IJESD 2017 Vol.8(9): 626-629 ISSN: 2010-0264
doi: 10.18178/ijesd.2017.8.9.1028
doi: 10.18178/ijesd.2017.8.9.1028
Identify the Odor Emission Sources in an Industrial Park by Integrated Data Mining Approach
Yu-Shiuan Cheng, Ho-Wen Chen, and Yen-Hisun Chuang
Abstract—Odorous gases are the most significant pollution
that resident argue about living in the surroundings nearby
industrial park. Sustainable ammonia emission is a common
odor sources in industrial areas. Odor often impacts to human
sensations and upper airway irritation, principally because
most volatile chemicals have the potential to activate temporary
burning, stinging, tingling or painful sensations in the eyes.
However, in the case of such multi-source odour emissions
especially industrial park, common chemical analyses or odour
concentration measurement methods are not often applicable.
Although several studies have been conducted for prevention
and control of odorous gases, no comprehensive research exists
about recent achievements in this area. Expected to Tainan
Science Park as a research area, using different kind of
historical data collection with possible odor emissions from
industrial park, and apply the Gaussian diffusion model to
simulate contamination of receptor. Following by Gaussian
diffusion model steps, connect with linear programming
method and also estimate pollution contribution. Then find out
the sources of pollution so that the future government utilize
cases for this petition as valid reference.
Index Terms—Odor, Southern Taiwan Science Park, Gaussian diffusion model, linear program.
The authors are with Tunghai University, Taiwan (e-mail: sunny84053078@gmail.com, hwchen@thu.edu.tw, wychen@thu.edu.tw).
Index Terms—Odor, Southern Taiwan Science Park, Gaussian diffusion model, linear program.
The authors are with Tunghai University, Taiwan (e-mail: sunny84053078@gmail.com, hwchen@thu.edu.tw, wychen@thu.edu.tw).
Cite: Yu-Shiuan Cheng, Ho-Wen Chen, and Yen-Hisun Chuang, "Identify the Odor Emission Sources in an Industrial Park by Integrated Data Mining Approach," International Journal of Environmental Science and Development vol. 8, no. 9, pp. 626-629, 2017.
General Information
- ISSN: 2010-0264 (Print); 2972-3698 (Online)
- Abbreviated Title: Int. J. Environ. Sci. Dev.
- Frequency: Bimonthly
- DOI: 10.18178/IJESD
- Editor-in-Chief: Prof. Richard Haynes
- Managing Editor: Ms. Cherry L. Chen
- Indexing: Scopus (CiteScore 2022: 1.4), Google Scholar, CNKI, ProQuest, EBSCO, etc.
- E-mail: ijesd@ejournal.net
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