オゾン処理による飲料水中微量汚染物質除去の経験的モデリング

This study presents an empirical modeling approach to estimate the abatement of ozone-resistant micropollutants in a pilot-scale ozonation system. The model specifically addresses the unique challenge of these compounds by treating the two distinct phases of ozone decomposition separately. The initial rapid ozone decomposition generates a high concentration of hydroxyl radicals (^•OH), which play a dominant role in micropollutant removal. Due to challenges in measuring ^•OH exposure in this phase, this study proposes an empirical model to predict hydroxyl radical exposure (HT) based on water quality parameters and ozone dosage. In the second phase, micropollutant abatement is modeled based on ozone exposure and the ratio of hydroxyl radical exposure over ozone exposure (R _ct). The combined contributions of both phases provide the total abatement efficiency. Key water quality and operational variables are statistically screened and integrated into multivariate regression models to estimate initial ozone demand (IOD), ozone decay rate (k), HT, and R _ct. Chlorobenzene, an ozone-resistant compound and common concern in water treatment utilities, serves as a probe compound for model establishment and validation. The modeling results demonstrate strong predictive accuracy (R ² = 0.89).