Abstract
Biomass burning smoke is often a significant source of airborne fine particles in regional areas where air quality monitoring is scarce. Emerging sensor technology provides opportunities to monitor air quality on a much larger geographical scale with much finer spatial resolution. It can also engage communities in the conversation around local pollution sources. The SMoke Observation Gadget (SMOG), a unit with a Plantower dust sensor PMS3003, was designed as part of a school-based Science, Technology, Engineering and Mathematics (STEM) project looking at smoke impacts in regional areas of Victoria, Australia. A smoke-specific calibration curve between the SMOG units and a standard regulatory instrument was developed using an hourly data set collected during a peat fire. The calibration curve was applied to the SMOG units during all field-based validation measurements at several locations and during different seasons. The results showed strong associations between individual SMOG units for PM2.5 concentrations (r2 = 0.93–0.99) and good accuracy (mean absolute error (MAE) < 2 μg m−3). Correlations of the SMOG units to reference instruments also demonstrated strong associations (r2 = 0.87–95) and good accuracy (MAE of 2.5–3.0 μg m−3). The PM2.5 concentrations tracked by the SMOG units had a similar response time as those measured by collocated reference instruments. Overall, the study has shown that the SMOG units provide relevant information about ambient PM2.5 concentrations in an airshed impacted predominantly by biomass burning, provided that an adequate adjustment factor is applied.
Highlights
It is well understood that there are negative health impacts from exposures to biomass smoke [1,2,3,4,5,6,7,8,9,10]
During winter, corrected SMoke Observation Gadget (SMOG) PM2.5 concentrations were significantly higher compared to PM2.5 measurements made with the Fidas or Esampler
We were able to conduct a number of field-based monitoring campaigns where the SMOG units were tested over a wide range of environmental conditions and PM2.5 concentration ranges
Summary
It is well understood that there are negative health impacts from exposures to biomass smoke [1,2,3,4,5,6,7,8,9,10]. Considerable resources are required to maintain such a network of reference air quality monitors in regional locations where biomass smoke events most frequently occur [19]. In response to this resourcing issue, the use of ‘low-cost’ air quality sensors can provide a useful alternative to traditional reference air quality monitors. These sensors have the potential to provide high resolution air quality monitoring, both in time and space. Applications of low-cost sensor networks can be extended to population exposure and health assessment [15,20]
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