Journal of the Korean GEO-environmental Society (한국지반환경공학회 논문집)

Korean Geo-Environmental Society (한국지반환경공학회)
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The Study of Statistical Optimization of MTBE Removal by Photolysis(UV/H2O2)

광분해반응을 통한 MTBE 제거에 대한 통계적 최적화 연구

  • 천석영 (경기대학교 환경에너지시스템공학과) ;
  • 장순웅 (경기대학교 환경에너지시스템공학과)
  • Received : 2011.06.24
  • Accepted : 2011.07.25
  • Published : 2011.09.01
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Abstract

This study investigate the use of ultraviolet(UV) light with hydrogen peroxide($H_2O_2$) for Methyl Tert Butyl Ether(MTBE) degradation in photolysis reactor. The process in general demands the generation of OH radicals in solution at the presence of UV light. These radicals can then attack the MTBE molecule and it is finally destroyed or converted into a simple harmless compound. The MTBE removal by photolysis were mathematically described as the independent variables such as irradiation intensity, initial concentration of MTBE and $H_2O_2$/MTBE ratio, and these were modeled by the use of response surface methodology(RSM). These experiments were carried out as a Box-Behnken Design(BBD) consisting of 15 experiments. Regression analysis term of Analysis of Variance(ANOVA) shows significantly p-value(p<0.05) and high coefficients for determination values($R^2$=94.60%) that allow satisfactory prediction of second-order regression model. And Canonical analysis yields the stationery point for response, with the estimate ridge of maximum responses and optimal conditions for Y(MTBE removal efficiency, %) are $x_1$=25.75 W of irradiation intensity, $x_2$=7.69 mg/L of MTBE concentration and $x_3$=11.04 of $H_2O_2$/MTBE molecular ratio, respectively. This study clearly shows that RSM is available tool for optimizing the operating conditions to maximize MTBE removal.

본 연구는 UV와 $H_2O_2$를 통한 광분해 반응기에서의 Methyl Tert Butyl Ether(MTBE) 제거에 대해 조사하였다. 이 공정은 일반적으로 UV의 존재 하에 수용액 상에 생성되는 OH 라디칼을 요구하며, 이 라디칼들은 MTBE 분자를 공격하여 최종적으로 파괴하거나 무해한 단순 화합물로 전환시킨다. 반응들은 조사강도, MTBE 초기농도와 $H_2O_2$/MTBE비의 독립변수를 수학적으로 표현하였고, 반응표면법(Response Surface Methodology; RSM)을 사용하여 모델화하였다. 이 실험들은 Box-Behnken Design(BBD)를 통한 15개의 실험을 포함하여 실시하였다. ANOVA의 회귀분석 항은 유의한 p-value(p<0.05)와 높은 결정계수($R^2$=94.60%)를 나타내어 2차 회귀모델의 예측이 적절한 것으로 나타났다. 그리고 반응에 대한 정준분석을 통해 예측된 Y에 대한 최적 반응과 최대반응의 예측된 능선을 통해 최적조건은 각각 조사강도인 $x_1$=25.75W, MTBE 초기농도의 $x_2$=7.69mg/L 와 $H_2O_2$/MTBE비인 $x_3$=11.04로 관찰되었다. 본 연구는 RSM이 MTBE 제거의 최대화와 운전조건의 최적화에 적용하기에 알맞은 것으로 나타났다.

Keywords

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