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染料废水由于具有高色度、高毒性、难降解性和易于在生物体内积累等特点引起人们高度重视[1],成为目前最难处理的工业废水之一。其中刚果红(congo red,CR)作为一种典型的联苯胺类直接偶氮染料,易溶于水,在生产和使用过程中流失率高,是染料废水中具有代表性的一种污染物[2],对人体和周围环境具有极大威胁,严重时可致癌、致畸、致突变,从而引起人们的广泛关注。近年来,常用的染料废水处理方法有化学氧化、生物降解、吸附、光催化等[3-6]。其中,吸附法由于效率高、设备简单、操作安全、可废物资源化等优点而受到普遍认可。常规吸附材料有活性炭、沸石、生物炭、有机膨润土和金属氧化物[7-11],虽然具有来源广泛、化学性能稳定等优点,但其成本高、产生二次污染等缺点也不容忽视。因此,选择价格低廉、吸附效果好、化学性能稳定的材料用于染料废水的处理备受关注。
市政污泥资源化问题是近期研究的热点,目前以污泥热解制取富氢燃气方向为主[12-13]。而污泥热解气化过程中的剩余半焦也是一种极具应用价值的吸附材料。相关研究[14-15]表明,其主要成分为固定碳,具有发达的孔隙结构和良好的表面特性,在吸附工业染料方面具有较好的应用前景[16-18]。李晋[19]的研究表明,以污泥焦炭为添加剂进行污泥热解制取剩余半焦,更有助于提高剩余半焦的比表面积。本研究以污泥焦炭为添加剂经机械化学预处理快速热解制备的半焦为吸附材料,以CR溶液模拟染料废水进行吸附实验。在制取高品质富氢燃气的同时,污泥热解剩余半焦可代替活性炭等传统吸附材料用于CR类染料废水的去除,可最大限度实现市政污泥资源化,具有“以废治废”的实践意义。
响应曲面法(response surface methodology, RSM)是一种能够优化工艺参数、减少实验次数以及评价各影响因素之间水平及交互作用的有效方法[20]。本研究采用响应曲面法中的Box-Behnken实验设计原理,探究了吸附剂投加量、CR初始浓度、温度及pH共4个影响因素对剩余半焦吸附CR的水平的影响及其之间的交互作用;同时通过比表面积及孔径分析、傅里叶变换红外光谱、X射线衍射等分析方法对剩余半焦进行了表征,分析了其吸附CR的机理,为污泥热解剩余半焦的利用探索新途径,为染料废水处理研究提供参考。
响应曲面法对污泥热解剩余半焦吸附水中刚果红的优化
Optimization of congo red adsorption in water by semicoke residuals from sludge pyrolysis based on response surface methodology
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摘要: 为了实现市政脱水污泥的资源化,以污泥快速热解制备富氢燃气剩余半焦作为吸附材料,对刚果红(CR)模拟染料废水进行了吸附研究。采用响应曲面法的Box-Behnken实验设计原理探究了吸附剂投加量、CR初始浓度、温度和溶液pH对CR去除率的影响,并分析了剩余半焦对CR的吸附机理。结果表明:各因素对CR去除率的影响顺序为吸附剂投加量>CR初始浓度>溶液pH>温度;最佳吸附条件下CR的去除率为98.97%,与预测值(99.61%)基本吻合;由交互作用响应曲面分析结果得出,适当的增加吸附剂投加量,降低CR初始浓度和溶液pH均有助于提高CR的去除率;污泥热解剩余半焦的XRD和FT-IR表征结果显示,其主要成分为含硅无机物,BET结果显示孔隙结构发达,可提供较多的吸附位点;吸附CR后,没有新的官能团产生,表明剩余半焦对CR的吸附主要为物理吸附。Abstract: As for the resource utilization of municipal sewage sludge, the semicoke residuals from sludge rapid pyrolysis for hydrogen-rich gas production was used to absorb the Congo red (CR) simulated dye wastewater. Box-Behnken design of response surface methodology was used to explore the effects of adsorbent dosage, initial concentration of CR, temperature and pH on CR removal rate. Furthermore, the CR adsorption mechanism by the semicoke residuals was analyzed. The results showed that the effect order of above factors on CR removal rate was following: the dosage of adsorbent > CR initial concentration > pH > temperature; the CR removal rate under the optimal adsorption conditions reached 98.97%, which was basically consistent with the predicted value of 99.61%. Through the analysis of the response surface interactions, increasing the amount of adsorbent to a certain extent, reducing the initial concentration of CR and the pH could improve the CR removal rate. The characterization results of XRD and FT-IR showed that the main components of semicoke residuals were silicon-containing inorganics, BET results demonstrated that the semicoke residuals had developed pore structure and provided many adsorption sites. No new functional groups were found after CR adsorption, which indicating that physical adsorption dominated CR adsorption on semicoke residuals.
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表 1 刚果红吸附体系各实验因素水平取值
Table 1. Level of experimental factors in the congo red adsorption system
各水平
编码取值吸附剂
投加量/(g·L−1)CR初始
浓度/(mg·L−1)温度/℃ pH −1 1.6 80 25 2 0 2 100 30 4 1 2.4 120 35 6 表 2 实验设计与结果
Table 2. Experimental design and results
编号 各编码水平 去除率/% (A)吸附剂
投加量/(g·L−1)(B)CR初始
浓度/(mg·L−1)(C)温度/℃ (D) pH 实验值 预测值 1 1.6 80 30 4 95.12 92.51 2 2.4 80 30 4 99.26 97.36 3 1.6 120 30 4 63.90 64.34 4 2.4 120 30 4 96.15 97.29 5 2 100 25 2 99.61 99.53 6 2 100 35 2 99.52 100.00 7 2 100 25 6 90.29 88.06 8 2 100 35 6 91.39 90.00 9 1.6 100 30 2 89.80 89.21 10 2.4 100 30 2 99.57 100.00 11 1.6 100 30 6 71.82 70.73 12 2.4 100 30 6 96.81 97.24 13 2 80 25 4 99.29 99.84 14 2 120 25 4 85.56 84.66 15 2 80 35 4 99.40 100.00 16 2 120 35 4 87.79 87.07 17 1.6 100 25 4 75.95 78.39 18 2.4 100 25 4 98.57 98.78 19 1.6 100 35 4 79.80 81.23 20 2.4 100 35 4 99.45 98.64 21 2 80 30 2 99.55 99.85 22 2 120 30 2 98.48 97.19 23 2 80 30 6 97.50 100.00 24 2 120 30 6 73.51 74.86 25 2 100 30 4 97.75 95.87 26 2 100 30 4 95.24 95.87 27 2 100 30 4 95.35 95.87 28 2 100 30 4 95.67 95.87 29 2 100 30 4 95.33 95.87 表 3 CR去除率的方差分析结果
Table 3. ANOVA of CR removal efficiency
方差来源 平方和 自由度 均方 F P 显著性 模型 2 652.36 14 189.45 53.55 <0.000 1 显著 A 1 071.94 1 1 071.94 303.00 <0.000 1 显著 B 598.15 1 598.15 169.08 <0.000 1 显著 C 5.44 1 5.44 1.54 0.235 4 D 354.47 1 354.47 100.19 <0.000 1 显著 AB 197.47 1 197.47 55.82 <0.000 1 显著 AC 2.22 1 2.22 0.63 0.442 0 AD 57.93 1 57.93 16.38 0.001 2 显著 BC 1.12 1 1.12 0.32 0.582 5 BD 131.34 1 131.34 37.12 <0.000 1 显著 CD 0.36 1 0.36 0.10 0.755 6 A2 220.30 1 220.30 62.27 <0.000 1 显著 B2 30.37 1 30.37 8.58 0.011 0 显著 C2 3.93 1 3.93 1.11 0.309 6 D2 2.52 1 2.52 0.71 0.413 3 残差 49.53 14 3.54 失拟性 44.98 10 4.50 3.95 0.098 7 不显著 净误差 4.55 4 1.14 总离差 2 701.89 28 注:判定系数R2=0.981 7,校正判定系数 $R_{{\rm{Adj}}}^2 = 0.963\;3$ 。 -
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