Abstract
Precise, location-specific fine dust measurement is central for the assessment of urban air quality. Classic measurement approaches require dedicated hardware, of which professional equipment is still prohibitively expensive (>10k$) for dense measurements, and inexpensive sensors do not meet accuracy demands. As a step towards filling this gap, we propose FeinPhone, a phone-based fine dust measurement system that uses camera and flashlight functions that are readily available on today’s off-the-shelf smart phones. We introduce a cost-effective passive hardware add-on together with a novel counting approach based on light-scattering particle sensors. Since our approach features a 2D sensor (the camera) instead of a single photodiode, we can employ it to capture the scatter traces from individual particles rather than just retaining a light intensity sum signal as in simple photometers. This is a more direct way of assessing the particle count, it is robust against side effects, e.g., from camera image compression, and enables gaining information on the size spectrum of the particles. Our proof-of-concept evaluation comparing several FeinPhone sensors with data from a high-quality APS/SMPS (Aerodynamic Particle Sizer/Scanning Mobility Particle Sizer) reference device at the World Calibration Center for Aerosol Physics shows that the collected data shows excellent correlation with the inhalable coarse fraction of fine dust particles (r > 0.9) and can successfully capture its levels under realistic conditions.
Highlights
Location-specific sensing of atmospheric particles plays an important role in capturing the dynamics of urban air quality as well as quantifying individual exposure
The World Calibration Center for Aerosol Physics (WCCAP) is a facility at the Leibniz Institute for Tropospheric Research (TROPOS, Leipzig, Germany), that is operated in cooperation with the German Federal Environmental
This paper presented FeinPhone, a phone-based fine dust measurement system that uses the camera and flash LED that are available on off-the-shelf smartphones as light receptor and emitter of a passive clip-on dust sensor respectively
Summary
Location-specific sensing of atmospheric particles plays an important role in capturing the dynamics of urban air quality as well as quantifying individual exposure. Numerous studies have revealed severe health effects of Particulate Matter (PM) pollution in the past [1,2,3]. The rise of real-time capable particle sensors has enabled a paradigm shift towards distributed measurements with high spatial and temporal resolution [4], with the potential to augment existing monitoring systems and enable citizen science environmental monitoring. Existing Particulate Matter (PM) sensing approaches, cannot meet the demands of these new sensing scenarios. PM sensing today generally requires dedicated devices. Professional equipment is too costly to be deployed on a large scale and inexpensive sensors are not yet ready for applications that require high accuracy [5,6]. Current low-cost laser-scattering sensors, such as the Nova
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