10th International Aerosol Conference
September 2 - September 7, 2018
America's Center Convention Complex
St. Louis, Missouri, USA

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Low-cost Sensor Calibration, Application, and Modification for Size Distribution and Refractive Index Measurements

JIAYU LI, Jiaxi Fang, Tandeep Chadha, Benjamin Sumlin, Rajan K. Chakrabarty, Pratim Biswas, Washington University in St Louis

     Abstract Number: 382
     Working Group: Low-Cost and Portable Sensors

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. Wang et al. (2015)1 compared three types of popular low-cost PM sensor from Sharp, Shenyei, and Samyoung and summarized advantages and disadvantages of each sensor. To ensure accurate and reliable representation of PM mass concentrations, we calibrated the Sharp sensor with an optical method to study signal’s dependence on composition and size distribution, which demonstrated why repeated calibration is needed for low-cost sensors2. Apart from laboratory studies, a networked low-cost PM sensor system has been applied in field measurements. They were deployed in households in Raipur, India to establish the spatiotemporal variation of PM concentrations3. From another study, in a woodworking shop, data collected by the networked sensor system was utilized to construct spatiotemporal PM concentration distributions using an ordinary Kriging method and an Artificial Neural Network model to elucidate particle generation and ventilation processes4.

Almost all of the optical particle sensors make an assumption on the refractive index of the aerosols. As a result, the output of the current sensors could be inaccurate depending on the difference in optical properties of the calibration aerosols and measured aerosols. An improved system (OPSC) utilizes a three-wavelength particle counter coupled with accelerating nozzle time of flight measurements to measure the size distribution of the aerosol and to predict the material properties of the aerosol based on the refractive index of the aerosol. The three-wavelength particle counter measures the scattered light from a single particle at a time while the time of flight measurements utilize the peak intervals between successive detectors to measure aerodynamic size. These two measurements coupled together can be used to calculate the refractive index of the aerosol using the drag force and Mie Lorentz calculations. However, such calculations are computationally intensive. To mitigate the computation issue, machine learning algorithm was used to train the data and simplify the algorithm.

1. Wang, Y., Li, J., Jing, H., Zhang, Q., Jiang, J., and Biswas, P. “Laboratory evaluation and calibration of three low-cost particle sensors for particulate matter measurement” Aerosol Science and Technology, 49:11, 1063-1077, 2015.
2. Li, J., and Biswas, P., "Optical characterization studies of a low-cost particle sensor" Aerosol and Air Quality Research, 17, 1591-1604, 2017.
3. Patel, S., Li, J., Pandey, A., Parvez, S., Chakrabarty, R. K., and Biswas, P., "Spatio-temporal measurement of indoor particulate matter concentrations using a wireless network of low-cost sensors in households using solid fuels", Environmental Research, 152, 59-65, 2016.
4. Li, J., Li, H., Ma, Y., Wang, Y., Abokifa, A., Lu, C., and Biswas, P., “Spatiotemporal distribution of indoor particulate matter concentration with low-cost sensor network”, Building and Environment, 127, 138, 2017.