Cleaner Chemical Engineering最新文献

Management of Fly ash (FA), a thermal power plant waste, is a major global issue since a sizeable fraction of fly ash's annual generation is not effectively valorised. FA is a heterogeneous mix of crystalline and amorphous phases containing significant amounts of aluminium and silicon elements alongside high surface energy, making FA an economically suitable catalyst support framework. Accordingly, the development of a low-cost, recyclable fly ash-supported tin oxide solid acid catalyst has been investigated for esterification of stearic acid (SA) with methanol to produce methyl stearate (MS); which is regarded as biodiesel and is presently being blended with petro-diesel as a cleaner fuel substitute. The characterisations of the prepared SnO₂-FA catalyst (SFC) have been performed through TGA, XRD, BET-BJH and FESEM-EDS analyses. The optimal process conditions (assessed through response surface methodology (RSM)) viz. 475.06 °C calcination temperature, 3.39:1 weight ratio of SnCl₄.5H₂O: FA and 73.16 °C esterification temperature rendered a significant 85.734% SA conversion. The optimal mesoporous SFC comprising SnO₂ active phase possessed 11 m²/g specific surface area (much greater than that of the support material, FA: 0.60 m²/g); 0.0109 cc/g pore volume and 2.9 nm modal pore size. Important fuel properties of the optimally produced MS conformed to the ASTM biodiesel (B100) standards. The overall environmental sustainability of the process assessed through the openLCA platform (ecoinvent database 3.8) revealed lower environmental impacts of the developed process. The LCA study divulges the fossil depletion potential and the global warming potential of the overall process to be 4.34 kg oil Eq. and 4.03 kg CO₂-Eq. respectively. The present study could establish a green and effective FA valorisation avenue through a sustainable methyl stearate (biodiesel) production process.

The present work was successfully designed to prepare effective adsorbents from Moringa oleifera shells (PMOS) and chemically activated by zinc chloride (ZnCl₂) and calcined at different temperatures as 200, 300, 400 and 500 °C, for methyl red (MR) dye removal. Thereafter, the prepared materials were characterized using diverse analytical techniques as SEM, FTIR, XRD and BET. The results showed that the activated carbon prepared at 500 °C had a larger specific surface area (610.031 m²/g) compared to its original precursor (only 3.16 m²/g) or even the rest of prepared adsorbents. The maximum MR sorption capacity of the PMOS of 500 °C was the highest as much as 28.67 mg/g at ambient temperature.

The sorption capacity of raw M. oleifera shells and the tests of calcination effect of this material on the improvement of their capacity were studied in batch system by varying operating conditions such as: contact time, dye concentration, adsorbent dose, pH and temperature. The results confirmed that PMOS calcined at 500 °C with 1.0 g/L of dose and in acidic to neutral media at 25 °C, gives the most significant elimination rate (25.46 mg/g). Thermodynamic study shows that the retention of MR is an exothermic physisorption using PMOS calcined at 200 and 300 °C. Unlike materials calcined at 400 and 500 °C, the process was exothermic chemisorption.

In addition, adsorption isotherms and kinetics were studied using experimental data fitting to further understand and describe the dynamic equilibrium, dynamic kinetics, and mechanism of MR adsorption onto the calcined materials. As compared to Freundlich isotherm model, the Langmuir isotherm model provided a better fit with the experimental data for the different calcined PMOS (at 200 °C, 300 °C, 400 °C and 500 °C) exhibiting a maximum monolayer adsorption capacity of 25.45, 27.10, 28.13 and 28.91 mg/g, respectively. The linear pseudo-first-order kinetic model was found to be suitable for describing the adsorptive kinetics of all prepared activated carbons.

Lignocellulosic materials represent one of the clean alternative energy sources that have carbon in their building blocks, which can be processed into liquid biofuel and useful chemicals. Elemental compositions of biomass such as carbon (C), hydrogen (H) and oxygen (O) are key indicators for establishing calorific value, energy efficiency and carbon footprint during direct application as fuel and feedstock in thermochemical conversion. These characteristics usually require very expensive equipment, which may not always be readily available for examination of biomass feedstock. This study presents a new predictive non-linear model for ultanal characteristics of lignocellulosic biomass (C, H and O) derived from the proxanal attributes such as fixed carbon (FC), volatile matter (VM) following least square method. Four hundred and fifty (450) proximate analysis data from literature were used for model development and fifty (50) experimentally determined data points for model validation. The elemental composition {C=C[VMFC,(VM)²,(FC)], H=H[(VMFC),VM,FC] and O=O[(VM)^0.75,(1/FC)^0.33]} prediction models were developed and evaluated using indices such as average absolute percentage error (AAPE), average bias percentage error (ABPE) and coefficient of determination (R-squared). The results of analysis showed AAPE, ABEP and R-squared of 2.12%, 0.06% and 0.9993; 2.88%, 0.11% and 0.9989; 3.16%, -0.04% and 0.9982 for C, H and O model respectively. This suggests that the developed models could be used to predict the ultanal attributes of lignocellulosic biomass within 60<VM<90 and 10<FC<30 with high fidelity. The models would serve as a quick means of assessing lignocellulosic biomass prior to any bioenergy application.

Genetic algorithm (GA) assisted optimization was used in the adsorptive removal of bromocresol green (BCG) from solution. The adsorbent was acid-functionalized corn cob (AFCC). The properties of the adsorbent were investigated via instrumental analysis involving Fourier Transform Infra-Red (FTIR) and Scanning electron microscopy (SEM). Non-linear modeling involving various degrees of isotherm models were used in the isotherm study. Adaptive neuro-fuzzy inference systems (ANFIS), response surface methodology (RSM), and artificial neural network (ANN) were used to model the BCG removal. The result of the instrumental analysis showed that the properties of the AFCC were enhanced after the acid carbonization process with a surface area of 903.7 m²/g. The modeling and predictive adeptness of the ANFIS, RSM, and ANN was very significant with correlation coefficient (R²) of 0.9984, 0.9865, and 0.9979 with root mean square error (RMSE) of 0.00308, 0.00898, and 0.00351, respectively. Validation of the models’ optimization indicated maximum adsorption capacities of 38.04, 34.41, and 41.94 mg/g for RSM-GA, ANN-GA, and ANFIS-GA, respectively. Freundlich, Khan, and Marczewski-Jaroniec isotherms best described the adsorption isotherm for two-term, three-term, and four-term isotherm modeling respectively. Calculated values of Gibbs free energy change (∆G_max = -7.55 KJ/mol), enthalpy change (∆H = 35.84 KJ/mol), and entropy change (∆S = 130.20 Jmol⁻¹K⁻¹) indicated the adsorption process was spontaneous, endothermic and with increased randomness respectively. The study showed that the low-cost AFCC obtained from agro-waste has desirable adsorbent properties for the treatment of BCG polluted wastewater.

Traditional methods of disposing and storing plastic waste in Ghana, such as at damping sites and landfills, have put the environment and human life at risk for years. A sustainable and efficient solution is to shift to a circular economy by recycling plastic waste into alternative fuels. Therefore, this study focussed on the segregation of plastic waste and its conversion into fuel products via pyrolysis in the temperature range of 350 – 420 °C. In a kilogram-scale pyrolysis fixed-bed batch reactor, a large quantity of condensate oil was produced with minimal amounts of non-condensable gases, chars, and waxes. Gas chromatography, Fourier transform infrared spectroscopy, differential scanning calorimetry, and thermal gravimetric analysis were used to characterise the condensate oils. The measured fuel properties of the various condensate oil types were remarkedly similar to those of commercial fuels (gasoline, diesel, and kerosene). This makes them suitable alternatives to conventional energy sources, with the potential to significantly improve living conditions, reduce environmental pollution, and cut down on the need to import refined fossil fuel. Finally, the condensate oil from the individual plastic waste types outperformed the mixed-plastic waste in terms of fuel properties and yield.

Algal biofuel is a promising green energy for the future, but harvesting algae remains a major challenge. To overcome this obstacle, magnetic separation using magnetic nanoparticles is proposed as a simple, highly efficient yet cost-effective method to collect microalgae. Magnetite (Fe₃O₄) nanoparticles are the typical materials of choice, but their performance varies depending on the pH of the water, furthermore, they can be toxic to algal cells. Hence, a more stable and non-toxic alternative replacement for Fe₃O₄ is needed. In this work, we explore the use of biocompatible manganese-containing magnetic ferrite nanoparticles (NPs) to harvest Chlorella sorokiniana and Scenedesmus obliquus microalgae. Using this novel NP, we achieved a harvesting efficiency of roughly 90% for Chlorella sorokiniana and 80% for Scenedesmus obliquus up to three cycles consistently throughout a wide pH range of 2–12. This was due to the high stability and reversible attachment of the NPs to the algal cells. Surface analysis of the NPs-Algae by Fourier transformed infrared (FTIR), the microbial adhesion to hydrocarbons (MATH), zeta potential, and the extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) theory indicated acid-base interactions and hydrophobicity effects are the driven forces for NPs-algae interaction instead of simple electrostatic attraction. Overall, our study provided a more efficient magnetic harvesting approach for algae and a more in-depth understanding of the separation mechanisms to improve and advance the algae biofuel industry.

The number of research activities to find alternative fuels for Internal Combustion Engines has increased tremendously in recent years, owing to depleting oil reserves and growing climate concerns. In this scenario, biodiesel is one of the few promising alternatives that can potentially replace conventional fuel. When vegetable oil is used for frying food items, it undergoes physiochemical changes. After a while, it is discarded as waste cooking oil (WCO) which can be used in the production of biodiesel. Since WCO is a degraded raw material, it is important to understand its effect on the quality of biodiesel produced in terms of engine performance and engine emission. In current research study, total polar matter (TPM) is considered as a measure of quality for waste cooking oil. Sunflower oil and palm olein were used in this study for comparison since both exhibit different fatty acid compositions. Among the properties considered in this study, the results found that the kinematic viscosity of the biodiesel gets highly affected by total polar matter content of waste cooking oil. Further, the study also identified correlations to predict the kinematic viscosity of biodiesel from total polar matter content of WCOs. The authors found no significant difference in engine performance during engine tests between the biodiesels produced from fresh oils and waste cooking oils. However, biodiesels produced from WCOs emitted slightly higher carbon monoxide than the biodiesel produced from fresh oils. On the contrary, nitric oxide and smoke emissions from biodiesels produced from waste cooking oils and fresh oils were similar. Even though waste cooking oil is a degraded feedstock, the biodiesel produced from it has no adverse effect on engine performance and emissions. Therefore, WCO oil can be considered as a promising feedstock in the sustainable production of biodiesel.

Petroleum refinery effluent (PRE) containing a high concentration of colloidal particles causing turbidity is a point source pollutant. There is currently no baseline for the residual concentration of colloids in industrial effluent. In the present study, the performance of land snail shells (LSS) characterized using FTIR and XRD techniques used for the treatment of PRE was investigated. The effluent collected from the outlet train of the industrial facility contains 220 NTU of turbidity corresponding to 520 mg/L of colloidal particles. Analysis of the industrial effluent yielded a COD to BOD ratio > 3.5 eliminating the option of a biological method of treatment. Coagulation-flocculation treatment of the PRE was carried-out following a standard nephelometric test. To clarify the applicability of LSS beyond removal efficiency, machine learning (ML), adsorption, and coag-flocculation kinetics were applied to investigate the treatment process. The predictive capacities of the ML models were compared using statistical metrics. The synergetic effects of operating variables were equally studied. The predicted optimum operating conditions of the treatment process were pH 6, dosage of 0.1 g/L, and a settling time of 30 minutes. The pseudo-second-order and coag-flocculation kinetics result confirmed the reduction of the colloidal particles that occurred via adsorption and inter-particle bridging mechanism. The flocculation outcome proved that the mixing regime 20 s⁻¹≤ G≤120 s⁻¹ promoted aggregation rate over breakage coefficient transcending to 90% removal efficiency. The finding shows that the stability of the finished water corresponds to the 23 mg/L threshold of residual colloidal particles, and 10NTU, which satisfied the EPA guideline for environmentally sustainable recovery.

Coal gasification fine slag (FS) is a solid waste of difficult-to-separate nature. In order to improve the reuse rate of coal gasification fine slag resources, so as to improve the value-added utilization and clean transformation for coal chemical industry, which is necessary to deeply study the composition characteristics and effective separation of FS. In this study, the dry pulverized coal gasification fine slag (DPFS) was divided into different particle sizes by wet screening, and the composition and structure characteristics of components with different particle sizes were investigated. Then a combined treatment method of airflow crushing and classification was used to separate DPFS. The results showed that the fixed carbon content, the ash composition, the micro morphology and the pore structure of FS were related to the particle size distribution. The fixed carbon content of particles with particle sizes ranging between 74–98 μm was the highest (about 39.98%), the particles with a size grade of 13–74 μm and larger than 98 μm was between 11.85 and 30.85%, The minimum fixed carbon content of 0–13 μm particle size is 8.69%. The microstructure of DPFS was composed of several relatively independent particle units with special morphology, including porous irregular particles, spherical particles, floccule, and the element contents of these particle units were very different. The residual carbon and ash components in the DPFS could be effectively separated and enriched in different products by airflow crushing and classification. When the grinding gas pressure was set to 0.5 MPa, the low carbon product with fixed carbon content of 4.99% and yield of 19.86% could be obtained. The mechanism of airflow crushing of FS showed that airflow crushing based on impact force and shear force could effectively separate the residual carbon and ash components, and greatly improve the separation and recovery rate of residual carbon. Therefore, the airflow crushing and classification has a good application prospect in the separation and enrichment of residual carbon of gasification fine slag.

This paper evaluated steam and CO₂-enhanced gasification of spent coffee ground (SCG) biomass, including energy and exergy aspects focusing on hydrogen production. The waste-to-hydrogen (WTH) conversion was performed via gasification (1000 °C) with a drop-tube-reactor investigating six different steam to biomass (SBR of 0.5, 0.8 and 1.2) and CO₂ to biomass (CO₂BR 0.09, 0.18 and 0.27) ratios. The syngas production indicated clear improvement against O₂/N₂ with an H₂ yield increase up to 69.21% and 18.32% for steam and CO₂ mediums. The energy and exergy analysis points out the 0.8 SBR as the optimum condition with 210% CGE and 48.05% exergy efficiency for H₂ production. As a strategy for carbon capture and usage, the medium with 0.27 CO₂BR provided a 28.52% exergy efficiency for H₂ production and reduced soot formation, showing a potential gasification medium for SCG. Results encourage waste-to-hydrogen prospection within circular economy principles, boosting circular economy principles in urban districts.