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Summary: This article proposes a methodology based on artificial intelligence to enhance methane production from waste paper. The proposed methodology combines fuzzy logic‐based modelling and modern optimization. Firstly, a robust Adaptive Network‐based Fuzzy Inference System model of methane production process through fuzzy logic modelling is created using experimental datasets. Second, a particle swarm optimizer was used to obtain the optimal process conditions. During the optimization procedure, the beating time and feedstock/inoculum ratio are employed as decision variables in order to maximize methane production. The obtained resulted from the proposed methodology are compared with those obtained by response surface methodology. The results of the comparison confirmed the superiority of the proposed methodology. The fuzzy model shows a better fitting to the experimental data compared to ANOVA. The fuzzy model showed a higher coefficient of determination and a lower value of root mean squared errors compared to ANOVA. Moreover, the proposed strategy, that is, modelling and optimization, is an effective method for increasing the biomethane yield at extended range conditions. [ABSTRACT FROM AUTHOR]

The paper and pulp industry stands out to be one of the industries that are growing at a fast pace. Besides their characteristics such as high water consumption of 695.7 million m3 per year and subsequent high energy consumption, there are plenty of environmental impacts arising from this industry. Approximately 300 different types of harmful organic pollutants such as phenols, dioxins, and other organic substances are the significant effluents of the paper and pulp industry. As per the regulations set by the world health organization (WHO), the permissible limit of such pollutants is less than 1 ppm. Since the complete degradation of these pollutants is difficult to achieve using conventional techniques, advanced oxidation processes (AOPs) are widely being used as promising alternatives. On the other hand, depleting non-renewable energy resources are forcing industries to look for energy-efficient technologies. Photocatalysis is one such AOPs, which has the potential to solve the energy-wastewater nexus and is the primary focus of this review in terms of waste treatment from the paper and pulp industry. The photocatalytic materials induce photoreactions by receiving photon energy from light. However, harnessing light energy to the fullest is a challenge owing to the limited share of UV spectrum in sunlight. Different composite photocatalysts at different loadings, pollutant concentrations, and contact time along with their respective efficiencies are reported. The enhancement in thermodynamic driving force due to shift in Fermi energy levels with a suitable example is explained. The dependence of photocatalysis on various factors such as organic species, temperature, and light intensity makes it tough to predict the precise kinetic model in real-life experiments. The hydrogen production from the degradation of organic pollutants was discussed vividly and by optimization of the processes, an estimated amount of 0.45% of the total world's energy could be produced from the paper and pulp industry alone. [ABSTRACT FROM AUTHOR]

The present study investigates the effect on methane production from waste paper when co-digested with macroalgal biomass. Both feedstocks were previously mechanically pretreated to reduce their particle size. The study was planned according two factors: the feedstock to inoculum (F/I) ratio and the waste paper to macroalgae (WP/MA) ratio. The F/I ratios checked were 0.2, 0.3 and 0.4 and the WP/MA ratios were 0:100, 25:75, 50:50, 75:25 and 100:0. The highest methane yield (386 L kg −1 VS added ) was achieved at an F/I ratio of 0.2 and a WP/MA ratio of 50:50. A biodegradability index of 0.87 obtained in this study indicates complete conversion of feedstock at an optimum C/N ratio of 26. Synergistic effect was found for WP/MA 25:75, 50:50 and 75:25 mixing ratios compared with the substrates mono-digestion. [ABSTRACT FROM AUTHOR]

[Display omitted] • A total of 20 different paper sludges were investigated. • A wide range of biomethane potentials was determined. • Inhibiting substances for some paper sludge were identified. • Co-digestion resulted in methane yield increase of 5–10%. • The possibility of anaerobic co-digestion could be demonstrated. In this work, the feasibility of the anaerobic digestion of paper sludge as a co-substrate in anaerobic digestion mechanical–biological treatment (MBT) plants is investigated. In the first phase, the biochemical properties, biomethane potential (BMP), and pollutant contents of 20 different industrial paper sludges are determined. Following the general evaluation in the BMP tests, the second phase of the project involves the semi-continuous co-digestion of six paper sludges in continuous stirred reactors (CSTR). Paper sludges are categorized according to their origin within the pulp and paper mills: Deinking Sludge (DS), Primary Sludge (PS) and Biological Sludge (BS). The analysis of potentially inhibiting elements shows that the concentrations of chlororganic compounds, mineral oil and some heavy metals are highest in DS, while the mean heavy metal loads in all paper sludges are relatively low compared to other industrial sludges. Large differences in total solids (TS) and volatile solids (VS) contents are observed among the different paper sludges investigated, with DS having the highest TS due to the high inorganic contents. The BMP of the investigated sludges ranges from 90 to 355 NL CH 4 kg−1 VS. In subsequent semi-continuous co-digestion experiments simulating MBT conditions, three DS and two fiber sludges (a mixture of PS and BS) show good methane generation rates, while one fiber sludge causes inhibition and indicates an increase in viscosity. In general, co-digestion of paper sludge in anaerobic digestion MBT plants can be a viable option for energy production and also facilitates a safe disposal of the paper sludge digestates. [ABSTRACT FROM AUTHOR]

In the anaerobic digestion of lignocellulosic materials such as waste paper, the accessibility of microorganisms to the fermentable sugars is restricted by their complex structure. A mechanical pretreatment with a Hollander beater was assessed in order to reduce the biomass particle size and to increase the feedstock’ specific surface area available to the microorganisms, and therefore improve the biogas yield. Pretreatment of paper waste for 60 min improves the methane yield by 21%, from a value of 210 ml/gVS corresponding to untreated paper waste to 254 ml/gVS. 30 min pretreatment have no significant effect on the methane yield. A response surface methodology was used to evaluate the effect of the beating time and feedstock/inoculum ratio on the methane yield. An optimum methane yield of 253 ml/gVS was achieved at 55 min of beating pretreatment and a F/I ratio of 0.3. [ABSTRACT FROM AUTHOR]

The EU has set the ambitious target of raising the share of EU energy consumption produced from renewable resources to 32% by 2030, with a target of climate neutrality by 2050. The aim of this paper is to assess the role of biomass usage in the context of these targets. The paper identifies the progress made between 2013 and 2022 by focusing on a selection of EU countries. The largest bioenergy increments of 130, 77, and 60 PJ were reported for Poland, Sweden, and the Netherlands. This study evaluates the crucial role of co-generation and heat in EU regions, with biomass usage between 55 and 80% of the combined heat and power (CHP) energy in Nordic countries. The future perspectives for bioenergy based on EU policies, biomass resources, and technical issues were addressed. The EU possesses around 9% of the global biomass supply, ensuring a certain level of biomass resource dependence. Thus, the biomass usage demand in energy production, non-energy sectors, and transport is expected to rise, leading to increments of 13–76% on biomass imports. It appears that bioenergy development is mostly limited by economic issues and uneven support for bioenergy in different EU countries as well as environmental issues. The study shows a promising and sustainable potential of bioenergy in the EU as a renewable energy source while minimizing negative impacts on the environment and the economy. By 2050, liquid biofuels are likely to be increasingly used in the transport sector. Non-energy sector usage of biomass is still in an early stage of development, except for the pulp and paper industry, and significant use of biomass in non-energy sectors seems unlikely in the near future. [ABSTRACT FROM AUTHOR]

This paper investigates carbon and energy mix risk in the equity prices of EU-Taxonomy orientated and renewable European electric utility companies. We calculate carbon intensity and energy mix factors to measure possible carbon and energy mix premia while investigating the performance of portfolios of EU-Taxonomy orientated and renewable European electric utilities. We use a unique dataset to extend the three-factor model presented by Fama and French (1993) and find evidence of a positive renewable energy mix premium for portfolios of EU-Taxonomy orientated firms and firms with a high level of renewable energy in the energy mix. A positive low-carbon premium is also found for these same portfolios. Lastly, based on the three-factor model, an EU-Taxonomy orientated portfolio outperforms both a non-orientated portfolio and a non-reporting portfolio while a renewable energy portfolio outperforms a conventional energy portfolio. Our results are important for regulators, investors and European electric utilities in assessing the impact environmental regulations have on a firm's cost of capital. [ABSTRACT FROM AUTHOR]

This study explored the association between renewable energy uptake and digitalization in the sector by reviewing relevant literature (published 2010–2022), with the aim of identifying the existing utilization of digital technologies within the sector, challenges to adoption, and future prospects. Different search engines (SCOPUS, Web of Science, and Google Scholar) were used to locate relevant papers and documents. The results revealed the high significance of digital technologies in supporting the renewable energy sector, with high costs and security risks representing the key challenges. Most papers reviewed had a positive outlook, but recommended further research and development for effective energy transition and resilient infrastructure. The current drivers of the integration of digital technologies to support the diffusion of renewable energy sources appear to extend beyond energy demand and involve many aspects of sustainability and sustainable development. Compared with previous reviews, this work has unique scope and novelty since it considers the bigger picture of the coupling between digitalization and the renewable energy sector, with a greater focus on critical areas in these two interconnected bodies that need to be addressed. The relatively small sample of relevant papers (69 from 836 hits) located in the literature review confirms the need for more research covering the subject in greater depth. [ABSTRACT FROM AUTHOR]

In this study, a microwave plasma reactor was used for pyrolysis of waste papers. The effects of different argon flow rates on char and gas generation were investigated. Changes in carbon and oxygen contents from those in paper to char were significant. Char yield of over 25 % was obtained with the heating value of about 38 MJ/kg. Average gas yield and total content of combustible fraction (CO, CH4 and H2) in the gas product were 2.56 m3/kg and 36 %, respectively. The heating value of gas product and carbon conversion efficiency of the process were maximum at 6.0 MJ/m3 and 73 %, respectively. [ABSTRACT FROM AUTHOR]

Wind and photovoltaic (PV) power forecasting are crucial for improving the operational efficiency of power systems and building smart power systems. However, the uncertainty and instability of factors affecting renewable power generation pose challenges to power system operations. To address this, this paper proposes a digital twin-based method for predicting wind and PV power. By utilizing digital twin technology, this approach provides a highly realistic simulation environment that enables accurate monitoring, optimal control, and decision support for power system operations. Furthermore, a digital twin platform for the AI (Artificial Intelligence) Grid is established, allowing real-time monitoring, and ensuring the safe, reliable, and stable operation of the grid. Additionally, a deep learning-based model WPNet is developed to predict wind and PV power at specific future time points. Four datasets are constructed based on weather conditions and historical wind and PV power data from the Flanders and Wallonia regions. The prediction models presented in this paper demonstrate excellent performance on these datasets, achieving mean square error (MSE) values of 0.001399, 0.001833, 0.000704, and 0.002708; mean absolute error (MAE) values of 0.025164, 0.027854, 0.018592, and 0.033501; and root mean square error (RMSE) values of 0.037409, 0.042808, 0.026541, and 0.052042, respectively. [ABSTRACT FROM AUTHOR]

Pulp and paper industry is a water-intensive industry. This industry commonly produces considerable amount of effluent, especially from virgin raw materials processing. The effluent, namely pulp and paper mill effluent has the potential to adversely affect the receiving watercourses. However, the nutrients in the pulp and paper mill effluent could be reused as a substrate in biohydrogen production. In this study, photofermentative biohydrogen production was investigated using Rhodobacter sphaeroides and pulp and paper mill effluent as a substrate. An application of low power ultrasound on R. sphaeroides was predicted to increase photofermentative biohydrogen production but excessive ultrasound effects might inhibit the production due to possible cell disruption. Hence, various ultrasonication duration (5, 10 and 15 min) and amplitude (15%, 30% and 45%) were applied on the bacteria to determine the recommended ultrasonication conditions for improving biohydrogen production. The recommended conditions were operated at ultrasonication amplitude and duration of 30% and 10 min, respectively. A maximum biohydrogen yield of 9.62 mL bioH 2 /mL medium was obtained under this condition, which was 66.7% higher than the result obtained using R. sphaeroides without undergoing ultrasonication (control). The light efficiency and cell concentration were increased by 67% and 150%, respectively, using ultrasonication amplitude and duration of 30% and 10 min, respectively as compared to the control. The present results demonstrated that moderate power of ultrasonication applied on R. sphaeroides was an effective method for enhancing photofermentative biohydrogen production using raw pulp and paper mill effluent as a bioresource. [ABSTRACT FROM AUTHOR]