In recent years, food packaging has evolved from an inert and polluting waste that remains after using the product toward an active item that can be consumed along with the food it contains. Edible films and coatings represent a healthy alternative to classic food packaging. Therefore, a significant number of studies have focused on the development of biodegradable enveloping materials based on biopolymers. Animal and vegetal proteins, starch, and chitosan from different sources have been used to prepare adequate packaging for perishable food. Moreover, these edible layers have the ability to carry different active substances such as essential oils—plant extracts containing polyphenols—which bring them considerable antioxidant and antimicrobial activity. This review presents the latest updates on the use of edible films/coatings with different compositions with a focus on natural compounds from plants, and it also includes an assessment of their mechanical and physicochemical features. The plant compounds are essential in many cases for considerable improvement of the organoleptic qualities of embedded food, since they protect the food from different aggressive pathogens. Moreover, some of these useful compounds can be extracted from waste such as pomace, peels etc., which contributes to the sustainable development of this industry.

This article assesses the surface water quality of the Strîmtori-Firiza reservoir by analyzing 14 physicochemical parameters among 9 metals in 18 sampling points. A series of possible reservoir pollutants were identified, depending on the nature of the pollutants and their loading. The novelty of the paper consists in the broad spectrum of investigations that includes spatial distribution cluster analysis and mathematical modeling. This article presents an innovative method of assessing the distributions of the metal loads as maps of metal distribution that are in accordance with the developed mathematical models that aim to present the pollutant distribution and the degree of correlation between the physicochemical indicators. The clusters were generated using Ward's and Nearest Neighbor methods that are less used in the studies concerning the analysis of water quality. Measures for maintaining the quality of the water reservoir are proposed considering the importance of the reservoir as source for drinking/industrial water.

Analgesics and nonsteroidal anti-inflammatory drugs (NSAIDs) such as paracetamol, diclofenac, and ibuprofen are frequently encountered in surface and ground water, thereby posing a significant risk to aquatic ecosystems. Our study reports the catalytic performances of nanosystems TiO2 -MexOy (Me = Ce, Sn) prepared by the sol-gel method and deposited onto glass slides by a dip-coating approach in the removal of paracetamol from aqueous solutions by catalytic ozonation. The effect of catalyst type and operation parameters on oxidation efficiency was assessed. In addition to improving this process, the present work simplifies it by avoiding the difficult step of catalyst separation. It was found that the thin films were capable of removing all pollutants from target com-pounds to the oxidation products.

Studies on the Nessler's reagent method were performed considering the spectrum of the complex formed of ammonium with the Nessler's reagent, the stability over the time of the absorbance of complex. The method was validated statistically and by recovery studies for linearity, precision, repeatability, and reproducibility. The obtained results proved that the method can be employed for the routine analysis of ammonium in diluted solution as the wet deposition samples. Analysis of wet depositions was performed on samples of precipitation collected from urban and rural.

The octane number (ON, MON and PON) for the molecular structures of 18 octane isomers have been correlated using the quantitative structureproperty relationship (QSPR) method, with topological index SD. For single parameter correlation the index SD shows poor results (RON, r = 0.406; MON, r = 0.490; PON, r = 0.448), whereas for two-parameter correlation almost any combination among the above DC was found to give relatively high r value. The best correlation coefficients are as follows: for RON, r = 0.993; MON, r = 0.968; PON, r = 0.985. For RON, the best model obtained by our regression analysis is RON = −227.218 + 7.63 ∗ SD − 37.111 ∗ DC , with r = 0.993, s = 4.8, F = 534