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    Improved Passive Treatment of High Zn and Mn Concentrations Using Caustic Magnesia (MgO): Particle Size Effects

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    High concentrations of divalent metals such as Zn, Mn, Cu, Pb, Ni, Cd, Co, etc. are not removed satisfactorily in conventional (calcite- or organic matter-based) passive treatment systems. Caustic magnesia (“MgO”) has been used successfully as an alternative alkaline material to remove these metals almost completely from water, but columns with coarse-grained MgO lost reactivity or permeability due to the accumulation of precipitates when only a small portion of the reagent had been spent. In the present study, MgO was mixed with wood chips to overcome these problems. Two columns with different MgO grain sizes were used to treat Zn- and Mn-rich water during one year. Performance was compared by measuring depth profiles of chemical parameters and hydraulic conductivity. The column containing 25% (v/v) of MgO with median particle size of about 3 mm displayed low reactivity and poor metal retention. In contrast, the column containing only 12.5% (v/v) of MgO with median particle size of 0.15 mm depleted Zn and Mn below detection limit throughout the study and had a good hydraulic performance. 95% of the applied MgO was consumed in the zone where Zn and Mn accumulated. The fine alkaline grains can dissolve almost completely before the growing layer of precipitates passivates them, whereas clogging is prevented by the large pores of the coarse inert matrix (wood chips). A reactive transport model corroborated the hypotheses that Zn(II) was removed due to its low solubility at pH near 10 achieved by MgO dissolution, whereas Mn(II) was removed due to rapid oxidation to Mn(III) at this pH and subsequent precipitation. The model also confirmed that the small size and large specific surface area of the MgO particles are the key factor to achieve a sufficiently fast dissolution.This study was funded by the Spanish Government projects REN-2003-09590-C04-02, CTM2006-28151-E/TECNO and CTM2007-66724-C02-01.Peer reviewe
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