硝基修饰的超高交联树脂对酚类化合物的吸附研究

对超高交联聚苯乙烯树脂进行硝基修饰,制得硝基修饰超高交联聚苯乙烯树脂JN-5(简称JN-5).JN-5树脂具有比表面积高、亲水性强等优点.对酚类化合物在水溶液中进行静态吸附研究,平衡吸附试验数据和吸附热力学计算结果都表明,JN-5对4种酚类化合物(对甲基苯酚、苯酚、对氯苯酚、对硝基苯酚)的吸附性能优于大孔吸附树脂XAD-4.这主要得益于JN-5的高比表面积和丰富的微孔结构.动态小柱吸附试验中,在流速4.77mL/h、303K的条件下,JN-5对苯酚的穿透吸附量为2.43mmol/g,总吸附量为3.26mmol/g,吸附后的树脂能用8%(质量分数)的NaOH溶液完全洗脱.     

沟渠式生物接触氧化法对有机物和氨氮的去除研究

生物接触氧化工艺是目前较为成熟的水质净化技术,国内外在河流水质净化、水体修复中都有较多的研究和应用.在实验室采用沟渠式生物接触氧化组合系统处理模拟村庄面源污水,较好地去除了有机物并实现氨氮转化.结果表明,当进水COD为130～290mg/L、氨氮为30～40mg/L、水力负荷为0.19～0.24m3/(m2·d)的条件下,该系统稳定运行11周,COD和氨氮的平均去除率分别达85%和79%.     

水体中钼污染物的迁移转化研究进展

水体的重金属钼污染在中国部分地区已经显现,明确钼迁移转化规律是治理钼污染的基础.在总结水体钼污染形成机制的基础上,综述了水体钼污染物迁移转化的研究进展.其中,在水体胶体对钼的吸附研究方面较深入,酸碱条件和胶体种类是钼迁移转化的主要影响因素.而目前的研究,对尾矿中不同种类原钼矿物迁移转化与环境条件相互作用的关系尚不明确.因此,解决实际钼污染同题还需更深入的系统性探索.     

醇胺溶液吸收与解吸CO2的研究

在温度333K、常压条件下,在羟乙基乙二胺(AEE)总量一定的溶液中,研究了不同浓度AEE对CO2的吸收性能;在总胺质量分数为40%的溶液中,研究了不同配比的AEE N-甲基二乙醇胺(MDEA)对CO2的吸收性能.考察了吸收过程中吸收速率、吸收量、吸收时间、AEE浓度以及吸收液温度的相互关系.控制解吸过程温度为393K,考察了CO2解吸量与解吸时间的关系.实验表明,适当降低AEE浓度有利于充分发挥AEE溶液的CO2吸收性能;在MDEA溶液中加入适量AEE,可以明显提高CO2的吸收与解吸性能;其中质量分数为20?E 20%MDEA的复合溶液在CO2吸收与解吸过程中表现出良好的实际操作性.     

不同加碱量下爆破制浆的源强试验研究

为了解爆破制浆的排污情况和废水处理的可行性,以烧碱和石灰作投加药剂,进行了不同加碱量条件下爆破制浆产生源强的试验研究,以确定最佳的加碱量和适宜的黑液提取率.研究表明,在加碱量相同的情况下,采用常规爆破浆样,浆样性能较好;在保持吨粗干浆产生的COD一致时,投加价格低廉的石灰,既能降低生产成本,又便于后续的废水处理;工程调试运行结果表明,控制吨粗干浆的石灰投加量为25～30 kg时,黑液提取率超过80%,最终出水COD<100 mg/L.     

上流式多级厌氧反应器中厌氧颗粒污泥特性研究

高品质厌氧颗粒污泥是厌氧反应器实现高效、稳定运行的关键和基础.在实现上流式多级厌氧反应器(UMAR)处理木薯变性淀粉废水高效运行的基础上,对厌氧颗粒污泥的浓度分布、粒径分布、沉降速度、产甲垸活性,辅酶F420和生物相等作进一步的研究.根据在实验工艺条件下培养得到的厌氧颗粒污泥的性能,探讨厌氧颗粒污泥的可能形成机制.     

垃圾焚烧炉渣对电镀废水中Cu的吸附特性

以垃圾焚烧炉渣作吸附剂,对电镀废水中Cu的吸附特性进行了研究,包括吸附速率、解吸速率、吸附等温线和连续柱吸附实验等。结果表明,炉渣对电镀废水中Cu的吸附平衡时间和解吸平衡时间均为8 h。炉渣对Cu的吸附等温线为直线型,可用Henry型方程进行拟合。连续柱吸附实验结果表明,炉渣对电镀废水在连续吸附55 h后吸附能力逐渐丧失,累计最大吸附量为921 μg/g,而炉渣对人工配水在连续吸附80 h后吸附能力完全丧失,累计最大吸附量为2 687 μg/g。     

Decolorization of cationic red X-GRL by wet air oxidation: performance optimization and degradation mechanism

The decolorization of a strong colored azo dye solution of cationic red X-GRL was investigated by wet air oxidation under relatively mild conditions (60-180 degrees C, PO2 = 0-1.2 MPa). Mono-factor experiments were carried out to investigate the effect of the operation factors and the relatively important parameters were selected for optimization using response surface methodology to explore the interactions of these relatively important parameters. Model regeneration analysis and the check experiments showed that the data of the general linear model agreed with the experiment results well. With multistage Monte-Carlo optimization, the best region of these variables could be predicted to dye color removal. At typical operational conditions, the intermediates of dye degradation were detected and confirmed by GC/MS system. Considering the intermediates and the structure analysis with the help of Gaussian 03W (version 6.0) and the theory of dye color, a possible degradation mechanism for the wet air oxidation of cationic red X-GRL was discussed and the probable degradation pathway was deduced.     

Application of artificial neural network approach and remotely sensed imagery for regional eco-environmental quality evaluation

Eco-environment quality evaluation is an important research theme in environment management. In the present study, Fuzhou city in China was selected as a study area and a limited number of 222 sampling field sites were first investigated in situ with the help of a GPS device. Every sampling site was assessed by ecological experts and given an Eco-environment Background Value (EBV) based on a scoring and ranking system. The higher the EBV, the better the ecological environmental quality. Then, three types of eco-environmental attributes that are physically-based and easily-quantifiable at a grid level were extracted: (1) remote sensing derived attributes (vegetation index, wetness index, soil brightness index, surface land temperature index), (2) meteorological attributes (annual temperature and annual precipitation), and (3) terrain attribute (elevation). A Back Propagation (BP) Artificial Neural Network (ANN) model was proposed for the EBV validation and prediction. A three-layer BP ANN model was designed to automatically learn the internal relationship using a training set of known EBV and eco-environmental attributes, followed by the application of the model for predicting EBV values across the whole study area. It was found that the performance of the BP ANN model was satisfactory and capable of an overall prediction accuracy of 82.4%, with a Kappa coefficient of 0.801 in the validation. The evaluation results showed that the eco-environmental quality of Fuzhou city is considered as satisfactory. Through analyzing the spatial correlation between the eco-environmental quality and land uses, it was found that the best eco-environmental areas were related to forest lands, whereas the urban area had the relatively worst eco-environmental quality. Human activities are still considered as a major impact on the eco-environmental quality in this area.     

Distribution of elements in needles of Pinus massoniana (Lamb.) was uneven and affected by needle age

Macronutrients (P, S, K, Na, Mg, Ca), heavy metals (Fe, Zn, Mn, Cu, Pb, Cr, Ni, Cd,) and Al concentrations as well as values of Ca/Al in the tip, middle and base sections, and sheaths of current year and previous year needles of Pinus massoniana from Xiqiao Mountain were analyzed and the distribution patterns of those elements were compared. The results indicated that many elements were unevenly distributed among the different components of needles. Possible deficiency of P, K, Ca, Mn and Al toxicity occurred in needles under air pollution. Heavy metals may threaten the health of Masson pine. Needle sheaths were good places to look for particulate pollutants, in this case including Fe, Cu, Zn, Pb, Cr, Cd and Al.