid in protecting human and environmental health. In this paper, we assess a number of linear calibration models used to convert raw sensor signals into ppm concentration values. We also examine different choices that can be made during calibration and data processing and explore cross sensitivities that impact this sensor type. The results illustrate the accuracy of the Figaro TGS 2600 sensor when methane is quantified from raw signals using the techniques described. The results also demonstrate the value of these tools for examining air quality trends and events on small spatial and temporal scales as well as their ability to characterize an area – highlighting their potential to provide preliminary data that can inform more targeted measurements or supplement existing monitoring networks.

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.

Low-Cost Air Quality Sensor Network in Munich

2020 ◽  
Author(s):  
Daniel Zollitsch ◽  
Jia Chen ◽  
Florian Dietrich ◽  
Benno Voggenreiter ◽  
Luca Setili ◽  
...  
Keyword(s):  
Air Quality ◽  
Real Time ◽  
Air Pollutants ◽  
Low Cost ◽  
Environmental Parameters ◽  
Calibration Method ◽  
Sensitivity Function ◽  
Machine Learning Algorithms ◽  
Urban Air ◽  
Monitoring Networks

<p>As the number of official monitoring stations for measuring urban air pollutants such as nitrogen oxides (NOx), particulate matter (PM) or ozone (O<sub>3</sub>) in most cities is quite small, it is difficult to determine the real human exposure to those pollutants. Therefore, several groups have established spatially higher resolved monitoring networks using low-cost sensors to create a finer concentration map [1-3].</p><p>We are currently establishing a low-cost, but high-accuracy network in Munich to measure the concentrations of NOx, PM, O<sub>3</sub>, CO and additional environmental parameters. For that, we developed a compact stand-alone sensor systems that requires low power, automatically measures the respective parameters every minute and sends the data to our server. There the raw data is transferred into concentration values by applying the respective sensitivity function for each sensor. These functions are determined by calibration measurements prior to the distribution of the sensors.</p><p>In contrast to the other existing networks, we will apply a recurring calibration method using a mobile high precision calibration unit (reference sensor) and machine learning algorithms. The results will be used to update the sensitivity function of each single sensor twice a week.  With the help of this approach, we will be able to create a calibrated real-time concentration map of air pollutants in Munich.</p><p>[1] Bigi et al.: Performance of NO, NO<sub>2</sub> low cost sensors and three calibration approaches within a real world application, Atmos. Meas. Tech., 11, 3717–3735, 2018</p><p>[2] Popoola et al., “Use of networks of low cost air quality sensors to quantify air quality in urban settings,” Atmos. Environ., 194, 58–70, 2018</p><p>[3] Schneider et al.: Mapping urban air quality in near real-time using observations from low-cost sensors and model information, Environ. Int., 106, 234–247, 2017</p>

scholarly journals High-resolution mapping of urban air quality with heterogeneous observations: a new methodology and its application to Amsterdam

2019 ◽  
Author(s):  
Bas Mijling
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Low Cost ◽  
Urban Air Pollution ◽  
Heterogeneous Data ◽  
Urban Air Quality ◽  
Quality Data ◽  
Urban Air ◽  
Reference Measurements ◽  
Concentration Patterns

Abstract. In many cities around the world people are exposed to elevated levels of air pollution. Often local air quality is not well known due to the sparseness of official monitoring networks, or unrealistic assumptions being made in urban air quality models. Low-cost sensor technology, which has become available in recent years, has the potential to provide complementary information. Unfortunately, an integrated interpretation of urban air pollution based on different sources is not straightforward because of the localized nature of air pollution, and the large uncertainties associated with measurements of low-cost sensors. In this study, we present a practical approach to producing high spatio-temporal resolution maps of urban air pollution capable of assimilating air quality data from heterogeneous data streams. It offers a two-step solution: (1) building a versatile air quality model, driven by an open source atmospheric dispersion model and emission proxies from open data sources, and (2) a practical spatial interpolation scheme, capable of assimilating observations with different accuracies. The methodology, called Retina, has been applied and evaluated for nitrogen dioxide (NO2) in Amsterdam, the Netherlands, during the summer of 2016. The assimilation of reference measurements results in hourly maps with a typical accuracy of 39 % within 2 km of an observation location, and 53 % at larger distances. When low-cost measurements of the Urban AirQ campaign are included, the maps reveal more detailed concentration patterns in areas which are undersampled by the official network. During the summer holiday period, NO2 concentrations drop about 10 % due to reduced urban activity. The reduction is less in the historic city center, while strongest reductions are found around the access ways to the tunnel connecting the northern and the southern part of the city, which was closed for maintenance. The changing concentration patterns indicate how traffic flow is redirected to other main roads. Overall, we show that Retina can be applied for an enhanced understanding of reference measurements, and as a framework to integrate low-cost measurements next to reference measurements in order to get better localized information in urban areas.

scholarly journals Design of an ozone and nitrogen dioxide sensor unit and its long-term operation within a sensor network in the city of Zurich

2017 ◽  
Author(s):  
Michael Mueller ◽  
Jonas Meyer ◽  
Christoph Hueglin
Keyword(s):  
Air Quality ◽  
Sensor Network ◽  
Data Transfer ◽  
Low Cost ◽  
Effective Procedure ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Monitoring Networks ◽  
Term Operation ◽  
Diffusion Tubes

Abstract. This study focuses on the investigation and quantification of low-cost sensor performance in application fields such as the extension of traditional air quality monitoring networks or the replacement of diffusion tubes. For this, sensor units consisting of two boxes featuring NO2 and O3 low-cost sensors and wireless data transfer were engineered. The sensor units were initially operated at air quality monitoring sites for three months for performance analysis and initial calibration. Afterwards, they were relocated and operated within a sensor network consisting of six locations for more than one year. Our analyses show that the employed O3 and NO2 sensors can be accurate to 2–5 and 5–7 ppb, respectively, during the first three months of operation. This accuracy, however, could not be maintained during their operation within the sensor network related to changes in sensor behaviour. Hence, the low-cost sensors in our configuration do not reach the accuracy level of NO2 diffusion tubes. Tests in the laboratory revealed that changes in relative humidity can impact the signal of the employed NO2 sensors similarly as changes in ambient NO2 concentration. All the employed low-cost sensors need to be individually calibrated. Best performance of NO2 sensors is achieved when the calibration models include also time dependent parameters accounting for changes in sensor response over time. Accordingly, an effective procedure for continuous data control and correction is essential for obtaining meaningful data. It is demonstrated that linking the measurements from low-cost sensors to the high quality measurements from routine air quality monitoring stations is an effective procedure for both tasks provided that time periods can be identified when pollutant concentrations can be accurately predicted at sensor locations.

scholarly journals Review of the Performance of Low-Cost Sensors for Air Quality Monitoring

Atmosphere ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 506 ◽  
Author(s):  
Federico Karagulian ◽  
Maurizio Barbiere ◽  
Alexander Kotsev ◽  
Laurent Spinelle ◽  
Michel Gerboles ◽  
...  
Keyword(s):  
Air Quality ◽  
Low Cost ◽  
Cost Effective ◽  
Coefficient Of Determination ◽  
Atmospheric Conditions ◽  
Site Location ◽  
Independent Evaluation ◽  
Spatial Coverage ◽  
Other Information ◽  
Reference Measurements

A growing number of companies have started commercializing low-cost sensors (LCS) that are said to be able to monitor air pollution in outdoor air. The benefit of the use of LCS is the increased spatial coverage when monitoring air quality in cities and remote locations. Today, there are hundreds of LCS commercially available on the market with costs ranging from several hundred to several thousand euro. At the same time, the scientific literature currently reports independent evaluation of the performance of LCS against reference measurements for about 110 LCS. These studies report that LCS are unstable and often affected by atmospheric conditions—cross-sensitivities from interfering compounds that may change LCS performance depending on site location. In this work, quantitative data regarding the performance of LCS against reference measurement are presented. This information was gathered from published reports and relevant testing laboratories. Other information was drawn from peer-reviewed journals that tested different types of LCS in research studies. Relevant metrics about the comparison of LCS systems against reference systems highlighted the most cost-effective LCS that could be used to monitor air quality pollutants with a good level of agreement represented by a coefficient of determination R2 > 0.75 and slope close to 1.0. This review highlights the possibility to have versatile LCS able to operate with multiple pollutants and preferably with transparent LCS data treatment.

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