Comparative study of the absorptive potential of raw and activated carbon <Emphasis Type="Italic">Acacia nilotica</Emphasis> for Reactive Black 5 dye

Acacia nilotica was used for the adsorption of Reactive Black 5 (RB5) dye from an aqueous solution. Both the raw and activated (with H₃PO₄) carbon forms of Acacia nilotica (RAN and ANAC, respectively) were used for comparison. Various parameters (including dye concentration, contact time, temperature, and pH) were optimized to obtain the maximum adsorption capacity. RAN and ANAC were characterized using Fourier transform infrared spectroscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The maximum experimental adsorption capacities for RAN and ANAC were 34.79 and 41.01 mg g^?1, respectively, which agreed with the maximum adsorption capacities predicted by the Langmuir, Freundlich, and Dubinin–Radushkevich equilibrium isotherm models. The adsorption data of ANAC showed a good fit to the isotherm models based on the coefficient of determination (R ²): Langmuir type II (R ² = 0.99) > Freundlich (R ² = 0.9853) > Dubinin–Radushkevich (R ² = 0.9659). This result suggested monolayer adsorption of RB5 dye. The adsorption of RB5 dye followed pseudo-second-order kinetics. The RAN adsorbent reflected an exothermic reaction (enthalpy change, ΔH = ?0.006 kJ mol^?1) and increased randomness (standard entropy change, ΔS = 0.038 kJ mol^?1) at the solid–solution interface. In contrast, ANAC reflected both exothermic [?0.011 kJ mol^?1 (303–313 K)] and endothermic [0.003 kJ mol^?1 (313–323 K)] reactions. However, the ΔS value of ANAC was lower when the RB5 adsorption increased from 313 to 323 K. The negative values for the Gibbs free energy change at all temperatures indicated that the adsorption of RB5 dye onto RAN and ANAC was spontaneous in the forward direction.     

Monitoring hawksbill turtle nesting sites in some protected areas from the Persian Gulf

Iranian nesting populations of the critically endangered hawksbill turtle(Eretmochelys imbricate) are some of the most important in the Indian Ocean. In this study, four of the most important hawksbill nesting grounds in the Persian Gulf, situated within three Iranian marine protected areas, were surveyed during nesting season,including Nakhiloo, Ommolgorm and Kharko Islands and the mainland beaches of the Naiband Marine-Coastal National Park(NMCNP). We present GIS maps of these key nesting grounds and describe sand texture of key nesting zones, along with conservation recommendations. About 9.2(28.3%) out of 32.5 km of all shores surveyed in this study were used by nesting hawksbill turtles follows: Nakhiloo: 1.4 km(52% of potential nesting area);Ommolgorm: 1.94 km(40%); Kharko: 3.4 km(28%), and NMCNP: 2.46 km(18.9%). The average nesting density was calculated as 131 nests/km at Nakhiloo, 76 nests/km at Ommolgorm, 7 nests/km at Kharko, and 15 nests per km at NMCNP. Highest nesting density was observed in Nakhiloo and Ommolgorm. It is thought that high hawksbill nesting density in these islands seems likely a result of limiting adequate nesting shores rather than the size of population, and also low density in Kharko and NMCNP more related to past and current pressures and low population density. With the exception of Ommolgorm Island, sands at the nesting grounds were well sorted.Grain size indicated that female hawksbill turtles in the Iranian Persian Gulf nest in sands that are generally mixed, with mean grain size ranging from coarse sands(0.4Φ;～0.5–1 mm) to fine sands(2Φ;～0.25 mm). We provide and discuss conservation recommendations and suggestions for future.     

Mapping the Risk of Burning in the Brazilian Amazon with the Use of Logistic Regression and Fuzzy Inference

Through the PRODESDIGITAL Project, the National Institute for Space Research (INPE) has been mapping vegetal coverage in the Brazilian Legal Amazon using Landsat satellite images. INPE not only identifies deforested areas but also releases a daily map of burning areas. Burning is frequently used as the cheapest way to deforest, to clear areas for farming and to increase the soil’s fertility in a short period of time. In many instances, these fires get out of control and end up accidentally invading areas of forest exploited by the lumber industry, agricultural plantations and pastures. However, the deforestation and burning area maps alone are insufficient for monitoring and control on a regional scale. It is necessary to know in an analytical way how actions (deforestation and burnings) that characterize human occupation are occurring in a region. In this research, two methods are used that allow the inclusion of co-variation in the estimation of variables of interest: logistic regression, which is a statistical method that considers a categorical or discrete response variable and discrete and/or continuous co-variation; and fuzzy logic, which makes use of artificial intelligence methods to incorporate into computational models information based on the knowledge or experience of a specialist. In both methods, the response variable may be related to the probability of occurrence of the environmental variable under study.     

Phosphorus dynamics and corn growth under applications of corn stalks biochar in a clay soil

Biochar prepared from corn stalks is used as a source of phosphorus in this study. The hypotheses were to investigate effects of biochar applications in clay soil on availability, changes of phosphorus pools and maximum adsorption of phosphorus as well as corn growth. The soil was placed in plastic pots with each contains 3 kg of this soil. Biochar was added at levels of 0 (control), 6.5 (B₁), 19 (B₂), and 38 (B₃) g pot^?1. In this experiment, the pot was planted with corn (Zea mays). The results of this study revealed that the biochar application enhanced available phosphorus (Olsen-P) from 11.51 to 17.10 mg kg^?1. Adding biochar significantly increased the amount of NH₄Cl-P, NaHCO₃-P_o, and NaOH I-P_o fractions (p?≤?0.05), but it significantly decreased HCl-P_i fraction (p?≤?0.05). Addition of biochar at the highest level increased the fresh and dry matter productions by up to about 75 and 48.7%, respectively, compared to the control. The phosphorus uptake by corn plants significantly increased with increasing levels of biochar. The removal efficiency (% sorption) and maximum adsorption (b) of phosphorus increased with increasing level of biochar addition compared to control. Consequently, it is recommended to add biochar produced from corn stalks to the soil in order to substitute phosphate fertilizers.     

Pseudo-static Seismic Bearing Capacity of Shallow Foundations in Unsaturated Soils Employing Limit Equilibrium Method

There exist many structures founded on unsaturated soil deposits. Shear strength augmentation due to the evolution of the matric suction within the unsaturated porous media enhances the bearing capacity of the overlying foundation. This paper presents the evaluation of the pseudo-static seismic bearing capacity of the shallow foundations resting on unsaturated soil deposits using limit equilibrium method. Adopting the Coulomb failure mechanism and Bishop effective stress concept, the bearing capacity equations are solved. The distribution of the matric suction beneath the footing is assumed to be linear. The results of the bearing capacity evaluation are validated against some experimental data found in literature for the static condition. For the seismic loading consideration, the pseudo-static method is utilized. The dual effect of the earthquake acceleration vertical component is thoroughly discussed and a suction transition point is introduced in which the minimum bearing capacity is observed to bear the same value for both upward and downward directions. The increase in the matric suction throughout the soil deposit leads to the increase in the soil shear strength, thus posing more resisting forces as well as higher ultimate bearing capacity. The offered solution is deemed a consistent and useful tool for the accurate prediction of the seismic bearing capacity of shallow footings resting on unsaturated soil deposits.

     

Development Optimization and Uncertainty Analysis Methods for Oil and Gas Reservoirs

Uncertainty complicates the development optimization of oil and gas exploration and production projects, but methods have been devised to analyze uncertainty and its impact on optimal decision-making. This paper compares two methods for development optimization and uncertainty analysis: Monte Carlo (MC) simulation and stochastic programming. Two example problems for a gas field development and an oilfield development are solved and discussed to elaborate the advantages and disadvantages of each method. Development optimization involves decisions regarding the configuration of initial capital investment and subsequent operational decisions. Uncertainty analysis involves the quantification of the impact of uncertain parameters on the optimum design concept. The gas field development problem is designed to highlight the differences in the implementation of the two methods and to show that both methods yield the exact same optimum design. The results show that both MC optimization and stochastic programming provide unique benefits, and that the choice of method depends on the goal of the analysis. While the MC method generates more useful information, along with the optimum design configuration, the stochastic programming method is more computationally efficient in determining the optimal solution. Reservoirs comprise multiple compartments and layers with multiphase flow of oil, water, and gas. We present a workflow for development optimization under uncertainty for these reservoirs, and solve an example on the design optimization of a multicompartment, multilayer oilfield development.     

Prediction of Dust Emission Due to Open Pit Mine Blasting Using a Hybrid Artificial Neural Network

Natural Resources Research - This study developed a new perspective of artificial neural networks using dimensional analysis to be applicable to certain prediction problems. To this end,...     

NMR Parameters Determination through ACE Committee Machine with Genetic Implanted Fuzzy Logic and Genetic Implanted Neural Network

Free fluid porosity and rock permeability, undoubtedly the most critical parameters of hydrocarbon reservoir, could be obtained by processing of nuclear magnetic resonance (NMR) log. Despite conventional well logs (CWLs), NMR logging is very expensive and time-consuming. Therefore, idea of synthesizing NMR log from CWLs would be of a great appeal among reservoir engineers. For this purpose, three optimization strategies are followed. Firstly, artificial neural network (ANN) is optimized by virtue of hybrid genetic algorithm-pattern search (GA-PS) technique, then fuzzy logic (FL) is optimized by means of GA-PS, and eventually an alternative condition expectation (ACE) model is constructed using the concept of committee machine to combine outputs of optimized and non-optimized FL and ANN models. Results indicated that optimization of traditional ANN and FL model using GA-PS technique significantly enhances their performances. Furthermore, the ACE committee of aforementioned models produces more accurate and reliable results compared with a singular model performing alone.     

Assessing the suitability of GlobeLand30 for mapping land cover in Germany

Global land cover (LC) maps have been widely employed as the base layer for a number of applications including climate change, food security, water quality, biodiversity, change detection, and environmental planning. Due to the importance of LC, there is a pressing need to increase the temporal and spatial resolution of global LC maps. A recent advance in this direction has been the GlobeLand30 dataset derived from Landsat imagery, which has been developed by the National Geomatics Center of China (NGCC). Although overall accuracy is greater than 80%, the NGCC would like help in assessing the accuracy of the product in different regions of the world. To assist in this process, this study compares the GlobeLand30 product with existing public and online datasets, that is, CORINE, Urban Atlas (UA), OpenStreetMap, and ATKIS for Germany in order to assess overall and per class agreement. The results of the analysis reveal high agreement of up to 92% between these datasets and GlobeLand30 but that large disagreements for certain classes are evident, in particular wetlands. However, overall, GlobeLand30 is shown to be a useful product for characterizing LC in Germany, and paves the way for further regional and national validation efforts.     

Bioleaching potential of bacterial communities in historic mine waste areas

Microbial activity has the potential to alter all cultural heritage in mining and metallurgy, due to metal mobilization by leaching. This communication shows the consequences of the bioleaching ability of two natural enrichments on copper slag samples from a historic ore smelting site in Sangerhausen (Mansfeld, Südharz, Saxony-Anhalt, Germany). Enrichment cultures gained from mine drainage were dominated by either the iron and sulfur-oxidizing Acidithiobacillus ferrivorans, or by the iron-oxidizing Leptospirillum. During 35 days of bioleaching in media containing copper slag pulp, inoculated with these enrichments, the change in pH and solubilized metal concentrations of the systems were monitored. Both bacterial strains were completely different from each other in their pattern of pH variation and rates of metal solubilization. The maximum removal of Cu (1725 mg/l) and Zn (715 mg/l) from copper slag substrate was achieved with enrichment culture of A. ferrivorans SCUT-1. However, maximum Mn (207 mg/l), Pb (86 mg/l), and Ni (75 mg/l) removal was observed with enrichment culture of Leptospirillum strain YQP-1. Implications for metal mobilization along with alteration of artifacts from not only historic mining areas but also aspects of decontamination and remediation are discussed.