scholarly journals Quantification of major particulate matter species from a single filter type using infrared spectroscopy – Application to a large-scale monitoring network

2021 ◽  
Author(s):  
Bruno Debus ◽  
Andrew T. Weakley ◽  
Satoshi Takahama ◽  
Kathryn M. George ◽  
Bret Schichtel ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Large Scale ◽  
Low Cost ◽  
Monitoring Network ◽  
Analytical Techniques ◽  
Atmospheric Composition ◽  
Aerosol Sampling ◽  
Monitoring Networks ◽  
Filter Type ◽  
Ft Ir

Abstract. To enable chemical speciation, monitoring networks collect particulate matter (PM) on different filter media, each subjected to one or more analytical techniques to quantify PM composition present in the atmosphere. In this work, we propose an alternate approach that uses one filter type (teflon or polytetrafluoroethylene, PTFE, commonly used for aerosol sampling) and one analytical method, Fourier Transform Infrared (FT-IR) spectroscopy to measure almost all of the major constituents in the aerosol. In the proposed method, measurements using the typical multi-filter, multi-analytical techniques are retained at a limited number of sites and used as calibration standards while sampling on PTFE and analysis by FT-IR is solely performed at the remaining locations. This method takes advantage of the sensitivity on the mid-IR domain to various organic and inorganic functional groups and offers a fast and inexpensive way of exploring sample composition. As a proof of concept, multiple years of samples collected within the Interagency Monitoring of PROtected Visual Environment network (IMPROVE) are explored with the aim of retaining high quality predictions for a broad range of atmospheric compounds including total mass, organic (OC), elemental (EC) and total (TC) carbon, sulfate, nitrate and crustal elements. Findings suggest that models based on only 21 sites, covering spatial and seasonal trends in atmospheric composition, are stable over a three year period within the IMPROVE network with prediction accuracy (R2 > 0.9, median bias less than 3 % for most constituents. Incorporating additional sites at low cost or partially replacing existing, more time and cost intensive techniques are among the potential benefits of one-filter, one-method approach.

scholarly journals Facile Synthesis of Calcium Carbonate Nanoparticles from Cockle Shells

2012 ◽  
Vol 2012 ◽  
pp. 1-5 ◽  
Author(s):  
Kh. Nurul Islam ◽  
A. B. Z. Zuki ◽  
M. E. Ali ◽  
Mohd Zobir Bin Hussein ◽  
M. M. Noordin ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Calcium Carbonate ◽  
Large Scale ◽  
Low Cost ◽  
Analytical Techniques ◽  
Variable Pressure ◽  
X Ray Diffraction ◽  
X Ray ◽  
Transmission Electron ◽  
Ft Ir

A simple and low-cost method for the synthesis of calcium carbonate nanoparticles from cockle shells was described. Polymorphically, the synthesized nanoparticles were aragonites which are biocompatible and thus frequently used in the repair of fractured bone and development of advanced drug delivery systems, tissue scaffolds and anticarcinogenic drugs. The rod-shaped and pure aragonite particles of30±5 nm in diameter were reproducibly synthesized when micron-sized cockle shells powders were mechanically stirred for 90 min at room temperature in presence of a nontoxic and nonhazardous biomineralization catalyst, dodecyl dimethyl betaine (BS-12). The findings were verified using a combination of analytical techniques such as variable pressure scanning electron microscopy (VPSEM), transmission electron microscopy (TEM), Fourier transmission infrared spectroscopy (FT-IR), X-ray diffraction spectroscopy (XRD), and energy dispersive X-ray analyser (EDX). The reproducibility and low cost of the method suggested that it could be used in industry for the large scale synthesis of aragonite nanoparticles from cockle shells, a low cost and easily available natural resource.

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 Long-Term Performance Assessment of Low-Cost Atmospheric Sensors in the Arctic Environment

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1919 ◽  
Author(s):  
Federico Carotenuto ◽  
Lorenzo Brilli ◽  
Beniamino Gioli ◽  
Giovanni Gualtieri ◽  
Carolina Vagnoli ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Relative Humidity ◽  
Air Temperature ◽  
Meteorological Parameters ◽  
Low Cost ◽  
Absolute Error ◽  
Atmospheric Composition ◽  
The Arctic ◽  
Svalbard Archipelago ◽  
Arctic Environment

The Arctic is an important natural laboratory that is extremely sensitive to climatic changes and its monitoring is, therefore, of great importance. Due to the environmental extremes it is often hard to deploy sensors and observations are limited to a few sparse observation points limiting the spatial and temporal coverage of the Arctic measurement. Given these constraints the possibility of deploying a rugged network of low-cost sensors remains an interesting and convenient option. The present work validates for the first time a low-cost sensor array (AIRQino) for monitoring basic meteorological parameters and atmospheric composition in the Arctic (air temperature, relative humidity, particulate matter, and CO2). AIRQino was deployed for one year in the Svalbard archipelago and its outputs compared with reference sensors. Results show good agreement with the reference meteorological parameters (air temperature (T) and relative humidity (RH)) with correlation coefficients above 0.8 and small absolute errors (≈1 °C for temperature and ≈6% for RH). Particulate matter (PM) low-cost sensors show a good linearity (r2 ≈ 0.8) and small absolute errors for both PM2.5 and PM10 (≈1 µg m−3 for PM2.5 and ≈3 µg m−3 for PM10), while overall accuracy is impacted both by the unknown composition of the local aerosol, and by high humidity conditions likely generating hygroscopic effects. CO2 exhibits a satisfying agreement with r2 around 0.70 and an absolute error of ≈23 mg m−3. Overall these results, coupled with an excellent data coverage and scarce need of maintenance make the AIRQino or similar devices integrations an interesting tool for future extended sensor networks also in the Arctic environment.

scholarly journals Strategies for Monitoring Multiuse Trail Networks

2017 ◽  
Vol 2644 (1) ◽  
pp. 100-110 ◽  
Author(s):  
Greg Lindsey ◽  
Jeffrey S. Wilson ◽  
Jueyu Wang ◽  
Tracy Hadden-Loh
Keyword(s):  
Nonprofit Organizations ◽  
Large Scale ◽  
Low Cost ◽  
Facility Planning ◽  
Monitoring Networks ◽  
Site Specific ◽  
New Challenges ◽  
Large Scale Networks ◽  
Selection Of

Many municipalities, park districts, and nonprofit organizations have begun monitoring nonmotorized traffic on multiuse trails as the need for information about the use of facilities has grown and relatively low-cost sensors for automated monitoring have become available. As they have gained experience, they have begun to move from site-specific monitoring on individual trails to a more comprehensive monitoring of trail networks. This case study review compares strategies developed by 10 organizations for monitoring traffic on multiuse trails, including local, multicounty, statewide, and multistate trail networks. The focus is on approaches to the design of monitoring networks, particularly the rationales or objectives for monitoring and the selection of monitoring sites. It is shown that jurisdictions are following principles of monitoring established by FHWA and that the design of monitoring networks is evolving to meet new challenges, including monitoring large-scale networks. Relevant outcomes and implications for practice are summarized. The researchers concluded that FHWA guidelines can be adapted to many circumstances and can increase information for decision making. Trail monitoring is informing decisions related to facility planning, investment, and safety.

scholarly journals Developing a Relative Humidity Correction for Low-Cost Sensors Measuring Ambient Particulate Matter

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2790 ◽  
Author(s):  
Andrea Di Antonio ◽  
Olalekan Popoola ◽  
Bin Ouyang ◽  
John Saffell ◽  
Roderic Jones
Keyword(s):  
Particle Size ◽  
Particulate Matter ◽  
Relative Humidity ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Low Cost ◽  
Monitoring Networks ◽  
Ambient Particulate Matter ◽  
Correction Algorithm ◽  
Ambient Conditions

There is increasing concern about the health impacts of ambient Particulate Matter (PM) exposure. Traditional monitoring networks, because of their sparseness, cannot provide sufficient spatial-temporal measurements characteristic of ambient PM. Recent studies have shown portable low-cost devices (e.g., optical particle counters, OPCs) can help address this issue; however, their application under ambient conditions can be affected by high relative humidity (RH) conditions. Here, we show how, by exploiting the measured particle size distribution information rather than PM as has been suggested elsewhere, a correction can be derived which not only significantly improves sensor performance but which also retains fundamental information on particle composition. A particle size distribution–based correction algorithm, founded on κ -Köhler theory, was developed to account for the influence of RH on sensor measurements. The application of the correction algorithm, which assumed physically reasonable κ values, resulted in a significant improvement, with the overestimation of PM measurements reduced from a factor of ~5 before correction to 1.05 after correction. We conclude that a correction based on particle size distribution, rather than PM mass, is required to properly account for RH effects and enable low cost optical PM sensors to provide reliable ambient PM measurements.

scholarly journals Measurement of carbonaceous aerosol with different sampling configurations and frequencies

2015 ◽  
Vol 8 (7) ◽  
pp. 2639-2648 ◽  
Author(s):  
Y. Cheng ◽  
K.-B. He
Keyword(s):  
Particulate Matter ◽  
Chemical Speciation ◽  
Fine Particulate Matter ◽  
Monitoring Network ◽  
Airborne Particulate Matter ◽  
Carbonaceous Aerosol ◽  
Monitoring Networks ◽  
Quartz Filter ◽  
Sampling Duration ◽  
The Impact

Abstract. A common approach for measuring the mass of organic carbon (OC) and elemental carbon (EC) in airborne particulate matter involves collection on a quartz fiber filter and subsequent thermal–optical analysis. Although having been widely used in aerosol studies and in PM2.5 (fine particulate matter) chemical speciation monitoring networks in particular, this measurement approach is prone to several types of artifacts, such as the positive sampling artifact caused by the adsorption of gaseous organic compounds onto the quartz filter, the negative sampling artifact due to the evaporation of OC from the collected particles and the analytical artifact in the thermal–optical determination of OC and EC (which is strongly associated with the transformation of OC into char OC and typically results in an underestimation of EC). The presence of these artifacts introduces substantial uncertainties to observational data on OC and EC and consequently limits our ability to evaluate OC and EC estimations in air quality models. In this study, the influence of sampling frequency on the measurement of OC and EC was investigated based on PM2.5 samples collected in Beijing, China. Our results suggest that the negative sampling artifact of a bare quartz filter could be remarkably enhanced due to the uptake of water vapor by the filter medium. We also demonstrate that increasing sampling duration does not necessarily reduce the impact of positive sampling artifact, although it will enhance the analytical artifact. Due to the effect of the analytical artifact, EC concentrations of 48 h averaged samples were about 15 % lower than results from 24 h averaged ones. In addition, it was found that with the increase of sampling duration, EC results exhibited a stronger dependence on the charring correction method and, meanwhile, optical attenuation (ATN) of EC (retrieved from the carbon analyzer) was more significantly biased by the shadowing effect. Results from this study will be useful for the design of China's PM2.5 chemical speciation monitoring network, which can be expected to be inaugurated in the near future.

Understanding Effectiveness of Eco Monitoring Networks: Information Theoretical Perspective

2013 ◽  
Vol 765-767 ◽  
pp. 2213-2219
Author(s):  
Su Min Li
Keyword(s):  
Large Scale ◽  
Theoretical Perspective ◽  
Monitoring Network ◽  
The Internet ◽  
Monitoring Networks ◽  
Large Networks ◽  
Moderate Size ◽  
Large Scale Data ◽  
Underlying Network ◽  
Scale Data

This work studies eco monitoring networks. As eco monitoring networks have been used to monitor large networks, questions arise whether decentralized inference is efficient and whether an eco monitoring network with a moderate size can monitor an underlying network at the Internet scale. This work studies the local effectiveness of decentralized inference done by individual monitors. Information theoretical measures, i.e., conditional non-uniformity factor is applied to quantify the effectiveness. Large-scale data from DShield is used to access the effectiveness of a real eco monitoring network.

scholarly journals Performance of a Low-Cost Sensor Community Air Monitoring Network in Imperial County, CA

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3031
Author(s):  
Paul English ◽  
Heather Amato ◽  
Esther Bejarano ◽  
Graeme Carvlin ◽  
Humberto Lugo ◽  
...  
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Monitoring Network ◽  
Data Interpretation ◽  
Air Monitoring ◽  
Least Square ◽  
Quality Data ◽  
Monitoring Networks ◽  
Time Data ◽  
Ordinary Least Square Regression

Air monitoring networks developed by communities have potential to reduce exposures and affect environmental health policy, yet there have been few performance evaluations of networks of these sensors in the field. We developed a network of over 40 air sensors in Imperial County, CA, which is delivering real-time data to local communities on levels of particulate matter. We report here on the performance of the Network to date by comparing the low-cost sensor readings to regulatory monitors for 4 years of operation (2015–2018) on a network-wide basis. Annual mean levels of PM10 did not differ statistically from regulatory annual means, but did for PM2.5 for two out of the 4 years. R2s from ordinary least square regression results ranged from 0.16 to 0.67 for PM10, and increased each year of operation. Sensor variability was higher among the Network monitors than the regulatory monitors. The Network identified a larger number of pollution episodes and identified under-reporting by the regulatory monitors. The participatory approach of the project resulted in increased engagement from local and state agencies and increased local knowledge about air quality, data interpretation, and health impacts. Community air monitoring networks have the potential to provide real-time reliable data to local populations.

scholarly journals Long-term field comparison of multiple low-cost particulate matter sensors in an outdoor urban environment

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Florentin M. J. Bulot ◽  
Steven J. Johnston ◽  
Philip J. Basford ◽  
Natasha H. C. Easton ◽  
Mihaela Apetroaie-Cristea ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Low Cost ◽  
Cost Effective ◽  
Personal Exposure ◽  
Monitoring Networks ◽  
Standard Equipment ◽  
Sensor Performance ◽  
Effective Manner ◽  
Micro Sensor ◽  
One Year

Abstract Exposure to ambient particulate matter (PM) air pollution is a leading risk factor for morbidity and mortality, associated with up to 8.9 million deaths/year worldwide. Measurement of personal exposure to PM is hindered by poor spatial resolution of monitoring networks. Low-cost PM sensors may improve monitoring resolution in a cost-effective manner but there are doubts regarding data reliability. PM sensor boxes were constructed using four low-cost PM micro-sensor models. Three boxes were deployed at each of two schools in Southampton, UK, for around one year and sensor performance was analysed. Comparison of sensor readings with a nearby background station showed moderate to good correlation (0.61 < r < 0.88, p < 0.0001), but indicated that low-cost sensor performance varies with different PM sources and background concentrations, and to a lesser extent relative humidity and temperature. This may have implications for their potential use in different locations. Data also indicates that these sensors can track short-lived events of pollution, especially in conjunction with wind data. We conclude that, with appropriate consideration of potential confounding factors, low-cost PM sensors may be suitable for PM monitoring where reference-standard equipment is not available or feasible, and that they may be useful in studying spatially localised airborne PM concentrations.

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