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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 7, issue 4 | Copyright
Atmos. Meas. Tech., 7, 1121-1131, 2014
https://doi.org/10.5194/amt-7-1121-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 30 Apr 2014

Research article | 30 Apr 2014

Field calibrations of a low-cost aerosol sensor at a regulatory monitoring site in California

D. M. Holstius1, A. Pillarisetti1, K. R. Smith1, and E. Seto2 D. M. Holstius et al.
  • 1University of California, Berkeley, USA
  • 2University of Washington, Seattle, USA

Abstract. Health effects attributed to ambient fine particulate matter (PM2.5) now rank it among the risk factors with the highest health burdens in the world, but existing monitoring infrastructure cannot adequately characterize spatial and temporal variability in urban PM2.5 concentrations, nor in human population exposures. The development and evaluation of more portable and affordable monitoring instruments based on low-cost sensors may offer a means to supplement and extend existing infrastructure, increasing the density and coverage of empirical measurements and thereby improving exposure science and control. Here, we report on field calibrations of a custom-built, battery-operated aerosol monitoring instrument we developed using low-cost, off-the-shelf optical aerosol sensors. We calibrated our instruments using 1 h and 24 h PM2.5 data from a class III US EPA Federal Equivalent Method (FEM) PM2.5 β-attenuation monitor in continuous operation at a regulatory monitoring site in Oakland, California. We observed negligible associations with ambient humidity and temperature; linear corrections were sufficient to explain 60% of the variance in 1 h reference PM2.5 data and 72% of the variance in 24 h data. Performance at 1 h integration times was comparable to commercially available optical instruments costing considerably more. These findings warrant further exploration of the circumstances under which this class of aerosol sensors may profitably be deployed to generate improved PM2.5 data sets.

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