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 PM10 and PM2.5. 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 PM10 levels of 98.3 and 40.7 ㎍/㎥, respectively, and PM2.5 concentrations of 86.5 and 16.6 ㎍/㎥, respectively. The monitored PM levels were investigated in a bimodal form during the sampling period. The PM10 and PM2.5 average correlations between PMX and the dust spectrometer were r2=0.81 and r2= 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 PM10 and 0.9 for PM2.5. 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 PM10 and 0.9 for PM2.5, whereas those for nonlinear regressions were 0.7 for PM10 and 0.9 for PM2.5. The higher correlation coefficient for PM10 by the nonlinear regression indicates that it is the better method for calibrating the system developed in this study
| Published in | International Journal of Environmental Monitoring and Analysis (Volume 1, Issue 1) |
| DOI | 10.11648/j.ijema.20130101.12 |
| Page(s) | 15-20 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2013. Published by Science Publishing Group |
Particulate Matter, Ubiquitous Sensor Network, Subway, Indoor Air Quality
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APA Style
Duckshin Park, Duckshin Park, Soon-Bark Kwon, Soon-Bark Kwon, Youngmin Cho, et al. (2013). Development and Calibration of A Particulate Matter Measurement Device with Wireless Sensor Network Function. International Journal of Environmental Monitoring and Analysis, 1(1), 15-20. https://doi.org/10.11648/j.ijema.20130101.12
ACS Style
Duckshin Park; Duckshin Park; Soon-Bark Kwon; Soon-Bark Kwon; Youngmin Cho, et al. Development and Calibration of A Particulate Matter Measurement Device with Wireless Sensor Network Function. Int. J. Environ. Monit. Anal. 2013, 1(1), 15-20. doi: 10.11648/j.ijema.20130101.12
AMA Style
Duckshin Park, Duckshin Park, Soon-Bark Kwon, Soon-Bark Kwon, Youngmin Cho, et al. Development and Calibration of A Particulate Matter Measurement Device with Wireless Sensor Network Function. Int J Environ Monit Anal. 2013;1(1):15-20. doi: 10.11648/j.ijema.20130101.12
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author = {Duckshin Park and Duckshin Park and Soon-Bark Kwon and Soon-Bark Kwon and Youngmin Cho and Youngmin Cho},
title = {Development and Calibration of A Particulate Matter Measurement Device with Wireless Sensor Network Function},
journal = {International Journal of Environmental Monitoring and Analysis},
volume = {1},
number = {1},
pages = {15-20},
doi = {10.11648/j.ijema.20130101.12},
url = {https://doi.org/10.11648/j.ijema.20130101.12},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijema.20130101.12},
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 PM10 and PM2.5. 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 PM10 levels of 98.3 and 40.7 ㎍/㎥, respectively, and PM2.5 concentrations of 86.5 and 16.6 ㎍/㎥, respectively. The monitored PM levels were investigated in a bimodal form during the sampling period. The PM10 and PM2.5 average correlations between PMX and the dust spectrometer were r2=0.81 and r2= 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 PM10 and 0.9 for PM2.5. 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 PM10 and 0.9 for PM2.5, whereas those for nonlinear regressions were 0.7 for PM10 and 0.9 for PM2.5. The higher correlation coefficient for PM10 by the nonlinear regression indicates that it is the better method for calibrating the system developed in this study},
year = {2013}
}
TY - JOUR T1 - Development and Calibration of A Particulate Matter Measurement Device with Wireless Sensor Network Function AU - Duckshin Park AU - Duckshin Park AU - Soon-Bark Kwon AU - Soon-Bark Kwon AU - Youngmin Cho AU - Youngmin Cho Y1 - 2013/02/20 PY - 2013 N1 - https://doi.org/10.11648/j.ijema.20130101.12 DO - 10.11648/j.ijema.20130101.12 T2 - International Journal of Environmental Monitoring and Analysis JF - International Journal of Environmental Monitoring and Analysis JO - International Journal of Environmental Monitoring and Analysis SP - 15 EP - 20 PB - Science Publishing Group SN - 2328-7667 UR - https://doi.org/10.11648/j.ijema.20130101.12 AB - 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 PM10 and PM2.5. 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 PM10 levels of 98.3 and 40.7 ㎍/㎥, respectively, and PM2.5 concentrations of 86.5 and 16.6 ㎍/㎥, respectively. The monitored PM levels were investigated in a bimodal form during the sampling period. The PM10 and PM2.5 average correlations between PMX and the dust spectrometer were r2=0.81 and r2= 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 PM10 and 0.9 for PM2.5. 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 PM10 and 0.9 for PM2.5, whereas those for nonlinear regressions were 0.7 for PM10 and 0.9 for PM2.5. The higher correlation coefficient for PM10 by the nonlinear regression indicates that it is the better method for calibrating the system developed in this study VL - 1 IS - 1 ER -
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