气象卫星遥感在干旱监测中的应用

本文根据ＮＯＡＡ极轨气象卫星ＡＶＨＲＲ资料计算生成植被指数相对距平图用于旱情监测，并在江苏省１９９４年特大干旱中进行了应用服务     

铁炭内电解垂直流人工湿地对污水厂尾水深度脱氮效果

针对污水厂尾水总氮(TN)含量偏高、微生物可利用碳源低的问题,构建铁炭内电解垂直流人工湿地(ICIE-VFCW)装置,研究了ICIE-VFCW对尾水的处理效果,并采用紫外-可见光光谱(UV-VIS)、凝胶过滤色谱(GFC),进一步探讨了ICIEVFCW强化脱氮机制.结果表明,ICIE-VFCW可提高系统对尾水中COD的去除,出水COD可稳定在30 mg·L~(-1)以下,全年、暖季、寒季COD平均去除率较普通垂直流人工湿地分别可提高10.16%、9.81%、11.22%.系统出水TN可维持在10 mg·L~(-1)以下,全年、暖季、寒季TN平均去除率较普通垂直流人工湿地分别提高13.72%、12.90%、16.17%.经过人工湿地处理后,污水中有机物的腐殖度、芳香度及相对分子质量(Mr)均有所下降,且ICIE-VFCW中Mr下降更为明显.湿地基质掺杂铁炭可促进尾水中大分子有机物转化为小分子,为微生物提供更多可利用碳源,从而提高脱氮效率.     

Preparation of MgO/B2O3 coatings by plasma spraying on SUS304 surface and effects of heat-resistant

This study mainly deals with the preparation of MgO/B₂O₃ coatings by plasma spraying on the SUS304 surface and the effects of heatresistant. The power materials of low thermal conductivity were selected to control the heat divergent performance of high temperature parts. The reticular micro-structure between the cover thermal layer and the substrate was prepared by using the plasma spraying method. The powder mixture of MgO and B₂O₃ were selected as spraying materials and the SUS304 was used as the substrate material. The MgO/B₂O₃ coating was prepared on the surface of the SUS304 to provide better cover thermal performance. The properties of the microstructures and the morphologies were studied by Optical Microscope, Scanning Electron Microscope, Electron Probe Microanalyzer, and X-ray Diffraction. The results showed that the cover thermal performance has been improved.     

双水相浮选-HPLC法测定水中氯硝柳胺

文章建立了双水相浮选-高效液相色谱法来测定环境水中氯硝柳胺的含量。选择丙酮为亲水有机溶剂,40%(NH4)2SO4溶液为分相剂。当pH为3.0,氮气流速为20 min/mL,浮选时间为30 min时,萃取率达93.4%。该方法具有高效、绿色环保以及低成本等优点,是一种测定水样中氯硝柳胺含量的新方法。     

供水管网水质评价方法的探讨及其应用

利用了模糊数学评价模型和综合指数评价模型分别对南方某市部分给水管网水质进行评价。评价结果分析表明,模糊数学评价法具有评价准确性好、操作简单的特点;综合指数法具有评价结果直观、精确度较高的优点。从评价结果上看,综合指数法较模糊数学评价法更为合理。     

Ambient air monitoring of PCDD/Fs and co-PCBs in Gyeonggi-do, Korea

We started the monitoring for PCDD/Fs in ambient air and soil in August 2001, and co-PCBs in January 2002. Decreasing of PCDD/Fs and co-PCBs levels in ambient air were observed. The higher PCDD/Fs levels were found in winter and lower in autumn. We found that the industrial incinerators influenced the PCDD/Fs levels in ambient air. In the 2,3,7,8-substituted PCDD/Fs concentration profiles, the three major congeners occupied 67% of the total mass. In case of co-PCBs, PCB#118, #105 and #77 were observed as the main congeners. Five cluster groups discriminated by ratio of four components, O(8)CDD, 1,2,3,4,6,7,8-H(7)CDD, 1,2,3,4,6,7,8-H(7)CDF and O(8)CDF, were obtained from HCA (hierarchical cluster analysis).     

QSARs for the toxicity of polychlorinated dibenzofurans through DFT-calculated descriptors of polarizabilities, hyperpolarizabilities and hyper-order electric moments

DFT-B3LYP method with 6-31G(**) basis set was employed to fully optimize the electronic structures of 135 polychlorinated dibenzofurans and parent compound, namely dibenzofuran. It was demonstrated that polarizability anisotropy and mean polarizability could change sensitively and systematically with chlorine number and substitution pattern. And new quantitative structure-activity relationships (QSARs) focused on the binding affinities of aryl hydrocarbon receptor (AhR), aryl hydrocarbon hydroxylase (AHH) and 7-ethoxyresorufin O-deethylase (EROD) induction potencies of PCDFs were developed. It was concluded that polarizability anisotropy in conjunction with hyperpolarizabilties and hyper-order electric moments, e.g. octupole moments could well interpret the variation of toxicity of different congeners and dispersion interaction should be the leading form among various interactions. Although the terms of hyperpolarizabilities and hyper-order electric moments were not the same significant ones as polarizability anisotropy, the long-range interactions characterized by them should not be ignored in explaining the toxicity.     

Effect of amorphous silica and silica sand on removal of chromium(VI) by zero-valent iron

The effect of two surfaces (amorphous silica and silica sand) on the reduction of chromium(VI) by zero-valent iron (Fe(0)) was investigated using batch reactors. The amendment of both surfaces significantly increased the rate and extent of Cr(VI) removal. The rate enhancement by amended surfaces is presumed to result from scavenging of Fe(0)-Cr(VI) reaction products by the provided surfaces, which minimized surface deactivation of Fe(0). The rate enhancing effect was greater for silica compared to sand, and the difference is attributed to silica's higher surface area, greater affinity for reaction products and pH buffering effect. For a given mass of Fe(0), the reactivity and longevity of Fe(0) to treat Cr(VI) increased with increasing dose of silica. Elemental analyses of the reacted iron and silica revealed that chromium removed from the solution was associated with both surfaces, with its mass distribution being approximately 1:1 per mass of iron and silica. The overall result suggests reductive precipitation was a predominant Cr(VI) removal pathway, which involves initial reduction of Cr(VI) to Cr(III), followed by formation of Cr(III)/Fe(III) hydroxides precipitates.     

Optimizing mixture properties of biodiesel production using genetic algorithm-based evolutionary support vector machine

Nowadays, biodiesel is used as one of the alternative renewable energy due to the increasing energy demand. However, optimum production of biodiesel still requires a huge number of expensive and time-consuming laboratory tests. To address the problem, this research develops a novel Genetic Algorithm-based Evolutionary Support Vector Machine (GA-ESIM). The GA-ESIM is an Artificial Intelligence (AI)-based tool that combines K-means Chaotic Genetic Algorithm (KCGA) and Evolutionary Support Vector Machine Inference Model (ESIM). The ESIM is utilized as a supervised learning technique to establish a highly accurate prediction model between the input--output of biodiesel mixture properties; and the KCGA is used to perform the simulation to obtain the optimum mixture properties based on the prediction model. A real biodiesel experimental data is provided to validate the GA-ESIM performance. Our simulation results demonstrate that the GA-ESIM establishes a prediction model with better accuracy than other AI-based tool and thus obtains the mixture properties with the biodiesel yield of 99.9%, higher than the best experimental data record, 97.4%.