1,721,321 research outputs found
GREEN CHEMISTRY: AN ANALYTICAL PERSPECTIVE
No full textIn the last two centuries chemistry has improved our quality of life through the production of thousands of useful products and materials, but this achievement comes at an environmental price. Green chemistry and its principle want to reduce or eliminate the negative environmental impacts and through design, innovation and new processes to restore the planet’s sustainable development. The term “Green Analytical Chemistry”, proposed by J. Namieśnik in the early 2000, at the beginning was scarcely employed in the analytical chemistry community in contrast with green catalyst development and green organic chemistry concepts. Nonetheless, efforts made in analytical chemistry in the past 10 years have led to the adaptation of existing methods and development of new techniques to save time and chemicals, and to improve overall performance in agreement with the green chemistry principles. It seems straightforward to consider green analytical chemistry as that part of the green chemistry devoted to analysis. The impact of the application of green principles to analytical chemistry can be easily realized by considering the number of analysis required around the world to control our health, the quality and safety of all kinds of products and to monitor the environment. In fact, it is well known that analysis requires employment of a great amount of chemicals and energy and it provides some collateral risks for both, operators and the environment, due to the use of toxic reagents and solvents and the generation of dangerous wastes. In this keynote lecture, some of the main tools to greening analytical procedures will be revised. In particular, the talk will focus on the efforts required for improving the analytical practices in order to minimize adverse effects such as: the replacement of toxic solvents and reagents by safer ones, the miniaturization of analytical procedures with a resulting reduction in the waste production and analysis time, the strong reduction of the analytical steps or the analysis of untreated samples. All of these steps are significant parts of methodologies that could contribute to improve the safety of analytical procedures and to minimize environmental dangers. Moreover, as green analytical chemistry procedures have to maintain and/or improve the quality of analytical data, chemometric aspects will be examined. In particular multiparametric measurements and remote sensing methodology able to enhance the information obtained with reduced analytical task will be discussed
PM2.5 PCA-APCS Source Apportionment of a site monitored near a waste incinerator plant located in Bologna Area
No full textReceptor modelling is one of the application of multivariate analysis dealing with the identification and quantitative apportionment of air pollutants to their potential sources.
Various statistical multivariate models including principal component analysis-absolute principal component scores (PCA-APCS) have been proposed to identify and to ascertain the contribution of different sources to monitored ambient concentrations. Many studies have been reported on the apportionment of the PM, but most of them are focused only on the inorganic species of PM10, and there are only few works dealing with the apportionment of PM2.5 monitored near incinerator plants. In this work the amount and distribution of both inorganic and organic components of PM2.5 were investigated and PCA-APCS method applied for source apportionment. The daily PM2.5 samples were collected in a monitoring station placed in the maximum impact area of the incinerator fallout previously determined by ADMS-Urban, a gaussian modified dispersion model
Advances in Programmed Field Decay Thermal Field Flow Fractionation of Polymers: Direct and inverse calibration methods
No full textThermal Field Flow Fractionation of charged Particles
No full textThermal Field Flow Fractionation (ThFFF) of various types of submicronic particles is experimentally investigated uder different conditions: ionic strength, pH, surfactants. These experiments allows for ThFFF calibration based on particle dimension (radius) and temperature. The influence of surface potential on thermofoteric motion was also eploited
Determinazione mediante SPNE-MEKC di nucleosidi
No full textL'impiego di nanoparticelle d’oro (AuNPs) come mezzo adsorbente è una applicazione in rapida espansione a causa delle loro proprietà intrinseche che le rendono uno strumento molto promettente. A tal proposito, tali nanomateriali possono essere sintetizzati in una vasta gamma dimensionale (1-150 nm) con una limitata dispersione dimensionale, sulla loro superficie possono essere adsorbiti più agenti di targeting e/o terapeutici, infine il nucleo è atossico, biocompatibile e inerte [3].
Lo scopo del presente lavoro è stato quello di valutare l'interazione tra alcune molecole ad attività farmacologica, il cui interesse è dovuto alla loro attività farmacologica come farmaci antibiotici, antivirali e/o antitumorali, e le nanoparticelle d’oro (AuNPs) e di indagare l'applicabilità di queste NPs in sistemi di nano-estrazione in fase solida (Solid Phase Nano Extraction SPNE)
Analisi chimica di miscele complesse di interesse ambientale: individuazione e caratterizzazione di serie omologhe
No full textLe serie omologhe di composti organici (come alcani, acidi carbossilici ecc.) possono essere considerate come marker molecolari per la caratterizzazione e l’individuazione delle sorgenti di emissione delle stesse, per esempio in un campione di tipo ambientale (sorgente antropogenica o sorgente biogenica). L’identificazione e la caratterizzazione di serie omologhe è stata effettuata tramite analisi GC-MS (Gas Cromatografia – Spettrometria di Massa). Un approccio di tipo matematico statistico, basato sullo studio della Funzione di Autocovarianza (ACVF), risulta essere uno strumento fondamentale per l’estrapolazione di informazioni molecolari e strutturali a partire dal segnale gascromatografico, in particolare per l’identificazione della presenza di serie omologhe e la quantificazione dei termini della serie stessa. L’individuazione delle sorgenti di emissione viene effettuata tramite il calcolo di alcuni indici parametrici che si riferiscono al rapporto tra quantità di termini pari rispetto ai dispari (e.g. CPI, Carbon Preference Index). Dallo studio statistico del cromatogramma ottenuto dall’analisi GC-MS è possibile determinare un indice correlabile al CPI
Fourier Analysis of Multicomponent Chromatograms. Recognition of Retention Patterns
No full textA procedure based on fitting the experimentally computed autocovariance function (ACVF) of multicomponent chromatograms to theoretical models is introduced by which both the single component interdistance model (IM) of the retention times is tested and the statistical attributes of the multicomponent chromatogram (I.e. number m of single components, peak width, and parameters of the IM) are determined. Four different IM—exponential, uniform, normal, and gamma—are considered. In essence, when fitted to these theoretical models, the experimental ACVF—expressing the chromatographic response correlation on the time distance—provides the information necessary to establish both the type of retention pattern and gives the necessary parameter estimation. The procedure is tested by using computer-generated chromatograms with different IMs and uncorrelated peak heights, in which density and m are varied. It is shown that the chromatographic attributes m and peak width derived from the best fitting IM are unbiased. Moreover, even if the best fitting IMs do not always coincide with the true model, because of their flexibility and approximating properties they always give a correct description of the retention pattern provided that the results are correctly interpreted. © 1992, American Chemical Society. All rights reserved
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