Transition index maps for urban growth simulation: application of artificial neural networks,weight of evidence and fuzzy multi-criteria evaluation

Transition index maps (TIMs) are key products in urban growth simulation models. However, their operationalization is still conflicting. Our aim was to compare the prediction accuracy of three TIM-based spatially explicit land cover change (LCC) models in the mega city of Mumbai, India. These LCC models include two data-driven approaches, namely artificial neural networks (ANNs) and weight of evidence (WOE), and one knowledge-based approach which integrates an analytical hierarchical process with fuzzy membership functions (FAHP). Using the relative operating characteristics (ROC), the performance of these three LCC models were evaluated. The results showed 85%, 75%, and 73% accuracy for the ANN, FAHP, and WOE. The ANN was clearly superior compared to the other LCC models when simulating urban growth for the year 2010; hence, ANN was used to predict urban growth for 2020 and 2030. Projected urban growth maps were assessed using statistical measures, including figure of merit, average spatial distance deviation, producer accuracy, and overall accuracy. Based on our findings, we recomend ANNs as an and accurate method for simulating future patterns of urban growth.     

Characterization and Optimization of Persian Gum/Whey Protein Bionanocomposite Films Containing Betanin Nanoliposomes for Food Packaging Utilization

Journal of Polymers and the Environment - In this study, composite packaging films were produced from relatively inexpensive materials including Whey protein isolate (WPI) and Persian gum (PG),...     

Indigenous knowledge about climate change and sustainability of nomadic livelihoods: understanding adaptability coping strategies

Environment, Development and Sustainability - Indigenous knowledge about climate change that makes adaptability necessary by coping strategies leads to the sustainability of nomadic livelihoods....     

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...     

Development of Regenerated Cellulose/Citric Acid Films with Ionic Liquids

Nowadays, the importance of green and biodegradable plastics as viable substitutes for non-degradable petroleum-based materials is felt more than ever. Regenerated cellulose (RC) as a potential candidate suffers from poor processability and inferior properties, limiting its wide applications. In this study, it is demonstrated that citric acid (CA) enhances physical, mechanical, and thermal properties of RC films, due to RC-citric acid compatibility. 1-ethyl-3-methylimidazolium chloride (EMIMCl) as a green ionic liquid was employed for the processing of RC. The optimum properties in terms of thermal stability, mechanical strength, contact angle, water uptake, and oxygen permeability were achieved at 10 wt% of CA. However, further incorporation of CA adversely affected the film properties. This behaviour was explained by the crosslinking and plasticizing effects of CA. Furthermore, in vitro cytotoxicity test demonstrated that RC/CA films are cytocompatible, suggesting the potential advantage of using these biopolymeric films for biomaterial and biological applications.

     

Synergism effects of phenol-degrading yeast and ammonia-oxidizing bacteria for nitrification in coke wastewater of Esfahan Steel Company.

Ammonia-oxidizing bacteria and phenol-degrading yeast were isolated in order to study the synergism effects of phenol-degrading yeast and ammonia-oxidizing bacteria for enhancing the nitrification in coke wastewater from the Isfahan Steel Company. The influent and effluent samples with approximately 600-1200 mg L(-1) ammonium and 550-2350 mg L(-1) phenol were collected aseptically in sterile flasks. The biodegradation of phenol and nitrification were studied with different treatments. The results showed that addition of Na2CO3 and autotrophic bacteria to wastewater increased the ammonium removal by 100%. Furthermore, the synergism effects of phenol-degrader yeast and autotrophic bacteria reduced the time for ammonium removal.     

Performance of activated carbon coated graphite bipolar electrodes on capacitive deionization method for salinity reduction

• Graphite bipolar electrodes act as an appropriate bed for the CDI process. • Activated carbon Coating improves the application of the electrodes. • CDI is an environmentally friendly method to apply for brackish water. • Initial concentration is the most important parameter in the CDI method. • CDI process in a batch-mode setup needs more development. This research investigates a capacitive deionization method for salinity reduction in a batch reactor as a new approach for desalination. Reductions of cost and energy compared with conventional desalination methods are the significant advantages of this approach. In this research, experiments were performed with a pair of graphite bipolar electrodes that were coated with a one-gram activated carbon solution. After completing preliminary tests, the impacts of four parameters on electrical conductivity reduction, including (1) the initial concentration of feed solution, (2) the duration of the tests, (3) the applied voltage, and (4) the pH of the solution, were examined. The results show that the maximum efficiency of electrical conductivity reduction in this laboratory-scale reactor is about 55%. Furthermore, the effects of the initial concentration of feed solution are more significant than the other parameters. Thus, using the capacitive deionization method for water desalination with low and moderate salt concentrations (i.e., brackish water) is proposed as an affordable method. Compared with conventional desalination methods, capacitive deionization is not only more efficient but also potentially more environmentally friendly.     

Investigating surface roughness,material removal rate and corrosion resistance in PMEDM of γ-TiAl intermetallic

Titanium aluminide intermetallics offer an attractive combination of low density and good oxidation, corrosion and ignition resistance with unique mechanical properties. In this study two series of machining tests are designed. Firstly the powder mixed electrical discharge machining (PMEDM) of γ-TiAl by means of different powders such as aluminum, chrome, silicon carbide, graphite and iron is performed to investigate the output characteristics of surface roughness and topography, material removal rate (MRR), electrochemical corrosion resistance of machined samples and also the machined surfaces are investigated by means of EDS and XRD analyses. Secondly after selection the aluminum powder as the most appropriate kind of powder, the current, pulse on time, powder size and powder concentration are changed in different levels for overall comparison between EDM and PMEDM output characteristics. In the first setting of input machining parameters, aluminum powder improves the surface roughness of TiAl sample about 32% comparing with EDM case and also aluminum particles with the size of 2 μm, in the second setting of input parameters lead to 54% enhancement of MRR comparing with EDM case. The electrochemical corrosion results show that, corrosion resistance of the samples which are machined by graphite and chrome powders respectively are about three and two times more than the sample which is machined without powder.     

Assessment of temporal and spatial water quality in international Gomishan Lagoon,Iran, using multivariate analysis

Coastal lagoon ecosystems are vulnerable to eutrophication, which leads to the accumulation of nutrients from the surrounding watershed over the long term. However, there is a lack of information about methods that could accurate quantify this problem in rapidly developed countries. Therefore, various statistical methods such as cluster analysis (CA), principal component analysis (PCA), partial least square (PLS), principal component regression (PCR), and ordinary least squares regression (OLS) were used in this study to estimate total organic matter content in sediments (TOM) using other parameters such as temperature, dissolved oxygen (DO), pH, electrical conductivity (EC), nitrite (NO₂), nitrate (NO₃), biological oxygen demand (BOD), phosphate (PO₄), total phosphorus (TP), salinity, and water depth along a 3-km transect in the Gomishan Lagoon (Iran). Results indicated that nutrient concentration and the dissolved oxygen gradient were the most significant parameters in the lagoon water quality heterogeneity. Additionally, anoxia at the bottom of the lagoon in sediments and re-suspension of the sediments were the main factors affecting internal nutrient loading. To validate the models, R², RMSECV, and RPDCV were used. The PLS model was stronger than the other models. Also, classification analysis of the Gomishan Lagoon identified two hydrological zones: (i) a North Zone characterized by higher water exchange, higher dissolved oxygen and lower salinity and nutrients, and (ii) a Central and South Zone with high residence time, higher nutrient concentrations, lower dissolved oxygen, and higher salinity. A recommendation for the management of coastal lagoons, specifically the Gomishan Lagoon, to decrease or eliminate nutrient loadings is discussed and should be transferred to policy makers, the scientific community, and local inhabitants.