Influence of Sensor Location on Indoor Air Pollution Source Identification Results
Publication: Journal of Environmental Engineering
Volume 145, Issue 11
Abstract
Sudden gaseous contaminants are usually highly unpredictable and even very toxic. If unable to be responded to in time, they will seriously endanger the safety of occupants. In order to realize quick source identification based on very limited sensors, two indexes were established according to a combination of the traditional optimization method and probability method. The identification process consisted of two stages. In the pretreatment stage, computational fluid dynamics (CFD) was taken to simulate the contaminant release processes from 16 control-body centers and 16 actual sources, and the concentration information from three sensors, , , and , was collected for later calculation. Then, in the source identification process, the identification index was solved based on the concentration information. The identification results show that when a single sensor is used for identification, the accuracy is greatly affected by the sensor position. When using dual-sensor combinations instead, the average accuracy rate can be increased by 13.5%. Dual-sensor combination scenarios can greatly improve accuracy and effectively eliminate the influence of sensor location.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This research was supported by Shenyang Young and Middle-Aged Science and Technology Innovation Talents Program (RC170313), Liaoning Provincial Natural Foundation (20170540761), Liaoning Baiqianwan Talents Program, and Liaoning Innovative Talents program.
References
Alifanov, O. 1994. Inverse heat transfer problems. New York: Springer.
Ao, L., Y. Wang, H. Guo, L. Bo, S. Zhang, and Y. Bai. 2015. “Assessment of pollution and identification of sources of heavy metals in the sediments of Changshou Lake in a branch of the Three Gorges Reservoir.” Environ. Sci. Pollut. Res. 22 (20): 16067–16076. https://doi.org/10.1007/s11356-015-4825-8.
Atmadja, J., and A. Bagtzoglou. 2001. “State of the art report on mathematical methods for ground water pollution source identification.” Environ. Forensics 2 (3): 205–214. https://doi.org/10.1006/enfo.2001.0055.
Bastani, A., F. Haghighat, and J. Kozinski. 2012. “Contaminant source identification within a Building: Toward design of immune buildings.” Build. Environ. 51 (5): 320–329. https://doi.org/10.1016/j.buildenv.2011.12.002.
Cai, H. 2006. Study on key issues of emergency ventilation to control indoor contaminant dispersion. [In Chinese.] Shanghai, China: Tongji Univ.
Cai, H., and X. Li. 2014. “Rapid identification of multiple constantly-released contaminant sources in indoor environments with unknown release time.” Build. Environ. 81 (7): 7–19. https://doi.org/10.1016/j.buildenv.2014.06.006.
Fang, W. 2015. Leakage detection and fault analysis of multi-sources looped pipe network based on GIS. [In Chinese.] Taiyuan, China: Taiyuan Univ. of Technology.
Gholampour, A., R. Nabizadeh, M. S. Hassanvand, H. Taghipour, M. Rafee, Z. Alizadeh, S. Faridi, and A. H. Mahvi. 2016. “Characterization and source identification of trace elements in airborne particulates at urban and suburban atmospheres of Tabriz, Iran.” Environ. Sci. Pollut. Res. 23 (2): 1703–1713. https://doi.org/10.1007/s11356-015-5413-7.
Han, K. H., J. S. Zhang, H. N. Knudsen, P. Wargocki, H. Chen, P. K. Varshney, and B. Guo. 2011. “Development of a novel methodology for indoor emission source identification.” Atmos. Environ. 45 (18): 3034–3045. https://doi.org/10.1016/j.atmosenv.2011.03.021.
Huang, S. 2012. IHCP for searching heat source based on ant colony algorithm. [In Chinese.] Shanghai, China: Univ. of Shanghai for Science and Technology.
Jiang, S., Y. Zhang, Y. Cai, and M. Zheng. 2013. “Groundwater contaminant identification by hybrid simplex method of simulated annealing.” J. Tongji Univ. 41 (2): 253–257. https://doi.org/10.3969/j.issn.0253-374x.2013.02.017.
Levy, A., S. Gannot, and E. A. P. Habets. 2011. “Multiple-hypothesis extended particle filter for acoustic source localization in reverberant environments.” IEEE Trans. Audio Speech Language Process. 19 (6): 1540–1555. https://doi.org/10.1109/TASL.2010.2093517.
Li, X., and B. Zhao. 2004. “Accessibility: A new concept to evaluate ventilation performance in a finite period of time.” Indoor Built Environ. 13 (4): 287–293. https://doi.org/10.1177/1420326X04045440.
Liu, X., and Z. Zhai. 2007. “Inverse modeling methods for indoor airborne contaminant tracking: Literature review and fundamentals.” Indoor Air 17 (6): 419–438. https://doi.org/10.1111/j.1600-0668.2007.00497.x.
Liu, X., and Z. Zhai. 2008. “Location identification for indoor instantaneous point contaminant source by probability-based inverse computational fluid dynamics modeling.” Indoor Air 18 (1): 2–11. https://doi.org/10.1111/j.1600-0668.2007.00499.x.
Liu, X., and Z. Zhai. 2009. “Prompt tracking of indoor airborne contaminant source location with probability-based inverse multi-zone modeling.” Build. Environ. 44 (6): 1135–1143. https://doi.org/10.1016/j.buildenv.2008.08.004.
Lovino, P., S. Salvestrini, and S. Capasso. 2008. “Identification of stationary sources of air contaminants by concentration statistical analysis.” Chemosphere 73 (4): 614–618.
Ma, L., Z. Yang, L. Li, and L. Wang. 2016. “Source identification and risk assessment of heavy metal contaminations in urban soils of Changsha, a mine-impacted city in Southern China.” Environ. Sci. Pollut. Res. 23 (17): 17058–17066. https://doi.org/10.1007/s11356-016-6890-z.
Mu, X. 2014. Numerical simulation of contaminants transport in an aircraft cabin. [In Chinese.] Nanjing, China: Nanjing Univ. of Science and Technology.
Pang, L., H. Qu, T. Hu, and J. Wang. 2012. “Prediction and identification of sudden pollution source.” [In Chinese.] Chin. J. Ship Res. 7 (3): 64–67. https://doi.org/10.3969/j.issn.1673-3185.2012.03.012.
Skaggs, T., and Z. Kabala. 1995. “Recovering the history of a ground water contaminant plume: Method of quasi-reversibility.” Water Resour. Res. 31 (11): 2669–2673. https://doi.org/10.1029/95WR02383.
Sohn, M., P. Reynolds, N. Singh, and A. Gadgil. 2002. “Rapidly locating and characterizing pollutant releases in buildings.” J. Air Waste Manage. Assoc. 52 (12): 1422–1432. https://doi.org/10.1080/10473289.2002.10470869.
Sreedharan, P., M. Sohn, A. Gadgil, and W. Nazaroff. 2006. “Systems approach to evaluating sensor characteristics for real-time monitoring of high-risk indoor contaminant releases.” Atmos. Environ. 40 (19): 3490–3502. https://doi.org/10.1016/j.atmosenv.2006.01.052.
Tikhonov, A., V. Arsenin, and F. St John. 1977. Solutions of ill-posed problems. Washington, DC: Halsted Press.
Vukovic, V., P. C. Tabares-Velasco, and J. Srebric. 2010. “Real-time identification of indoor contaminant source positions based on neural network locator of contaminant sources and optimized sensor networks.” J. Air Waste Manage. Assoc. 60 (9): 1034–1048. https://doi.org/10.3155/1047-3289.60.9.1034.
Wang, R. 2011. Research on pollution identification technology in limited space. [In Chinese.] Beijing: North China Univ. of Technology.
Wei, C., and L. Pang. 2013. “Accidental continued contaminant identification study in three-dimensional enclosed space by a single sensor.” [In Chinese.] J. Astronautics 34 (8): 1172–1176. https://doi.org/10.3873/j.issn.1000-1328.2013.08.020.
Yang, J., X. Li, and B. Zhao. 2004. “Prediction of transient contaminant dispersion and ventilation performance using the concept of accessibility.” Energy Build. 36 (3): 293–299. https://doi.org/10.1016/j.enbuild.2003.12.002.
Yin, S. 2011. Quantitatively identify unsteady gas contaminant releases in indoor environment by inverse CFD modeling. [In Chinese.]. Dalian, China: Dalian Univ. of Technology.
Zhang, J., C. Jiang, Z. Wang, X. Jia, and J. Yuan. 2010. “PSO algorithm for back-calculation of source intensity.” China Saf. Sci. J. 20 (10): 123–128. https://doi.org/10.3724/SP.J.1142.2010.40486.
Zhang, T., and Q. Chen. 2007. “Identification of contaminant sources in enclosed spaces by a single sensor.” Indoor Air 17 (6): 439–449. https://doi.org/10.1111/j.1600-0668.2007.00489.
Zhang, T., H. Li, and S. Wang. 2012. “Inversely tracking indoor airborne particles to locate their release sources.” Atmos. Environ. 55 (3): 328–338. https://doi.org/10.1016/j.atmosenv.2012.03.066.
Information & Authors
Information
Published In
Copyright
©2019 American Society of Civil Engineers.
History
Received: Jul 23, 2018
Accepted: Mar 5, 2019
Published online: Sep 14, 2019
Published in print: Nov 1, 2019
Discussion open until: Feb 14, 2020
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.