Development and Calibration of A Particulate Matter Measurement Device with Wireless Sensor Network Function

Abstract

A Zigbee-based ubiquitous sensor network (USN) has many industrial applications and provides flexible measuring environments. In particular, the USN system can replace existing measuring devices in harsh environments such as subway stations. To monitor the intensities of various pollutants and air qualities in subway tunnels, this study applied the USN technique. A novel wireless sensor module, PMX, was designed and manufactured to simultaneously detect PM 10 and PM 2.5. Measurements were conducted at a subway station in Seoul. The PM concentrations using PMX were measured, analyzed, and compared with those obtained using an established commercial dust spectrometer (Grimm Aerosol Technik, 1.109). The measurements were performed from 24 March 2010 to 9 April 2010. PMX and the dust spectrometer measured PM 10 levels of 98.3 and 40.7 ㎍/㎥, respectively, and PM 2.5 concentrations of 86.5 and 16.6 ㎍/㎥, respectively. The monitored PM levels were investigated in a bimodal form during the sampling period. The PM 10 and PM 2.5 average correlations between PMX and the dust spectrometer were r 2 =0.81 and r 2 = 0.97, respectively. The two systems showed a similar time series trend, even though the measured values differed. A simple correlation analysis of the two data groups showed coefficients of determination of 0.7 for PM 10 and 0.9 for PM 2.5. The PMX data were mostly concentrated around the trend curve. Therefore, calibration of PMX data was required prior to use in the field. For the calibration, simple linear regression and nonlinear regression were used. The resulting correlation coefficients of simple linear regressions were 0.8 for PM 10 and 0.9 for PM 2.5 , whereas those for nonlinear regressions were 0.7 for PM 10 and 0.9 for PM 2.5. The higher correlation coefficient for PM 10 by the nonlinear regression indicates that it is the better method for calibrating the system developed in this study.