AAAR 36th Annual Conference October 16 - October 20, 2017 Raleigh Convention Center Raleigh, North Carolina, USA
Abstract View
Optical Characterization of the Low-Cost Sensor and Its Application with Robots
JIAYU LI, Pratim Biswas, Washington University in St Louis
Abstract Number: 203 Working Group: Instrumentation and Methods
Abstract Compact low-cost sensors for measuring particulate matter (PM) concentrations are receiving significant attention as they can be used in larger numbers and in a distributed manner. To ensure accurate and reliable determination of PM mass concentrations, a relationship of the scattering signal to mass concentration should be established. The scattering signal depends on the aerosol size distributions and particle refractive index. A systematic calibration of a low-cost particle sensor (Sharp GP2Y1010AU0F) was carried out by both experimental and computational studies. Sodium chloride, silica, and sucrose aerosols were used as test cases with size distributions measured using a scanning mobility particle sizer (SMPS). Calculations of the scattered light intensity were done using these measured size distributions and known refractive index of the particles. The calculated scattered light intensity showed better linearity with the sensor signal compared to the mass concentration. To obtain a more accurate mass concentration estimation, a model was developed to determine a calibration factor (K). K is not universal for all aerosols but depends on the size distribution and refractive index. To improve accuracy in estimation of mass concentration, an expression for K as a function of geometric mean diameter, geometric standard deviation, and refractive is proposed. This approach not only provides a more accurate estimation of PM concentration but also provides an estimate of the aerosol number concentration.
The calibrated sensor was applied to several scenarios for air quality measurement. One application was in a wood-working shop wherein a set of distributed sensors was used to map the plume. Another application involved mounting the wireless sensors on a robot to automatically determine the highest concentration in a region. This application will be very helpful on wildfire rescue and industrial leakage detection.
Wang, Yang et al. Aerosol Sci. Technol. 49.11 (2015): 1063-1077. Jiayu Li et al. Aerosol Air Qual. Res. (to appear in 2017).