微量金属元素投加量优化组合对污泥发酵产乙酸的影响

污泥厌氧发酵生产乙酸是实现污泥减量化和资源化的有效途径. 为了提高污泥中的ρ(乙酸),分别考察了Fe2+、Co2+、Cu2+、Zn2+和Mn2+5种微量金属元素的投加影响. 结果表明,5种微量元素都可以促进污泥中乙酸的产生,作用大小依次为Co2+>Mn2+>Fe2+> Zn2+>Cu2+. 但当Fe2+、Co2+、Cu2+、Zn2+和Mn2+投加量(以w计)分别超过0.100 0%、0.006 0%、0.002 0%、0.004 0%和0.100 0%时,ρ(乙酸)却明显下降. 分别选取Fe2+(0.040 0%~0.150 0%)、Co2+(0.002 0%~0.008 0%)、Cu2+(0.000 5%~0.006 0%)、Zn2+(0.000 5%~0.010 0%)和Mn2+(0.040 0%~0.150 0%)进行响应面条件优化试验. 在Fe2+、Mn2+投加量均为0.090 0%,Co2+、Zn2+投加量均为0.005 0%,Cu2+投加量为0.003 5%的组合优化条件下,ρ(乙酸)高达3 452 mg/L,比优化前提高了61.80%. 最优的微量元素投量组合条件下获得的试验结果与二次响应面回归模型预测值(3 475 mg/L)拟合率高达99.34%,表明所建立的回归模型可行. 

Optimizing Doses of Trace Metal Elements for Production of Acetic Acid from Excess Sludge Using Response Surface

Abstract:Converting excess sludge to acetic acid is considered a promising and feasible path. This process not only achieves the objectives of controlling pollution and reducing sludge volumes, but also efficiently explores the resource of organic substances in sludge. Anaerobic microorganisms involved in the fermentation of acetic acid have inherent requirements for trace metal elements, but this is not often reported in literature. The effects of Fe²⁺, Co²⁺, Cu²⁺, Zn²⁺ and Mn²⁺ on the production of acetic acid were investigated in this study. The experimental results showed that these metal elements had the potential to enhance the production of acetic acid, with the influence as follows:Co²⁺>Mn²⁺>Fe²⁺>Zn²⁺>Cu²⁺. However, the production of acetic acid decreased obviously while the mass fractions of Fe²⁺, Co²⁺, Cu²⁺, Zn²⁺ and Mn²⁺ were more than 0.1000%, 0.0060%, 0.0020%, 0.0040% and 0.1000%, respectively. Response surface was then employed to optimize the mixing doses of various metal elements for acetic acid production in the case that the mass ranges were set as 0.0400%-0.1500%(Fe²⁺), 0.0020%-0.0080%(Co²⁺), 0.0005%-0.0060%(Cu²⁺), 0.0005%-0.0100% (Zn²⁺) and 0.0400%-0.1500%(Mn²⁺). The optimal mixing conditions were 0.0900% of Fe²⁺, 0.0900% of Mn²⁺, 0.0050% of Co²⁺, 0.0050% of Zn²⁺ and 0.0035% of Cu²⁺. Under these conditions, the concentration of acetic acid increased by 61.8% and reached up to 3452 mg/L. Moreover, the result of fitting between the model prediction (3475 mg/L) and the experiment under the optimal conditions came up to 99.34%, which indicated that the established polynomial regression model was feasible.