999 resultados para Resource Extraction
Resumo:
A procedure for the determination of seven indicator PCBs in soils and sediments using microwave-assisted extraction (MAE) and headspace solid-phase microextraction (HS-SPME) prior to GC-MS/MS is described. Optimization of the HS-SPME was carried out for the most important parameters such as extraction time, sample volume and temperature. The adopted methodology has reduced consumption of organic solvents and analysis runtime. Under the optimized conditions, the method detection limit ranged from 0.6 to 1 ng/g when 5 g of sample was extracted, the precision on real samples ranged from 4 to 21% and the recovery from 69 to 104%. The proposed method, which included the analysis of a certified reference material in its validation procedure, can be extended to several other PCBs and used in the monitoring of soil or sediments for the presence of PCBs.
Resumo:
The main objective of this research is to exploit the possibility of using an ex situ solvent extraction technique for the remediation of soils contaminated with semi-volatile petroleum hydrocarbons. The composition of the organic phase was chosen in order to form a single phase mixture with an aqueous phase and simultaneously not being disturbed (forming stable emulsions) by the soil particles hauling the contaminants. It should also permit a regeneration of the organic solvent phase. As first, we studied the miscibility domain of the chosen ternary systems constituted by ethyl acetate–acetone–water. This system proved to satisfy the previous requirements allowing for the formation of a single liquid phase mixture within a large spectrum of compositions, and also allowing for an intimate contact with the soil. Contaminants in the diesel range within different functional groups were selected: xylene, naphthalene and hexadecane. The analytical control was done by gas chromatography with FID detector. The kinetics of the extractions proved to be fast, leading to equilibrium after 10 min. The effect of the solid–liquid ratio on the extraction efficiency was studied. Lower S/L ratios (1:8, w/v) proved to be more efficient, reaching recoveries in the order of 95%. The option of extraction in multiple contacts did not improve the recovery in relation to a single contact. The solvent can be regenerated by distillation with a loss around 10%. The contaminants are not evaporated and they remain in the non-volatile phase. The global results show that the ex situ solvent extraction is technically a feasible option for the remediation of semi-volatile aromatic, polyaromatic and linear hydrocarbons.
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Microwave-assisted extraction (MAE) of agar from Gracilaria vermiculophylla, produced in an integrated multitrophic aquaculture (IMTA) system, from Ria de Aveiro (northwestern Portugal), was tested and optimized using response surface methodology. The influence of the MAE operational parameters (extraction time, temperature, solvent volume and stirring speed) on the physical and chemical properties of agar (yield, gel strength, gelling and melting temperatures, as well as, sulphate and 3,6-anhydro-Lgalactose contents) was evaluated in a 2^4 orthogonal composite design. The quality of the extracted agar compared favorably with the attained using traditional extraction (2 h at 85ºC) while reducing drastically extraction time, solvent consumption and waste disposal requirements. Agar MAE optimum results were: an yield of 14.4 ± 0.4%, a gel strength of 1331 ± 51 g/cm2, 40.7 ± 0.2 _C gelling temperature, 93.1 ± 0.5ºC melting temperature, 1.73 ± 0.13% sulfate content and 39.4 ± 0.3% 3,6-anhydro-L-galactose content. Furthermore, this study suggests the feasibility of the exploitation of G. vermiculophylla grew in IMTA systems for agar production.
Resumo:
An electrochemical method is proposed for the determination of maltol in food. Microwave-assisted extraction procedures were developed to assist sample pre-treating steps. Experiments carried out in cyclic voltammetry showed an irreversible and adsorption controlled reduction of maltol. A cathodic peak was observed at -1.0 V for a Hanging Mercury Drop Electrode versus an AgCl/Ag (in saturated KCl), and the peak potential was pH independent. Square wave voltammetric procedures were selected to plot calibration curves. These procedures were carried out with the optimum conditions: pH 6.5; frequency 50 Hz; deposition potential 0.6 V; and deposition time 10 s. A linear behaviour was observed within 5.0 × 10-8 and 3.5 × 10-7 M. The proposed method was applied to the analysis of cakes, and results were compared with those obtained by an independent method. The voltammetric procedure was proven suitable for the analysis of cakes and provided environmental and economical advantages, including reduced toxicity and volume of effluents and decreased consumption of reagents.
Resumo:
This work reports the study of the combination of soil vapor extraction (SVE) with bioremediation (BR) to remediate soils contaminated with benzene. Soils contaminated with benzene with different water and natural organic matter contents were studied. The main goals were: (i) evaluate the performance of SVE regarding the remediation time and the process efficiency; (ii) study the combination of both technologies in order to identify the best option capable to achieve the legal clean up goals; and (iii) evaluate the influence of soil water content (SWC) and natural organic matter (NOM) on SVE and BR. The remediation experiments performed in soils contaminated with benzene allowed concluding that: (i) SVE presented (a) efficiencies above 92% for sandy soils and above 78% for humic soils; (b) and remediation times from 2 to 45 h, depending on the soil; (ii) BR showed to be an efficient technology to complement SVE; (iii) (a) SWC showed minimum impact on SVE when high airflow rates were used and led to higher remediation times for lower flow rates; (b) NOM as source of microorganisms and nutrients enhanced BR but hindered the SVE due the limitation on the mass transfer of benzene from the soil to the gas phase.
Resumo:
The present work describes the development of an analytical method for the determination of methiocarb and its degradation products (methiocarb sulfoxide and methiocarb sulfone) in banana samples, using the QuEChERS (quick, easy, cheap, effective, rugged, and safe) procedure followed by liquid chromatography coupled to photodiode array detector (LCPAD). Calibration curves were linear in the range of 0.5−10 mg L−1 for all compounds studied. The average recoveries, measured at 0.1 mg kg−1 wet weight, were 92.0 (RSD = 1.8%, n = 3), 84.0 (RSD = 3.9%, n = 3), and 95.2% (RSD = 1.9%, n = 3) for methiocarb sulfoxide, methiocarb sulfone, and methiocarb, respectively. Banana samples treated with methiocarb were collected from an experimental field. The developed method was applied to the analysis of 24 samples (peel and pulp) and to 5 banana pulp samples. Generally, the highest levels were found for methiocarb sulfoxide and methiocarb. Methiocarb sulfone levels were below the limit of quantification, except in one sample (not detected).
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QuEChERS original method was modified into a new version for pesticides determination in soils. The QuEChERS method is based on liquid–liquid portioning with ACN and was followed by cleanup step using dispersive SPE and disposable pipette tips. Gas chromatographic separation with MS detection was carried out for pesticides quantification. The method was validated using recovery experiments for 36 multiclass pesticides. Mean recoveries of pesticides at each of the four spiking levels between 10–300 µg/kg of soil ranged from 70–120% for 26 pesticides with RSD values less than 15%. The method achieved low limit of detection less than 7.6 µ g/kg. Matrix effects were observed for 13 pesticides. Matrix effects were compensated by using matrix-matched calibration. The method was applied successfully using d-SPE or DPX in the analysis of the pesticides in soils from organic farming and integrated pest management.
Resumo:
Food lipid major components are usually analyzed by individual methodologies using diverse extractive procedures for each class. A simple and fast extractive procedure was devised for the sequential analysis of vitamin E, cholesterol, fatty acids, and total fat estimation in seafood, reducing analyses time and organic solvent consumption. Several liquid/liquid-based extractive methodologies using chlorinated and non-chlorinated organic solvents were tested. The extract obtained is used for vitamin E quantification (normal-phase HPLC with fluorescence detection), total cholesterol (normal-phase HPLC with UV detection), fatty acid profile, and total fat estimation (GC-FID), all accomplished in <40 min. The final methodology presents an adequate linearity range and sensitivity for tocopherol and cholesterol, with intra- and inter-day precisions (RSD) from 3 to 11 % for all the components. The developed methodology was applied to diverse seafood samples with positive outcomes, making it a very attractive technique for routine analyses in standard equipped laboratories in the food quality control field.
Resumo:
An analytical method using microwave-assisted extraction (MAE) and liquid chromatography (LC) with fluorescence detection (FD) for the determination of ochratoxin A (OTA) in bread samples is described. A 24 orthogonal composite design coupled with response surface methodology was used to study the influence of MAE parameters (extraction time, temperature, solvent volume, and stirring speed) in order to maximize OTA recovery. The optimized MAE conditions were the following: 25 mL of acetonitrile, 10 min of extraction, at 80 °C, and maximum stirring speed. Validation of the overall methodology was performed by spiking assays at five levels (0.1–3.00 ng/g). The quantification limit was 0.005 ng/g. The established method was then applied to 64 bread samples (wheat, maize, and wheat/maize bread) collected in Oporto region (Northern Portugal). OTAwas detected in 84 % of the samples with a maximum value of 2.87 ng/g below the European maximum limit established for OTA in cereal products of 3 ng/g.
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Future distribution systems will have to deal with an intensive penetration of distributed energy resources ensuring reliable and secure operation according to the smart grid paradigm. SCADA (Supervisory Control and Data Acquisition) is an essential infrastructure for this evolution. This paper proposes a new conceptual design of an intelligent SCADA with a decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). This SCADA model is used to support the energy resource management undertaken by a distribution network operator (DNO). Resource management considers all the involved costs, power flows, and electricity prices, allowing the use of network reconfiguration and load curtailment. Locational Marginal Prices (LMP) are evaluated and used in specific situations to apply Demand Response (DR) programs on a global or a local basis. The paper includes a case study using a 114 bus distribution network and load demand based on real data.
Resumo:
This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.
Resumo:
The automatic acquisition of lexical associations from corpora is a crucial issue for Natural Language Processing. A lexical association is a recurrent combination of words that co-occur together more often than expected by chance in a given domain. In fact, lexical associations define linguistic phenomena such as idiomes, collocations or compound words. Due to the fact that the sense of a lexical association is not compositionnal, their identification is fundamental for the realization of analysis and synthesis that take into account all the subtilities of the language. In this report, we introduce a new statistically-based architecture that extracts from naturally occurring texts contiguous and non contiguous. For that purpose, three new concepts have been defined : the positional N-gram models, the Mutual Expectation and the GenLocalMaxs algorithm. Thus, the initial text is fisrtly transformed in a set of positionnal N-grams i.e ordered vectors of simple lexical units. Then, an association measure, the Mutual Expectation, evaluates the degree of cohesion of each positional N-grams based on the identification of local maximum values of Mutual Expectation. Great efforts have also been carried out to evaluate our metodology. For that purpose, we have proposed the normalisation of five well-known association measures and shown that both the Mutual Expectation and the GenLocalMaxs algorithm evidence significant improvements comparing to existent metodologies.
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Securing group communication in wireless sensor networks has recently been extensively investigated. Many works have addressed this issue, and they have considered the grouping concept differently. In this paper, we consider a group as being a set of nodes sensing the same data type, and we alternatively propose an efficient secure group communication scheme guaranteeing secure group management and secure group key distribution. The proposed scheme (RiSeG) is based on a logical ring architecture, which permits to alleviate the group controller’s task in updating the group key. The proposed scheme also provides backward and forward secrecy, addresses the node compromise attack, and gives a solution to detect and eliminate the compromised nodes. The security analysis and performance evaluation show that the proposed scheme is secure, highly efficient, and lightweight. A comparison with the logical key hierarchy is preformed to prove the rekeying process efficiency of RiSeG. Finally, we present the implementation details of RiSeG on top of TelosB sensor nodes to demonstrate its feasibility.
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Composition is a practice of key importance in software engineering. When real-time applications are composed it is necessary that their timing properties (such as meeting the deadlines) are guaranteed. The composition is performed by establishing an interface between the application and the physical platform. Such an interface does typically contain information about the amount of computing capacity needed by the application. In multiprocessor platforms, the interface should also present information about the degree of parallelism. Recently there have been quite a few interface proposals. However, they are either too complex to be handled or too pessimistic.In this paper we propose the Generalized Multiprocessor Periodic Resource model (GMPR) that is strictly superior to the MPR model without requiring a too detailed description. We describe a method to generate the interface from the application specification. All these methods have been implemented in Matlab routines that are publicly available.
Resumo:
Consider the problem of scheduling a set of implicit-deadline sporadic tasks to meet all deadlines on a uniform multiprocessor platform where each task may access at most one of |R| shared resources and at most once by each job of that task. The resources have to be accessed in a mutually exclusive manner. We propose an algorithm, GIS-vpr, which offers the guarantee that if a task set is schedulable to meet deadlines by an optimal task assignment scheme that allows a task to migrate only when it accesses or releases a resource, then our algorithm also meets the deadlines with the same restriction on the task migration, if given processors 4 + 6|R| times as fast. The proposed algorithm, by design, limits the number of migrations per job to at most two. To the best of our knowledge, this is the first result for resource sharing on uniform multiprocessors with proven performance guarantee.