Journal of Renewable Energy and Environment
Volume:7 Issue: 4, Autumn 2020

Carbon-dioxide Capture and Utilization (CCU) technology is an efficient process in the portfolio of greenhouse gas reduction approaches and is programmed to mitigate global warming. Given that the prime intention of CCU technologies is to prevent CO2 emissions into the atmosphere, it remains to be seen if these approaches cause other environmental impacts and consequences. Therefore, the Life Cycle Assessment (LCA) approach was considered to account for all environmental aspects, in addition to the emission of greenhouse gases. In this study, the Life Cycle Inventory (LCI) methodology was employed to quantify the environmental impacts of indirect carbonation of Red Mud (RM), a waste byproduct of alumina production line in Jajarm Alumina Plant, Iran by CO2 exhausted from the plant stacks based on International Organization for Standardizations (ISO) of ISO 14040 and ISO 14044. The results confirmed the reduction of CO2 emission by 82 %. The study of carbon footprint based on ISO 14064 under the criterion of PAS 2050 revealed CO2 emission equivalent to 2.33 kg/ ton RM, proving that CCU managed to mitigate the CO2 emission by 93 % compared to the conventional technology employed in Jajarm Plant, which produced around 34 kg CO2 per 1 ton RM. Furthermore, the economic evaluation of the process brought about 243 $/ton RM in profit via the sales of products including silica, aluminum, hematite, and calcium carbonate. The outcomes of the present study highlight that the intended CCU technology is a practicable approach for large-scale applications.

In the present study, the performance of a Desiccant Evaporative Cooling System (DECS) under eight different designs to provide the desired indoor air conditions for administration buildings was explored via TRNSYS software. An administration building in Chabahar, Iran as a region with a high cooling load demand was considered for the study. The simulation results indicated that the two-stage desiccant cooling system (Des. H) was the most suitable design, and it enjoyed the potential to keep the indoor air conditions within the standard recommendations. It was also shown that Des. H is the superior design in terms of energy performance and can meet the space cooling load requirements. The study showed that Des. H had the highest COP value with 2.83. The possible application of solar energy to the regeneration process of the Des. H was also studied. The simulations revealed that Des. H with and without the solar panels had less energy consumption than the existing system. The study showed that the application of Des. H could ensure 26.97 % saving in power per year in comparison to the existing system. Moreover, it was demonstrated that the addition of PVT panels to Des. H could increase the rate of annual power saving to about 68.03 %.

Climate change refers to any significant and long-term alterations in global or regional weather conditions. The impact of climate change on the industrial plans is enormous, while the water supply sector has been challenged to examine how it could continuously operate in the current situation. Optimization of energy consumption and reduction of Greenhouse Gases (GHG) emissions are some of the priorities of water companies. The objective of the study is to propose a novel evaluation approach to the feasibility of using renewable energies (solar, wind, and biomass) in the water and wastewater industry. Tehran Water and Wastewater Company consists of six regional districts and forecasting of its energy consumption, power costs, and carbon tax rates for the next ten years was done by using the regression model. The results indicated that increase in water supply and electricity consumption was evidenced by the increase in Tehran's annual population. GHG emissions were calculated in two scenarios, the first of which is based on the total supply of required electricity from conventional power plants and the second is on the generation of approximately one-third by renewable energies. In addition to the higher emissions of carbon dioxide (CO2) from diesel and oil power plants than the natural gas-fueled plants, by increasing the carbon tax to more than 30 USD per tonne of CO2, it is expected that the emissions will be reduced by 30 % in all fossil-fueled power plant types. Results showed that a small amount of tax was not effective in reducing GHG emissions.

This paper deals with the problem of maximizing the extracted power from a wind turbine in the presence of model uncertainties and input saturation. An adaptive second-order integral terminal sliding mode speed control method is utilized to address this problem. The presented method benefits from the advantages of several control techniques, i.e., adaptability, robustness, finite-time convergence, and the capability of coping with the input saturation. The robust nature of the designed controller causes its high performance in facing the uncertainties in the wind turbine model. In this paper, to compensate for the effect of input saturation, an auxiliary dynamic variable is added to the tracking error and also an adaptation law is designed so that the finite-time convergence of the closed-loop system can be achieved. Moreover, to reduce the mechanical stresses which are the result of the chattering phenomenon, a second-order sliding surface is employed. The finite-time convergence of the designed controller has been proven by the Lyapunov stability theorem in which the finite-time convergence of the tracking error to zero is guaranteed. Finally, to illustrate the effectiveness and satisfactory performance of the proposed controller, two comparative simulations are carried out. The results of this comparison show that the proposed controller has less error to track the optimal speed and when the model uncertainties and input saturation occur in the wind turbine system, the proposed controller is almost 3 % more efficient than the existing controllers.

This study offers an effective solution to meet the growing demands of biogas plants for energy. This paper presents a model and simulates the digestion process of biogas production from the organic and food processing waste that contains high moisture. Biogas is produced by bacteria through the bio-degradation of organic material under anaerobic conditions. According to the findings, in case of biogas production, the broiler chicken manure is approximately 88 %. From the analysis, it is observed that the chicken broiler waste is approximately 88 % more efficient than the unsorted waste. In addition,  in the case of digestate, the cow manure is approximately 6.25 % more efficient than the garden waste. The present study aims to investigate the performance of different types of  wastes regarding biogas production. To this end, different types of waste were considered in data analysis. According to the data analysis, biogas production is highly affected by the type of waste.

Given that the catalyst and catalyst support properties have a key role to play in the electrochemical activity of fuel cells, in this research, the synergism effect of Pt and Ru nanoparticles reduced on catalyst support [synthesized Carbon Aerogel-Carbon Nanotube (CA-CNT)] was investigated. The catalyst support was synthesized by sol-gel method and the catalyst nanoparticles were reduced on catalyst support using impregnation and hydrothermal method. Different molar ratios of Pt:Ru (i.e., 0:1, 1:0, 3:1, 2:1, 1:1, 1:2, and 1:3) were applied as electrocatalysts for Methanol Oxidation Reaction (MOR). The electrochemical performance of these catalysts was compared with that of commercial Pt/C (20 % wt) for MOR. The physical properties of the synthesized catalyst support (CNT-CA) were studied using FESEM and BET techniques. Moreover, XRD and ICP analyses were employed for investigating each of the synthesized catalyst (Pt/CNT-CA and Ru/CNT-CA). The cyclic voltammetry and chronoamperometry methods were used to conduct electrochemical analysis. Research results indicated that synthesis methods were reliable. Moreover, CNT-CA had a proper performance as the catalyst support and the Pt:Ru with a 3:1 molar ratio was the best catalyst among all the synthesized catalysts for MOR.

Combined Heat and Power (CHP) systems have increasingly drawn attention in recent years due to their higher efficiency and lower Greenhouse Gas (GHG) emission. Input-output matrix modeling was considered here as one of the efficient approaches for optimizing these energy networks. In this approach, power flow and energy conversion through plant components were modeled by an overall efficiency matrix including dispatch factors and plant component efficiencies. The purpose of this paper is to propose a modification of the objective function presented in some previous studies. This procedure was performed by adding the parameters of plant component lifetime and environmental costs to the objective function. Thus, the optimization problem was formulated by minimizing the total system levelized cost instead of simply hourly energy cost. The study results revealed that producing the electricity by the trigeneration system led to achieving 1256 MWh annual electricity savings that otherwise must be purchased from the grid. The results also showed a significant reduction in annual CO2 emissions (703.31 tons per year). Furthermore, if the price of purchasing CHP electricity was considered three times more than the current ones, payback times would be less than 5 years.