典型废矿物油的产生工艺及其重金属含量特征研究

分析了6种典型废矿物油的产生工艺及特性,研究了废矿物油样品的重金属浓度特征。结果表明,不同产生工艺和工作环境,油品的损耗程度和产污情况存在明显差异。典型废矿物油样品中检出的主要重金属包括Cr、Ni、Zn、Cu、Pb、Mo和Ba等7种。其中,Zn浓度相对较高,Cr、Cu、Mo和Ba的浓度次之,Ni和Pb的浓度相对较少。Zn、Mo、Ba主要来自于添加剂掺入,Cr、Ni、Cu、Pb主要来自使用过程中磨料混入或杂质进入。6种废矿物油直接进入环境中的重金属当量浓度表现为废车用润滑油>废液压油>废淬火油>废冷冻机油>废防锈油>废白油。其中,废车用润滑油和废液压油的重金属潜在危害最高。废矿物油再生利用过程中,重金属绝大部分进入废渣中(如油渣、蒸馏残渣、废白土等),少部分残留在再生产品中;焚烧处置过程中,重金属的去向为烟气和底灰。因此,需要针对废矿物油的处置与资源化利用过程进行严格管理,防止其中重金属的二次污染。     

铸造废砂／废地膜／粘附土三元复合体系的研究

通过X射线衍射分析、红外光谱分析、热分析、电镜及能谱分析、图像分析,可以判断废旧地膜上粘附土的主要矿物质是结晶二氧化硅（粉粒级石英）,它们与聚合物基废弃物复合材料中作为填料的铸造石英砂的性状类同。废旧地膜可以不经清洗,直接与铸造废砂制备复合材料,这可大大降低复合材料的加工成本。这种复合材料实际上是由基体PE、粘附土中大量的SiO2和铸造石英砂SiO2组成的三元复合体系。     

基于地质环境评价的九江市区不同功能用地优化布局

从地质环境角度,对九江市区不同功能用地类型进行了系统划分,并针对划分的主要功能用地类型(居住及公共设施用地、工业及仓储用地、生态绿化用地)分别进行了地质环境适宜性评价,根据评价结果,结合九江市区的用地现状,提出了不同功能用地优化布局建议,为九江市区后期用地规划与调整提供了依据.     

铸型旧砂再生方法及系统设施选择

通过实例,针对某铸造分厂砂处理生产工艺落后,旧砂对车间、环境及产品质量的影响,提出了建立旧砂再生系统的技术改造方案,阐述了旧砂干法再生方法及系统设施选择,分析了砂处理后取得的环境效益和经济效益。可为中小型铸造厂提供借鉴。     

废旧家电产品回收性能评价指标体系的建立

针对家电产品回收工艺流程决策评价的多阶段、多目标的特点,以及不同类型家电产品和不同回收工艺过程的动态特性,采用层次分类方法建立了以经济指标和环境指标为主要内容的回收工艺流程评价指标体系,对指标体系的组成进行了较为详细的分析,讨论了应该考虑的因素及有关计算方法。以电冰箱为例,用改进的模糊层次分析法与遗传算法相结合,介绍了回收工艺流程的优化决策方法。建立的指标体系不仅可以根据评价对象进行动态修改,而且具有较强的可操作性。     

Degradation of metabolites accumulated of benzo[a]pyrene by coupling Penicillium Chrysogenum with KMnO4

Several main metabolites of benzo[a]pyrene （BaP） formed by Penicillium chrysogenum, Benzo[a]pyrene-1,6-quinone （BP 1,6- quinone）, trans-7,8-dihydroxy-7,8-dihydrobenzo[a]pyrene （BP 7,8-diol）, 3-hydroxybenzo[a]pyrene （3-OHBP）, were identified by high-performance liquid chromatography （HPLC）. The three metabolites were liable to be accumulated and were hardly further metabolized because of their toxicity to microorganisms. However, their further degradation was essential for the complete degradation of BaP. To enhance their degradation, two methods, degradation by coupling Penicillium chrysogenum with KMnO4 and degradation only by Penicillium chrysogenum, were compared; Meanwhile, the parameters of degradation in the superior method were optimized. The results showed that （1） the method of coupling Penicillium chrysogenum with KMnO4 was better and was the first method to be used in the degradation of BaP and its metabolites; （2） the metabolite, BP 1,6-quinone was the most liable to be accumulated in pure cultures; （3） the effect of degradation was the best when the concentration of KMnO4 in the cultures was 0.01% （w/v）, concentration of the three compounds was 5 mg/L and pH was 6.2. Based on the experimental results, a novel concept with regard to the bioremediation of BaP-contaminated environment was discussed, considering the influence on environmental toxicity of the accumulated metabolites.     

Denitrification potential enhancement by addition of external carbon sources in a pre-denitrification process

The aim of this study is to investigate the denitrification potential enhancement by addition of external carbon sources and to estimate the denitrification potential for the predenitrification system using nitrate utilization rate （NUR） batch tests. It is shown that the denitrification potential can be substantially increased with the addition of three external carbon sources, i.e. methanol, ethanol, and acetate, and the denitrification rates of ethanol, acetate, and methanol reached up to 9.6, 12, and 3.2 mgN/（g VSS.h）, respectively, while that of starch wastewater was only 0.74 mgN/（g VSS,h）. By comparison, ethanol was found to be the best external carbon source. NUR batch tests with starch wastewater and waste ethanol were carried out. The denitfification potential increased from 5.6 to 16.5 mg NO3-N/L owing to waste ethanol addition. By means of NUR tests, the wastewater characteristics and kinetic parameters can be estimated, which are used to determine the denitrification potential of wastewater, to calculate the denitrification potential of the plant and to predict the nitrate effluent quality, as well as provide information for developing carbon dosage control strategy.     

Variation of soil fertility and carbon sequestration by planting Hevea brasiliensis in Hainan Island, China

The development of rubber industry depends on the sustainable management of rubber plantation. To evaluate the environmental effects of planting Hevea brasiliensis on a subsystem of tropical forest ecosystem, the variation of soil fertility and carbon sequestration under rubber plantation within 30-year life period were investigated in Hainan Island. Results showed that （1） with the increase of stand age of rubber plantation, soil fertility decreased all along. From 1954 to 1995, soil organic matter, total N, available K and available P decreased by 48.2%, 54.1%, 56.7% and 64.1%, respectively. （2） If the complete return of litters was considered without additional fertilizer application to the soil of the rubber plantations, the consumption periods for P, N, K, Mg were only 825 years, 329 years, 94 years and 65 years, respectively~ To improve soil fertility is essential for rubber plantation development. （3） The C sequestration of rubber trees per hectare accounts for 272.08 t within 30-year life period and 57.91% of them was fixed in litters. In comparison with C sequestration by rain forest （234.305 t/hm^2） and by secondary rain forest （150.203 t/hm^2）, rubber forest has more potentials for C fixation. On the base of above results, the following measures would benefit the maintenance of soil fertility and the development of rubber industry, including applying fertilizer to maintain the balance of soil nutrients, intercropping leguminous plant to improve soil fertility, reducing the collection of litters, optimizing soil properties to improve element P availability such as applying CaCO3. The information gathered from the study can be used as baseline data for the sustainable management of rubber plantation elsewhere.     

Treatment of 2-phenylamino-3-methyl-6-di-n-butylaminofluoran production effluent by combination of biological treatments and Fenton＇s oxidation

High strength refractory organic stream is produced during the production of 2-phenylamino-3-methyl-6-di-n-butylaminofluoran （One Dye Black 2, abbr. ODB 2）, a novel heat-sensitive material with a promising market. In this study, a combination of acidificationprecipitation, primary biological treatment, Fenton＇s oxidation and another biological treatment was successfully used for the removal of COD from 18000-25000 mg/L to below 200 mg/L from the ODB 2 production wastewater in a pilot experiment. A COD removal of 70%-80% was achieved by acidification-precipitation under a pH of 2.5-3.0. The first step biodegradafion permitted an average COD removal of 70% under an hydraulic residence time （HRT） of 30 h. By batch tests, the optimum conditions of Fenton＇s oxidation were acquired as： Fe^2＋ dose 6.0 mmol/L; H2O2 dose 3000 mg/L; and reaction time 6 h. The second step biological treatment could ensure an effluent COD below 200 mg/L under an HRT of 10 h following the Fenton＇s treatment.     

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.