本研究探討砷在兩種砷處理介質中之吸附平衡、動力及管柱傳輸行為。研究中採用一商業化之粒狀氫氧化鐵(Bayoxide E33)及一陰離子交換樹脂(Arsenex)來進行吸附砷之試驗。實驗包括吸附動力與平衡、背景電解質與管柱試驗等，並以孔隙擴散模式(Pore Diffusion Model)來模擬吸附動力，以瞭解砷之吸附特性。
研究結果顯示，以多孔性的氫氧化鐵所構成的E33，其主要晶相的鑑定為α-FeOOH(Goethite)，吸附五價砷平衡所需的時間需7小時，在中性pH的條件下，初始濃度為10mg/L時吸附量可達31mg/g，而在初始濃度2.6mg/L時吸附量為15.3mg/g，此平衡吸附的結果與管柱試驗有相同的結果；而pH值越小情況下，對於五價砷吸附量越高。若加入背景電解質NaNO3，E33對砷的去除率隨著離子強度的增高而降低。
　　在Arsenex方面，其主要元素為N、C、H、Cl，且根據FTIR的鍵結圖譜可以推測其為作用基為胺基，吸附五價砷動力平衡所需的時間需4小時左右，在中性pH的條件下，初始濃度為10mg/L時吸附量可達16mg/g，若加入背景電解質NaNO3，砷的去除率亦隨著離子強度的增高而降低。且另以CO2為干擾物質進行曝氣與無曝氣的試驗，以測定總無機碳來得知溶液中所含的CO2的量，結果發現系統在曝氣的狀態下，pH=7.5時CO2的量降低了2mg/L，且吸附量提高至39mg/g，與無曝氣的狀態比較約提升2.3倍，明顯的在pH越高時，受CO2的影響也越大。
　　模式方面利用孔隙擴散模式去模擬吸附劑吸附砷之吸附動力，並利用兩種等溫吸附模式(Freundlich 及 Langmuir Isotherm)所求得之參數，來推估最佳化的孔隙擴散係數。模擬E33在中性pH值吸附動力時，所得到最佳化的孔隙擴散係數(Dp)為4.0×10-10 m2/sec，其曲折度(tourosity,τ)為2.5，並可以有效預測不同砷濃度下之吸附行為。該模式也可以模擬砷在Arsenex中之吸附動力行為，所得到的最佳化的孔隙擴散係數(Dp)為5.0×10-9 m2/sec。最佳化之DP值用於預測不同砷濃度及不同曝氣條件下，也均能有效描述砷在Arsenex中之吸附動力行為，顯示該模式之應用性。

　　Arsenic is commonly present in many ground water sources around the world. To remove arsenic from groundwater, several advanced techniques, including adsorption and ion exchange, are often employed in drinking water treatment processes. In this study, the transport and adsorption of arsenate within one ferric hydroxide based adsorbent (E33 from Bayer) and one ion exchange resin (Arsenex from Pyrolite) is elucidated.
　　Several instruments were employed for the surface analysis of the two media, including x-ray diffraction, scanning electron microscopy, x-ray fluorescence, and Fourier transformed infra-red spectrometer. Surface analysis of E33 indicated that the medium is porous and is mainly composed of goethite. For Arsenex, the major elements are nitrogen, chlorine, hydrogen, and carbon, and the major exchange function group is amide group.
　　A batch reactor with temperature was used to determine the adsorption kinetics and capacity of arsenic onto the two media. The experimental results revealed that the adsorption equilibrium was established within 7 hours for E33 and 4 hours for Arsenex. The uptake of arsenate decreased as pH increased for E33, since the surface charge of E33 becomes more negative at higher pH. 　　However, the arsenate uptake increased as pH increased due to the fact that more di-valent arsenate ions were produced at higher pH. After fitting the arsenate uptake data, both the Freundlich and Langmuir isotherm equations may be used to describe the experimental uptake data for both media.
　　A pore diffusion model, combined with the isotherm parameters, was used to simulate the adsorption kinetic data. In fitting the models to the experimental data, only one parameter, pore diffusivity (Dp), is adjusted. The models conform closely to the experimental data, and the extracted pore diffusion coefficient of arsenate was 4.0×10-10 m2/sec for E33 and 5.0×10-9 for Arsenex. The model with the extracted diffusion coefficients was able to predict the kinetic adsorption curves for other experimental conditions, indicating that the model is appropriate for the systems tested in this study. The extracted diffusivities are found different from those in two other metal oxide/arsenate systems reported earlier. This may be attributed to the different porosity observed for the four adsorbents.

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