Variation and prediction of assimilable organic matters in a water treatment process and the distribution system

碩士 === 國立中山大學 === 環境工程研究所 === 98 === The growth of the heterotrophic plate count in distribution system, causing deterioration of drinking water quality, is called biological re-growth or after-growth. There are many methods to solve above problems such as disinfecting and washing in pipeline. Among...

Full description

Bibliographic Details
Main Authors: Po-feng Chen, 陳渤丰
Other Authors: Jie-Chung Lou
Format: Others
Language:zh-TW
Published: 2010
Online Access:http://ndltd.ncl.edu.tw/handle/19139377896238664797
Description
Summary:碩士 === 國立中山大學 === 環境工程研究所 === 98 === The growth of the heterotrophic plate count in distribution system, causing deterioration of drinking water quality, is called biological re-growth or after-growth. There are many methods to solve above problems such as disinfecting and washing in pipeline. Among them, to lower the concentration of assimilable organic carbon(AOC) in drinking water under a certain level is showed the best control method for inhibiting the growth of microorganisms. AOC is showed as an item of the organic amounts by using microorganisms. The samples of water after disinfecting is took into bacterial of P17 and NOX. Then we measure the growth number counts of two kind of bacterial in their plate to transfer and obtain the concentration of AOC. In this study we investigate the variation of AOC in a tradition water treatment plant and its distribution system by using the results of sampling and analysis of the related items of water quality. Results showed the proportional of AOC-P17 was highest in contains of AOC. The removal of AOC during processes of water treatment was effectively found. But the pre-chlorination caused the increase of AOC level in water let the concentration of AOC be detected over 50μg acetate-C/L in treated water and the distribution system. AOC level decreased with the increasing distance of distribution system. For the well relation with drinking water quality and treatment units, we should control the biological stability to obtain a good water quality of treated water. Finally we analysis 13 items of water quality by using AutoNet(6.03) with AOC to do the prediction model work. After data simulation and training analysis, three models of AOC prediction (denoted as WTP, Distribution system and WTP& Distribution system) were obtained. The comparisons of three models in inner and outer verification showed good correlation results as well.