Sources and mitigation of methane emissions by sectors: A critical review

The environmental community rightly recognizes global warming as one of the gravest threats to the planet. Methane (CH₄), one of the greenhouse gases causing global warming, is emitted from a variety of sources and its concentration in atmosphere has increased dramatically over the last few centuries. Therefore, the increasing concentrations of methane are of special concern because of its effects on climate and atmospheric chemistry. Anthropogenic sources of methane can be collected under the titles of agriculture, energy, waste and industry on the basis of sectors. This paper aims at examining the past trends in emissions, the sources and mitigation strategies of the methane. As a result of the study, it is determined that the agricultural sector is the biggest source of methane emissions among the sectors. The energy, waste and industry follow the agricultural sources respectively.     

Uncertainties in estimating the roughness coefficient of rock fracture surfaces

Joint roughness has a critical role in the deformation behavior of discontinuous rock masses. Several subjective (visual comparison) and quantitative (statistical and fractal) approaches have been proposed for estimating rock joint roughness coefficient (JRC). Using a large collection of 223 published joint profiles, this study investigates variability of the JRC estimates by these approaches. Among the profile parameters, maximum height (R _z), ultimate slope (λ), and fractal dimension (D _h–L, determined using the hypotenuse leg method) show a lower sensitivity to the sampling interval than the root mean square of the first deviation (Z ₂), profile elongation index (δ), fractal dimension (D _c, determined using the compass-walking method), and standard deviation of the angle i (σ _i ). Accordingly, this study proposes two separate sets of equations for quantitatively estimating JRC. The performances of these equations are examined by performing direct shear tests on 23 rock joint samples. The subjective approach is found to underestimate JRC by less than two units because it ignores (1) the main trend of the compared profile and (2) the limited scope of the standard profiles. Following these results, the visual comparison chart is updated by explicitly adding a scale bar for the y-axes of the standard profiles. Several basic rules for visual comparisons are also proposed.

     

Investigation of factors affecting the dispersibility of clays and estimation of dispersivity

Dispersive soils have caused failure of many slopes and earth fills due to external and internal erosion. This study aims to investigate various factors used for identification of dispersivity and to develop some new approaches for the prediction of dispersivity of clays. To achieve this purpose, physical and index properties, as well as degree of dispersivity of 29 clay samples taken from five different locations in and around the city of Ankara were determined. Various statistical prediction models were used for prediction of new dispersivity classes obtained by weighting ranking method. It was determined that dispersivity classes obtained from physical and chemical dispersivity tests performed on the same clay samples using distilled water were different from each other. In addition, crumb and pinhole tests were performed by using test waters with varying TDS values on five selected samples to find the impact of water chemistry on dispersivity. It is concluded from all dispersivity tests that total dissolved salts (TDS) values and sodium percentage (SP) remarkably affect the degree of dispersivity, and the use of these two parameters give more reliable results for the determination of dispersivity. By considering all these facts and to predict the most reliable dispersivity class, all dispersivity classes obtained from physical and chemical dispersivity tests were reevaluated by a weighted ranking system, and new dispersivity classes were assigned. In order to estimate these new dispersivity classes, various statistical models were established by using results of chemical analysis of pore water of clay samples. For this purpose, prediction models including soft computing methods such as decision tree and logistic regression are used and most reliable prediction models having the highest prediction performance are suggested.     

CFD simulation of free-surface flow over triangular labyrinth side weir

Side weirs are extensively used in the hydraulic and environmental engineering applications. The modeling of free surface flow over a labyrinth side weir is a sophisticated problem in the hydraulic engineering. The water surface profiles over the triangular labyrinth side weirs were investigated by many of the researchers experimentally and theoretically. In this study, the free surface flow over the triangular labyrinth side weir was modeled by using Volume of Fluids (VOF) method to describe the flow characteristics in subcritical flow conditions. A valid method, Grid Convergence Index (GCI) was used to determine the numerical uncertainty of the simulation results. The simulation results were compared with experimental observations, and good agreements were obtained between the both results.     

Surface‐modified carbon black derived from used car tires as alternative,reusable, and regenerable catalysts for H2 release studies from sodium borohydride methanolysis

Carbon black (CB) obtained from used car tire rubbers were treated with concentrated sulfuric and nitric acids. The oxidized CB (CB‐COO‐Na⁺) is subsequently modified with epichlorohydrin (ECH) and amines including polyethylene imine (PEI). These modified CBs such as CB‐PEI are used as metal‐free catalysts in methanolysis of sodium borohydride (NaBH₄) to produce hydrogen. The hydrogen generation rate (HGR) of 3089 ± 44.69 mL.min^‐1.g^‐1 is accomplished at room temperature with CB‐PEI‐hydrochloric acid (HCl) catalyst. The resulting activation energy of 34.7 kJ/mol for the temperature range of ?20°C to +30°C compares favorably to most of alternative catalysts reported in literature while reaction catalyzing capabilities of CB‐PEI‐HCl particles extend to the subzero temperature range (?20°C‐0°C). The reuse and regeneration studies conducted for the CB‐PEI‐HCl catalyst showed that these catalysts do provide complete conversion at every use up to five consecutive runs and retain 50 ± 2.5% of the original hydrogen generation rate at the fifth consecutive reuse. The CBs‐based catalysts are fully regenerated with HCl treatment.     

Determining parameters of heat exchangers for heat recovery in a Cu–Cl thermochemical hydrogen production cycle

A heat exchanger is a device built for efficient heat transfer from one medium to another. Shell and tube heat exchangers are separated wall heat exchangers and are commonly used in the nuclear and process industry. The CuCl cycle is used to thermally crack water in to H₂ and O₂. The present study presents the heat exchanger thermal design using analysis of variance for heat recovery from oxygen at 500 °C, coming from the molten salt reactor. Polynomial regressions in terms of the amount of chlorine in the oxygen, the mass flow rate on the tube side, and the shell's outlet temperature are estimated for various exchanger parameters and the results are compared with the bell Delaware method. Based on energy and exergy analysis, this study also discusses the best possible path for the recovered heat from oxygen. Optimal heat exchanger parameters are estimated by Design-Expert^® Stat-Ease for most effective heat recovery.     

Artificial neural network and regression models for performance prediction of abrasive waterjet in rock cutting

An experimental study is carried out for modeling the rock cutting performance of abrasive waterjet. Kerf angle (KA) is considered as a performance criteria and modeled using artificial neural network (ANN) and regression analysis based on operating variables. Three operating variables, including traverse speed, standoff distance, and abrasive mass flow rate, are studied for obtaining different results for the KA. Data belonging to the trials are used for construction of ANN and regression models. The developed models are then tested using a test data set which is not utilized during construction of models. Additionally, the regression model is validated using various statistical approaches. The results of regression analysis are also used to determine the significant operating variables affecting the KA. Furthermore, the performances of derived models are compared for showing the accuracy levels in prediction of the KA. As a result, it is concluded that both ANN and regression models can give adequate prediction for the KA with an acceptable accuracy level. The compared results reveal also that the corresponding ANN model is more reliable than the regression model. On the other hand, the standoff distance and traverse speed are statistically determined as dominant operating variables on the KA, respectively.     

A novel method for determining effects of fire damage on the safety of the Type I pressure hydrogen storage tanks

Consumption of the fossil fuels causes greenhouse gas effect and environmental pollution, which are two basic problems of our age. As a result of this problem, clean and renewable alternative energy sources are beginning to replace fossil fuels. Nowadays, the use of hydrogen energy, which is one of the clean energy, is increasing in transportation and industrial areas. Increasing of hydrogen energy usage, scientists are attempting to solve the many safety problems (such as fire, burst, impact and hydrogen embrittlement) that can occur during the storage and consumption of hydrogen energy. In this study, during the event of fire, the safety of metallic Type I pressure hydrogen storage tanks is investigated by using a novel approach. In this new approach, the mechanical strength drops of the tank materials that is related with temperature rising are added to the safety calculations. In the study, 6061 T6 aluminum and SS 316L stainless steel alloys were used as hydrogen tank material. The safety of hydrogen tanks modelled using these alloys was investigated under different temperature conditions (22, 100, 200 and 300 °C) and internal pressure (15, 20 and 25 MPa).