Laboratory waste minimization by recovery of silver as nano-silver colloidal dispersion from waste silver chloride

The use of cyclic experiments, where the product of one reaction becomes the starting material for the next experiment, was proposed as an effective protocol for waste minimization in an educational lab. A simple, cheap and pollution-free method was developed for recovering silver as nano-silver colloidal dispersion from waste silver chloride in the laboratories of the Faculty of Health, Safety and Environment. Silver nanoparticles of the size 5–18 nm were recovered in the presence of sodium borohydride as a reducing agent and polyvinylpyrrolidone as a stabilizer agent. The nano-silver particles were studied for their formation, structure, stability and size using UV–Vis spectroscopy, transmission electron microscopy and dynamic light scattering techniques. The antibacterial assays of nanoparticles showed satisfactory results for Escherichia coli ATCC25922, Staphylococcus aureus ATCC 29213, and Acinetobacter baumanii (Clinical isolate). A laboratory experiment was designed in which students synthesize yellow colloidal silver solution from chemical waste silver chloride and estimate particle size using visible spectroscopy.     

Photo–degradable and recyclable starch/Fe3O4/TiO2 nanocomposites: feasibility of an approach to reduce the recycling labor cost in plastic waste management

Environmental Science and Pollution Research - In this research, a biodegradable starch/Fe3O4/TiO2 bio-nanocomposites (SFT) were produced using different nano Fe3O4/TiO2 (FT) (3, 5, and 10 (wt% dry...     

Habitat suitability for the Caucasian frog <Emphasis Type="Italic">Rana macrocnemis</Emphasis> Boulenger, 1885 (Amphibia:Anura: Ranidae)

Modeling the distribution patterns of species is a generally efficient tool to assess their ecological characteristics. In this study, we compared ecological niche factor analysis (ENFA) and maximum entropy (Maxent) techniques to predict the most suitable distribution range of Rana macrocnemis. The Maxent model predicted potential suitable habitats for R. macrocnemis with high success rates (AUC Training data = 0.877 ± 0.039). According to the map constructed, three important variables had high contribution to species presence: temperature (50.4%), land cover (24.6%) and elevation (14.4%) variables. The ENFA results were relatively similar to Maxent jackknife analysis. The results implied that R. macrocnemis prefers grassland and needle leaf deciduous forest with high elevations, and low temperature.     

Effects of aerobic exercise on histopathology and toxicology of ZnO and nano ZnO in male rats

The effects of four weeks of aerobic exercise on histopathological and toxicological effects induced by nano ZnO and ZnO powders in male rats were evaluated. Tissue sections of liver and kidneys of ZnO and nano ZnO rats showed some histopathological changes, which were partly reverted by exercise. ZnO and nano ZnO treatments caused an increase in the level of tumor necrosis factor-α, while the mean of Interleukin 10 was declined. Exercise training enhanced the mean value of and declined mean level of in rats treated with ZnO and nano ZnO. The ZnO and ZnO groups demonstrated the highest means of insulin resistance, low density lipoprotein, cholesterol, triglyceride levels and lower mean value of compared to the other groups, while exercise resulted in improvement in mean of these factors.     

Bottled water quality ranking via the multiple-criteria decision-making process: a case study of two-stage fuzzy AHP and TOPSIS

Environmental Science and Pollution Research - Access to healthy drinking water is vital to human health and development. Bottled water consumption has been on the rise in recent years. As several...     

Biomonitoring of unmetabolized polycyclic aromatic hydrocarbons (PAHs) in urine of waterpipe/cigarette café workers

Environmental Science and Pollution Research - Fresh tobacco or the smoke resulting from waterpipe and cigarette contains large amounts of polycyclic aromatic hydrocarbons (PAHs), which consumption...     

Trace element concentration levels in three bird species in Hormod Protected Area,Larestan, Iran

The objective of the present study was to investigate the levels of Cd, Pb, Co, and Cu, in A. chukar, A. griseogularis, and Columba livia, in order to (1) examine the age- and gender-related variation in trace metal accumulation and (2) to determine the significance between metal concentrations in the kidney, liver, and pectoral muscle. Mean concentrations of Cd and Pb in the kidney of A. chukar, A. griseogularis, and C. livia were 3.7, 4.1, and 3.9?µg/g and 15.9, 13.6, and 15.5?µg/g, respectively. In the liver, they were 4.8, 4.3, and 3.9?µg/g and 21.4, 21.3, and 21.1?µg/g, and in the pectoral muscle, 2.3, 2.3, and 2.2?µg/g and 7.1, 7.1, and 7.8?µg/g, respectively. Metal concentrations in three bird species were decreased in the sequence of liver?>?kidney?>?pectoral muscle. Trace metal concentrations in the three species were higher in females than in males. The mean concentrations of Cd in the kidney and liver were higher than the background levels, as well as Pb concentrations in the liver were higher than the toxic level.     

LaSVM-based big data learning system for dynamic prediction of air pollution in Tehran

Due to critical impacts of air pollution, prediction and monitoring of air quality in urban areas are important tasks. However, because of the dynamic nature and high spatio-temporal variability, prediction of the air pollutant concentrations is a complex spatio-temporal problem. Distribution of pollutant concentration is influenced by various factors such as the historical pollution data and weather conditions. Conventional methods such as the support vector machine (SVM) or artificial neural networks (ANN) show some deficiencies when huge amount of streaming data have to be analyzed for urban air pollution prediction. In order to overcome the limitations of the conventional methods and improve the performance of urban air pollution prediction in Tehran, a spatio-temporal system is designed using a LaSVM-based online algorithm. Pollutant concentration and meteorological data along with geographical parameters are continually fed to the developed online forecasting system. Performance of the system is evaluated by comparing the prediction results of the Air Quality Index (AQI) with those of a traditional SVM algorithm. Results show an outstanding increase of speed by the online algorithm while preserving the accuracy of the SVM classifier. Comparison of the hourly predictions for next coming 24 h, with those of the measured pollution data in Tehran pollution monitoring stations shows an overall accuracy of 0.71, root mean square error of 0.54 and coefficient of determination of 0.81. These results are indicators of the practical usefulness of the online algorithm for real-time spatial and temporal prediction of the urban air quality.     

Hospital site selection using fuzzy AHP and its derivatives

Environmental managers are commonly faced with sophisticated decisions, such as choosing the location of a new facility subject to multiple conflicting criteria. This paper considers the specific problem of creating a well-distributed network of hospitals that delivers its services to the target population with minimal time, pollution and cost. We develop a Multi-Criteria Decision Analysis process that combines Geographical Information System (GIS) analysis with the Fuzzy Analytical Hierarchy Process (FAHP), and use this process to determine the optimum site for a new hospital in the Tehran urban area. The GIS was used to calculate and classify governing criteria, while FAHP was used to evaluate the decision factors and their impacts on alternative sites. Three methods were used to estimate the total weights and priorities of the candidate sites: fuzzy extent analysis, center-of-area defuzzification, and the α-cut method. The three methods yield identical priorities for the five alternatives considered. Fuzzy extent analysis provides less discriminating power, but is simpler to implement and compute than the other two methods. The α-cut method is more complicated, but integrates the uncertainty and overall attitude of the decision-maker. The usefulness of the new hospital site is evaluated by computing an accessibility index for each pixel in the GIS, defined as the ratio of population density to travel time. With the addition of a new hospital at the optimum site, this index improved over about 6.5 percent of the geographical area.