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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/amt-2020-188
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2020-188
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 24 Jun 2020

Submitted as: research article | 24 Jun 2020

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This preprint is currently under review for the journal AMT.

Assessing the accuracy of low-cost optical particle sensors using a physics-based approach

David H. Hagan1,2 and Jesse H. Kroll1,3 David H. Hagan and Jesse H. Kroll
  • 1Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
  • 2QuantAQ, Inc., Somerville, MA 02143, USA
  • 3Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA

Abstract. Low-cost sensors for measuring particulate matter (PM) offer the ability to understand human exposure to air pollution at spatiotemporal scales that have previously been impractical. However, such low-cost PM sensors tend to be poorly characterized, and their measurements of mass concentration can be subject to considerable error. Recent studies have investigated how individual factors can contribute to this error, but these studies are largely based on empirical comparisons and generally do not examine the role of multiple factors simultaneously. Here, we present a new physics-based framework and open-source software package (opcsim) for evaluating the ability of low-cost optical particle sensors (optical particle counters and nephelometers) to accurately characterize the size distribution and/or mass loading of aerosol particles. This framework, which uses Mie Theory to calculate the response of a given sensor to a given particle population, is used to estimate the relative error in mass loading for different sensor types, given variations in relative humidity, aerosol optical properties, and the underlying particle size distribution. Results indicate that such error, which can be substantial, is dependent on the sensor technology (nephelometer vs. optical particle counter), the specific parameters of the individual sensor, and differences between the aerosol used to calibrate the sensor and the aerosol being measured. We conclude with a summary of likely sources of error for different sensor types, environmental conditions, and particle classes, and offer general recommendations for choice of calibrant under different measurement scenarios.

David H. Hagan and Jesse H. Kroll

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Status: open (until 19 Aug 2020)
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David H. Hagan and Jesse H. Kroll

Model code and software

opcsim D. H. Hagan and J. H. Kroll https://doi.org/10.5281/zenodo.3905043

David H. Hagan and Jesse H. Kroll

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Short summary
Assessing the error of low-cost particulate matter (PM) sensors has been difficult as each empirical study presents unique limitations. Here, we present a new, open-sourced, physics-based model (opcsim) and use it to understand how the properties of different particle sensors alter their accuracy. We offer a summary of likely sources of error for different sensor types, environmental conditions, and particle classes, and offer recommendations for the choice of optimal calibrant.
Assessing the error of low-cost particulate matter (PM) sensors has been difficult as each...
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