Cleaner Engineering and Technology最新文献

The 2023 being on its way to be the warmest year in the 174-year global surface temperature history it is becoming more and more evident how crucial it is to break the linkage between economic growth and greenhouse gas emissions.

The pulp and paper industry is highly energy intensive industry sector. It is the fourth largest industrial energy user and currently produces approximately 1.3% of global greenhouse gas emissions. While the demand for paper and paperboard products keeps rising, it is essential for the industry to find energy efficient solutions for reducing the environmental impact of the pulp and paper products. 80% of the progress in energy efficiency in Finnish paper mills is due to improved technology and more optimal operational modes. Optimizing existing processes has bigger effect on energy efficiency than closing old and starting new paper mills.

Pulp refining is one of the most energy intense steps in the paperboard production, representing 15%–18% of the total energy consumption of a paper mill. The effect of a commercial cellulase enzyme product was evaluated for energy savings and avoided emissions in the refining process of a paperboard mill. Data from a paperboard line using Bleached Softwood Kraft Pulp (BSKP) from a separate pulp mill was provided by a Finnish paperboard mill containing production runs both with and without commercial cellulase product ECOPULP® R. Data was collected from the mill automation system to evaluate and compare a refining capacity restricted run and a run that was not refining capacity restricted.

Analysis of the data showed a reduction of refining energy by approximately 16%–17% when the cellulase enzyme was used. This corresponds to 2 kg of CO₂ emissions avoided per tonne of pulp refined when calculated using the Finnish average electricity emissions intensity in 2022. Use of the cellulase enzyme enabled the refining results that could not have been reached with the bare mechanical refining capacity of the mill.

Cellulases can be efficient processing aids in pulp refining. The reduction of required mechanical refining and electrical power to run the refiners to achieve the required freeness can significantly affect the carbon footprint of the paperboard products, whereas the negative impact of emissions from enzyme production is negligible. Reduction of CO₂ emissions is especially significant in the areas where the electricity mix used for the production is based heavily on fossil fuels.

The synthesis of novel benzo-[7]-annulene-1,3-dicarbonitrile analogues has been accomplished using an environmentally friendly and green protocol. This mortar and pestle grinding method that is both ethically responsible and commercially practical. By producing the necessary benzo-[7]-annulene-1,3-dicarbonitrile analogues with good results (89%–97%) in a short reaction time (≤30 min), this approach successfully indicates that even aldehydes with severe steric hindrance play an active part in the process. The faster work-up processes, the reduction of operating difficulties, and the increased yields are notable among its advantages over earlier systems. This strategy uses a mortar and pestle grinding method, which is well known for following guidelines that are both economically sensible and environmentally friendly. It is important to note that this novel approach offers a considerable advancement over earlier approaches that were characterized by drawn-out work-up procedures, operational complexity, and low yields.

The low levels of reuse and recycling of solid waste in cities in developing countries can be attributed to decision-making processes with sub investment that do not consider waste streams, recovery capacities, and potential for recycling. This is due to a lack of understanding of the systemic structure of urban waste management.

This article presents the development of a model of an urban waste management system that integrates decisions based on strategies that close cycles, belonging to the concept of a circular economy. These strategies aim to increase the potential use of organic waste, plastics, and glass.

The model was built using the Systems Dynamics methodology, which allows obtaining mathematical models for the study and observation of trends and future scenarios of complex systems. The model is made up of three modules: health, financial, and circular economy. The strategies evaluated and compared in the simulation environment were: Economic incentives at the price of the material used; Increase in waste sorting capacity; Increase in the capacity to use waste.

Methodologically, novel mathematical representations were achieved for the estimation of the useful life of sanitary landfills. Likewise, a mathematical formulation was found for the automatic evaluation of the efficiency in the capacity to use different wastes, which allows to know the need for investment or increase of capacity to use the type of waste evaluated.

Methodologically, novel mathematical representations were achieved for the estimation of the useful life of sanitary landfills. These new mathematical representations allow for the automatic evaluation of the efficiency in the capacity to use different wastes. This information can be used to determine the need for investment or increase of capacity to use the type of waste evaluated.

In the pursuit of sustainable materials for composite fabrication, this study investigates the utilization of eco-friendly sugarcane biochar as a filler to enhance the mechanical properties of S-Glass/polyester hybrid composites. The incorporation of sugarcane biochar aims to mitigate environmental concerns associated with conventional fillers while simultaneously improving composite performance. Two techniques were utilized in the fabrication composites such as hand layup and vacuum bagging methods. Composite was fabricated with varying weight percentage of sugarcane biochar concentrations such as 5, 10, and 15 wt%. The mechanical behaviour of the composites was assessed through tensile, flexural, impact, and hardness tests. It is noted that the composites that comprised sugarcane biochar at concentrations as high as 10 wt% demonstrated the highest mechanical strength and performance. The maximum tensile strength of 119 MPa, flexural strength of 154 MPa and impact strength of 45 MPa was noted on the 10 wt% biochar composite. The findings underscore the effectiveness of sugarcane biochar as a filler in improving the mechanical behaviour of S-Glass/polyester hybrid composites. The successful integration of sugarcane biochar not only contributes to the development of sustainable composite materials but also highlights its potential to achieve superior mechanical performance.

Catalyst waste slag (CWS) is generated in large amounts when fabricating the catalyst required in the fluid cracking catalyst (FCC) process used for oil refining. Currently, CWS is landfilled. This paper characterizes the CWS and measures its pozzolanic activity. It determines whether the CWS can be used as partial Portland cement (PC) replacement for the first time in the literature. CWS is primarily composed of Al₂O₃ and CaO. It contains a negligible quantity of heavy metals that can be immobilised in a matrix. The raw CWS is totally amorphous and extremely reactive which results in flash set. Calcination is an effective method to control the reactivity of CWS. Reactivity increased when CWS was calcined between 300 and 600 °C and it peaked at 500 °C, but this caused flash set. Calcination at 800 °C lowers reactivity (as the highly disordered aluminium phases achieve a greater order) which allows for proper handling. Temperatures over 800 °C caused partial crystallization significantly lowering reactivity.

The 800°C-calcined CWS reached high mechanical index (6.25), comparable to other pozzolans such as fly ash and red mud, and greater than alum sludge. CWS combines lime profusely and develops more abundant cementing hydrates than similar pozzolans such as calcined alum sludge. The pozzolanic reaction of the 800°C-calcined CWS provides abundant cementing minerals including AFt and AFm phases, calcium aluminium carbonate hydrates and calcium aluminium hydrates.

The high reactivity of CWS and its prolific production of cementing phases in pozzolanic reactions indicate that it can be used as a supplementary cementitious material in PC and lime systems; and that it can be used as a precursor to produce low-carbon and geopolymer cements. CWS constitutes a reactive aluminium source which, in a PC system, participates in hydration reactions and can enhance the properties of the resultant materials.

In this paper, a large-scale screw-extrusion 3D printer specifically tailored for additive manufacturing applications is introduced, primarily focusing on crafting parawood powder/polylactic acid (PLA) furniture. Boasting a large build volume (700 × 700 × 700 mm³), the printer incorporates a meticulously designed screw extruder to ensure the precise feeding of composite material pellets. The investigation delves into the nuanced relationship between variations in the extruder nozzle orifice diameter and the resulting impact on the extrusion rate, directly correlating these variations with the motor speed. Additionally, the influence of the parawood powder/PLA ratio is explored through comprehensive mechanical property testing of the printed specimens. Optimal outcomes were attained with a 15 %w/w parawood powder composition, yielding an impressive ultimate strength of 54 MPa under specific printing conditions. The efficacy of the large-scale screw-extrusion 3D printer was robustly validated through the successful production of a parawood powder/PLA stacking chair, meeting the criteria stipulated in the Thai industrial standard. Furthermore, an identified parawood powder/PLA component, characterized by a rectangular cylinder with a cross-sectional area of 19.4 × 24.0 mm², holds promising potential for versatile applications in furniture assembly. This innovative extrusion 3D printing approach, combined with meticulously optimized parameters, has unequivocal potential for manufacturing a diverse array of parawood powder/PLA furniture, elevating the value of parawood byproducts and contributing to waste reduction during processing.

The integration of Decentralized Energy Resources (DERs), Energy Storage Systems (ESS), and Electric Vehicles (EVs) into grid-connected networks presents a transformative paradigm in modern power systems. This article introduces a synergistic control framework tailored for optimizing frequency stability within grid-integrated distributed networks. The proposed approach leverages advanced control algorithms to orchestrate the dynamic interaction between DERs, ESS, and EVs, ensuring seamless operation and enhanced grid resilience. The effectiveness of the proposed control strategy is demonstrated in mitigating frequency deviations, thereby contributing to a more stable and reliable grid infrastructure. This article introduces a novel approach utilizing the Selfish Herd Optimization (SHO) algorithm to address this critical issue. Inspired by the self-preservation behavior observed in animal herding, the SHO algorithm is adapted to coordinate the operation of DERs with loads within a distributed network. By dynamically adjusting their output based on local frequency measurements, DERs collectively exhibit a self-organizing behavior, resulting in improved frequency stability. The SHO based PID controller is also proven to be far more effective at controlling frequency than the traditional PI controller. The findings underscore the potential of bio-inspired algorithms in enhancing the resilience of grid-integrated DER systems, offering a promising avenue for future grid control methodologies.

This research evaluated the performance of components and sections involved in industrial beer production using exergetic and exergoeconomics methodologies. The system was segmented into five production sections, and three energy input types were considered. The exergetic studies showed an operational exergetic efficiency of 3.33%, with an overall exergetic destruction rate of 5.54 MW and a specific destruction rate of 9.72 kW/hl for beer production. The overall improvement potential and sustainability index were estimated at 4.98 MW and 1.03, respectively. The brewhouse and packaging hall were identified as the sections with the highest production inefficiency, 58.73% and 30.40%, respectively. The exergoeconomic studies revealed a cost rate of 0.1704 USD/s for beer production, with the wort kettle, filling and cocking machine, Kieselguhr candle filter, whirlpool, and brite beer tank identified as the top five significant components in descending order. The efficiency of the system was critically affected by the activities in the packaging hall, particularly those involving energy inputs that cannot be recovered or attributed to the processed stream, beer. Further research is required to determine the cost savings of optimization measures identified from additional steam throttling, downsizing of some main pumps, and exergy loss during heating of wort and beer chilling processes.

Using a single hidden layer neural network in estimating orientation angles for solar photovoltaics lacks the complexity required to model nonlinear relationships between input variables and the optimal orientation angles for solar photovoltaics. It struggles to generalize well to new and unseen data. More sophisticated neural network architectures such as deep learning with multi-hidden perceptron (MLP) can solve these issues by changing the architecture by deepening the network. Deepening the network will increase complexity, energy consumption, and time complexity. The study uses a novel approach to outperform traditional MLP models with two, three, four, and five hidden layers. An innovative approach was proposed by enhancing a single hidden layer MLP with a quadratic polynomial function, utilizing two robust methodologies, Least Absolute Residuals (LAR) and Bisquare methods. The results demonstrate that these approaches yield significant improvements in Root Mean Square Error (RMSE) and coefficient of determination (R squared). LAR-based MLP showed superiority over both bisquare-based and conventional MLPs methods in R2 and RMSE, ranging from 1.13 to 1.18 and 2.53 to 3.06, respectively. The study outperformed conventional MLP architectures with five hidden layers regarding accuracy and efficiency. The proposed model offers a more effective and less complex solution for data prediction tasks.

In recent years, fuel cell co-generation systems (FC-CGS) have attracted attention for contributing to the environment and are becoming increasingly popular. Considering the current situation, technical specifications for general FC-CGS environmental impact assessments have been published by the International Electrotechnical Commission (IEC) Technical Committee 105 Working Group 14 (TC105WG14). Additionally, several combinations of renewable energy systems, energy storage, and energy-saving technologies have been proposed to obtain more environmental benefits. In this study, several scenarios for combining a polymer electrolyte fuel cell co-generation system (PEFC-CGS) with a battery and PV were created, system operation was discussed, and an environmental impact assessment was conducted. The evaluation was based on IEC standards, considering performance degradation during the usage phase. As a result, it was found that a system in which PEFC-CGS operated in load-following mode, combined with battery and PV, could reduce global warming potential (GWP) by about 36%. There was almost no difference in the PEFC-CGS degradation rate owing to the difference in the operating methods. However, the battery degradation rate showed approximately a 45% difference depending on the scenario. In addition, an environmental gain of ${\eta }_{eco-gain}$ was proposed that expresses the reduction rate from the BAU scenario. Finally, a sensitivity analysis was conducted by changing the weather conditions. The results showed that even when solar radiation was varied, eco-gain was much better than when PV was not installed.