Recognizing that bioenergy with carbon capture and storage (BECCS) may still take years to mature, this study focuses on another photosynthesis-based, negative-carbon technology that is readier to ...implement in China: biomass intermediate pyrolysis poly-generation (BIPP). Here we find that a BIPP system can be profitable without subsidies, while its national deployment could contribute to a 61% reduction of carbon emissions per unit of gross domestic product in 2030 compared to 2005 and result additionally in a reduction in air pollutant emissions. With 73% of national crop residues used between 2020 and 2030, the cumulative greenhouse gas (GHG) reduction could reach up to 8620 Mt CO
-eq by 2050, contributing 13-31% of the global GHG emission reduction goal for BECCS, and nearly 4555 Mt more than that projected for BECCS alone in China. Thus, China's BIPP deployment could have an important influence on achieving both national and global GHG emissions reduction targets.
Albania’s electricity sector lacks energy storage systems (ESS); hence, large quantities of electricity generated during the off-peak time, and excess electricity cannot be stored. On the other hand, ...the transmission capacity upgrades do not keep pace with the growth in peak electric demand; thus, congestion-related issues occur. Congestion of transmission lines has led to considerable uncertainties. Drin River cascade is located north of Albania. It possesses enormous potential energy that is not used due to a lack of ESS. Security of supply, rational use of renewable energy sources (RES), diversification of the electricity sector, increased competitiveness, sheltering more future RES capacities that can benefit from deferring investment in the existing transmission system, and environmental protection are some of these the main benefits of integrating ESS. Regarding the energy transition, the Albanian government’s endeavor aims to maintain and further develop a flexible, sustainable, secure, efficiently supplied, and affordable energy supply system. The results of the simulation executed by using ES-select software to produce multiple benefits from a single device from the chosen application’s list (App1–App6) showed that the most adequate ESS for storing excess electricity in the Drin River cascade are: compressed air energy storage (CAES-c), pumped hydro energy storage (PHES), and sodium-sulfur batteries (NaS). Integrating such systems in the central or bulk generation makes the circumvented cost in 10 years profitable; therefore, moving towards 2030, it would be extremely difficult to tackle the energy sector’s challenges alone, without integrating the ESS.
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•Food waste COD/TS ratio of about 1.6.•Reduced transport in University campus.•VS destruction efficiency of about 74%.•Equity payback 9 years.•Risks are concentrate on Electricity price and Plant ...Investment.
China has implemented a number of laws and policies to promote the reuse of food wastes generated in restaurants and catering services. Resources in terms of energy and fertilizer are recovered from food wastes. In this study, in order to treat canteen food waste generated inside the campus of Huazhong University of Science and Technology (Wuhan, China), a medium scale biogas plant is designed and then simulated using BioWin software. According to obtained simulation results, the total daily biogas production rate is 2013 m3/d and the volatile solids destruction efficiency is about 74%. The campus has about 29 canteens and more than 61,700 students, so it is the ideal place for such a project, because the food waste in this case is concentrated and easy to collect. About 3300 tons of food waste are available per year in HUST, which can be transformed into 1136 MWh of electricity by using a biogas plant with an internal combustion engine. Due to reduced cost of transport and current reduction of taxes for renewable energy plants, the simple payback period of such a project results to be 7.8 years, while the equity payback is 9 years. Sensitivity analysis and risk analysis have shown that project economic feasibility depends strongly on Electricity Export Rate and Initial Investment. A change of these two parameters in the order of 10% can shift equity payback from 9 years to a maximum value of 12.4 years. The development of a Carbon Credit Market can be an important way to increase the economic convenience of this type of projects.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZRSKP
New energy technologies are gaining rising importance because of climate change and increasing energy demand, and they show an enormous potential to mitigate environmental issues. With the purpose of ...maximizing the renewable energy utilization, combined heat and power systems are considered more effective, economical, and ecological. However, renewable energy-based combined heat and power systems are still in the development phase. Hence, this study presents a new methodology to produce combined electricity and heat from wind and solar PV systems to meet the energy demand of small, distributed communities. For this scope, an optimization model is developed to exploit rationally the power generation from renewables and meet the electricity and heating demand of two selected communities. The curtailed energy of solar and wind systems is used to produce heat by a thermal load controller combined with a natural gas boiler. The developed model is also integrated with the grid station for energy exchange. This study contributes also to evaluate the economic and environmental feasibility of combined heat and power systems, and determine the best optimal operational strategies to extend the renewable energy utilization and minimize energy costs. The obtained results show that a significant amount of clean energy can be produced, covering the 79% of the energy demand of the selected communities, at the lowest levelized cost of energy of 0.013 €/kWh; meanwhile, the proposed system reduces 4129 tons of CO2 emissions annually.
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Microalgae cultivation is booming in agriculture, aquaculture, and bioenergy sectors. A wide range of bioactive compounds with attractive properties can be produced with microalgae, including ...pigments, vitamins, proteins, carbohydrates, and lipids. The biofuel yields from microalgae can exceed the yields obtained with energy crops by 10–100 times. Therefore, such cultivation is promising for the regulation of the biosynthesis of microalagae with phytohormones, which can enhance the production of high-valued bioproducts. This review reports the effect of auxins, abscisic acid, cytokinins, gibberellins, and ethylene on microalgal growth and metabolites, as well as the crosstalk of different phytohormones. The use of phytohormones is also promising because it can also reduce the inputs necessary to grow the selected microalgae and maximize the yields.
The solid fraction obtained by mechanical separation of digestate from anaerobic digestion plants is an attractive feedstock for the pyrolysis process. Especially in the case of digestate obtained ...from biogas plants fed with energy crops, this can be considered a lignin rich residue. The aim of this study is to investigate the pyrolytic kinetic characteristics of solid digestate. The Starink model-free method has been used for the kinetic analysis of the pyrolysis process. The average Activation Energy value is about 204.1 kJ/mol, with a standard deviation of 25 kJ/mol, which corresponds to the 12% of the average value. The activation energy decreased along with the conversion degree. The variation range of the activation energy is about 99 kJ/mol, this means that the average value cannot be used to statistically represent the whole reaction. The Master-plots method was used for the determination of the kinetic model, obtaining that n-order was the most probable one. On the other hand, the process cannot be modeled with a single-step reaction. For this reason it has been used an independent parallel reactions scheme to model the complete process.
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•Anaerobic digestion is a viable method for the conversion of food waste.•The maximum biogas production observed at the pH equal 7.0.•Methane yield variations range from 216 to 1476 mL CH4/ g VS.•The ...range of phosphorus content was: 0–3.66.%•The range of potassium content was: 0–10.45% and that of nitrogen was 0.05–6.15%.
Considerable amounts of expired food waste are generated every day. They are rich in organic carbon and in other elements, including nitrogen, phosphorus and potassium, which cannot be wasted. The present work tested expired food waste in terms of biogas production efficiency in anaerobic digestion (AD) process. A database was extrapolated from the tests carried out in order to obtain a complete list of physico-chemical and biochemical methane potential (BMP) of 88 expired food waste. Many studies are based on the analysis of a small number of samples, which are don't present a complete picture of all the types of food waste. The organic composition and other factors such as pH, temperature, C/N ratio of the samples varies considerably with the region, the season and the processing characteristics, resulting in methane yield variations, ranging from 216 to 1476 mL CH4/gVS. Therefore, knowledge of the appropriate physical and chemical properties of the feedstock, working conditions and the effects of the inhibition of various components on the anaerobic digestion processes is a key element, necessary to optimize energy production from food waste.
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Internal concentration polarization (ICP) is currently a major bottleneck in the forward osmosis process. Proper modelling of the internal concentration polarization is therefore vital for improving ...the process performance and efficiency. This study assessed the feasibility of several machine learning methods for internal concentration polarization prediction, including artificial neural networks, extreme gradient boosting (XGBoost), Categorical boosting (CatBoost), Random forest, and linear regression. Among the many algorithms evaluated, the CatBoost regression outperformed other methods in terms of coefficient of determination (R2) and the mean square error. The CatBoost algorithm's prediction power was then evaluated using non-training (user-provided) data and compared to solution diffusion models. The results indicated that the machine learning algorithms could predict ICP in the process with high accuracy for the provided dataset and excellent generalizability for future testing data. Furthermore, machine learning algorithms may offer insights into the input features that majorly affect ICP modelling in the forward osmosis process.
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•Internal concentration polarization is predicted through machine learning models.•Artificial Neural networks and gradient tree boosting models are compared.•Neural network and Categorial boosting models showed better predictive power.•Categorical boosting outperformed other machine learning models.•Comparison against solution diffusion models is made.
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The increasing global demand for biofuels for energy security and to reduce the effects of climate change has created an opportunity to explore new sources of biomass, of which, microalgae is the ...most promising one. The Laboratory of the Biomass Research Centre (CRB, University of Perugia) is equipped with a photobioreactor that is used to cultivate microalgae under batch conditions. Tests were carried out a temperature of 22 °C and a Photosynthetic Photon Flux Density of 140 µE·m−2·s−1. Cultures were characterized in terms of biomass produced and lipid fraction distribution. The novelty of this paper is the measure of the fuel properties of Selenastrum capricornutum, a new strain for biodiesel production. In particular, after the microalgae have been collected and oil has been extracted, this has been transesterified using a methanol/NaOH solution. The resulting biodiesel has been analyzed with a high-resolution gas chromatograph to determine the concentration of the different methylesters.
Tunisia, like many other countries in the world, suffers from a shortage of conventional energy resources. Further, it exhibits large and increasing volumes of organic wastes that cause environmental ...and health problems. In this study, the considered wastes consist of the organic fraction of municipal solid wastes (OFMSW), the olive mill wastewater (OMWW), and the chicken wastes (CW). These bio-wastes can therefore be valorized by a biological process such as the anaerobic digestion to satisfy on the one hand the energy demands and on the other hand, to reduce the environmental problems. Accordingly, the first aim of this work is to investigate the biomethane potential of the mentioned bio-wastes and to assess the energetic content of the obtained biomethane production. Secondly, a theoretical analysis is conducted by using the Buswell equation to predict the biomethane generation and to determine the biodegradability of the studied substrates mixture. Finally, the experimental findings are used to carry out a kinetic study, by using four kinetic models to assess their suitability to fit the present anaerobic digestion process. To do this, the biomethane potential estimation of these biomasses, under mesophilic conditions, is carried out at a laboratory scale by using the biochemical methane potential (BMP) tests. These testes are performed under an optimal substrate-to-inoculums ratio and a controlled temperature during the testing period at a laboratory scale. The experimental results show that the net yield of the biomethane from the studied bio-wastes mixture is equal to 0.384 Nm
3
/kg VS, which is equivalent to 130.29 Nm
3
of biomethane, extracted from one ton of these bio-wastes mixture. The theoretical and the experimental results of the net produced biomethane show that the substrates mixture biodegradability is found equal to 66.89%. The studied kinetic models show good agreements with the experimental results, with a correlation coefficient R
2
≥ 95. It is found that the Gompertz model is the best one for predicting the anaerobic digestion process, due to the lowest root mean square prediction estimate (RMSPE) coefficient, as compared with the other studied kinetic models.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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