环境工艺方法论研究——资源扩容法

资源扩容法是探索新型环境工程工艺的重要方法,其核心思想是认为世界上不存在绝对的废弃物,只有放错位置的资源。本文通过对资源扩容法理论及其应用实例的详细论述,揭示了资源扩容法所蕴涵的哲学理论。     

响应面法和神经网络优化Acinetobacter sp. DNS32发酵基质

为了提高阿特拉津降解菌Acinetobacter sp.DNS32的产量,分别采用响应曲面法和基于人工神经网络的遗传算法对阿特拉津降解菌DNS32发酵培养基中3个重要基质成分(玉米粉、豆饼粉、K2HPO4)进行优化研究。响应曲面法确定3种成分的含量为玉米粉39.494 g/L,豆饼粉25.638 g/L和K2HPO43.265 g/L时,预测发酵活菌最大生物量为7.079×108CFU/mL,实测量为7.194×108CFU/mL;人工神经网络结合遗传算法优化确定3种主要成分含量为玉米粉为39.650 g/L,豆饼粉为25.500 g/L,K2HPO4为2.624 g/L时,预测最大值为7.199×108CFU/mL,实测量为7.244×108CFU/mL;最终确定培养基配方:玉米粉为39.650 g/L,豆饼粉为25.500 g/L,K2HPO4为2.624 g/L,CaCO3为3.000 g/L,MgSO4.7H2O和NaCl均为0.200 g/L;优化后阿特拉津降解菌DNS32发酵生物量比优化前提高了36.6%。结果表明,在阿特拉津降解菌DNS32发酵培养基组分优化方面,响应面法和基于人工神经网络的遗传算法都是可行的,基于人工神经网络的遗传算法具有更好的拟合度和预测准确度。     

响应面法优化聚丙烯酸/腐殖酸/累托石吸附剂的制备条件

以累托石、丙烯酸及腐殖酸为原料制备出能同时吸附重金属和多环芳烃的吸附剂聚丙烯酸/腐殖酸/累托石,采用响应面试验设计法优化吸附剂的制备条件。利用Design Expert软件,建立了预测吸附剂对Cd2+、菲吸附量的二次回归模型,对回归模型进行了方差分析,并确定了吸附剂的最佳制备条件。结果表明,二次回归模型能较好地模拟Cd2+、菲的吸附量与影响因子丙烯酸中和度、引发剂量和交联剂量之间的关系。各因子对Cd2+吸附量的影响次序为:交联剂量>引发剂量>丙烯酸中和度;对菲吸附量的影响次序为引发剂量>交联剂量>丙烯酸中和度。吸附剂的最佳制备条件为:累托石、丙烯酸和腐殖酸三者的质量比为65∶30∶5,丙烯酸中和度、引发剂量和交联剂量分别为75.16%、2.57%和0.44%。在此优化条件下制备的吸附剂对Cd2+和菲的吸附量分别为170.19 mg/g和7.36 mg/g。     

一种基于预测法的电磁兼容设计方法

文章以数模混合电路设计实践为基础,介绍了一种基于预测法的电磁兼容设计方法。先以电磁兼容测试理论为基础介绍数模混合电路设计中的电磁兼容方法,在以此方法建立电磁兼容设计模型,并通数模混合电路实践来检验和改进设计模型。     

响应面法优化超临界水氧化处理农药废水

在间歇式超临界水氧化系统中对草甘膦农药废水进行降解实验。选取温度、反应时间、过氧量3个量为因素量,总有机碳(TOC)去除率为响应量进行中心组合设计（CCD）。在实验的基础上,利用响应面分析法（RSM）对实验结果进行分析及参数优化：建立了TOC去除率与各个因素关系的二次多项式数学模型;分析了各个因素单独的及相互作用对TOC去除率的影响;优化结果表明,在温度483℃、反应时间29.2 min、过氧量148.4%的条件下,达到了最佳效果,此时TOC的去除率为100%。     

响应曲面法优化复合絮凝剂的制备工艺

为了提高染料废水中COD和色度的去除效果,采用响应曲面法对聚硅酸类新型复合絮凝剂的制备工艺进行了优化实验研究。在单因素实验基础上采用Box-Behnken Design(BBD)实验设计方法,设计出了影响染料废水处理效果的3因素3水平共15组实验,其中n(Fe+Al):n(Si)的摩尔比为4～6,n(B+Mg):n(Si)的摩尔比为0.3～0.7,熟化时间为1～3 d。根据15组实验结果,以COD去除率和色度去除率为响应值分别建立了二次多项式响应曲面模型。模型优化结果显示,在n(Fe+Al):n(Si)摩尔比为5∶1,n(B+Mg):n(Si)为0.5∶1,熟化时间为2 d的条件下,制备得到的新型复合絮凝剂聚硅酸铝铁硼镁具有最佳的絮凝处理性能和脱色效果,能有效去除染料废水中的COD和色度,其中出水色度接近于0,COD的去除率达到87.65%,模型验证实验进一步验证了本文所建立的响应曲面法在复合絮凝剂制备工艺优化中的有效性。     

响应面优化CCl4增强超声降解左旋氧氟沙星模拟废水

利用响应面优化实验设计方法对CCl₄增强超声降解左旋氧氟沙星模拟废水的影响因素进行探讨和分析,考察了溶液初始pH值、超声功率、左旋氧氟沙星初始浓度的影响。应用Box-Behnken中心组合设计得到一个二次多项式数学模型,确定了US/CCl₄降解左旋氧氟沙星的优化条件:初始pH值6.8,超声功率189 W,左旋氧氟沙星初始浓度为5 mg/L时,左旋氧氟沙星的去除率达到最大(82.99%)。经实验验证, 实际值与模型预测值吻合性良好,偏差仅为0.036%。     

响应面法和神经网络优化Acinetobactersp．DNS32发酵基质

为了提高阿特拉津降解菌Acinetobactersp．DNS32的产量,分别采用响应曲面法和基于人工神经网络的遗传算法对阿特拉津降解菌DNS32发酵培养基中3个重要基质成分（玉米粉、豆饼粉、K：HPO。）进行优化研究。响应曲面法确定3种成分的含量为玉米粉39．494g／L,豆饼粉25．638g／L和K。HPO。3．265g／L时,预测发酵活菌最大生物量为7．079×10^8CFU／mL,实测量为7．194×10^8CFU／mL;人工神经网络结合遗传算法优化确定3种主要成分含量为玉米粉为39．650g／L,豆饼粉为25．500g／L,K2HPO4为2．624g／L时,预测最大值为7．199×10^8CFU／mL,实测量为7．244×10。CFU／mL;最终确定培养基配方：玉米粉为39．650g／L,豆饼粉为25．500g／L,K2HPO4为2．624g／L,CaCO3为3．000g／L,MgSO4·7H2O和NaCl均为0．200g／L;优化后阿特拉津降解菌DNS32发酵生物量比优化前提高了36．6％。结果表明,在阿特拉津降解菌DNS32发酵培养基组分优化方面,响应面法和基于人工神经网络的遗传算法都是可行的,基于人工神经网络的遗传算法具有更好的拟合度和预测准确度。     

Network design for water quality monitoring of surface freshwaters: a review

To date, many water quality monitoring networks for surface freshwaters have been rather haphazardly designed without a consistent or logical design strategy. Moreover, design practices in recent years indicate a need for cost-effective and logistically adaptable network design approaches. There are many variables that need to be included in a comprehensive yet practical monitoring network: a holistic appraisal of the monitoring objectives, representative sampling locations, suitable sampling frequencies, water quality variable selection, and budgetary and logistical constraints are examples. In order to investigate the factors which affect the development of an effective water quality monitoring network design methodology, a review of past and current approaches is presented.     

Multi-response optimization of Fenton process for applicability assessment in landfill leachate treatment

Fenton process, as a pretreatment method, was found to be effective in the primary treatment of mature/medium landfill leachate. However, the main problem of the process is the large amount of produced sludge that requires an accurate feasibility evaluation for operational applications. In this study, the response surface methodology was applied for the modeling and optimization of Fenton process in three target responses, (1) overall COD removal, (2) sludge to iron ratio (SIR) and (3) organics removal to sludge ratio (ORSR), where the latter two were new self-defined responses for prediction of sludge generation and applicability assessment of the process, respectively. The effective variables included the initial pH, [H₂O₂]/[Fe²⁺] ratio and Fe²⁺ dosage. According to the statistical analysis, all the proposed models were adequate (with adjusted R² of 0.9116–0.9512) and had considerable predictive capability (with prediction R² up to 0.9092 and appropriate adequate precision). It was found that all the variables had significant effects on the responses, specifically by their observed role in dominant oxidation mechanism. The optimum operational conditions obtained by overlay plot, were found to be initial pH of 5.7, [H₂O₂]/[Fe²⁺] ratio of 17.72 and [Fe²⁺] of 195 mM, which led to 69% COD removal, 2.4 (l sludge/consumed mole Fe²⁺) of SIR and 16.5 (gCOD removed/l produced sludge) for ORSR in verification test, in accordance with models-predicted values. Finally, it was observed that [H₂O₂]/[Fe²⁺] ratio and Fe²⁺ dosage had significant influence on COD removal, while Fe²⁺ dosage and [H₂O₂]/[Fe²⁺] ratio had remarkable effects on SIR and ORSR responses, respectively.