Model characterization in measurements of environmental pollutants via data correlation of sensor outputs

The aim of this paper is to develop a simple air pollutant model for the analysis and the characterization of environmental data, acquired by means of multisensor monitoring system and elaborated by suitable software agents. Modeling is basically important in order to validate measured data and to forecast the time-varying behavior of contaminating substances. The proposed model is initially based on the individuation of possible correlations existing between some pollutants. Afterward, to increase the accuracy of estimated values, the influence of meteorological quantities is taken into account to improve significantly the so-obtained model. Finally, some information about reliability degree of estimate is provided.     

Performance of Reed?Solomon codes using the Guruswami?Sudan algorithm with improved interpolation efficiency

List decoding is a novel method for decoding Reed-Solomon (RS) codes that generates a list of candidate transmitted messages instead of one unique message as with conventional algebraic decoding, making it possible to correct more errors. The Guruswami-Sudan (GS) algorithm is the most efficient list decoding algorithm for RS codes. Until recently only a few papers in the literature suggested practical methods to implement the key steps (interpolation and factorisation) of the GS algorithm that make the list decoding of RS codes feasible. However, the algorithm's high decoding complexity is unsolved and a novel complexity-reduced modification to improve its efficiency is presented. A detailed explanation of the GS algorithm with the complexity-reduced modification is given with simulation results of RS codes for different list decoding parameters over the AWGN and Rayleigh fading channels. A complexity analysis is presented comparing the GS algorithm with our modified GS algorithm, showing the modification can reduce complexity significantly in low error weight situations. Simulation results using the modified GS algorithm show larger coding gains for RS codes with lower code rates, with more significant gains being achieved over the Rayleigh fading channels.     

A methodology for the prioritization of operating experience in nuclear power plants

The processing of operating experience at nuclear power plants is critically important to safe and reliable operations because it represents the process by which important external information is incorporated into the organization. Nuclear power plants typically receive between 800 and 1000 pieces of operating experience every year, of which 70–80 meet the criteria for a more extensive review. This paper deals with the prioritization of these items. Specifically, a prioritization methodology utilizing multiattribute utility theory has been developed. What sets this methodology apart from other techniques employing multiattribute methods is its emphasis on deliberations to achieve consensus among objectives and preferences among those objectives. Along with an explanation of this methodology, the results of its application to the prioritization of operating experience at a nuclear power plant are presented. Lastly, the results of a workshop that was held at MIT are presented. The workshop demonstrated the feasibility of the prioritization methodology and the validity of the case study results.     

Trade and the environment: identifying "hot spot" sectors

A prioritization methodology was developed to identify key "hot spot" sectors that are vulnerable to adverse environmental impacts from trade liberalization. The methodology relies on internationally approved analytical techniques and indicators relevant to the trade and environment issue. Key outputs of this research include the identification of appropriate economic and environmental indicators, an information compilation strategy, and a step-wise procedure to perform the prioritization process. The methodology presented may reduce time and expenses previously incurred in identifying environmental hot spots. It also may assist in prioritizing actions to mitigate negative consequences of trade liberalization in specific sectors. Electronic Publication     

Sift‐proofness of Dangerous Goods Packagings – An Incompletely Defined Requirement

Sift‐proofness is a requirement for different types of dangerous goods packagings for solid substances according to the international Dangerous Goods Regulations. In these regulations, a sift‐proof packaging is defined as a packaging that is completely impermeable to dry contents. This means indirectly that absolutely no mass transport of solid substances is allowed. Moreover, this requirement applies both to the original filling substance and to fine solid material generated during transport. Further specifications, test conditions or tolerable limit values are not given. This is in contrast to physical principles and the usual practice in other fields of technology in which sift‐proofness is relevant. This paper shows the necessary steps for how the requirements for sift‐proofness of dangerous goods packagings can be defined more precisely. Physical basics of the term ‘sift‐proofness’ are explained. A qualitative as well as a quantitative approach is possible. In any case, it is essential to carry out appropriate vibration tests to assess the sift‐proofness. There is a need for systematical investigations of the sift‐proofness of dangerous goods packagings. Copyright © 2017 John Wiley & Sons, Ltd.     

Real-Time Monitoring of High-Dimensional Functional Data Streams via Spatio-Temporal Smooth Sparse Decomposition

High-dimensional data monitoring and diagnosis has recently attracted increasing attention among researchers as well as practitioners. However, existing process monitoring methods fail to fully use the information of high-dimensional data streams due to their complex characteristics including the large dimensionality, spatio-temporal correlation structure, and nonstationarity. In this article, we propose a novel process monitoring methodology for high-dimensional data streams including profiles and images that can effectively address foregoing challenges. We introduce spatio-temporal smooth sparse decomposition (ST-SSD), which serves as a dimension reduction and denoising technique by decomposing the original tensor into the functional mean, sparse anomalies, and random noises. ST-SSD is followed by a sequential likelihood ratio test on extracted anomalies for process monitoring. To enable real-time implementation of the proposed methodology, recursive estimation procedures for ST-SSD are developed. ST-SSD also provides useful diagnostics information about the location of change in the functional mean. The proposed methodology is validated through various simulations and real case studies. Supplementary materials for this article are available online.     

Integrated pollution prevention and control for heavy ceramic industry in Galicia (NW Spain)

The heavy ceramic industry (building materials and refractory products manufacture) is an important source of pollutants to the environment. For this reason these industrial sub-sectors are included in prevention and control pollution policies, specifically those of the European Union. The IPPC Directive pays particular attention to the mineral industries, not least to the ceramic industry (epigraph 3.5, Annex I). In this paper, a methodology which is being applied to support IPPC installations and the competent administrative authority in Galicia (NW Spain) is presented. For that, the Galician heavy ceramic industry is analysed, as also are the ways to study the Best Available Techniques (BAT) with a view to establishing the emission limit values (ELV) for each specific case. Hence, a technological state of the art has been carried out for both sub-sectors, from the point of view of implementation of the IPPC in Galicia. Following this, the processes are described briefly and an analysis of the consumption and emission levels of the main pollutants is made. An inventory that includes the best environmental practices and the preventive and abatement candidate techniques as BAT was elaborated for both considered sub-sectors. An information data sheet for each candidate BAT is presented as a method to help both the industries and the competent authority to identify a candidate technique of the inventory as BAT. Three illustrative examples of the application of this procedure are presented for different emissions to environmental media for Galician installations.     

Uncertainty Estimation in Simultaneous Measurements of Levels and Permittivities of Liquids Using TDR Technique

Time-domain reflectometry (TDR) based on instruments are commonly used for several monitoring methods, particularly in soil moisture and volumetric water-content evaluation. Furthermore, significant advantages of TDR methodology, mostly related to the possible determination in real-time and to a nondestructive approach of the spatial location and nature of various objects, make this technique an appealing candidate for a variety of environmental and industrial applications. In this paper, we show that the suitable combination of TDR-detecting functionalities can lead to a joint quantitative and qualitative monitoring method for liquid-control purposes, so that, in one shot, the analysis of TDR data allow the measurement of liquid levels, the determination of multiple interfaces in layered media, as well as the evaluation of dielectric properties, thus opening challenging perspectives for several monitoring applications, particularly in fluid-processing-related industry. For such purposes, a detailed analysis of the uncertainty of the proposed measurement method is mandatory; hence, a metrological characterization of the method is carried out, demonstrating that the presented technique is definitely valid for simultaneously measuring levels and dielectric constants of liquids, with uncertainties under 2%. Results obtained for different liquid samples validate the approach on a wide range of dielectric materials and demonstrate the robustness and reliability of the proposed TDR technique.     

Corrosive effects from the deposition of gaseous pollutants on surfaces of cultural and artistic value inside museums.

The objectives of the project were to assess the critical relationships between environmental factors and damage of the artifacts and other cultural property exposed inside museums, by studying: (a) the outdoor/indoor pollutant concentration and their transfer inside the museum; (b) the distribution and circulation of pollutants inside the museum influenced by various factors; (c) chemical interactions between pollutants in the gas phase leading to removal and/or formation of secondary pollutants; (d) the final deposition of the indoor pollutants on surfaces of artistic interest and the damage on them, governed by strictly defined physicochemical parameters. All the above information, together with the main factors influencing each stage, were obtained by applying the methodology developed and described in detail here. Measurements of rate constants of reactions in the gas phase, of physicochemical deposition parameters on artefacts, and the synergistic effects of pollutants on the deposition parameters, were conducted. Seven PC programmes for analysing the experimental data were written and used. The pollutants, the solid materials and the museums chosen in this programme are only examples needed to develop the necessary methodology. The numerical results obtained serve the purpose of exemplifying the procedures and not enriching the world's bibliography with useless empirical information. Two commercially available protectives for marble were investigated from the point of view of their reactivity towards SO2 by using a diffusional technique. From measurements of SO2 concentration carried out on three types of marble, the deposition velocities have been calculated. Indoor monitoring of the church of San Luigi dei Francesi and of the Museo della Civiltá Romana in Rome has shown that indoor production of nitrous acid most likely results from heterogeneous reactions indoors, on the walls and the exposed surfaces.     

Broad spectrum analysis of 109 priority compounds listed in the 76/464/CEE Council Directive using solid-phase extraction and GC/EI/MS

A single multiresidue method was developed to determine 109 priority organic compounds included in the 76/464/EEC Council Directive on Pollution of the European Union. Such Directive includes 132 priority pollutants with a broad spectrum of polarities to be analyzed in drinking and surface waters, with the aim to protect water quality. From this list, the compounds analyzed included benzidines, chloroanilines, chloronitrobenzenes, chloronitrotoluenes, chlorophenols, chloronitrotoluidines, PAHs, PCBs, pesticides, phenylurea, and triazine herbicides. The method was developed in four steps. First, automated off-line solid-phase extraction using polymeric sorbent Oasis 60 mg cartridges was optimized to trap 109 compounds. Second, gas chromatography coupled to mass spectrometry with electron impact ionization (GC/EI/MS) was used in selected ion monitoring (SIM) mode for tentative identification of target analytes. Third, GC/EI/MS under full scan conditions was used for spectrum identification and analyte confirmation. Last, quantification was performed from SIM chromatogram using surrogates and internal standard. This method offered excellent sensitivity and selectivity, and the preconcentration of 200 mL permitted the achievement of limits of detection at the low nanogram/liter level and recoveries between 70 and 120%. Such methodology was applied to determine 109 organic compounds in French surface waters, and several pollutants were detected at levels from ppt to ppb. This multiresidue method developed was highly reproducible and robust and permitted a high sample throughput.     

Analytical Quality Control Information System for Chemical Reagents and High-Purity Materials

An information system has been designed for monitoring the quality of chemical reagents and high-purity substances. The information system is based on the international CALS standard (ISO-10303 STEP). It contains the following information for the main elements of analytical monitoring: a list of elements to be monitored (substance classifier), details of the analytical procedure (including the sampling and sample preparation steps), performance parameters of the instruments, metrological support, and normative documentation (GOST standards, technical specifications, and others).     

Results of the MITRA project: monitoring and intervention for the transportation of dangerous goods

The objective of the MITRA (monitoring and intervention for the transportation of dangerous goods) project was to prototype a new operational system for monitoring the transportation of dangerous goods in Europe based on regional responsibilities. This concept, based on systems used in air traffic control, aims to provide civil security centres with real-time knowledge of the position and contents of dangerous vehicles circulating in their area of responsibility, and, in the event of a dangerous situation, to issue warnings, alerts and crisis management information, thereby allowing intervention teams to react immediately with maximum safety. The project was funded by the European Commission under the 6th Framework Programme (STREP--specific targeted research project--under the Information Society Technologies priority). It started on 1 September 2004 and ended on 31 October 2006. This paper presents the results of this project and the conclusions derived from the field tests carried out in Germany and in the French/Spanish border region in order to test the proposed operational system.     

一种改进的无线信道中压缩视频码流的错误隐藏算法

无线信道传输环境不稳定,容易产生随机和突发误码,这对码流相关性很强的压缩视频信号将产生很恶劣的影响,并将在解码端扩散.本文分析了传统错误隐藏算法的原理和局限性,针对信源语义错误隐藏技术计算量大、可能不能得到目标片的缺点,提出一种新的算法,根据无线信道误码的特点,产生与信道情况相关的候选片,利用压缩感知技术的模糊匹配特性,用解析方式得到目标片,并可在此基础上对信道恶劣的情况提出重传建议,计算简单,客观恢复质量较好.     

A nonparametric change detection approach in social networks

A network provides powerful means of representing relationships between entities in complex physical, biological, cyber, and social systems. Any phenomena in those areas may be realized as changes in the structure of the associated networks. Hence, change detection in dynamic networks is an important problem in many areas, such as fraud detection, cyber intrusion detection, and health care monitoring. This article proposes a new methodology for monitoring dynamic networks for quick detection of structural changes in network streams and also estimating the location of the change-point. The proposed methodology utilizes the eigenvalues for the adjacency matrices of network snapshots and employs a nonparametric hypothesis to test if the distribution of the eigenvalues for the current snapshot is different from those of the previous ones along a sliding window of reference networks. The statistic of the nonparametric test, energy distance among eigenvalues, is monitored using a one-sided exponentially weighted moving average control chart. Then, after an anomaly detection signal from the monitoring scheme, eigenvalues for the snapshots are employed to calculate the energy statistic at various time steps to locate the change-point. The proposed method is intended to detect two types of structural changes in the networks: (1) change in the communication rates among individuals and (2) change in the community structure of the network. The proposed methodology is applied to both simulated and real-world data. Results indicate that the proposed methodology provides a reliable tool for monitoring networks streams and also estimating change-points locations for precise assessing of the networks under investigation.     

Organochlorine and organophosphoric insecticides, herbicides and heavy metals residue in industrial wastewaters in Cyprus

Most industries in Cyprus possess permits either for disposal at central wastewater treatment plants (the treated effluent of which is reused or disposed into the sea), or discharge on soil, or reuse either for irrigation or groundwater recharge or discharge into the sea. A preliminary investigation undertaken by the University of Cyprus in regards to dangerous substances was the first step towards establishing a new licensing and monitoring system. Liquid-liquid extraction was used for the extraction of the selected pesticides from wastewaters. Gas chromatography with two different detection methods (ECD and FTD) was applied for the determination of 17 pesticides (12 organochlorine insecticides, 3 organophosphoric insecticides and 2 herbicides). In addition ICP and a mercury evaporation unit were used to determine the concentrations of heavy metals in the samples. The results revealed the presence of several priority substances in wastewaters, in most cases at concentrations well below the regulatory limits. Non-compliance was observed for a limited number of metals. Sixteen out of 17 organic substances that were monitored for 1-year period time were traced in different wastewater streams. What was found out is that there is a need to expand the analytical determinations and the monitoring to more wastewater streams and more priority substances, in order to safeguard the water resources in Cyprus.     

Estimating probabilistic confidence for mixture components identified using a spectral search algorithm

Providing a confidence measure associated with the substance(s) identified in an unknown mixture by a spectral search technique is critical for non-expert users of devices and techniques based on spectroscopy. In this work, a technique for estimating probabilities associated with substances identified by spectral searching is described. In the proposed approach, a mixture analysis algorithm processes the spectrum of an unknown sample using a spectral library to generate a list of substances that may be present in the sample. The partial correlation of each of the substances in the list is then computed. The estimation of the probability is accomplished through a generalized linear model that converts the partial correlation values to a probability measure for each of the mixture components. The statistical properties of partial correlation allow probability estimation irrespective of whether a substance is present in a pure form or within a mixture. The technique was evaluated using both simulated and real Raman spectra of multi-component mixtures, and adequate performance was demonstrated.     

Occurrence and distribution of polycyclic aromatic hydrocarbons in reclaimed water and surface water of Tianjin, China

Persistent organic pollutants (POPs) such as polycyclic aromatic hydrocarbons (PAHs) are of great concern due to their persistence, bioaccumulation and toxic effects. In this work, 16 PAHs included in the US Environmental Protection Agency's (EPA) priority pollutant list were analyzed using solid-phase extraction-gas chromatography-mass spectrometry (SPE-GC-MS) with a selected ion monitoring (SIM) mode. Reclaimed water and surface water sampling was undertaken in Tianjin, northern China. Total PAH concentrations varied from 1800 to 35,000 ng/L in surface waters (main rivers, tributaries, ditches, etc.) with mean value of 14,000 ng/L and from 227 to 600 ng/L in reclaimed water with mean value of 352 ng/L, respectively. The PAH profiles were dominated by low molecular weight PAHs (two- and three-ring components) in reclaimed water samples and surface water samples. These indicated that PAHs in reclaimed water and surface water might origin from oil or sewage contamination (petrogenic input). To elucidate sources, molecular indices based on indices among phenanthrene versus anthracene and fluoranthene versus pyrene were used to evaluate the possible source (pyrogenic and petrogenic sources, respectively) of PAH contamination in reclaimed water and surface water. The collected data showed that petrogenic input was predominant at almost all the stations investigated. To discriminate pattern differences and similarities among samples, principal component analysis (PCA) was performed using a correlation matrix. PCA revealed the latent relationships among all the surface water stations investigated and confirmed our analytical results. The analysis results of the ratios and PCA in this study showed that the ratios and PCA could be applied to the surface water investigation to some extent.     

Identification of the pharmaceuticals for human use contaminating the Italian aquatic environment

A predictive approach seems useful to identify pharmaceuticals in the environment and give an idea of overall levels of contamination, so as to restrict monitoring to those molecules most likely to be contaminants. We propose an approach based on two parts. The first is to rank the molecules according to the predicted environmental loads; the second is to refine the list by analysing the pharmaceuticals in sewage treatment plants (STPs) and comparing the concentrations with levels previously measured in surface water. This approach identified a restricted group of priority pollutants (ofloxacin, furosemide, atenolol, hydrochlorothiazide, carbamazepine, ibuprofen, spiramycin, bezafibrate, erythromycin, lincomycin and clarithromycin) in the aquatic environment in Italy, for further studies and monitoring.