Feasibility of honeycomb monolith supported sugar catalyst to produce biodiesel from palm fatty acid distillate (PFAD)

Carbon coated monolith was prepared by sucrose solution 65 wt.% via dip-coating method. Sulfonation of incomplete carbonized carbon coated monolith was carried out in order to synthesize solid acid catalyst. The textural structure characteristics of the solid acid catalyst demonstrated a low surface area and pore volume. Palm fatty acid distillate (PFAD), a by-product of palm oil refineries, was utilized as oil source in biodiesel production. The esterification reaction subjected to different reaction conditions was performed by using the sulfonated carbon coated monolith as heterogeneous catalyst. The sulfonation process had been performed by using vapour of concentrated H₂SO₄ that was much easier and efficient than liquid phase sulfonation. Total acidity value of carbon coated monolith was measured for unsulfonated sample (0.5 mmol/g) and sulfonated sample (4.2 mmol/g). The effect of methanol/oil ratio, catalyst amount and reaction time were examined. The maximum methyl ester content was 89% at the optimum condition, i.e. methanol/oil molar ratio (15:1), catalyst amount (2.5 wt.% with respect to PFAD), reaction time (240 min) and temperature 80 °C. The sugar catalyst supported on the honeycomb monolith showed comparable reactivity compared with the sugar catalyst powder. However, the catalyst reusability studies showed decrease in FFA% conversion from 95.3% to 68.8% after four cycles as well as the total acidity of catalyst dropped from the value 4.2 to 3.1 mmol/g during these cycles. This might be likely due to the leaching out of SO₃H group from the sulfonated carbon coated monolith surface. The leaching of active species reached a plateau state after fourth cycle.     

Modeling of a sequencing batch reactor treating municipal wastewater using multi-layer perceptron and radial basis function artificial neural networks

A sequencing batch reactor was modeled using multi-layer perceptron and radial basis function artificial neural networks (MLPANN and RBFANN). Then, the effects of influent concentration (IC), filling time (FT), reaction time (RT), aeration intensity (AI), SRT and MLVSS concentration were examined on the effluent concentrations of TSS, TP, COD and NH₄⁺-N. The results showed that the optimal removal efficiencies would be obtained at FT of 1 h, RT of 6 h, aeration intensity of 0.88 m³/min and SRT of 30 days. In addition, COD and TSS removal efficiencies decreased and TP and NH₄⁺-N removal efficiencies did not change significantly with increases of influent concentration. The TSS, TP, COD and NH₄⁺-N removal efficiencies were 86%, 79%, 94% and 93%, respectively. The training procedures of all contaminants were highly collaborated for both RBFANN and MLPANN models. The results of training and testing data sets showed an almost perfect match between the experimental and the simulated effluent of TSS, TP, COD and NH₄⁺-N. The results indicated that with low experimental values of input data to train ANNs the MLPANN models compared to RBFANN models are more precise due to their higher coefficient of determination (R²) and lower root mean squared errors (RMSE) values.     

Molecular behavior and interactions with microbes during anaerobic degradation of bio-derived DOM in waste leachate

It is the key to control bio-derived dissolved organic matters (DOM) in order to reduce the effluent concentration of wastewater treatment, especially for waste leachate with high organic contaminants. In the present study, the anaerobic degradation of aerobically stabilized DOM was investigated with DOM substrate isolated through electrodialysis. The degradation of bio-derived DOM was confirmed by reduction of 15% of total organic carbon in 100 days. We characterized the molecular behavior of bio-derived DOM by coupling molecular and biological information analysis. Venn based Sankey diagram of mass features showed the transformation of bio-derived DOM mass features. Occurrence frequency analysis divided mass features into six categories so as to distinguish the fates of intermediate metabolites and persistent compounds. Reactivity continuum model and machine learning technologies realized the semi-quantitative determination on the kinetics of DOM mass features in the form of pseudo-first order, and confirmed the reduction of inert mass features. Furthermore, network analysis statistically establish relationship between DOM mass features and microbes to identify the active microbes that are able to utilize bio-derived DOM. This work confirmed the biological technology is still effective in controlling recalcitrant bio-derived DOM during wastewater treatment.     

制革废水治理方法的研究

对制革废水进行了实验研究，提出了制革废水的处理方法．即首先对铬鞣废水进行单独处理，回收鞣革液，再采用聚合硅酸系混凝剂和聚丙烯酰胺（ＰＡＭ）来处理混合废水的新方法．     

上杭紫金山金矿废水废渣的处理及生态环境影响

金矿的开采会产生大量的废渣和废矿石，氰化法提金则产生大量含氰废水，如果未能妥善处理，将严重污染地表水和地下水，以及周边生态环境。该文对上杭紫金山金矿的生产工艺、废水废渣处理情况进行了调研，并提出矿山生态环境保护措施建议。     

废旧塑料的回收利用

废旧塑料是重要的再生资源，合理利用不仅环境保护，也将增加经济效益，阐述了废旧塑料回收利用情况及发展前景。     

废气污染控制高新技术的研究与应用

列举了大量的事实，重点介绍了几种高新技术在废气污染控制中的研究与应用，说明了向环保发展迟缓领挑战依赖于科学技术，而环保的发展又向科学技术提出了更高的要求。     

固相萃取-UPLC-MS/MS法测定环境水体中多种抗生素

采用固相萃取-超高效液相色谱串联质谱法测定环境水样中25种磺胺类和喹诺酮类抗生素,通过优化试验条件,使方法在2.00μg/L～200μg/L范围内线性良好,方法检出限为1.01ng/L～2.85ng/L,7次测定结果的RSD为2.3%～8.0%。将该方法用于自来水和地表水测定,结果均为未检出,高、低质量浓度水平的加标回收率为61.2%～102%。     

HPLC-三重四级杆质谱法测定医疗废水中抗生素残留

采用固相萃取/高效液相色谱-三重四级杆质谱法同时测定医疗废水中的20种超痕量抗生素残留,通过优化试验条件,使方法在100μg/L～100μg/L范围内线性良好,方法检出限为024ng/L～122ng/L。空白水样和实际水样3个质量浓度水平的加标回收率分别为80.2%～108%和75.8%～114%,6次测定结果的RSD分别为2.4%～8.4%和1.7%～8.1%。将该方法用于测定重庆市2家三甲医院医疗废水中的超痕量抗生素残留,结果有11种抗生素检出,其余均为未检出。     

生物滴滤池法处理废气动力学模式研究

基于物料平衡和微生物降解废水中污染物的动力学模式,以丙酮、甲苯为处理对象提出了生物滴滤池处理废气的模式。当入口浓度C_(in)较低,小于临界浓度C_(crit),时,C=C_(in)EXP((-B/V_g)·H);当人口浓度C_(in)较高,大于临界浓度C_(crit)时,C=C_(in)-(K_0X/V_g)·H。研究表明,实验结果与模式计算结果吻合较好。