2 research outputs found
Understanding the ability of low-cost MOx sensors to quantify ambient VOCs
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
data in high time and spatial resolution. These 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 and 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 quadrupole mass
spectrometer (PTR-QMS) 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 in 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.</p
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Assessing a low-cost methane sensor quantification system for use in complex rural and urban environments
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