Performance evaluation and optimization of fluidized bed boiler in ethanol plant using irreversibility analysis

This research aims to evaluate the performance of a fluidized bed boiler in an ethanol production plant through exergy and irreversibility analysis. The study also includes the optimization of the pre-heater and the deaerator in order to improve the system efficiency. Operational data from the ethanol production plant was collected between 2015 and early 2016. The total exergy derived from the fuel was determined to be 7783 kJ/s, while the exergy efficiency of the system was found to be 26.19%, with 2214 kJ/s used in steam production, while 71.55% was lost to component irreversibility and waste heat from the pre-heater. The exergy efficiencies of individual components of the system such as the boiler, deaerator, and pre-heater were found to be 25.82%, 40.13%, and 2.617%, respectively, with the pre-heater having the lowest efficiency. Thus, the pre-heater has the highest potential to significantly improve the efficiency of the boiler system. The optimization of the pre-heater shows that a rise in temperature in the outlet of the pre-heater positively affects the exergy efficiency of the deaerator

Exergy intensity and environmental consequences of the medical face masks curtailing the COVID-19 pandemic: Malign bodyguard?

On January 30, 2020, the World Health Organization identified SARS-CoV-2 as a public health emergency of global concern. Accordingly, the demand for personal protective equipment (PPE), including medical face masks, has sharply risen compared with 2019. The new situation has led to a sharp increase in energy demand and the environmental impacts associated with these product systems. Hence, the pandemic's effects on the environmental consequences of various PPE types, such as medical face masks, should be assessed. In light of that, the current study aimed to identify the environmental hot-spots of medical face mask production and consumption by using life cycle assessment (LCA) and tried to provide solutions to mitigate the adverse impacts. Based on the results obtained, in 2020, medical face masks production using fossil-based plastics causes the loss of 2.03 × 103 disability-adjusted life years (DALYs); 1.63 × 108 PDF*m2*yr damage to ecosystem quality; the climate-damaging release of 2.13 × 109 kg CO2eq; and 5.65 × 1010 MJ damage to resources. Besides, annual medical face mask production results in 5.88 × 104 TJ demand for exergy. On the other hand, if used makes are not appropriately handled, they can lead to 4.99 × 105 Pt/yr additional damage to the environment in 2020 as determined by the EDIP 2003. Replacement of fossil-based plastics with bio-based plastics, at rates ranging from 10 to 100%, could mitigate the product's total yearly environmental damage by 4–43%, respectively. Our study calls attention to the environmental sustainability of PPE used to prevent virus transmission in the current and future pandemics

Pretreatment of lignocelluloses for enhanced biogas production: A review on influencing mechanisms and the importance of microbial diversity

Received 13 August 2019; Received in revised form 10 July 2020; Accepted 28 July 2020, Available online 11 August 2020.As one of the most efficient methods for waste management and sustainable energy production, anaerobic digestion (AD) countenances difficulties in the hydrolysis of lignocelluloses biomass. Different pretreatment methods have been applied to make lignocelluloses readily biodegradable by microorganisms. These pretreatments can affect biogas yield by different mechanisms at molecular scale, including changes in chemical composition, cellulose crystallinity, degree of polymerization, enzyme adsorption/desorption, nutrient accessibility, deacetylation, and through the formation of inhibitors. The present article aims at critically reviewing the reported molecular mechanisms affecting biogas yield from lignocelluloses via different types of pretreatments. Then, a new hypothesis concerning the impact of pretreatment on the microbial community developed (throughout the AD process from an identical inoculum) was also put forth and was experimentally examined through a case study. Four different leading pretreatments, including sulfuric acid, sodium hydroxide, aqueous ammonia, and sodium carbonate, were performed on rice straw as model lignocellulosic feedstock. The results obtained revealed that the choice of pretreatment method also plays a pivotally positive or negative role on biogas yield obtained from lignocelluloses through alteration of the microbial community involved in the AD. Considerable changes were observed in the archaeal and bacterial communities developed in response to the pretreatment used. Sodium hydroxide, with the highest methane yield (338 mL/g volatile solid), led to a partial switch from acetoclastic to the hydrogenotrophic methane production pathway. The findings reported herein undermine the default hypothesis accepted by thousands of previously published papers, which is changes in substrate characteristics by pretreatments are the only mechanisms affecting biogas yield. Moreover, the results obtained could assist with the development of more efficient biogas production systems at industrial scale by offering more in-depth understanding of the interactions between microbial community structure, and process parameters and performance

Multivariable optimization of carbon nanoparticles synthesized from waste facial tissues by artificial neural networks, new material for downstream quenching of quantum dots

In this study, water-soluble carbon nanoparticles (CNPs) were synthesized by using waste facial tissue as a non-recyclable waste and the efficiency of CNPs in quenching mechanism of cadmium-telluride quantum dots (QDs) was investigated. In addition, CNPs synthesis was modeled by using artificial neural networks (ANN). To find the optimum model, ANN was trained by using different algorithms. Then, the generated models were statistically assessed and subsequently, the capability of the selected model for predicting the mean diameter size of the nanoparticles was verified. Based on the results, the model GA-4-7-1 had the most optimal statistical characteristics. Furthermore, the most pronounced effect on mean diameter size was associated to HNO3 concentration while temperature demonstrated the least influence. Moreover, the quenching study confirmed the capability of the synthesized CNPs in quenching QDs

Potential of Acid-Activated Bentonite and SO3H-Functionalized MWCNTs for Biodiesel Production From Residual Olive Oil Under Biorefinery Scheme

Application of acid-activated bentonite and SO3H-functionlized multiwall carbon nanotubes (SO3H-MWCNTs) for lowering free fatty acids (FFAs) content of low-quality residual olive oil, prior to alkali-catalyzed transesterification was investigated. The used bentonite was first characterized by Scanning Electron Microscopy (SEM), Inductively Coupled Plasma mass spectrometry (ICP-MS), and X-ray fluorescence (XRF), and was subsequently activated by different concentrations of H2SO4 (3, 5, and 10 N). Specific surface area of the original bentonite was measured by Brunauer, Emmett, and Teller (BET) method at 45 m2/g and was best improved after 5 N-acid activation (95–98°C, 2 h) reaching 68 m2/g. MWCNTs was synthesized through methane decomposition (Co-Mo/MgO catalyst, 900°C) during the chemical vapor deposition (CVD) process. After two acid-purification (HCl, HNO3) and two deionized-water-neutralization steps, SO3H was grafted on MWCNTs (concentrated H2SO4, 110°C for 3 h) and again neutralized with deionized water and then dried. The synthesized SO3H-MWCNTs were analyzed using Fourier-Transform Infrared Spectroscopy (FTIR) and Transmission Electron Microscopy (TEM). The activated bentonite and SO3H-MWCNTs were utilized (5 wt.% and 3 wt.%, respectively), as solid catalysts in esterification reaction (62°C, 450 rpm; 15:1 and 12:1 methanol-to-oil molar ratio, 27 h and 8 h, respectively), to convert FFAs to their corresponding methyl esters. The results obtained revealed an FFA to methyl ester conversion of about 67% for the activated bentonite and 65% for the SO3H-MWCNTs. More specifically, the acid value of the residual olive oil was decreased significantly from 2.5 to 0.85 and 0.89 mg KOH/g using activated bentonite and SO3H-MWCNTs, respectively. The total FFAs in the residual olive oil after esterification was below 0.5%, which was appropriate for efficient alkaline-transesterification reaction. Both catalysts can effectively pretreat low-quality oil feedstock for sustainable biodiesel production under a biorefinery scheme. Overall, the acid-activate bentonite was found more convenient, cost-effective, and environment-friendly than the SO3H-MWCNTs

Sustainable economic growth potential of biomass-enriched countries through bioenergy production: State-of-the-art assessment using product space model

The current study aims to examine the economically viable biomass feedstocks for bioenergy generation and their export potential. The Product Space Model (PSM) is the primary tool used to achieve the aim by accomplishing certain objectives. The study’s findings show that Pakistan has abundant biomass resources for energy production. Canola oil, leather flesh wastes, and poultry fattening show the highest PRODY values, 46,735, 44,438, and 41,791, respectively. These have high-income potential and are considered feasible for export after meeting local energy demand. While goat manure, cashew nutshell, and cotton stalk show lower income potential having values of 3,641, 4,225, and 4,421, respectively. The biowastes having low-income potential are more beneficial to utilize in energy generation plants within the country. The United States is observed to make the most sophisticated products, indicated by an EXPY value of 36296.89. While the minimum level of sophistication is observed for Indonesia, as revealed by its EXPY value of 22235.41 among all considered countries. The PSM policy map analysis of the current study shows that Pakistan and Argentina are located in the Parsimonious Policy quadrant, suggesting shifting toward unexploited products closely related to the existing export baskets. Although the United States, China, India, Indonesia, and Brazil are found in the most desired Let-it-be Policy quadrant. They have more room to diversify their industries and enhance their export potential. The study has practical applications in economic, social, and environmental perspectives, focusing on economic, clean, and sufficient energy. Furthermore, exportable biomass feedstocks are identified to strengthen the economy. Further research must be conducted to evaluate other indicators of the PSM to explore the proximity aspect of PSM, as it would provide a clearer picture of bioenergy and biomass export prospects

Measurement of moisture content in a fluidized bed dryer using an electrostatic sensor array

Fluidized bed dryers have been widely applied to dry raw materials or final products due to the advantages of good mixing efficiency and high heat and mass transfer rate. In order to control and optimize the drying process of fluidized bed dryers, it is necessary to develop reliable methods to measure the moisture content of solid particles in the bed. Because of the advantages of non-intrusiveness, simple structure and high sensitivity, an electrostatic sensor array has been developed to monitor the drying process. Experimental investigations were conducted on a lab-scale fluidized bed dryer. The moisture content during the drying process was measured using the sampled particles as reference. It is found that the fluctuation of the electrostatic signals can reflect the change in moisture content. However, the relationship between the fluctuation of the electrostatic signal and the moisture content depends on the air velocity in the dryer. To eliminate the velocity effect on moisture content measurement, a model between the moisture content and the root-mean-square magnitude of the electrostatic signal is established. The effectiveness of the model is validated using experimental results under a range of conditions. The findings indicate that the electrostatic sensor array can measure the moisture content in the bed with a maximum error of ±15%

Application of a neural fuzzy model combined with simulated annealing algorithm to predict optimal conditions for polyethylene waste non-isothermal pyrolysis

Adaptive neural fuzzy model Simulated annealing algorithm A B S T R A C T In the present study, the waste polyethylene (PE) pyrolysis under different non-isothermal conditions was investigated to estimate the optimal conversions and pyrolysis rates. The pyrolysis study was carried out using Thermogravimetry (TG) of the virgin and the waste PE under different heating rates of 5, 10, 15 and 20 C/min. The TG experiments indicated that the virgin and the waste PE pyrolysis processes mainly underwent in the temperature range of 390-510 C. Subsequently, the adaptive neural fuzzy model was adopted to predict the conversions and the pyrolysis rates of the virgin and the waste PE. The optimal operating conditions in different temperature ranges were optimized by the simulated annealing algorithm (SA). Moreover, the R-squared values of the virgin PE conversions (~1) and pyrolysis rates (> 0.999), and the waste PE conversions (~1) and pyrolysis rates (> 0.999) revealed the high accuracy of the adaptive neural fuzzy model predicted results