接枝二茂铁介体微生物传感器对污水BOD的快速测定

采用接枝二茂铁为介体的微生物传感器测量污水的BOD。将二茂铁(ferrocene,Fc)通过缩合反应接枝到大分子介孔材料SBA-15的表面用作微生物生化反应传递电子的介体,与活性污泥提取的微生物混合,并用聚乙烯醇(PVA)进行固定化,以此制备成微生物敏感膜,并与玻碳电极耦合,构建三电极传感系统,用于快速测量污水水样的BOD。结果表明,传感器的线性范围为2～300 mg/L,连续测量20个样品的精密度为4.2%,能连续工作35 d。并讨论了pH,温度和重金属对传感器响应的影响。通过对实际水样的测试表明,测得的BOD与BOD5的具有良好的相关性。     

An electronic nose to classify Iberian pig fats with different fatty acid composition

Fatty acid analysis is frequently performed in fat and other raw materials to classify them according to their fatty acid composition, but the need to carry out online determinations has generated a growing interest in more rapid options. This research was done to evaluate the ability of a polymer-sensor based electronic nose to classify Iberian pig fat samples with different fatty acid compositions. Significant correlations were found between individual fatty acids and sensor responses, proving that sensor response data were not fortuitously sorted. Significant correlations also appeared between some sensors and water activity, which was considered during the sample classification. Two supervised pattern recognition techniques were attempted to process the sensor responses: 85.5% of the samples were correctly classified by discriminant analysis, but the percentage increased to 97.8% using a one-hidden layer back-propagation artificial neural network. The electronic nose (specifically, sensor responses analyzed by a neural network) achieved success similar to that obtained using the more usual fatty acid analysis by gas chromatography.     

UHT脱脂纯牛奶感官评价和电子鼻分析相关性研究

选取四种市售不同品牌的UHT脱脂纯牛奶作为研究对象,通过感官描述性分析和电子鼻技术对其风味属性进行评价。采用主成分分析(PCA)和聚类分析(CA)结合偏最小二乘回归法(PLSR)法将电子鼻传感器性能和感官属性进行相关性分析。结果表明样品奶油味及脂质感评分均较低;电子鼻的十个传感器对四个样品的区分效果良好;基于感官属性和传感器响应值的PLSR分析建立的相关性模型,能够很好地解释感官属性和传感器响应值的相关性,反映脱脂纯牛奶样品的整体信息。本文结合两种技术方法,弥补了人工感官评价存在的主观性与智能感官分析的局限性影响,旨在为后续改善脱脂纯牛奶风味提供技术参考。     

A novel microbial BOD biosensor developed by the immobilization of P. Syringae in micro‐cellular polymers

BACKGROUND: A biochemical oxygen demand (BOD) sensor, based on an immobilized Pseudomonas syringae in highly porous micro‐cellular polymer (MCP) in combination with a dissolved oxygen electrode, has been developed for the analysis of biodegradable organic compounds in aqueous samples. Microorganisms were immobilized in a molded MCP disk and a wastewater sample was injected into the biocomposite disk by a flow injection system. Dissolved oxygen (DO) changes as a measure of soluble BOD was read with a DO probe placed into a flow cell carrying biocatalytically activated disk. RESULTS: Optimal response of the MCP BOD sensor was obtained at pH 6.8 and 25 °C with a typical response time of 3–5 min for a 2 mm thick molded polymeric disk. The sensor showed detection linearity over the range 5–100 mg L^?1 BOD₅ (r² > 0.99) at a flow rate of 0.6 mL min^?1. The repeatability and reproducibility of the sensor response were found to be 3.08% and 7.77%, respectively. BOD values produced with this biosensor for various municipal and industrial wastewaters correlated well with those determined by the conventional 5‐day BOD test. CONCLUSION: This new biosensor was different from present amperometric BOD biosensor configurations in which the biocatalyst (microbial/enzymatic) is placed between cellulose and Teflon membranes installed on a DO probe. The use of a molded MCP disk coniainng microbial activity offers better stability and lifetime for commercial use in environmental monitoring. Copyright © 2008 Society of Chemical Industry     

The differentiation of biodegradable and non‐biodegradable dissolved organic matter in wastewaters using fluorescence spectroscopy

The chemical and biochemical oxygen demand values of a number of synthetic and wastewater samples were determined using fluorescence spectroscopy. Treated and untreated sewage samples were obtained from a local sewage treatment works while synthetic samples were analysed before, during, and after treatment via a rotating biodisc contactor. Fluorescence intensities were normalised using the water Raman signal as an internal standard and corrections applied to take into account the attenuation effects caused by the sample matrix. The fluorescence emission spectra (λ_exc = 280 nm) of synthetic and sewage samples were very similar in that two main fluorescence bands centred around 350 nm and 440 nm were observed in all samples. Normalised fluorescence data, centred at 350 nm, correlate well with corresponding BOD, COD and TOC values (R² values ranging between 0.93 and 0.98). Using BOD, COD and TOC data the fluorescence at 350 nm and 440 nm can be apportioned to biodegradable and non‐biodegradable dissolved organic matter respectively. The findings of this research show that fluorescence data can be used to quantify oxygen demand values (chemical and biochemical) and total organic carbon values. Furthermore, the fluorescence spectral response can be apportioned to biodegradable (BOD) and non‐biodegradable (COD ? BOD) dissolved organic matter. The potential of using fluorescence spectroscopy as a possible tool for real‐time monitoring of sewage wastes is discussed. © 2002 Society of Chemical Industry     

The use of electronic and human nose for monitoring rapeseed oil autoxidation

This work was aimed at assessing the effectiveness of the electronic nose to monitor off‐flavor associated with lipid oxidation as a supplementary tool to human sensory panel assessment. Therefore, correlations between electronic nose and sensory analysis were determined. Also GC analyses and chemical analyses of oil samples were run to characterize the analyzed samples with well‐described parameters. Refined rapeseed oil was subjected to an accelerated storage test for 12 days at 60 °C and to an ambient temperature storage test in which it was stored in retail plastic bottles for up to 6 months. PCA of electronic nose data samples stored at an elevated temperature was related to PCA of sensory analysis, and similarities in sample clustering were observed. For samples stored at room temperature, the human panel showed greater sensitivity than the electronic nose. Prediction models based on PLS of electronic nose data were able to predict the sensory quality changes during storage at elevated and room temperature, ranging from 0.721 to 0.989 and from 0.849 to 0.881 (p <0.05), respectively. PV and p‐AV were well predicted on the basis of both electronic nose (0.989, 0.998 for elevated temperature; 0.907, 0.881 for room temperature) and sensory analysis data (0.973, 0.993 for elevated temperature; 0.939, 0.886 for room temperature). Applicability of the electronic nose technology to verify sensory and rancidity changes during storage showed to be promising in quality control of oils.     

浅析炼油废水中BOD与COD的关系

对水中ＢＯＤ５和ＣＯＤＣｒ的相关性进行了分析,结果表明,炼油厂废水中ＢＯＤ５与ＣＯＤＣｒ数值之间线性关系显著,在生产稳定的情况下,只要测定出废水中的ＣＯＤＣｒ,就可通过回归方程及置信区间算出ＢＯＤ５。     

Developmental studies of an adaptive on-line softsensor for biological wastewater treatments

Efficient monitoring and automatic control systems for biological wastewater treatment processes, especially those dealing with bioinhibitory pollutants, such as phenol, are urgently required in order to meet increasingly stringent environmental regulations. Practical on-line sensors of variables that describe water quality, such as BOD or individual toxic pollutants such as phenol, are not commercially available; e.g. phenol is generally monitored off-line by spectrofluorometry. Inference software sensors could be an attractive alternative for on-line monitoring of these variables. As a first step towards the development of inferential sensors for biological wastewater treatment processes, we consider in this study, a simplistic version of such a process which consists of a continuous culture of Pseudomonas putida Q5 degrading phenol. In this work, we propose a neural network based inferential sensor for phenol monitoring using on-line biomass concentration measurements by spectrophotometry. The network was built with wavelets as the basis functions and the adaptive algorithm for the weights was based on a Lyapunov stability analysis. Predicted phenol output of the network showed good agreement with experimental data, over fairly broad ranges of inlet phenol concentration and dilution rate step changes. Simulations were conducted to find convergence conditions and to investigate possible sources for errors in phenol estimates.     

Determination of Origin of Commercial Flavored Rapeseed Oil by the Pattern of Volatile Compounds Obtained via GC–MS and Flash GC Electronic Nose

Flavored rapeseed oil (FRO) is a typical hot‐pressed oil and is widely consumed in China due to its strong characteristic flavor and intensive color. In this study, volatile profiles of 33 representative commercial rapeseed oils in China are characterized by gas chromatography‐mass spectrometry (GC‐MS) and flash gas chromatography (GC) electronic nose system. 51 volatile compounds are identified and the nitriles (methallyl cyanide and 5‐cyano‐1‐pentene), aldehydes (nonanal, 3‐furaldehyde, and 5‐methyl‐2‐furancarboxaldehyde), alcohols (1,5‐hexadien‐3‐ol, 2‐furanmethanol, and phenylethyl alcohol), and pyrazines (2,5‐dimethyl‐pyrazine and 2,6‐dimethyl‐pyrazine) are the major volatile compounds in FROs. Glucosinolate degradation products account for the highest proportion of these volatiles, which are found to have a positive correlation with the erucic acid content (R² = 0.796, p < 0.01). FRO from Sichuan province in the southwest of China can be characterized by the obvious distinctions in flash GC electronic nose combined with principal component analysis, which indicates that the flash GC electronic nose can be used as a promising method to identify the origins of FRO. Practical Applications: This work is helpful for expanding the knowledge of volatiles of commercial flavored rapeseed oil. The data can also serve as a basis for the quality assessment of hot‐pressed rapeseed oil. Meanwhile, the flash GC electronic nose combined with principal component analysis can be used as a promising method for the classification of flavor rapeseed oil production areas.     

Semi‐specific biosensors for measuring BOD in dairy wastewater

BACKGROUND: Semi‐specific microbial biochemical oxygen demand (BOD) biosensors were constructed using living cells of Escherichia coli R17.1.3 (E. coli) and Raoultella terrigena P74.3 (R. terrigena) immobilized in agarose gel matrix. The research involved comparison with the Pseudomonas fluorescens P75 (P. fluorescens) biosensor that had no specificity in decomposing lactose and milk derivates. The constructed BOD biosensors were calibrated with OECD synthetic wastewater and tested with different wastewater samples. RESULTS: The linear range of the calibration curve was 5–200 mg L^?1 BOD₇ for R. terrigena and P. fluorescens based biosensors and 150 mg L^?1 BOD₇ for the E. coli based biosensor. Service life was 60 days for E. coli and P. fluorescens based biosensors and 40 days for R. terrigena based biosensors. BOD values for dairy industry wastewater obtained with current semi‐specific biosensors considerably overestimate BOD₇, while universal biosensors underestimate BOD₇ obtained by the conventional 7‐day BOD test. CONCLUSION: In spite of extensive overestimation of BOD₇ the semi‐specific biosensors enabled better estimation of BOD in dairy industry wastewater than a reference P. fluorescens biosensor. The best result, in terms of service life, stability, sensitivity and reproducibility was accomplished with semi‐specific E.coli biosensor. Copyright © 2010 Society of Chemical Industry     

氧化沟工艺中污水监测指标的相关性分析

通过对某生活污水处理厂氧化沟中水质的监测数据进行统计、分析,探讨了主要污染指标在系统运行过程中的相关性。通过对其进行回归计算分析后,发现它们之间有着较为明显的线性相关性。其中出水指标回归计算及检验结果如下:BOD5、SS、TN、TP与CODCr之间的相关系数r分别为0.9612、0.9675、0.9541、0.8705,检验值F都大于F0.01。据此若测得一指标后,可以利用其相关性,换算出其它指标的量值,从而减少监测项目。     

电子鼻在咖啡产品品质检测中的应用研究

借助电子鼻检测不同类别咖啡产品的气味在传感器上的响应值,并采用主成分分析(PCA)、判别因子(DFA)和统计质量控制分析法(SQC)进行分析.结果显示,焙炒咖啡和速溶咖啡气味差异明显.电子鼻技术能够有效区分不同类别的咖啡产品,亦能将不同焙炒程度的咖啡气味区分开来,利用该技术可对咖啡产品的质量进行有效监控.     

Soft Computing of Biochemical Oxygen Demand Using an Improved T–S Fuzzy Neural Network

It is difficult to measure the online values of biochemical oxygen demand (BOD) due to the characteristics of nonlinear dynamics, large lag and uncertainty in wastewater treatment process. In this paper, based on the knowledge representation ability and learning capability, an improved T–S fuzzy neural network (TSFNN) is introduced to predict BOD values by the soft computing method. In this improved TSFNN, a K-means clustering is used to initialize the structure of TSFNN, including the number of fuzzy rules and parameters of membership function. For training TSFNN, a gradient descent method with the momentum item is used to adjust antecedent parameters and consequent parameters. This improved TSFNN is applied to predict the BOD values in effluent of the wastewater treatment process. The simulation results show that the TSFNN with K-means clustering algorithm can measure the BOD values accurately. The algorithm presents better approximation performance than some other methods.     

高压脉冲放电/臭氧协同作用提高油田污水可生化性实验

分别考察了高压脉冲放电单独作用、O3单独作用以及两者协同作用下对油田污水COD、BOD5以及BOD5/COD指标的影响,探讨上述技术应用于提高油田污水可生化性的可行性;同时对处理前后水样进行GC-MS 分析以研究可生化性提高的机理.结果表明:协同作用的处理效率明显高于两者单独作用,5 min的处理时间就可以提高BOD5/COD至0.31,10min后BOD5/COD已达0.46,可生化性能大大增强,协同作用提高油田污水可生化性在技术上完全可行;GO-MS分析表明:高压脉冲放电/O3协同作用短时间内提高油田污水生化性的原因是将难降解高分子有机物氧化成为易生物降解的低分子量物质.     

Use of the SAW Sensor Electronic Nose for Detecting the Adulteration of Virgin Coconut Oil with RBD Palm Kernel Olein

An electronic nose (zNose™) was applied to the detection of adulteration of virgin coconut oil. The system, which is based on a surface acoustic wave sensor was used to generate a pattern of volatile compounds present in the samples. Virgin coconut oil was mixed with refined, bleached and deodorized palm kernel olein at a level of adulteration from 1 to 20% (wt/wt). Adulterant peaks were identified from the chromatogram profile and fitted to a curve using linear regression. The best relationship (R ² = 0.91) was obtained between the peak tentatively identified as methyl dodecanoate and the percentage of palm kernel olein added. Pearson’s correlation coefficients (r) of 0.92 and 0.89 were obtained between adulterant peak methyl dodecanoate and of the iodine and peroxide values, respectively. Principal component analysis (PCA) was used to differentiate between pure and adulterated samples. The PCA provided good differentiation of samples with 74% of the variation accounted for by PC 1 and 17% accounted for by PC 2. Pure samples formed a separate cluster from all of the adulterated samples.     

基于Monod方程建立的BOD动力学模型研究

以Monod方程为基础,建立了生化需氧量BOD的—Monod-BOD模型,同时采用差压法测定了生活污水的BOD5。建立的模型与测定的城市污水的BOD5的数据回归分析拟合情况较好,通过与一级动力学模型的残差平方、模型的选用标准（MSC）和相关指数对比结果表明,在描述城市生活污水BOD的降解过程中,Monod-BOD模型均要优于传统一级动力学,所建模型可以用于生活污水中有机物降解过程的描述。     

Impact of anaerobic lagoons on the performance of BOD and TSS removals at the Haspolat (Mia Milia) Wastewater Treatment Plant

One of the most common tests for the determination of strength and organic content of wastewater is the Biochemical Oxygen Demand (BOD). The capital of Cyprus, Nicosia has upgraded its wastewater treatment plant during the 2000s, providing a significant improvement in BOD and TSS treatment performances. These performances are tested by the data collected from 1994 until 2005 by using one-way ANOVA and least significant difference (LSD) tests. The tests showed significant difference (p < 0.05) in the means of the samples investigated before and after the upgrading of the treatment plant.Experimental results showed that the installation of innovative anaerobic lagoons was able to reduce the BOD and TSS concentrations to desirable values that fell within the discharge limits of national and international effluent standards. However, the limits for the reuse of effluent for irrigation purposes require more improvement on the treatment technology. The significant improvement in BOD removal percentages increased the BOD removal performance up to 93%, whereas the TSS removal performance increased to 84%.     

On‐line monitoring of wastewater quality: a review

Real‐time monitoring of wastewater quality remains an unresolved problem to the wastewater treatment industry. In order to comply with increasingly stringent environmental regulations, plant operators as well as instrument manufacturers have expressed the need for new standards and improved comparability and reliability of existing techniques. A review of currently available methods for monitoring global organic parameters (BOD, COD, TOC) is given. The study reviews both existing standard techniques and new innovative technologies with the focus on the sensors' potential for on‐line and real‐time monitoring and control. Current developments of biosensors, optical sensors and sensor arrays as well as virtual sensors for the monitoring of wastewater organic load are presented and the interests and limitations of these techniques with respect to their application to the wastewater monitoring are discussed. © 2001 Society of Chemical Industry     

Characterization and analysis of petrochemical wastewater through particle size distribution,biodegradability, and chemical composition

The centralized treatment method is a widely used form of wastewater treatment that tends to be less effective at removing toxic substances. Therefore, a detailed analysis of the composition of wastewater can provide important information for the design of an effective wastewater treatment process. The objective of this paper was to investigate particle size distribution(PSD), biodegradability, and the chemical composition of the petrochemical wastewater discharges. For this purpose, this project selected the petrochemical wastewater and treated wastewater of China National Offshore Oil Corporation Zhongjie Petrochemical Co, Ltd. as the analysis objects.The step-by-step filtration method, along with a molecular weight classification method, was selected to build the chemical oxygen demand(COD) and biochemical oxygen demand(BOD) fingerprints of petrochemical wastewater and treated wastewater. The results showed that the main pollutants were settleable particles in petrochemical wastewater, which contributed to over 54.85% of the total COD. The colloidal particles with particle sizes in the range of 450–1000 nm had the highest COD value in the treated wastewater, which contributed34.17% of the total COD of treated wastewater. The results of the BOD analysis showed that the soluble fractions were the main reason that treated wastewaters did not meet the treatment standards. Tests on the organic compounds in petrochemical wastewater found that there were mainly linear paraffins, branched paraffins, benzene series compounds, and some plasticizers in the influent of the petrochemical wastewater. The most abundant pollutants in treated petrochemical wastewater were the adjacent diisobutyl phthalate and the linear alkanes.Fourier transform infrared(FTIR) transmission spectroscopy analysis showed that the settleable particles of petrochemical wastewater and membrane bioreactor(MBR)-treated wastewater contained multiple types of organic substances. The results also indicated that removing the oil-settleable substances, the colloidal particles(450–1000 nm), and the soluble organics will be necessary for the treatment of petrochemical wastewater.     

Characterization of Differences in Flavor in Virgin Rapeseed Oils by Using Gas Chromatography–Mass Spectrometry,Electronic Nose,and Sensory Analysis

Flavor profiles of virgin rapeseed oils (VROs) are comparatively studied for the discrimination and authentication of various flavor types by using gas chromatography–mass spectrometry (GC‐MS), electronic nose (E‐nose), and sensory analysis. The relative odor activity values (ROAVs) of key odorants detected by GC‐MS and E‐nose data are visualized to discriminate VROs with various flavors by using multivariate analysis. The correlation of sensory data, ROAVs of key odorants, and E‐nose data is analyzed. Results show that 47 key odorants comprising aldehydes, isothiocyanates, nitriles, pyrazines, ketones, acids, and alcohols are identified based on their ROAVs. The VROs are divided into three groups and the flavor type of each group is determined, namely, green‐pungent, nutty, and oxidized oil flavor by the three techniques. The above flavor types are mainly attributed to the contributions of isothiocyanates, pyrazines, and aldehydes, respectively, according to the compounds' ROAVs. The correlation of the three techniques is investigated by partial least squares regression: GC‐MS data are confirmed to have good correlation with sensory data. Practical Applications: VROs are characterized by their intense flavor and consequently receiving growing interest among consumers. In this study, different flavor profiles of VROs were comparatively studied using GC‐MS, E‐nose, and sensory analysis. It is found that 47 volatile compounds including aldehydes, isothiocyanates, nitriles, pyrazines, ketones, acids, and alcohols were the key odorants to VRO flavors. The VROs were divided into three types by the three techniques, that is, green‐pungent, nutty, and oxidized oil flavor. The three flavor types were attributed to the contributions of isothiocyanates, pyrazines, and aldehydes, respectively, based on the compounds' ROAVs and GC‐MS was confirmed to have good correlation with sensory data. Although E‐nose cannot correlate all flavor types in the oils, this technique is rapid and low‐cost for VRO discrimination according to various aroma characteristics. GC‐MS and E‐nose can be regarded as potential techniques for flavor discrimination in VROs.