Pollutant emission characteristics of rice husk combustion in a vortexing fluidized bed incinerator

Rice husk with high volatile content was burned in a pilot scale vortexing fluidized bed incinerator. The fluidized bed incinerator was constructed of 6 mm stainless steel with 0.45 m in diameter and 5 m in height. The emission characteristics of CO, NO, and SO2 were studied. The effects of operating parameters, such as primary air flow rate, secondary air flow rate, and excess air ratio on the pollutant emissions were also investigated. The results show that a large proportion of combustion occurs at the bed surface and the freeboard zone. The SO2 concentration in the flue gas decreases with increasing excess air ratio, while the NOx concentration shows reverse trend. The flow rate of secondary air has a significant impact on the CO emission. For a fixed primary air flowrate, CO emission decreases with the secondary air flowrate. For a fixed excess air ratio, CO emission decreases with the ratio of secondary to primary air flow. The minimum CO emission of 72 ppm is attained at the operating condition of 40% excess air ratio and 0.6 partition air ratio. The NOx and SO2 concentrations in the flue gas at this condition are 159 and 36 ppm, which conform to the EPA regulation of Taiwan.     

流化床污泥干燥器床料的颗粒度对流化情况的影响

以上海白龙港污水处理厂流化床污泥干燥系统为研究对象,针对流化床污泥干燥器流化情况的好坏分析,在确定其它变量（流化风量、给料分配器转速、料层压差、运行负荷等）不变的情况下,对床料颗粒度的工艺参数进行研究实验,总结颗粒度的工艺参数对流化情况的运行变化规律,从而提高了流化床污泥干燥系统的稳定性、连续性和高效性。     

铁山港海草生态区水体自净能力与水、生、化之间的关系

利用2008年1月～11月间对铁山港湾海草生态区进行的4个季节全面调查所获取的数据资料,首次探讨了该生态区水体自净能力与水动力特征及生物、化学因子之间的关系。结果表明:研究海区之所以具有较强的水体自净能力,其一与该海区具有强潮型的往复流水动力特征有关,在水体自净过程中起主导控制作用;其二与海区具有适宜的水温、快速的复氧能力、富足的溶解氧(DO)水平、最适合好氧微生物繁殖生长的环境条件有关,明显偏低的总有机碳(TOC)含量和丰富的总氮(TN)储量是有机物获得快速降解、营养盐获得快速再生、化学净化能力较强的重要体现;其三与生物链作用所体现的生化过程影响有关,DO含量与生物因子多呈显著以上负相关的季节变化特征以及三种形态N与生物因子在不同季节显示的相关性以事实佐证了这一点;而富足的TN储量、显著偏低的溶解无机氮(DIN)含量与繁盛的浮游动植物生物量及丰富的生物多样性同时出现的特征,正是研究海区具有较强生物净化能力的综合体现。与化学净化能力相比,生物净化能力显示出更强的优势,具有海草生态区的水体自净特点。     

内循环活性炭生物流化床处理农药生产废水的试验研究

采用内循环活性炭生物流化床反应器处理某农药厂生产废水,通过试验研究了该反应器在室温条件下处理农药生产废水的性能.结果表明:当进水pH值控制在7.0～7.5、水力停留时间为6h、曝气量控制在使活性炭处于流化状态时,CODcr的去除率为50％,总氮的去除率为32.33％,同时可生化性明显提高,生物毒性有所降低.     

序批式移动床生物膜反应器富集反硝化聚磷菌及其在单污泥系统中的应用

本文介绍了在单污泥系统中选择和富集反硝化聚磷菌的国内外研究进展,对不同研究者提出的选择和富集反硝化聚磷菌的方法进行了分析和评价,并提出将反硝化聚磷菌与移动床生物膜反应器工艺结合起来,在序批式移动床生物膜反应器悬浮填料上选择和富集反硝化聚磷菌,进一步认识了反硝化聚磷菌的生化特征,使其成为反应器中优势菌群,以及该工艺今后的研究重点。     

微压流化式复合生物反应器处理含酚废水效能的研究

通过连续动态试验,对新型微压流化式复合生物反应器(MP-FHBR)处理模拟苯酚废水的效能进行研究.结果表明,MP-FHBR的COD容积负荷可达4.86kg/(m3·d)、苯酚容积负荷可达1.96kg/(m3·d),出水COD低于200mg/L、出水苯酚浓度低于1mg/L,COD和苯酚去除率分别达到90%和99%以上.当苯酚容积负荷达到2.04kg/(m3·d),苯酚在反应器中逐渐累积,反应器内微生物的TTC-比脱氢酶活性下降.当MP-FHBR进水苯酚浓度为800mg/L时,最佳水力停留时间为9～10h.水力负荷对反应器沉淀池的泥水分离效果影响较大,限制了反应器的进水量,所以MP-FHBR主要适用于处理较高浓度的含酚废水.     

基于BP神经网络的煤层自燃预测

在全面分析影响煤层自燃因素的基础上,建立了煤层自燃预测的人工神经网络模型.应用该模型对某煤田的多个煤层样本进行了训练和预测,网络经过10次训练后,误差达到设定的最小值,6次预测测试中最大误差仅为0.027 8,最小的为0.000 1.研究表明,该模型精度较高,可用于预测煤层自燃的实际应用.     

含硫油品储罐腐蚀产物自燃性的研究

通过模拟储油罐中硫铁化物的生成方式, 分析和研究了H2S气体在无氧条件下,与不同相对湿度的Fe2O3、Fe3O4和Fe(OH)3反应所生成的硫铁化物的自燃性.不同相对湿度的试样经6 h硫化后,其自燃性明显不同.以Fe2O3试样为例,相对湿度为0的硫化产物氧化升温最高为256 ℃,平均升温速率为10.8 ℃/min; 相对湿度为5%、10%和15%的硫化产物,氧化升温最高温度分别为474 ℃、408 ℃和388 ℃,平均升温速率分别为20.5 ℃/min、18.3 ℃/min和13.5 ℃/min.实验结果表明, 不同相对湿度、不同物质的硫化产物,其自燃性有显著差异,样品的相对湿度对硫化产物的自燃性有重要影响.对各种干燥样品的硫化产物进行电镜分析发现,由不同物质硫化所生成的硫化产物结构不同,致使其自燃性有较大差异.硫铁化物氧化反应放热是引发油罐着火的主要因素.     

Emissions of SO2, NO and N2O in a circulating fluidized bed combustor during co-firing coal and biomass

This paper presents the experimental investigations of the emissions of SO2, NO and N2O in a bench scale circulating fluidized bed combustor for coal combustion and co-firing coal and biomass. The thermal capacity of the combustor is 30 kW. The setup is electrically heated during startup. The influence of the excess air, the degree of the air staging, the biomass share and the feeding position of the fuels on the emissions of SO2, NO and N2O were studied. The results showed that an increase in the biomass shares resulted in an increase of the CO concentration in the flue gas, probably due to the high volatile content of the biomass. In co-firing, the emission of SO2 increased with increasing biomass share slightly, however, non-linear increase relationship between SO2 emission and fuel sulfur content was observed. Air staging significantly decreased the NO emission without raising the SO2 level. Although the change of the fuel feeding position from riser to downer resulted in a decrease in the NO emission level, no obvious change was observed for the SO2 level. Taking the coal feeding position R as a reference, the relative NO emission could significantly decrease during co-firing coal and biomass when feeding fuel at position D and keeping the first stage stoichiometry greater than 0.95. The possible mechanisms of the sulfur and nitrogen chemistry at these conditions were discussed and the ways of simultaneous reduction of SO2, NO and N2O were proposed.     

Anaerobic tapered fluidized bed reactor for starch wastewater treatment and modeling using multilayer perceptron neural network

Anaerobic treatability of synthetic sago wastewater was investigated in a laboratory anaerobic tapered fluidized bed reactor(ATFBR) with a mesoporous granular activated carbon(GAC)as a support material.The experimental protocol was defined to examine the effect of the maximum organic loading rate(OLR),hydraulic retention time(HRT),the efficiency of the reactor and to report on its steady- state performance.The reactor was subjected to a steady-state operation over a range of OLR up to 85.44 kg COD/(m~3.d).The COD removal efficiency was found to be 92% in the reactor while the biogas produced in the digester reached 25.38 m~3/(m~3·d) of the reactor. With the increase of OLR from 83.7 kg COD/(m~3.d),the COD removal efficiency decreased.Also an artificial neural network(ANN) model using multilayer perceptron(MLP)has been developed for a system of two input variable and five output dependent variables. For the training of the input-output data,the experimental values obtained have been used.The output parameters predicted have been found to be much closer to the corresponding experimental ones and the model was validated for 30% of the untrained data.The mean square error(MSE)was found to be only 0.0146.