Indoor Air Quality Diagnostic Expert System for optimal improvement measures

碩士 === 國立臺北科技大學 === 環境工程與管理研究所 === 101 === The Taiwan government enacted the Indoor Air Quality Management Act (IAQMA) in the year 2011. This Act defines indoor air pollutants and indoor air quality standards. There are many factors which affect indoor air quality like ventilation, decorating materi...

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Bibliographic Details
Main Authors: Shau-Yuan Liu, 劉紹淵
Other Authors: 曾昭衡
Format: Others
Language:zh-TW
Published: 2013
Online Access:http://ndltd.ncl.edu.tw/handle/r77ga9
Description
Summary:碩士 === 國立臺北科技大學 === 環境工程與管理研究所 === 101 === The Taiwan government enacted the Indoor Air Quality Management Act (IAQMA) in the year 2011. This Act defines indoor air pollutants and indoor air quality standards. There are many factors which affect indoor air quality like ventilation, decorating materials, human inhalation, office utensil etc. and this makes the best combination of improvement measures unique to a specific place. The goal in this study was to design an assessment model which could assess the contribution of different improvement measures in real site. This optimal improvement measures assessment model was based on a receptor model and combined with a mass balance model. The mass balance model was used to establish the characteristic factors at the experimental site. Finally, the results of the improvement experiment verified the feasibility of this assessment model. The improvement measures in this study included a total heat exchanger and two air cleaners. The total heat exchanger could increase 48.7 m3/hr of ventilation (VE). One air cleaner had an HEPA filter (HE) and an active carbon filter (AC) installed. The other air cleaner had a ZnO photo catalyst filter (PC) installed. The results of the first group of experiments showed that the contributions of HE were: 10.0%~84.8%, AC: 14.7%~89.4% and PC: 0.5%~0.6%. The results of the second group of experiments showed that the contributions of VE were: 55.9%~79.1%, HE: 20.9%~43.4%, AC: 0.0%~0.0%, PC: 0.0%~0.7%.